15885 lines
342 KiB
Plaintext
15885 lines
342 KiB
Plaintext
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mappings {
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frameworkName: "tensorflow"
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opName: "unique"
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inputFrameworkOpName: "UniqueV2"
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rule {
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ruleName: "ndarraymapping"
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functionName: "ndarraymapping"
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inputTensorName: "x"
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outputTensorName: "input"
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inputToOutput {
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key: "input"
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value: "x"
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}
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ruleType: "tensor"
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inputFrameworkOpName: "UniqueV2"
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}
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}
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mappings {
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frameworkName: "tensorflow"
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opName: "conv2d"
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inputFrameworkOpName: "Conv2D"
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rule {
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ruleName: "ndarraymapping"
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functionName: "ndarraymapping"
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inputTensorName: "input"
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inputTensorName: "filter"
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outputTensorName: "input"
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outputTensorName: "weights"
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inputToOutput {
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key: "input"
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value: "input"
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}
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inputToOutput {
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key: "weights"
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value: "filter"
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}
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ruleType: "tensor"
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inputFrameworkOpName: "Conv2D"
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}
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rule {
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ruleName: "argdescriptorconstant"
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functionName: "argdescriptorconstant"
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inputIntName: "pH"
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transformerArgs {
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transformerArgs {
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name: "pH"
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argIndex: 4
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}
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inputFrameworkOpName: "Conv2D"
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}
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rule {
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ruleName: "argdescriptorconstant"
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functionName: "argdescriptorconstant"
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inputIntName: "pW"
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ruleType: "attribute"
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transformerArgs {
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key: "value"
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transformerArgs {
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name: "pW"
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argType: INT64
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argIndex: 5
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}
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}
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inputFrameworkOpName: "Conv2D"
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}
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rule {
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ruleName: "argdescriptorconstant"
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functionName: "argdescriptorconstant"
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inputIntName: "wFormat"
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ruleType: "attribute"
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transformerArgs {
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key: "value"
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transformerArgs {
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name: "wFormat"
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argType: INT64
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argIndex: 10
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}
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}
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inputFrameworkOpName: "Conv2D"
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}
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rule {
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ruleName: "stringnotequalsadapterrule"
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functionName: "stringnotequalsadapterrule"
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inputStringAttrName: "data_format"
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outputIntName: "isNCHW"
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inputFloatName: "data_format"
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inputToOutput {
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key: "isNCHW"
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value: "data_format"
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}
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ruleType: "attribute"
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transformerArgs {
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key: "isNCHW"
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transformerArgs {
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name: "data_format"
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argIndex: 9
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stringValue: "NCHW"
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}
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inputFrameworkOpName: "Conv2D"
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}
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rule {
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ruleName: "stringequals"
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functionName: "stringequals"
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inputStringAttrName: "padding"
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inputStringAttrName: "padding"
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outputIntName: "isSameMode"
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inputToOutput {
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key: "isSameMode"
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value: "padding"
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}
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ruleType: "attribute"
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transformerArgs {
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key: "isSameMode"
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transformerArgs {
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name: "padding"
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argType: STRING
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argIndex: 8
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stringValue: "SAME"
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}
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}
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inputFrameworkOpName: "Conv2D"
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|
}
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rule {
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ruleName: "conditionalfieldvalueintindex"
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functionName: "conditionalfieldvalueintindex"
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inputStringAttrName: "data_format"
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outputIntName: "sH"
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inputFloatName: "targetValue"
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inputFloatName: "trueIndex"
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inputFloatName: "falseIndex"
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inputFloatName: "attributeNameOfListAttribute"
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inputToOutput {
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|
|
key: "sH"
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|
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value: "data_format"
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|
}
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|
|
ruleType: "attribute"
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|
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transformerArgs {
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|
|
key: "sH"
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|
transformerArgs {
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|
|
name: "targetValue"
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|
stringValue: "NCHW"
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|
|
}
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|
transformerArgs {
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|
|
name: "trueIndex"
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|
int64Value: 2
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argIndex: 2
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}
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transformerArgs {
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name: "falseIndex"
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|
int64Value: 1
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argIndex: 2
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}
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transformerArgs {
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name: "attributeNameOfListAttribute"
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|
argIndex: 2
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|
|
stringValue: "strides"
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}
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}
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|
|
transformerArgs {
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||
|
|
key: "sH"
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|
transformerArgs {
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|
|
name: "targetValue"
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|
|
stringValue: "NCHW"
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|
|
}
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|
transformerArgs {
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|
|
name: "trueIndex"
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|
|
int64Value: 2
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|
|
argIndex: 2
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}
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transformerArgs {
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|
name: "falseIndex"
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|
int64Value: 1
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|
argIndex: 2
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}
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transformerArgs {
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|
name: "attributeNameOfListAttribute"
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|
|
argIndex: 2
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stringValue: "strides"
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}
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}
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||
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transformerArgs {
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||
|
|
key: "sH"
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|
transformerArgs {
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|
|
name: "targetValue"
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|
|
stringValue: "NCHW"
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}
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transformerArgs {
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|
|
name: "trueIndex"
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int64Value: 2
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argIndex: 2
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}
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transformerArgs {
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name: "falseIndex"
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int64Value: 1
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argIndex: 2
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}
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transformerArgs {
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name: "attributeNameOfListAttribute"
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argIndex: 2
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stringValue: "strides"
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}
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}
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transformerArgs {
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||
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|
key: "sH"
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|
transformerArgs {
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|
name: "targetValue"
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|
stringValue: "NCHW"
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}
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transformerArgs {
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|
name: "trueIndex"
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int64Value: 2
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argIndex: 2
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}
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transformerArgs {
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name: "falseIndex"
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int64Value: 1
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argIndex: 2
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}
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transformerArgs {
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name: "attributeNameOfListAttribute"
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argIndex: 2
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stringValue: "strides"
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}
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|
}
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||
|
|
inputFrameworkOpName: "Conv2D"
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||
|
|
}
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||
|
|
rule {
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||
|
|
ruleName: "conditionalfieldvalueintindex"
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||
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|
functionName: "conditionalfieldvalueintindex"
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||
|
|
inputStringAttrName: "data_format"
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||
|
|
outputIntName: "sW"
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||
|
|
inputFloatName: "targetValue"
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inputFloatName: "trueIndex"
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|
inputFloatName: "falseIndex"
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inputFloatName: "attributeNameOfListAttribute"
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|
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inputToOutput {
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|
|
key: "sW"
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|
|
value: "data_format"
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|
}
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||
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|
ruleType: "attribute"
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transformerArgs {
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||
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key: "sW"
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transformerArgs {
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|
|
name: "targetValue"
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stringValue: "NCHW"
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}
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transformerArgs {
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name: "trueIndex"
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int64Value: 3
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transformerArgs {
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name: "falseIndex"
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int64Value: 2
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}
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transformerArgs {
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name: "attributeNameOfListAttribute"
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argIndex: 3
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stringValue: "strides"
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}
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transformerArgs {
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key: "sW"
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transformerArgs {
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name: "targetValue"
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stringValue: "NCHW"
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}
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transformerArgs {
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name: "trueIndex"
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int64Value: 3
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argIndex: 3
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}
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transformerArgs {
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name: "falseIndex"
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int64Value: 2
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argIndex: 3
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transformerArgs {
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name: "attributeNameOfListAttribute"
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argIndex: 3
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stringValue: "strides"
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}
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}
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transformerArgs {
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key: "sW"
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transformerArgs {
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|
name: "targetValue"
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|
stringValue: "NCHW"
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}
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transformerArgs {
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||
|
|
name: "trueIndex"
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|
|
int64Value: 3
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argIndex: 3
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}
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transformerArgs {
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||
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|
name: "falseIndex"
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|
|
int64Value: 2
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argIndex: 3
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}
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transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
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||
|
|
argIndex: 3
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|
|
stringValue: "strides"
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|
|
}
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||
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}
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||
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transformerArgs {
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||
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|
key: "sW"
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||
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transformerArgs {
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||
|
|
name: "targetValue"
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|
|
stringValue: "NCHW"
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||
|
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}
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||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
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||
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|
argIndex: 3
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||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
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||
|
|
int64Value: 2
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|
argIndex: 3
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}
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||
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transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
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||
|
|
argIndex: 6
|
||
|
|
}
|
||
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|
transformerArgs {
|
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|
name: "falseIndex"
|
||
|
|
int64Value: 1
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||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
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||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
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||
|
|
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|
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argIndex: 6
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}
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||
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transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
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||
|
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argIndex: 6
|
||
|
|
}
|
||
|
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transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
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|
|
stringValue: "NCHW"
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||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
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|
|
int64Value: 2
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|
|
argIndex: 6
|
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|
|
}
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transformerArgs {
|
||
|
|
name: "falseIndex"
|
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|
|
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|
|
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|
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|
|
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|
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|
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transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "kH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "kH"
|
||
|
|
int64Value: -1
|
||
|
|
argType: INT64
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "kW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "kW"
|
||
|
|
int64Value: -1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2D"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "random_poisson"
|
||
|
|
inputFrameworkOpName: "RandomPoisson"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "shape"
|
||
|
|
inputTensorName: "rate"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
outputTensorName: "lambda"
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
value: "shape"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "lambda"
|
||
|
|
value: "rate"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "RandomPoisson"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "seed"
|
||
|
|
outputIntName: "seed"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "seed"
|
||
|
|
value: "seed"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomPoisson"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "maxpool2d"
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "dW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dW"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "dH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dH"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "extraParam0"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 9
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringnotequalsadapterrule"
|
||
|
|
functionName: "stringnotequalsadapterrule"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "isNCHW"
|
||
|
|
inputFloatName: "data_format"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNCHW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNCHW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argIndex: 10
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "padding"
|
||
|
|
argType: STRING
|
||
|
|
argIndex: 8
|
||
|
|
stringValue: "SAME"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "kH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "kW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "size"
|
||
|
|
inputFrameworkOpName: "Size"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Size"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "out_type"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "out_type"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Size"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "squaredsubtract"
|
||
|
|
inputFrameworkOpName: "SquaredDifference"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SquaredDifference"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "SquaredDifference"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "SquaredDifference"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "randomuniform"
|
||
|
|
inputFrameworkOpName: "StatelessRandomUniform"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "shape"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
value: "shape"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "StatelessRandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "max"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "max"
|
||
|
|
doubleValue: 1.0
|
||
|
|
argType: DOUBLE
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "StatelessRandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "min"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "min"
|
||
|
|
argType: DOUBLE
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "StatelessRandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
outputIntName: "seed"
|
||
|
|
inputToOutput {
|
||
|
|
key: "seed"
|
||
|
|
value: "seed"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "StatelessRandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "datatypetoint"
|
||
|
|
functionName: "datatypetoint"
|
||
|
|
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|
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|
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|
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|
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|
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|
|
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|
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|
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|
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|
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mappings {
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|
|
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|
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|
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inputToOutput {
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|
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|
|
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|
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|
|
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|
|
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transformerArgs {
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transformerArgs {
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|
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|
|
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|
|
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|
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|
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|
|
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rule {
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|
|
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|
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transformerArgs {
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transformerArgs {
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|
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|
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|
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|
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mappings {
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|
|
frameworkName: "tensorflow"
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|
|
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|
|
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rule {
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|
|
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|
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|
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|
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|
inputToOutput {
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|
|
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|
|
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|
|
}
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|
|
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|
||
|
|
inputFrameworkOpName: "Digamma"
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||
|
|
}
|
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|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "random_shuffle"
|
||
|
|
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|
||
|
|
rule {
|
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|
|
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|
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|
|
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|
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|
|
inputToOutput {
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|
|
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|
|
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|
|
}
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|
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|
|
inputFrameworkOpName: "RandomShuffle"
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||
|
|
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|
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|
|
rule {
|
||
|
|
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|
|
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|
|
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|
|
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|
|
inputToOutput {
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|
|
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|
|
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|
|
}
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|
|
ruleType: "attribute"
|
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|
|
inputFrameworkOpName: "RandomShuffle"
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|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
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|
|
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|
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|
|
rule {
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
inputToOutput {
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|
|
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|
|
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|
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|
|
}
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|
|
inputToOutput {
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|
|
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|
||
|
|
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|
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|
|
}
|
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|
|
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|
||
|
|
inputFrameworkOpName: "AdjustHue"
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|
|
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|
rule {
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|
|
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|
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|
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|
|
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|
transformerArgs {
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|
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|
transformerArgs {
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|
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|
|
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|
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|
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|
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|
|
}
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|
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mappings {
|
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|
|
frameworkName: "tensorflow"
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|
|
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|
|
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|
rule {
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|
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|
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|
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|
|
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|
|
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|
}
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|
|
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|
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|
|
inputFrameworkOpName: "Assert"
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|
|
}
|
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|
|
}
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|
mappings {
|
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|
|
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|
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|
|
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|
||
|
|
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rule {
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|
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|
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|
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rule {
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|
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|
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|
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|
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transformerArgs {
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|
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|
transformerArgs {
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|
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|
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|
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|
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mappings {
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
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|
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|
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|
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transformerArgs {
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|
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transformerArgs {
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|
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|
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|
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|
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|
|
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||
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|
mappings {
|
||
|
|
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|
||
|
|
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|
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|
|
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|
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|
|
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|
|
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|
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||
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|
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|
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|
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|
|
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||
|
|
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|
|
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||
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|
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|
||
|
|
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||
|
|
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|
|
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|
||
|
|
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||
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|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
|
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||
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|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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||
|
|
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|
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|
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|
|
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|
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|
|
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|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
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|
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||
|
|
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||
|
|
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|
||
|
|
inputToOutput {
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||
|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
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|
|
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|
|
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||
|
|
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|
|
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|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
mappings {
|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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|
|
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|
|
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|
|
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||
|
|
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||
|
|
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|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "UnsortedSegmentProd"
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||
|
|
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|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
|
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|
||
|
|
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|
|
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|
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|
|
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||
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|
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|
|
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|
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|
|
inputToOutput {
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||
|
|
key: "input"
|
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|
|
value: "x"
|
||
|
|
}
|
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|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "y"
|
||
|
|
}
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|
ruleType: "tensor"
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||
|
|
inputFrameworkOpName: "Sub"
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||
|
|
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rule {
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||
|
|
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|
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|
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|
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|
transformerArgs {
|
||
|
|
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|
|
transformerArgs {
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|
|
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|
|
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|
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|
|
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|
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|
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|
|
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|
rule {
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|
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|
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|
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|
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inputToOutput {
|
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|
|
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|
|
value: "T"
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|
|
}
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|
ruleType: "attribute"
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|
|
inputFrameworkOpName: "Sub"
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|
|
}
|
||
|
|
}
|
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|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
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|
|
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|
|
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|
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|
|
ruleName: "ndarraymapping"
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|
|
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|
inputTensorName: "x"
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|
inputTensorName: "y"
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|
|
outputTensorName: "input"
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||
|
|
outputTensorName: "y"
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||
|
|
inputToOutput {
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|
|
key: "input"
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|
|
value: "x"
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||
|
|
}
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|
|
inputToOutput {
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|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
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|
|
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||
|
|
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||
|
|
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rule {
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|
|
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|
|
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|
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|
ruleType: "attribute"
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|
transformerArgs {
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|
|
key: "value"
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|
transformerArgs {
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||
|
|
name: "inPlace"
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|
|
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|
|
}
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|
}
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|
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|
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|
rule {
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||
|
|
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|
|
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|
|
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|
|
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|
inputToOutput {
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|
|
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|
|
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|
|
}
|
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|
|
ruleType: "attribute"
|
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|
|
inputFrameworkOpName: "NotEqual"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "expm1"
|
||
|
|
inputFrameworkOpName: "Expm1"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Expm1"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Expm1"
|
||
|
|
}
|
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|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
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||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Expm1"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "relu6"
|
||
|
|
inputFrameworkOpName: "Relu6"
|
||
|
|
rule {
|
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|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Relu6"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
}
|
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|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Relu6"
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||
|
|
}
|
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|
|
rule {
|
||
|
|
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|
|
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|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "cutoff"
|
||
|
|
argType: DOUBLE
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "cutoff"
|
||
|
|
argType: DOUBLE
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Relu6"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "reduce_sum"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
key: "input"
|
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|
|
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||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Sum"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Sum"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
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|
||
|
|
outputIntName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Sum"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "DynamicStitch"
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "DynamicStitch"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "DynamicStitch"
|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "keepDims"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
|
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||
|
|
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|
||
|
|
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|
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|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "ExpandDims"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Min"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputBooleanName: "keep_dims"
|
||
|
|
outputBooleanName: "keepDims"
|
||
|
|
inputToOutput {
|
||
|
|
key: "keepDims"
|
||
|
|
value: "keep_dims"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Min"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
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|
||
|
|
outputIntName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Min"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "space_to_batch"
|
||
|
|
inputFrameworkOpName: "SpaceToBatch"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "paddings"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "padding"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "padding"
|
||
|
|
value: "paddings"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SpaceToBatch"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "SpaceToBatch"
|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
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||
|
|
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|
||
|
|
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|
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|
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|
|
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||
|
|
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|
|
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|
|
}
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|
||
|
|
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|
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|
|
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transformerArgs {
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|
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transformerArgs {
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|
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|
|
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|
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|
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mappings {
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|
|
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|
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inputToOutput {
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|
|
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|
|
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|
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||
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|
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rule {
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transformerArgs {
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transformerArgs {
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transformerArgs {
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|
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transformerArgs {
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|
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rule {
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|
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|
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|
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|
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rule {
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|
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|
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|
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|
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|
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|
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|
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|
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|
mappings {
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|
frameworkName: "tensorflow"
|
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|
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|
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rule {
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|
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|
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|
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||
|
|
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|
|
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|
rule {
|
||
|
|
ruleName: "valuemapping"
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|
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|
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|
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|
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|
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|
value: "T"
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|
|
}
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|
ruleType: "attribute"
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|
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|
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|
}
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mappings {
|
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|
|
frameworkName: "tensorflow"
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|
|
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|
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|
|
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|
rule {
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|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
inputToOutput {
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|
|
key: "input"
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|
|
value: "x"
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|
|
}
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|
|
inputToOutput {
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|
|
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|
|
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|
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|
|
}
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|
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|
|
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|
|
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|
|
}
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|
|
mappings {
|
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|
|
frameworkName: "tensorflow"
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|
|
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|
|
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|
|
rule {
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|
|
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|
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|
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|
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|
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|
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|
inputToOutput {
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|
|
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|
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|
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|
|
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|
|
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|
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|
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|
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|
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rule {
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|
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rule {
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|
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|
|
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mappings {
|
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|
|
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|
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|
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|
rule {
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|
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|
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|
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|
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|
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|
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|
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|
}
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|
|
}
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mappings {
|
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|
|
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|
|
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|
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rule {
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|
|
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|
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|
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|
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|
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|
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|
|
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rule {
|
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|
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|
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|
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|
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|
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|
inputToOutput {
|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
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|
|
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|
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|
|
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|
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|
|
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|
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|
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|
|
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|
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|
|
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|
|
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|
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|
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|
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|
|
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|
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|
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|
|
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transformerArgs {
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
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|
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|
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|
|
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|
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|
|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
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|
|
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||
|
|
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|
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|
|
}
|
||
|
|
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|
||
|
|
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||
|
|
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|
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|
|
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|
||
|
|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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||
|
|
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|
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||
|
|
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||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
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|
|
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||
|
|
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|
|
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|
}
|
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|
|
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|
|
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|
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|
|
}
|
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|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
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||
|
|
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|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Placeholder"
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||
|
|
}
|
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|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
inputTensorName: "x"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
|
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|
|
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|
|
}
|
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|
|
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|
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|
|
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||
|
|
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|
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|
|
}
|
||
|
|
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||
|
|
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||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
rule {
|
||
|
|
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|
|
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|
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|
|
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|
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|
|
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|
||
|
|
inputTensorName: "num_upper"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "minLowerT"
|
||
|
|
outputTensorName: "maxUpperT"
|
||
|
|
inputToOutput {
|
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|
|
key: "input"
|
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|
|
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|
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|
|
}
|
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|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
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|
|
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|
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|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
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|
|
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|
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|
|
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|
||
|
|
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|
|
}
|
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|
|
}
|
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|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
|
rule {
|
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|
|
ruleName: "ndarraymapping"
|
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|
|
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|
|
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|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
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|
|
key: "input"
|
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|
|
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|
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|
|
}
|
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|
|
inputToOutput {
|
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|
|
key: "y"
|
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|
|
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|
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|
|
}
|
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|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ApproximateEqual"
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|
|
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|
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|
|
rule {
|
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|
|
ruleName: "argdescriptorconstant"
|
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|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ApproximateEqual"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "stop_gradient"
|
||
|
|
inputFrameworkOpName: "StopGradient"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "StopGradient"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "StopGradient"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_add"
|
||
|
|
inputFrameworkOpName: "TensorScatterAdd"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "tensor"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
inputTensorName: "updates"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
outputTensorName: "updates"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "tensor"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorScatterAdd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "lock"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "lock"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "TensorScatterAdd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "checkIndices"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "checkIndices"
|
||
|
|
argType: BOOL
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "TensorScatterAdd"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "avgpool2d"
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "value"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "value"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringnotequalsadapterrule"
|
||
|
|
functionName: "stringnotequalsadapterrule"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "isNCHW"
|
||
|
|
inputFloatName: "data_format"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNCHW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNCHW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argIndex: 10
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "padding"
|
||
|
|
argType: STRING
|
||
|
|
argIndex: 8
|
||
|
|
stringValue: "SAME"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "kH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "kW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pH"
|
||
|
|
inputIntName: "pW"
|
||
|
|
inputIntName: "dW"
|
||
|
|
inputIntName: "dH"
|
||
|
|
inputIntName: "extraParam0"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dW"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dH"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 9
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dW"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dH"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 9
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dW"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dH"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 9
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dW"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dH"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 9
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dW"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "dH"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 9
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "unique_with_counts"
|
||
|
|
inputFrameworkOpName: "UniqueWithCountsV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "UniqueWithCountsV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "depthwise_conv2d"
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "filter"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "weights"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "weights"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringnotequalsadapterrule"
|
||
|
|
functionName: "stringnotequalsadapterrule"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "isNCHW"
|
||
|
|
inputFloatName: "data_format"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNCHW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNCHW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argIndex: 9
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "padding"
|
||
|
|
argType: STRING
|
||
|
|
argIndex: 8
|
||
|
|
stringValue: "SAME"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraysizeat"
|
||
|
|
functionName: "ndarraysizeat"
|
||
|
|
outputIntName: "kH"
|
||
|
|
inputFloatName: "filter"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kH"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "filter"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraysizeat"
|
||
|
|
functionName: "ndarraysizeat"
|
||
|
|
outputIntName: "kW"
|
||
|
|
inputFloatName: "filter"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kW"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "filter"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthwiseConv2dNative"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pH"
|
||
|
|
inputIntName: "pW"
|
||
|
|
inputIntName: "wFormat"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "wFormat"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 10
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "wFormat"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 10
|
||
|
|
}
|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "wFormat"
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
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||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "LogMatrixDeterminant"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "RealDiv"
|
||
|
|
rule {
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||
|
|
ruleName: "ndarraymapping"
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||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "RealDiv"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RealDiv"
|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "abs"
|
||
|
|
inputFrameworkOpName: "Abs"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
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|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Abs"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Abs"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Abs"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "identity"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
inputToOutput {
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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||
|
|
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|
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|
|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "kD"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kD"
|
||
|
|
value: "ksize"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kD"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "sH"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sH"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 3
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "sW"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sW"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 2
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "sD"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sD"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sD"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPool3D"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "tensorarraywritev3"
|
||
|
|
inputFrameworkOpName: "TensorArrayWriteV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayWriteV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "softmax_cross_entropy_loss_with_logits"
|
||
|
|
inputFrameworkOpName: "SoftmaxCrossEntropyWithLogits"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "labels"
|
||
|
|
inputTensorName: "features"
|
||
|
|
outputTensorName: "labels"
|
||
|
|
outputTensorName: "logits"
|
||
|
|
inputToOutput {
|
||
|
|
key: "labels"
|
||
|
|
value: "labels"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "logits"
|
||
|
|
value: "features"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SoftmaxCrossEntropyWithLogits"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "SoftmaxCrossEntropyWithLogits"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "segment_max"
|
||
|
|
inputFrameworkOpName: "SegmentMax"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
inputTensorName: "segment_ids"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "idxSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "idxSegments"
|
||
|
|
value: "segment_ids"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SegmentMax"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "conv3dnew"
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "filter"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "weights"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "weights"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "isNCDHW"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNCDHW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNCDHW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argType: STRING
|
||
|
|
argIndex: 13
|
||
|
|
stringValue: "NDHWC"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "paddingMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "paddingMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "paddingMode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "padding"
|
||
|
|
argType: STRING
|
||
|
|
argIndex: 12
|
||
|
|
stringValue: "SAME"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraysizeat"
|
||
|
|
functionName: "ndarraysizeat"
|
||
|
|
outputIntName: "kD"
|
||
|
|
inputFloatName: "filter"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kD"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kD"
|
||
|
|
transformerArgs {
|
||
|
|
name: "filter"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraysizeat"
|
||
|
|
functionName: "ndarraysizeat"
|
||
|
|
outputIntName: "kH"
|
||
|
|
inputFloatName: "filter"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kH"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "filter"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraysizeat"
|
||
|
|
functionName: "ndarraysizeat"
|
||
|
|
outputIntName: "kW"
|
||
|
|
inputFloatName: "filter"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kW"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "filter"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "sD"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sD"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sD"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "sH"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sH"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 2
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "sW"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sW"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 3
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 8
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "dH"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dH"
|
||
|
|
value: "dilations"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 3
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 11
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "dW"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dW"
|
||
|
|
value: "dilations"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
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|
||
|
|
argType: INT64
|
||
|
|
argIndex: 10
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv3D"
|
||
|
|
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|
||
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|
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|
||
|
|
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|
||
|
|
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||
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|
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|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
key: "dD"
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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||
|
|
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|
|
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|
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|
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|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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||
|
|
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||
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rule {
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||
|
|
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|
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|
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|
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|
|
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|
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inputToOutput {
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|
|
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|
|
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inputToOutput {
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|
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}
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inputToOutput {
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||
|
|
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|
|
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|
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|
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||
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|
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rule {
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||
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transformerArgs {
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||
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|
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transformerArgs {
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transformerArgs {
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||
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|
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transformerArgs {
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|
|
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|
|
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|
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|
|
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|
}
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|
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}
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|
|
}
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|
mappings {
|
||
|
|
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|
|
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|
|
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rule {
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|
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|
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inputToOutput {
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|
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|
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}
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|
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}
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mappings {
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|
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inputToOutput {
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|
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rule {
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|
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mappings {
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|
frameworkName: "tensorflow"
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|
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|
rule {
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|
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|
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inputToOutput {
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|
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}
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rule {
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|
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|
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|
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|
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|
transformerArgs {
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|
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|
transformerArgs {
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|
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|
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|
|
}
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|
}
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|
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|
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|
}
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mappings {
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|
|
frameworkName: "tensorflow"
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|
|
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|
|
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|
rule {
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|
|
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|
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|
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||
|
|
outputTensorName: "input"
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|
|
inputToOutput {
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|
|
key: "input"
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|
|
value: "x"
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|
|
}
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|
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||
|
|
inputFrameworkOpName: "Erfc"
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|
|
}
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|
|
rule {
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||
|
|
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|
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|
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|
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inputToOutput {
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|
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|
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|
}
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|
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|
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|
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rule {
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|
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|
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|
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|
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|
transformerArgs {
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||
|
|
key: "value"
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|
|
transformerArgs {
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|
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|
|
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|
|
}
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|
}
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|
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|
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|
|
}
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mappings {
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||
|
|
frameworkName: "tensorflow"
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||
|
|
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|
|
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|
rule {
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||
|
|
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|
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|
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||
|
|
inputTensorName: "y"
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||
|
|
outputTensorName: "input"
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||
|
|
outputTensorName: "y"
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||
|
|
inputToOutput {
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||
|
|
key: "input"
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|
|
value: "x"
|
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|
|
}
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|
|
inputToOutput {
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|
|
key: "y"
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||
|
|
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|
|
}
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|
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||
|
|
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||
|
|
}
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|
rule {
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||
|
|
ruleName: "argdescriptorconstant"
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|
|
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|
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||
|
|
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|
|
transformerArgs {
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||
|
|
key: "value"
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||
|
|
transformerArgs {
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||
|
|
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||
|
|
argType: BOOL
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||
|
|
}
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||
|
|
}
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||
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|
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|
|
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||
|
|
rule {
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||
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|
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||
|
|
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||
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|
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|
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|
inputToOutput {
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|
|
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|
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|
|
}
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|
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|
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|
|
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||
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mappings {
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||
|
|
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||
|
|
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||
|
|
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|
rule {
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|
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|
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|
|
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|
|
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|
|
inputToOutput {
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|
|
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|
|
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|
|
}
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|
|
inputToOutput {
|
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|
|
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|
|
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||
|
|
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||
|
|
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||
|
|
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|
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|
|
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|
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transformerArgs {
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|
|
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|
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|
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|
|
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|
|
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transformerArgs {
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|
|
name: "padValue"
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|
|
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|
|
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|
|
}
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||
|
|
transformerArgs {
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|
|
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|
|
transformerArgs {
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|
|
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||
|
|
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|
|
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|
|
transformerArgs {
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||
|
|
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|
|
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|
|
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||
|
|
}
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||
|
|
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|
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|
|
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|
|
mappings {
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|
|
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||
|
|
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||
|
|
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||
|
|
rule {
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|
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|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
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|
|
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|
|
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||
|
|
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|
|
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||
|
|
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|
||
|
|
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||
|
|
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||
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|
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||
|
|
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||
|
|
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|
|
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||
|
|
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||
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|
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|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
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|
|
}
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||
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|
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||
|
|
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||
|
|
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|
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|
|
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|
|
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|
|
}
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|
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indexOverrides {
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|
|
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|
|
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|
|
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|
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|
|
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||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
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||
|
|
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||
|
|
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||
|
|
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||
|
|
}
|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
rule {
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||
|
|
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||
|
|
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||
|
|
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|
||
|
|
inputTensorName: "size"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
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|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
rule {
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||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
|
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|
|
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|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
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|
|
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|
|
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|
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|
|
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|
||
|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
inputToOutput {
|
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|
|
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|
|
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|
|
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|
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|
|
inputToOutput {
|
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|
|
key: "indices"
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|
|
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|
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|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "check_numerics"
|
||
|
|
inputFrameworkOpName: "CheckNumericsV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "tensor"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "tensor"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "CheckNumericsV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "convertinputstringtondarray"
|
||
|
|
functionName: "convertinputstringtondarray"
|
||
|
|
inputStringAttrName: "message"
|
||
|
|
inputToOutput {
|
||
|
|
key: "message"
|
||
|
|
value: "message"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "CheckNumericsV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "select"
|
||
|
|
inputFrameworkOpName: "Select"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputTensorName: "t"
|
||
|
|
inputTensorName: "e"
|
||
|
|
outputTensorName: "cond"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "cond"
|
||
|
|
value: "condition"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "t"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "e"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Select"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "assign"
|
||
|
|
inputFrameworkOpName: "Assign"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "ref"
|
||
|
|
inputTensorName: "value"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "ref"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "value"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Assign"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "size_list"
|
||
|
|
inputFrameworkOpName: "TensorArraySize"
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "TensorArraySize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "rint"
|
||
|
|
inputFrameworkOpName: "Rint"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Rint"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Rint"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Rint"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "dilation2d"
|
||
|
|
inputFrameworkOpName: "Dilation2D"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "filter"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "weights"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "weights"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Dilation2D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
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|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "padding"
|
||
|
|
argType: STRING
|
||
|
|
stringValue: "SAME"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Dilation2D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
outputIntName: "rates"
|
||
|
|
inputToOutput {
|
||
|
|
key: "rates"
|
||
|
|
value: "rates"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Dilation2D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "strides"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Dilation2D"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "avgpool3dnew"
|
||
|
|
inputFrameworkOpName: "AvgPool3D"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "AvgPool3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
argType: INT64
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
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|
|
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||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
argType: STRING
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "kW"
|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
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|
||
|
|
argType: INT64
|
||
|
|
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|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AvgPool3D"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "kD"
|
||
|
|
value: "ksize"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kD"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
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|
|
argType: INT64
|
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|
|
}
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
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||
|
|
int64Value: 3
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||
|
|
argType: INT64
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|
|
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||
|
|
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|
||
|
|
}
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||
|
|
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||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
|
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||
|
|
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|
|
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||
|
|
inputToOutput {
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||
|
|
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|
|
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|
||
|
|
}
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||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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||
|
|
transformerArgs {
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||
|
|
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||
|
|
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||
|
|
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|
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|
|
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|
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|
|
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||
|
|
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|
|
rule {
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||
|
|
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||
|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
||
|
|
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||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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||
|
|
transformerArgs {
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||
|
|
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||
|
|
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|
|
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|
|
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||
|
|
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|
|
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|
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|
|
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||
|
|
}
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|
|
mappings {
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||
|
|
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||
|
|
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|
|
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|
|
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|
|
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||
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|
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||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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||
|
|
inputToOutput {
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|
|
key: "input"
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|
|
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|
|
}
|
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|
|
inputToOutput {
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|
|
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||
|
|
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|
||
|
|
}
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|
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||
|
|
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||
|
|
}
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|
|
rule {
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||
|
|
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|
|
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|
|
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||
|
|
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|
|
transformerArgs {
|
||
|
|
key: "value"
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||
|
|
transformerArgs {
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|
|
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|
|
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|
|
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|
|
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|
|
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||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
inputToOutput {
|
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|
|
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|
|
value: "T"
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|
|
}
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|
|
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|
|
inputFrameworkOpName: "Add"
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|
|
}
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||
|
|
}
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||
|
|
mappings {
|
||
|
|
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||
|
|
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|
|
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|
rule {
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|
|
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|
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|
|
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||
|
|
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||
|
|
inputToOutput {
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|
|
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|
|
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|
||
|
|
}
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||
|
|
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||
|
|
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||
|
|
}
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||
|
|
rule {
|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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|
|
transformerArgs {
|
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|
|
key: "value"
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|
|
transformerArgs {
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|
|
name: "inPlace"
|
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|
|
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|
|
}
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||
|
|
}
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||
|
|
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|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
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|
|
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|
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|
|
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|
|
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||
|
|
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|
|
inputToOutput {
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|
|
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|
|
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|
|
}
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|
|
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|
||
|
|
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|
||
|
|
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||
|
|
rule {
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||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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||
|
|
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||
|
|
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|
|
}
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||
|
|
}
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||
|
|
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||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "RightShift"
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||
|
|
}
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||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
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||
|
|
argType: BOOL
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||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "RightShift"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RightShift"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
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||
|
|
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|
||
|
|
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|
||
|
|
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||
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|
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||
|
|
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||
|
|
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||
|
|
rule {
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||
|
|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
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|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
}
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||
|
|
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||
|
|
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||
|
|
}
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||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
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|
|
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||
|
|
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||
|
|
}
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||
|
|
}
|
||
|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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|
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|
|
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||
|
|
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||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
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|
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|
|
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|
||
|
|
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|
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|
|
inputToOutput {
|
||
|
|
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|
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|
|
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||
|
|
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|
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|
|
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|
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|
|
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|
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|
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|
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|
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|
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|
|
opName: "gruCell"
|
||
|
|
inputFrameworkOpName: "GRUBlockCell"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "h_prev"
|
||
|
|
inputTensorName: "w_ru"
|
||
|
|
inputTensorName: "w_c"
|
||
|
|
inputTensorName: "b_ru"
|
||
|
|
inputTensorName: "b_c"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "hLast"
|
||
|
|
outputTensorName: "Wru"
|
||
|
|
outputTensorName: "Wc"
|
||
|
|
outputTensorName: "bru"
|
||
|
|
outputTensorName: "bc"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "hLast"
|
||
|
|
value: "h_prev"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wru"
|
||
|
|
value: "w_ru"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wc"
|
||
|
|
value: "w_c"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "bru"
|
||
|
|
value: "b_ru"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "bc"
|
||
|
|
value: "b_c"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "GRUBlockCell"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "randomuniform"
|
||
|
|
inputFrameworkOpName: "RandomUniform"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "shape"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
value: "shape"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "RandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "max"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "max"
|
||
|
|
doubleValue: 1.0
|
||
|
|
argType: DOUBLE
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "RandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "min"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "min"
|
||
|
|
argType: DOUBLE
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "RandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "datatypetoint"
|
||
|
|
functionName: "datatypetoint"
|
||
|
|
outputIntName: "dtype"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomUniform"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "seed"
|
||
|
|
outputIntName: "seed"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "seed"
|
||
|
|
value: "seed"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomUniform"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "bitwise_and"
|
||
|
|
inputFrameworkOpName: "BitwiseAnd"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BitwiseAnd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BitwiseAnd"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "enter"
|
||
|
|
inputFrameworkOpName: "Enter"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Enter"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputStringAttrName: "frame_name"
|
||
|
|
outputStringAttrName: "frameName"
|
||
|
|
inputBooleanName: "is_constant"
|
||
|
|
outputBooleanName: "isConstant"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isConstant"
|
||
|
|
value: "is_constant"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "frameName"
|
||
|
|
value: "frame_name"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Enter"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "sin"
|
||
|
|
inputFrameworkOpName: "Sin"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Sin"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Sin"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Sin"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "unique"
|
||
|
|
inputFrameworkOpName: "Unique"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Unique"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "roll"
|
||
|
|
inputFrameworkOpName: "Roll"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "axis"
|
||
|
|
inputTensorName: "shift"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "dimensions"
|
||
|
|
outputTensorName: "shiftsI"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "axis"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "shiftsI"
|
||
|
|
value: "shift"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Roll"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
outputIntName: "shift"
|
||
|
|
inputToOutput {
|
||
|
|
key: "shift"
|
||
|
|
value: "shift"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Roll"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "in_top_k"
|
||
|
|
inputFrameworkOpName: "InTopK"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "targets"
|
||
|
|
inputTensorName: "predictions"
|
||
|
|
outputTensorName: "target"
|
||
|
|
outputTensorName: "predictions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "target"
|
||
|
|
value: "targets"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "predictions"
|
||
|
|
value: "predictions"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "InTopK"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "k"
|
||
|
|
outputIntName: "k"
|
||
|
|
inputToOutput {
|
||
|
|
key: "k"
|
||
|
|
value: "k"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "InTopK"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "sorted"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "sorted"
|
||
|
|
boolValue: true
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "InTopK"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "reverse_sequence"
|
||
|
|
inputFrameworkOpName: "ReverseSequence"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "seq_lengths"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "seqLengths"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "seqLengths"
|
||
|
|
value: "seq_lengths"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ReverseSequence"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "batch_dim"
|
||
|
|
inputIntName: "seq_dim"
|
||
|
|
outputIntName: "batchDim"
|
||
|
|
outputIntName: "seqDim"
|
||
|
|
inputToOutput {
|
||
|
|
key: "batchDim"
|
||
|
|
value: "batch_dim"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "seqDim"
|
||
|
|
value: "seq_dim"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "ReverseSequence"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "unsorted_segment_min"
|
||
|
|
inputFrameworkOpName: "UnsortedSegmentMin"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
inputTensorName: "segment_ids"
|
||
|
|
inputTensorName: "num_segments"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "idxSegments"
|
||
|
|
outputTensorName: "numSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "idxSegments"
|
||
|
|
value: "segment_ids"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "numSegments"
|
||
|
|
value: "num_segments"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "UnsortedSegmentMin"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "numSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "numSegments"
|
||
|
|
value: "num_segments"
|
||
|
|
}
|
||
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|
|
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|
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|
|
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|
|
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|
|
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transformerArgs {
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|
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mappings {
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mappings {
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|
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inputToOutput {
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|
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|
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|
}
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|
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|
inputFrameworkOpName: "ScatterNdUpdate"
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|
|
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|
}
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mappings {
|
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|
|
frameworkName: "tensorflow"
|
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|
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|
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rule {
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inputToOutput {
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mappings {
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|
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|
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rule {
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transformerArgs {
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transformerArgs {
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|
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|
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}
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mappings {
|
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|
frameworkName: "tensorflow"
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rule {
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|
ruleName: "ndarraymapping"
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inputToOutput {
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|
}
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inputToOutput {
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|
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|
|
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|
}
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|
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|
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|
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rule {
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transformerArgs {
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transformerArgs {
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mappings {
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|
frameworkName: "tensorflow"
|
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rule {
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|
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inputToOutput {
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|
|
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inputToOutput {
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|
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rule {
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|
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|
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|
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|
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rule {
|
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|
|
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|
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|
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|
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|
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inputToOutput {
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|
|
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|
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|
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|
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|
|
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|
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mappings {
|
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|
|
frameworkName: "tensorflow"
|
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|
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|
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|
|
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rule {
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|
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|
|
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|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
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|
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|
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|
|
frameworkName: "tensorflow"
|
||
|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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rule {
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|
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rule {
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|
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|
|
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|
|
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|
|
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|
|
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|
|
inputToOutput {
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|
|
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|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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rule {
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|
|
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|
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|
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|
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rule {
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|
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|
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transformerArgs {
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|
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transformerArgs {
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|
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|
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|
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|
|
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mappings {
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|
|
frameworkName: "tensorflow"
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||
|
|
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|
||
|
|
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||
|
|
rule {
|
||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
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|
|
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||
|
|
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|
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|
|
inputToOutput {
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
rule {
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|
|
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|
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|
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|
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|
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|
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|
mappings {
|
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|
|
frameworkName: "tensorflow"
|
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|
|
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|
||
|
|
inputFrameworkOpName: "Log1p"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Log1p"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Log1p"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Log1p"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "matrix_set_diag"
|
||
|
|
inputFrameworkOpName: "MatrixSetDiag"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "diagonal"
|
||
|
|
outputTensorName: "input"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "diagonal"
|
||
|
|
value: "diagonal"
|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "MatrixSetDiag"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchMatrixSetDiag"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "dynamic_partition"
|
||
|
|
inputFrameworkOpName: "DynamicPartition"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "partitions"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "DynamicPartition"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "num_partitions"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "numPartitions"
|
||
|
|
value: "num_partitions"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "DynamicPartition"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "mod"
|
||
|
|
inputFrameworkOpName: "Mod"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Mod"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Mod"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Mod"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_mul"
|
||
|
|
inputFrameworkOpName: "ScatterMul"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
inputTensorName: "updates"
|
||
|
|
inputTensorName: "ref"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
outputTensorName: "updates"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "ref"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ScatterMul"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "broadcast_to"
|
||
|
|
inputFrameworkOpName: "BroadcastTo"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "shape"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
value: "shape"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BroadcastTo"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "random_poisson"
|
||
|
|
inputFrameworkOpName: "RandomPoissonV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "shape"
|
||
|
|
inputTensorName: "rate"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
outputTensorName: "lambda"
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "lambda"
|
||
|
|
value: "rate"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "RandomPoissonV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
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|
||
|
|
outputIntName: "seed"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomPoissonV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "asin"
|
||
|
|
inputFrameworkOpName: "Asin"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Asin"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Asin"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Asin"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "space_to_depth"
|
||
|
|
inputFrameworkOpName: "SpaceToDepth"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
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|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "SpaceToDepth"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "block_size"
|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "SpaceToDepth"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "isNHWC"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNHWC"
|
||
|
|
value: "data_format"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNHWC"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "tile"
|
||
|
|
inputFrameworkOpName: "Tile"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "multiples"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "reps_vector"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "reps_vector"
|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Tile"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
inputIntName: "dimensions"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dimensions"
|
||
|
|
argType: INT64
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Tile"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "is_static_reps"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "is_static_reps"
|
||
|
|
boolValue: true
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Tile"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "depth_to_space"
|
||
|
|
inputFrameworkOpName: "DepthToSpace"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "DepthToSpace"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "block_size"
|
||
|
|
outputIntName: "block_size"
|
||
|
|
inputToOutput {
|
||
|
|
key: "block_size"
|
||
|
|
value: "block_size"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "DepthToSpace"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "isNHWC"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNHWC"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNHWC"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argType: STRING
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "NHWC"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DepthToSpace"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "invert_permutation"
|
||
|
|
inputFrameworkOpName: "InvertPermutation"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "InvertPermutation"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "InvertPermutation"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "InvertPermutation"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "crop_and_resize"
|
||
|
|
inputFrameworkOpName: "CropAndResize"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "image"
|
||
|
|
inputTensorName: "boxes"
|
||
|
|
inputTensorName: "box_ind"
|
||
|
|
inputTensorName: "crop_size"
|
||
|
|
outputTensorName: "image"
|
||
|
|
outputTensorName: "boxes"
|
||
|
|
outputTensorName: "boxIndexes"
|
||
|
|
outputTensorName: "newImageSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "image"
|
||
|
|
value: "image"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "boxes"
|
||
|
|
value: "boxes"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "boxIndexes"
|
||
|
|
value: "box_ind"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "newImageSize"
|
||
|
|
value: "crop_size"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "CropAndResize"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringtoindex"
|
||
|
|
functionName: "stringtoindex"
|
||
|
|
inputStringAttrName: "method"
|
||
|
|
outputIntName: "method"
|
||
|
|
inputFloatName: "bilinear"
|
||
|
|
inputFloatName: "nearest"
|
||
|
|
inputToOutput {
|
||
|
|
key: "method"
|
||
|
|
value: "method"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "method"
|
||
|
|
transformerArgs {
|
||
|
|
name: "bilinear"
|
||
|
|
stringValue: "bilinear"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "nearest"
|
||
|
|
stringValue: "nearest"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "method"
|
||
|
|
transformerArgs {
|
||
|
|
name: "bilinear"
|
||
|
|
stringValue: "bilinear"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "nearest"
|
||
|
|
stringValue: "nearest"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "CropAndResize"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "extrapolation_value"
|
||
|
|
outputDoubleName: "extrapolationVal"
|
||
|
|
inputToOutput {
|
||
|
|
key: "extrapolationVal"
|
||
|
|
value: "extrapolation_value"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "CropAndResize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "read_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayRead"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayRead"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "importDataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "importDataType"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayRead"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_nd"
|
||
|
|
inputFrameworkOpName: "ScatterNd"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
inputTensorName: "updates"
|
||
|
|
inputTensorName: "shape"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
outputTensorName: "updates"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
value: "shape"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ScatterNd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "lock"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "lock"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ScatterNd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "checkIndices"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "checkIndices"
|
||
|
|
argType: BOOL
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ScatterNd"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "strided_slice"
|
||
|
|
inputFrameworkOpName: "StridedSlice"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "begin"
|
||
|
|
inputTensorName: "end"
|
||
|
|
inputTensorName: "strides"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "v_begin"
|
||
|
|
outputTensorName: "v_end"
|
||
|
|
outputTensorName: "v_stride"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "v_begin"
|
||
|
|
value: "begin"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "v_end"
|
||
|
|
value: "end"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "v_stride"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "StridedSlice"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "begin_mask"
|
||
|
|
inputIntName: "end_mask"
|
||
|
|
inputIntName: "ellipsis_mask"
|
||
|
|
inputIntName: "new_axis_mask"
|
||
|
|
inputIntName: "shrink_axis_mask"
|
||
|
|
outputIntName: "begin_mask"
|
||
|
|
outputIntName: "end_mask"
|
||
|
|
outputIntName: "ellipsis_mask"
|
||
|
|
outputIntName: "new_axis_mask"
|
||
|
|
outputIntName: "shrink_axis_mask"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "begin_mask"
|
||
|
|
value: "begin_mask"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "end_mask"
|
||
|
|
value: "end_mask"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "ellipsis_mask"
|
||
|
|
value: "ellipsis_mask"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "new_axis_mask"
|
||
|
|
value: "new_axis_mask"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "shrink_axis_mask"
|
||
|
|
value: "shrink_axis_mask"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "StridedSlice"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayScatter"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayScatter"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayScatter"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "size_list"
|
||
|
|
inputFrameworkOpName: "TensorArraySizeV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArraySizeV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "size_list"
|
||
|
|
inputFrameworkOpName: "TensorArraySizeV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArraySizeV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "next_iteration"
|
||
|
|
inputFrameworkOpName: "NextIteration"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NextIteration"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "solve"
|
||
|
|
inputFrameworkOpName: "MatrixSolve"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "matrix"
|
||
|
|
inputTensorName: "rhs"
|
||
|
|
outputTensorName: "a"
|
||
|
|
outputTensorName: "b"
|
||
|
|
inputToOutput {
|
||
|
|
key: "a"
|
||
|
|
value: "matrix"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "b"
|
||
|
|
value: "rhs"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "MatrixSolve"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputBooleanName: "adjoint"
|
||
|
|
outputBooleanName: "useAdjoint"
|
||
|
|
inputToOutput {
|
||
|
|
key: "useAdjoint"
|
||
|
|
value: "adjoint"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "MatrixSolve"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "fused_batch_norm"
|
||
|
|
inputFrameworkOpName: "FusedBatchNorm"
|
||
|
|
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|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "scale"
|
||
|
|
inputTensorName: "offset"
|
||
|
|
inputTensorName: "mean"
|
||
|
|
inputTensorName: "variance"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "scale"
|
||
|
|
outputTensorName: "offset"
|
||
|
|
outputTensorName: "mean"
|
||
|
|
outputTensorName: "variance"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scale"
|
||
|
|
value: "scale"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "offset"
|
||
|
|
value: "offset"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "mean"
|
||
|
|
value: "mean"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "variance"
|
||
|
|
value: "variance"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FusedBatchNorm"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "epsilon"
|
||
|
|
outputDoubleName: "epsilon"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "epsilon"
|
||
|
|
value: "epsilon"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FusedBatchNorm"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "invertbooleannumber"
|
||
|
|
functionName: "invertbooleannumber"
|
||
|
|
outputIntName: "isTraining"
|
||
|
|
inputBooleanName: "is_training"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isTraining"
|
||
|
|
value: "is_training"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FusedBatchNorm"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dataFormat"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataFormat"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dataFormat"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argType: STRING
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "FusedBatchNorm"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_max"
|
||
|
|
inputFrameworkOpName: "TensorScatterMax"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "tensor"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
inputTensorName: "updates"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
outputTensorName: "updates"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "tensor"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorScatterMax"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "greater_equal"
|
||
|
|
inputFrameworkOpName: "GreaterEqual"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "GreaterEqual"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "GreaterEqual"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "GreaterEqual"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_nd_sub"
|
||
|
|
inputFrameworkOpName: "ScatterNdSub"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
inputTensorName: "updates"
|
||
|
|
inputTensorName: "ref"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
outputTensorName: "updates"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "ref"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ScatterNdSub"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "equals"
|
||
|
|
inputFrameworkOpName: "Equal"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Equal"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Equal"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "read_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayReadV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayReadV3"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "importDataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "importDataType"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayReadV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "floormod"
|
||
|
|
inputFrameworkOpName: "FloorMod"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FloorMod"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "FloorMod"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FloorMod"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "read_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayReadV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayReadV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "importDataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "importDataType"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayReadV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "biasadd"
|
||
|
|
inputFrameworkOpName: "BiasAdd"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "value"
|
||
|
|
inputTensorName: "bias"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "bias"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "value"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "bias"
|
||
|
|
value: "bias"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BiasAdd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputBooleanName: "nchw"
|
||
|
|
inputToOutput {
|
||
|
|
key: "nchw"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "nchw"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argType: STRING
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BiasAdd"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "identity"
|
||
|
|
inputFrameworkOpName: "Identity"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Identity"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Identity"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Identity"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "unstack"
|
||
|
|
inputFrameworkOpName: "Unpack"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "value"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "value"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Unpack"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "axis"
|
||
|
|
inputIntName: "num"
|
||
|
|
outputIntName: "dimensions"
|
||
|
|
outputIntName: "num"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "axis"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "num"
|
||
|
|
value: "num"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Unpack"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "exit"
|
||
|
|
inputFrameworkOpName: "Exit"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Exit"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "add"
|
||
|
|
inputFrameworkOpName: "AddV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "AddV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AddV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "AddV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "tanh"
|
||
|
|
inputFrameworkOpName: "Tanh"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Tanh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Tanh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Tanh"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "toggle_bits"
|
||
|
|
inputFrameworkOpName: "Invert"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Invert"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "lstmBlockCell"
|
||
|
|
inputFrameworkOpName: "LSTMBlockCell"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "cs_prev"
|
||
|
|
inputTensorName: "h_prev"
|
||
|
|
inputTensorName: "w"
|
||
|
|
inputTensorName: "wci"
|
||
|
|
inputTensorName: "wcf"
|
||
|
|
inputTensorName: "wco"
|
||
|
|
inputTensorName: "b"
|
||
|
|
outputTensorName: "xt"
|
||
|
|
outputTensorName: "cLast"
|
||
|
|
outputTensorName: "yLast"
|
||
|
|
outputTensorName: "W"
|
||
|
|
outputTensorName: "Wci"
|
||
|
|
outputTensorName: "Wcf"
|
||
|
|
outputTensorName: "Wco"
|
||
|
|
outputTensorName: "b"
|
||
|
|
inputToOutput {
|
||
|
|
key: "xt"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "cLast"
|
||
|
|
value: "cs_prev"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "yLast"
|
||
|
|
value: "h_prev"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "W"
|
||
|
|
value: "w"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wci"
|
||
|
|
value: "wci"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wcf"
|
||
|
|
value: "wcf"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wco"
|
||
|
|
value: "wco"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "b"
|
||
|
|
value: "b"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "LSTMBlockCell"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "forget_bias"
|
||
|
|
inputFloatName: "cell_clip"
|
||
|
|
outputDoubleName: "forgetBias"
|
||
|
|
outputDoubleName: "clippingCellValue"
|
||
|
|
inputToOutput {
|
||
|
|
key: "forgetBias"
|
||
|
|
value: "forget_bias"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "clippingCellValue"
|
||
|
|
value: "cell_clip"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "LSTMBlockCell"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "invertbooleannumber"
|
||
|
|
functionName: "invertbooleannumber"
|
||
|
|
outputIntName: "peephole"
|
||
|
|
inputBooleanName: "use_peephole"
|
||
|
|
inputToOutput {
|
||
|
|
key: "peephole"
|
||
|
|
value: "use_peephole"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "LSTMBlockCell"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "log"
|
||
|
|
inputFrameworkOpName: "Log"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Log"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Log"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Log"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "non_max_suppression_v3"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV4"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "boxes"
|
||
|
|
inputTensorName: "scores"
|
||
|
|
inputTensorName: "max_output_size"
|
||
|
|
inputTensorName: "iou_threshold"
|
||
|
|
inputTensorName: "score_threshold"
|
||
|
|
outputTensorName: "boxes"
|
||
|
|
outputTensorName: "scales"
|
||
|
|
outputTensorName: "maxOutSize"
|
||
|
|
outputTensorName: "iouThreshold"
|
||
|
|
outputTensorName: "scoreThreshold"
|
||
|
|
inputToOutput {
|
||
|
|
key: "boxes"
|
||
|
|
value: "boxes"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scales"
|
||
|
|
value: "scores"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "iouThreshold"
|
||
|
|
value: "iou_threshold"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scoreThreshold"
|
||
|
|
value: "score_threshold"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV4"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "maxOutputSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutputSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV4"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "less_equal"
|
||
|
|
inputFrameworkOpName: "LessEqual"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "LessEqual"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "LessEqual"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "LessEqual"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "non_max_suppression"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "boxes"
|
||
|
|
inputTensorName: "scores"
|
||
|
|
inputTensorName: "iou_threshold"
|
||
|
|
inputTensorName: "max_output_size"
|
||
|
|
outputTensorName: "boxes"
|
||
|
|
outputTensorName: "scales"
|
||
|
|
outputTensorName: "iouThreshold"
|
||
|
|
outputTensorName: "maxOutputSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "boxes"
|
||
|
|
value: "boxes"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scales"
|
||
|
|
value: "scores"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "iouThreshold"
|
||
|
|
value: "iou_threshold"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutputSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "scoreThreshold"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "scoreThreshold"
|
||
|
|
doubleValue: 0.5
|
||
|
|
argType: DOUBLE
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
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|
||
|
|
outputIntName: "maxOutputSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutputSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "non_max_suppression_v3"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "boxes"
|
||
|
|
inputTensorName: "scores"
|
||
|
|
inputTensorName: "max_output_size"
|
||
|
|
inputTensorName: "iou_threshold"
|
||
|
|
inputTensorName: "score_threshold"
|
||
|
|
outputTensorName: "boxes"
|
||
|
|
outputTensorName: "scales"
|
||
|
|
outputTensorName: "maxOutSize"
|
||
|
|
outputTensorName: "iouThreshold"
|
||
|
|
outputTensorName: "scoreThreshold"
|
||
|
|
inputToOutput {
|
||
|
|
key: "boxes"
|
||
|
|
value: "boxes"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scales"
|
||
|
|
value: "scores"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "iouThreshold"
|
||
|
|
value: "iou_threshold"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scoreThreshold"
|
||
|
|
value: "score_threshold"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV3"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutputSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "onehot"
|
||
|
|
inputFrameworkOpName: "OneHot"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "OneHot"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "depth"
|
||
|
|
outputDoubleName: "on"
|
||
|
|
outputDoubleName: "off"
|
||
|
|
inputToOutput {
|
||
|
|
key: "on"
|
||
|
|
value: "on_value"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "off"
|
||
|
|
value: "off_value"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "depth"
|
||
|
|
value: "depth"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "OneHot"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
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|
||
|
|
outputIntName: "dimensions"
|
||
|
|
outputIntName: "dataType"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "axis"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "OneHot"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "transpose"
|
||
|
|
inputFrameworkOpName: "Transpose"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "perm"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "permuteDims"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "permuteDims"
|
||
|
|
value: "perm"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Transpose"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Transpose"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "square"
|
||
|
|
inputFrameworkOpName: "Square"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Square"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Square"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Square"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "compare_and_bitpack"
|
||
|
|
inputFrameworkOpName: "CompareAndBitpack"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "threshold"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "threshold"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "CompareAndBitpack"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "segment_min"
|
||
|
|
inputFrameworkOpName: "SegmentMin"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
inputTensorName: "segment_ids"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "idxSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "idxSegments"
|
||
|
|
value: "segment_ids"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SegmentMin"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "switch"
|
||
|
|
inputFrameworkOpName: "Switch"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
inputTensorName: "pred"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "predicate"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "predicate"
|
||
|
|
value: "pred"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Switch"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "unsorted_segment_max"
|
||
|
|
inputFrameworkOpName: "UnsortedSegmentMax"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
inputTensorName: "segment_ids"
|
||
|
|
inputTensorName: "num_segments"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "idxSegments"
|
||
|
|
outputTensorName: "numSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "idxSegments"
|
||
|
|
value: "segment_ids"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "numSegments"
|
||
|
|
value: "num_segments"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "UnsortedSegmentMax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "numSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "numSegments"
|
||
|
|
value: "num_segments"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "UnsortedSegmentMax"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "segment_sum"
|
||
|
|
inputFrameworkOpName: "SegmentSum"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
inputTensorName: "segment_ids"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "idxSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "idxSegments"
|
||
|
|
value: "segment_ids"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SegmentSum"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "resize_bilinear"
|
||
|
|
inputFrameworkOpName: "ResizeBilinear"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "images"
|
||
|
|
inputTensorName: "size"
|
||
|
|
outputTensorName: "image"
|
||
|
|
outputTensorName: "newImageSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "image"
|
||
|
|
value: "images"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "newImageSize"
|
||
|
|
value: "size"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ResizeBilinear"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputBooleanName: "align_corners"
|
||
|
|
inputBooleanName: "half_pixel_centers"
|
||
|
|
outputBooleanName: "alignCorners"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "alignCorners"
|
||
|
|
value: "align_corners"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "halfPixelCenter"
|
||
|
|
value: "half_pixel_centers"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "ResizeBilinear"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "softmax"
|
||
|
|
inputFrameworkOpName: "Softmax"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "logits"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "logits"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Softmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "dimension"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dimension"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dimension"
|
||
|
|
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|
||
|
|
argType: INT64
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
inputToOutput {
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||
|
|
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|
||
|
|
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|
|
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|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Erf"
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||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
inputTensorName: "x"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Erf"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Erf"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Erf"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "split_list"
|
||
|
|
inputFrameworkOpName: "TensorArraySplitV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
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|
|
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|
||
|
|
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||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "TensorArraySplitV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "relu"
|
||
|
|
inputFrameworkOpName: "Relu"
|
||
|
|
rule {
|
||
|
|
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||
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|
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|
|
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||
|
|
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|
|
inputToOutput {
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|
|
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||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Relu"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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|
||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "cutoff"
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||
|
|
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||
|
|
}
|
||
|
|
}
|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
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||
|
|
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||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
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||
|
|
argType: BOOL
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||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Relu"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "ceil"
|
||
|
|
inputFrameworkOpName: "Ceil"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
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|
|
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|
||
|
|
outputTensorName: "input"
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||
|
|
inputToOutput {
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|
|
key: "input"
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||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Ceil"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
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||
|
|
inputDataTypeName: "T"
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||
|
|
outputDataTypeName: "dataType"
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||
|
|
inputToOutput {
|
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|
|
key: "dataType"
|
||
|
|
value: "T"
|
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|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Ceil"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Ceil"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "l2_loss"
|
||
|
|
inputFrameworkOpName: "L2Loss"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
key: "input"
|
||
|
|
value: "t"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "L2Loss"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
outputDataTypeName: "dtype"
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||
|
|
inputToOutput {
|
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|
|
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||
|
|
value: "T"
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|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "L2Loss"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "switch"
|
||
|
|
inputFrameworkOpName: "If"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "input"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "predicate"
|
||
|
|
value: "cond"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "If"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "cast"
|
||
|
|
inputFrameworkOpName: "Cast"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Cast"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "DstT"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "DstT"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Cast"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "datatypetoint"
|
||
|
|
functionName: "datatypetoint"
|
||
|
|
outputIntName: "dst"
|
||
|
|
inputDataTypeName: "DstT"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dst"
|
||
|
|
value: "DstT"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Cast"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "minimum"
|
||
|
|
inputFrameworkOpName: "Minimum"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Minimum"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "non_max_suppression"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppression"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "boxes"
|
||
|
|
inputTensorName: "scores"
|
||
|
|
inputTensorName: "max_output_size"
|
||
|
|
outputTensorName: "boxes"
|
||
|
|
outputTensorName: "scales"
|
||
|
|
outputTensorName: "maxOutputSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "boxes"
|
||
|
|
value: "boxes"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scales"
|
||
|
|
value: "scores"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutputSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppression"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "scoreThreshold"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "scoreThreshold"
|
||
|
|
doubleValue: 0.5
|
||
|
|
argType: DOUBLE
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "NonMaxSuppression"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "iou_threshold"
|
||
|
|
inputToOutput {
|
||
|
|
key: "iouThreshold"
|
||
|
|
value: "iou_threshold"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppression"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "maxOutputSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutputSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppression"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "lstmBlock"
|
||
|
|
inputFrameworkOpName: "BlockLSTM"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "seq_len_max"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "cs_prev"
|
||
|
|
inputTensorName: "h_prev"
|
||
|
|
inputTensorName: "w"
|
||
|
|
inputTensorName: "wci"
|
||
|
|
inputTensorName: "wcf"
|
||
|
|
inputTensorName: "wco"
|
||
|
|
inputTensorName: "b"
|
||
|
|
outputTensorName: "maxTSLength"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "cLast"
|
||
|
|
outputTensorName: "yLast"
|
||
|
|
outputTensorName: "W"
|
||
|
|
outputTensorName: "Wci"
|
||
|
|
outputTensorName: "Wcf"
|
||
|
|
outputTensorName: "Wco"
|
||
|
|
outputTensorName: "b"
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxTSLength"
|
||
|
|
value: "seq_len_max"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "cLast"
|
||
|
|
value: "cs_prev"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "yLast"
|
||
|
|
value: "h_prev"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "W"
|
||
|
|
value: "w"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wci"
|
||
|
|
value: "wci"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wcf"
|
||
|
|
value: "wcf"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wco"
|
||
|
|
value: "wco"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "b"
|
||
|
|
value: "b"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BlockLSTM"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "forget_bias"
|
||
|
|
inputFloatName: "cell_clip"
|
||
|
|
outputDoubleName: "forgetBias"
|
||
|
|
outputDoubleName: "clippingCellValue"
|
||
|
|
inputToOutput {
|
||
|
|
key: "forgetBias"
|
||
|
|
value: "forget_bias"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "clippingCellValue"
|
||
|
|
value: "cell_clip"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "BlockLSTM"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "invertbooleannumber"
|
||
|
|
functionName: "invertbooleannumber"
|
||
|
|
outputIntName: "peephole"
|
||
|
|
inputBooleanName: "use_peephole"
|
||
|
|
inputToOutput {
|
||
|
|
key: "peephole"
|
||
|
|
value: "use_peephole"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "BlockLSTM"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "dataFormat"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dataFormat"
|
||
|
|
argType: INT64
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BlockLSTM"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "shape_of"
|
||
|
|
inputFrameworkOpName: "Shape"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Shape"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Shape"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "out_type"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "out_type"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Shape"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "check_numerics"
|
||
|
|
inputFrameworkOpName: "CheckNumerics"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "tensor"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "tensor"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "CheckNumerics"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "convertinputstringtondarray"
|
||
|
|
functionName: "convertinputstringtondarray"
|
||
|
|
inputStringAttrName: "message"
|
||
|
|
inputToOutput {
|
||
|
|
key: "message"
|
||
|
|
value: "message"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "CheckNumerics"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "reduce_max"
|
||
|
|
inputFrameworkOpName: "Max"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "reduction_indices"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Max"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputBooleanName: "keep_dims"
|
||
|
|
outputBooleanName: "keepDims"
|
||
|
|
inputToOutput {
|
||
|
|
key: "keepDims"
|
||
|
|
value: "keep_dims"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Max"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
outputIntName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Max"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "tensorarrayv3"
|
||
|
|
inputFrameworkOpName: "TensorArrayV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "datatypetoint"
|
||
|
|
functionName: "datatypetoint"
|
||
|
|
outputIntName: "dataType"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_max"
|
||
|
|
inputFrameworkOpName: "ScatterMax"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "ref"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
inputTensorName: "updates"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
outputTensorName: "updates"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "ref"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ScatterMax"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "isnan"
|
||
|
|
inputFrameworkOpName: "IsNan"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "IsNan"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "IsNan"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "gather_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayGather"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayGather"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayGather"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "bincount"
|
||
|
|
inputFrameworkOpName: "Bincount"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "weights"
|
||
|
|
inputTensorName: "arr"
|
||
|
|
inputTensorName: "size"
|
||
|
|
outputTensorName: "weights"
|
||
|
|
outputTensorName: "values"
|
||
|
|
outputTensorName: "min"
|
||
|
|
inputToOutput {
|
||
|
|
key: "weights"
|
||
|
|
value: "weights"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "values"
|
||
|
|
value: "arr"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "min"
|
||
|
|
value: "size"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Bincount"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
outputIntName: "outputType"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
inputToOutput {
|
||
|
|
key: "outputType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Bincount"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "space_to_batch_nd"
|
||
|
|
inputFrameworkOpName: "SpaceToBatchND"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "block_shape"
|
||
|
|
inputTensorName: "paddings"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "blockShape"
|
||
|
|
outputTensorName: "padding"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "blockShape"
|
||
|
|
value: "block_shape"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "padding"
|
||
|
|
value: "paddings"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SpaceToBatchND"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
outputIntName: "blocks"
|
||
|
|
inputToOutput {
|
||
|
|
key: "blocks"
|
||
|
|
value: "block_shape"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "SpaceToBatchND"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "SpaceToBatchND"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "reduce_prod"
|
||
|
|
inputFrameworkOpName: "Prod"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "reduction_indices"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Prod"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputBooleanName: "keep_dims"
|
||
|
|
outputBooleanName: "keepDims"
|
||
|
|
inputToOutput {
|
||
|
|
key: "keepDims"
|
||
|
|
value: "keep_dims"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
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|
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|
|
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|
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|
||
|
|
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|
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|
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|
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|
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|
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|
||
|
|
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|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
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|
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||
|
|
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|
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|
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|
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inputToOutput {
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|
|
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|
|
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||
|
|
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|
|
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|
||
|
|
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||
|
|
}
|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "BatchMatMulV2"
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|
|
rule {
|
||
|
|
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|
||
|
|
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|
|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
inputToOutput {
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||
|
|
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||
|
|
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|
||
|
|
}
|
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|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
|
}
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|
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||
|
|
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|
|
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|
rule {
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|
|
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|
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|
transformerArgs {
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||
|
|
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|
transformerArgs {
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|
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|
|
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|
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|
|
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|
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|
|
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|
rule {
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|
|
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|
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|
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|
|
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||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
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||
|
|
name: "beta"
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
}
|
||
|
|
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|
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|
|
inputFrameworkOpName: "BatchMatMulV2"
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||
|
|
}
|
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|
|
rule {
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
inputToOutput {
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
||
|
|
inputFrameworkOpName: "BatchMatMulV2"
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||
|
|
}
|
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|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "transZ"
|
||
|
|
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|
||
|
|
argIndex: 2
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchMatMulV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "unique_with_counts"
|
||
|
|
inputFrameworkOpName: "UniqueWithCounts"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "UniqueWithCounts"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "randomuniform"
|
||
|
|
inputFrameworkOpName: "RandomUniformInt"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "shape"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
value: "shape"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "RandomUniformInt"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "seed"
|
||
|
|
outputIntName: "seed"
|
||
|
|
inputToOutput {
|
||
|
|
key: "seed"
|
||
|
|
value: "seed"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomUniformInt"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "min"
|
||
|
|
value: "minval"
|
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|
|
}
|
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|
|
inputToOutput {
|
||
|
|
key: "max"
|
||
|
|
value: "maxval"
|
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|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomUniformInt"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "Tout"
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|
|
}
|
||
|
|
ruleType: "attribute"
|
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|
|
inputFrameworkOpName: "RandomUniformInt"
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||
|
|
}
|
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|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
inputDataTypeName: "Tout"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "Tout"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomUniformInt"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "selu"
|
||
|
|
inputFrameworkOpName: "Selu"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "features"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Selu"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
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||
|
|
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|
|
}
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||
|
|
}
|
||
|
|
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|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "argmin"
|
||
|
|
inputFrameworkOpName: "ArgMin"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
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||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "dimension"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "ArgMin"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
|
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|
||
|
|
}
|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
outputBooleanName: "alignCorners"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Atanh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Atanh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "split_v"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "value"
|
||
|
|
inputTensorName: "size_splits"
|
||
|
|
inputTensorName: "split_dim"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "sizes"
|
||
|
|
outputTensorName: "_a"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "_a"
|
||
|
|
value: "split_dim"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SplitV"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "split_dim"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "SplitV"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
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|
||
|
|
outputIntName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "split_dim"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "SplitV"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "mirror_pad"
|
||
|
|
inputFrameworkOpName: "MirrorPad"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "paddings"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "paddings"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "paddings"
|
||
|
|
value: "paddings"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "MirrorPad"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringnotequalsadapterrule"
|
||
|
|
functionName: "stringnotequalsadapterrule"
|
||
|
|
inputStringAttrName: "mode"
|
||
|
|
outputIntName: "mode"
|
||
|
|
inputFloatName: "mode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "mode"
|
||
|
|
value: "mode"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "mode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "mode"
|
||
|
|
stringValue: "REFLECT"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MirrorPad"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "isSymmetric"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "isSymmetric"
|
||
|
|
boolValue: true
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MirrorPad"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "shapes_of"
|
||
|
|
inputFrameworkOpName: "ShapeN"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ShapeN"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ShapeN"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "cos"
|
||
|
|
inputFrameworkOpName: "Cos"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Cos"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Cos"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Cos"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "sqrt"
|
||
|
|
inputFrameworkOpName: "Sqrt"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Sqrt"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Sqrt"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Sqrt"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "deconv2d_tf"
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input_sizes"
|
||
|
|
inputTensorName: "filter"
|
||
|
|
inputTensorName: "out_backprop"
|
||
|
|
outputTensorName: "gradIShape"
|
||
|
|
outputTensorName: "weights"
|
||
|
|
outputTensorName: "gradO"
|
||
|
|
inputToOutput {
|
||
|
|
key: "gradIShape"
|
||
|
|
value: "input_sizes"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "weights"
|
||
|
|
value: "filter"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "gradO"
|
||
|
|
value: "out_backprop"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
inputIntName: "wFormat"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "wFormat"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 10
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringnotequalsadapterrule"
|
||
|
|
functionName: "stringnotequalsadapterrule"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
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|
||
|
|
inputFloatName: "data_format"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNCHW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNCHW"
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
stringValue: "NCHW"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
stringValue: "SAME"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
value: "data_format"
|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
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|
||
|
|
stringValue: "strides"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
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|
||
|
|
argIndex: 3
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 6
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindex"
|
||
|
|
functionName: "conditionalfieldvalueintindex"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "dW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 7
|
||
|
|
stringValue: "dilations"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "kH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "kH"
|
||
|
|
int64Value: -1
|
||
|
|
argType: INT64
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "kW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "kW"
|
||
|
|
int64Value: -1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Conv2DBackpropInput"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "floordiv"
|
||
|
|
inputFrameworkOpName: "FloorDiv"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FloorDiv"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "FloorDiv"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FloorDiv"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "stack_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayConcatV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayConcatV3"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayConcatV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "stack_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayConcatV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayConcatV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayConcatV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "identity"
|
||
|
|
inputFrameworkOpName: "CopyHost"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "CopyHost"
|
||
|
|
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|
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|
|
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||
|
|
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|
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|
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|
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|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
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|
|
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|
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|
|
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|
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|
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|
|
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|
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inputToOutput {
|
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|
|
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|
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|
|
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|
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|
|
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|
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|
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|
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|
|
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|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
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|
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|
|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Neg"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
inputDataTypeName: "T"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
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|
||
|
|
}
|
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|
|
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|
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|
|
inputFrameworkOpName: "Neg"
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||
|
|
}
|
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|
|
rule {
|
||
|
|
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|
|
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|
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||
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|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Neg"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "top_k"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TopKV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "needSort"
|
||
|
|
value: "sorted"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TopKV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "k"
|
||
|
|
value: "k"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TopKV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "resize_area"
|
||
|
|
inputFrameworkOpName: "ResizeArea"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputTensorName: "size"
|
||
|
|
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|
||
|
|
outputTensorName: "size"
|
||
|
|
inputToOutput {
|
||
|
|
key: "image"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "size"
|
||
|
|
value: "size"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ResizeArea"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "alignCorners"
|
||
|
|
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|
||
|
|
}
|
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|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "ResizeArea"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "b"
|
||
|
|
value: "rhs"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "MatrixTriangularSolve"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "useAdjoint"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "isLower"
|
||
|
|
value: "lower"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "MatrixTriangularSolve"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "softsign"
|
||
|
|
inputFrameworkOpName: "Softsign"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "features"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "features"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Softsign"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Softsign"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "gather"
|
||
|
|
inputFrameworkOpName: "GatherV2"
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
inputTensorName: "indices"
|
||
|
|
outputTensorName: "input"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "params"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "GatherV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
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|
|
transformerArgs {
|
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|
|
key: "value"
|
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|
|
transformerArgs {
|
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|
|
name: "inPlace"
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||
|
|
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|
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|
|
}
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|
|
}
|
||
|
|
inputFrameworkOpName: "GatherV2"
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||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "axis"
|
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|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "GatherV2"
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||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "fake_quant_with_min_max_args"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxArgs"
|
||
|
|
rule {
|
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|
|
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|
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|
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|
|
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||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
key: "input"
|
||
|
|
value: "inputs"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxArgs"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
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|
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|
|
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||
|
|
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|
||
|
|
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|
||
|
|
inputBooleanName: "narrow_range"
|
||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
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|
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|
|
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|
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|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
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|
|
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|
||
|
|
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|
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|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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||
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "All"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
|
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|
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|
|
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|
||
|
|
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||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Tan"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Tan"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Tan"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Tan"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "fill"
|
||
|
|
inputFrameworkOpName: "Fill"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputTensorName: "value"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
outputTensorName: "outputs"
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "outputs"
|
||
|
|
value: "value"
|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Fill"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputDoubleName: "value"
|
||
|
|
inputToOutput {
|
||
|
|
key: "value"
|
||
|
|
value: "value"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Fill"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
outputIntName: "dtype"
|
||
|
|
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|
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|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Fill"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "scatter_add"
|
||
|
|
inputFrameworkOpName: "ScatterAdd"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "ref"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
inputTensorName: "updates"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
outputTensorName: "updates"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "ref"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ScatterAdd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "lock"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
name: "lock"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ScatterAdd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "checkIndices"
|
||
|
|
argType: BOOL
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ScatterAdd"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "max_pool_with_argmax"
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "kH"
|
||
|
|
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|
||
|
|
argType: INT64
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "kW"
|
||
|
|
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|
||
|
|
argType: INT64
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
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||
|
|
transformerArgs {
|
||
|
|
name: "sH"
|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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||
|
|
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||
|
|
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||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
||
|
|
argType: INT64
|
||
|
|
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|
||
|
|
}
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||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
transformerArgs {
|
||
|
|
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|
||
|
|
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|
|
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|
|
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|
|
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|
|
}
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||
|
|
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||
|
|
}
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|
rule {
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|
|
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|
|
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||
|
|
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|
||
|
|
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|
|
transformerArgs {
|
||
|
|
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|
|
transformerArgs {
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|
|
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|
|
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|
|
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|
|
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|
|
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|
}
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|
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|
|
}
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|
rule {
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|
|
ruleName: "argdescriptorconstant"
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|
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||
|
|
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||
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|
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|
|
transformerArgs {
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|
|
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|
|
transformerArgs {
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|
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|
|
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|
|
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|
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|
|
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|
}
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||
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|
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||
|
|
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||
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|
rule {
|
||
|
|
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||
|
|
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||
|
|
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||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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||
|
|
transformerArgs {
|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "isNHWC"
|
||
|
|
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|
||
|
|
argType: INT64
|
||
|
|
argIndex: 10
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "sameMode"
|
||
|
|
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|
||
|
|
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|
||
|
|
argIndex: 8
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "MaxPoolWithArgmax"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "matrix_diag_part"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "MatrixDiagPart"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MatrixDiagPart"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "fused_batch_norm"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "scale"
|
||
|
|
inputTensorName: "offset"
|
||
|
|
inputTensorName: "mean"
|
||
|
|
inputTensorName: "variance"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "scale"
|
||
|
|
outputTensorName: "offset"
|
||
|
|
outputTensorName: "mean"
|
||
|
|
outputTensorName: "variance"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scale"
|
||
|
|
value: "scale"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "offset"
|
||
|
|
value: "offset"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "mean"
|
||
|
|
value: "mean"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "variance"
|
||
|
|
value: "variance"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV3"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "epsilon"
|
||
|
|
outputDoubleName: "epsilon"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "epsilon"
|
||
|
|
value: "epsilon"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV3"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "invertbooleannumber"
|
||
|
|
functionName: "invertbooleannumber"
|
||
|
|
outputIntName: "isTraining"
|
||
|
|
inputBooleanName: "is_training"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isTraining"
|
||
|
|
value: "is_training"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV3"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dataFormat"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataFormat"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dataFormat"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argType: STRING
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "gather_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayGatherV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayGatherV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayGatherV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "noop"
|
||
|
|
inputFrameworkOpName: "NoOp"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NoOp"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "gather_list"
|
||
|
|
inputFrameworkOpName: "TensorArrayGatherV3"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TensorArrayGatherV3"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TensorArrayGatherV3"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "lrn"
|
||
|
|
inputFrameworkOpName: "LRN"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "LRN"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "depth_radius"
|
||
|
|
outputIntName: "depth"
|
||
|
|
inputFloatName: "alpha"
|
||
|
|
inputFloatName: "bias"
|
||
|
|
inputFloatName: "beta"
|
||
|
|
outputDoubleName: "alpha"
|
||
|
|
outputDoubleName: "bias"
|
||
|
|
outputDoubleName: "beta"
|
||
|
|
inputToOutput {
|
||
|
|
key: "depth"
|
||
|
|
value: "depth_radius"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "alpha"
|
||
|
|
value: "alpha"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "bias"
|
||
|
|
value: "bias"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "beta"
|
||
|
|
value: "beta"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "LRN"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "LRN"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "betainc"
|
||
|
|
inputFrameworkOpName: "Betainc"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "a"
|
||
|
|
inputTensorName: "b"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "a"
|
||
|
|
outputTensorName: "b"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "a"
|
||
|
|
value: "a"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "b"
|
||
|
|
value: "b"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Betainc"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "diag_part"
|
||
|
|
inputFrameworkOpName: "DiagPart"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "DiagPart"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "DiagPart"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "concat"
|
||
|
|
inputFrameworkOpName: "Concat"
|
||
|
|
rule {
|
||
|
|
ruleName: "multiinputindex"
|
||
|
|
functionName: "multiinputindex"
|
||
|
|
inputTensorName: "values"
|
||
|
|
inputTensorName: "concat_dim"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "concatDimension"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "values"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "concatDimension"
|
||
|
|
value: "concat_dim"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Concat"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "concatDimension"
|
||
|
|
inputToOutput {
|
||
|
|
key: "concatDimension"
|
||
|
|
value: "concat_dim"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Concat"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "isDynamicAxis"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "isDynamicAxis"
|
||
|
|
boolValue: true
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Concat"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Concat"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "segment_prod"
|
||
|
|
inputFrameworkOpName: "SegmentProd"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "data"
|
||
|
|
inputTensorName: "segment_ids"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "idxSegments"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "data"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "idxSegments"
|
||
|
|
value: "segment_ids"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "SegmentProd"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "top_k"
|
||
|
|
inputFrameworkOpName: "TopK"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TopK"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "k"
|
||
|
|
outputIntName: "k"
|
||
|
|
inputBooleanName: "sorted"
|
||
|
|
outputBooleanName: "needSort"
|
||
|
|
inputToOutput {
|
||
|
|
key: "needSort"
|
||
|
|
value: "sorted"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "k"
|
||
|
|
value: "k"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TopK"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "fake_quant_with_min_max_vars_per_channel"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxVarsPerChannel"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "inputs"
|
||
|
|
inputTensorName: "min"
|
||
|
|
inputTensorName: "max"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "min"
|
||
|
|
outputTensorName: "max"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "inputs"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "min"
|
||
|
|
value: "min"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "max"
|
||
|
|
value: "max"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxVarsPerChannel"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "num_bits"
|
||
|
|
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|
||
|
|
inputBooleanName: "narrow_range"
|
||
|
|
outputBooleanName: "narrowed"
|
||
|
|
inputToOutput {
|
||
|
|
key: "numBits"
|
||
|
|
value: "num_bits"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "narrowed"
|
||
|
|
value: "narrow_range"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxVarsPerChannel"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "maximum"
|
||
|
|
inputFrameworkOpName: "Maximum"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Maximum"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Maximum"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Maximum"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "mergeadd"
|
||
|
|
inputFrameworkOpName: "AccumulateNV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "multiinputindex"
|
||
|
|
functionName: "multiinputindex"
|
||
|
|
inputTensorName: "inputs"
|
||
|
|
outputTensorName: "inArrs"
|
||
|
|
inputToOutput {
|
||
|
|
key: "inArrs"
|
||
|
|
value: "inputs"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "AccumulateNV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "AccumulateNV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "asinh"
|
||
|
|
inputFrameworkOpName: "Asinh"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Asinh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Asinh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Asinh"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "fused_batch_norm"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "scale"
|
||
|
|
inputTensorName: "offset"
|
||
|
|
inputTensorName: "mean"
|
||
|
|
inputTensorName: "variance"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "scale"
|
||
|
|
outputTensorName: "offset"
|
||
|
|
outputTensorName: "mean"
|
||
|
|
outputTensorName: "variance"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scale"
|
||
|
|
value: "scale"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "offset"
|
||
|
|
value: "offset"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "mean"
|
||
|
|
value: "mean"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "variance"
|
||
|
|
value: "variance"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "epsilon"
|
||
|
|
outputDoubleName: "epsilon"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "epsilon"
|
||
|
|
value: "epsilon"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
outputIntName: "isTraining"
|
||
|
|
inputBooleanName: "is_training"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isTraining"
|
||
|
|
value: "is_training"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "dataFormat"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataFormat"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "dataFormat"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argType: STRING
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "FusedBatchNormV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "Reciprocal"
|
||
|
|
inputFrameworkOpName: "Reciprocal"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Reciprocal"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "in_top_k"
|
||
|
|
inputFrameworkOpName: "InTopKV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "targets"
|
||
|
|
inputTensorName: "predictions"
|
||
|
|
outputTensorName: "target"
|
||
|
|
outputTensorName: "predictions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "target"
|
||
|
|
value: "targets"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "predictions"
|
||
|
|
value: "predictions"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "InTopKV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "k"
|
||
|
|
value: "k"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "InTopKV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "sorted"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "sorted"
|
||
|
|
boolValue: true
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "InTopKV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "less"
|
||
|
|
inputFrameworkOpName: "Less"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Less"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Less"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Less"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "nth_element"
|
||
|
|
inputFrameworkOpName: "NthElement"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "n"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "n"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "n"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NthElement"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "invertbooleannumber"
|
||
|
|
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|
||
|
|
outputIntName: "reverse"
|
||
|
|
inputBooleanName: "reverse"
|
||
|
|
inputToOutput {
|
||
|
|
key: "reverse"
|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "NthElement"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "matmul"
|
||
|
|
inputFrameworkOpName: "BatchMatMul"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BatchMatMul"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "alpha"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "alpha"
|
||
|
|
doubleValue: 1.0
|
||
|
|
argType: DOUBLE
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchMatMul"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "beta"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "beta"
|
||
|
|
doubleValue: 1.0
|
||
|
|
argType: DOUBLE
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchMatMul"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "invertbooleannumber"
|
||
|
|
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|
||
|
|
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|
||
|
|
outputIntName: "transY"
|
||
|
|
inputBooleanName: "adj_x"
|
||
|
|
inputBooleanName: "adj_y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "transX"
|
||
|
|
value: "adj_x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "transY"
|
||
|
|
value: "adj_y"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "BatchMatMul"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "transZ"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "transZ"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchMatMul"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "multiply"
|
||
|
|
inputFrameworkOpName: "Mul"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Mul"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Mul"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Mul"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "IdentityN"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Lu"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "diag"
|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Diag"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Diag"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Range"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
inputTensorName: "start"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
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|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Range"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "from"
|
||
|
|
value: "start"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "to"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "step"
|
||
|
|
value: "delta"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Range"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Range"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "histogram_fixed_width"
|
||
|
|
inputFrameworkOpName: "HistogramFixedWidth"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputTensorName: "nbins"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "range"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "range"
|
||
|
|
value: "value_range"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "numBins"
|
||
|
|
value: "nbins"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "HistogramFixedWidth"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "nbins"
|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "HistogramFixedWidth"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "DivNoNan"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "BroadcastArgs"
|
||
|
|
rule {
|
||
|
|
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|
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|
|
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||
|
|
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|
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|
|
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||
|
|
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||
|
|
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||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "s1"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BroadcastArgs"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "updates"
|
||
|
|
value: "updates"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ScatterDiv"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
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|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Reshape"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Copy"
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Copy"
|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
mappings {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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||
|
|
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||
|
|
inputToOutput {
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||
|
|
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||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "MatrixInverse"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
boolValue: true
|
||
|
|
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|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchMatrixInverse"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
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||
|
|
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|
||
|
|
inputTensorName: "y"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
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|
||
|
|
}
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "argdescriptorconstant"
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||
|
|
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|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
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||
|
|
argType: BOOL
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|
|
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|
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|
|
}
|
||
|
|
inputFrameworkOpName: "Atan2"
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||
|
|
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|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Atan2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "batch_to_space"
|
||
|
|
inputFrameworkOpName: "BatchToSpace"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "crops"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "crop"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "crop"
|
||
|
|
value: "crops"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BatchToSpace"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "block_size"
|
||
|
|
outputIntName: "blockSize"
|
||
|
|
inputToOutput {
|
||
|
|
key: "blockSize"
|
||
|
|
value: "block_size"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "BatchToSpace"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "acos"
|
||
|
|
inputFrameworkOpName: "Acos"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Acos"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Acos"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Acos"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "gather_nd"
|
||
|
|
inputFrameworkOpName: "GatherNd"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "params"
|
||
|
|
inputTensorName: "indices"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "indices"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "params"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "indices"
|
||
|
|
value: "indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "GatherNd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "GatherNd"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "checkIndices"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "checkIndices"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "GatherNd"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "maxpool2d"
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "extraParam0"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "extraParam0"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 9
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pH"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "pW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "pW"
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "dW"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dW"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 6
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "dH"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dH"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 7
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringnotequalsadapterrule"
|
||
|
|
functionName: "stringnotequalsadapterrule"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "isNCHW"
|
||
|
|
inputFloatName: "data_format"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isNCHW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isNCHW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "data_format"
|
||
|
|
argIndex: 10
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "padding"
|
||
|
|
argType: STRING
|
||
|
|
argIndex: 8
|
||
|
|
stringValue: "SAME"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindexndarray"
|
||
|
|
functionName: "conditionalfieldvalueintindexndarray"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
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|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
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|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
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|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 2
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindexndarray"
|
||
|
|
functionName: "conditionalfieldvalueintindexndarray"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "sW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "sW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "sW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 3
|
||
|
|
stringValue: "strides"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindexndarray"
|
||
|
|
functionName: "conditionalfieldvalueintindexndarray"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "kH"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kH"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kH"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 2
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "conditionalfieldvalueintindexndarray"
|
||
|
|
functionName: "conditionalfieldvalueintindexndarray"
|
||
|
|
inputStringAttrName: "data_format"
|
||
|
|
outputIntName: "kW"
|
||
|
|
inputFloatName: "targetValue"
|
||
|
|
inputFloatName: "trueIndex"
|
||
|
|
inputFloatName: "falseIndex"
|
||
|
|
inputFloatName: "attributeNameOfListAttribute"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kW"
|
||
|
|
value: "data_format"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
key: "kW"
|
||
|
|
transformerArgs {
|
||
|
|
name: "targetValue"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "NCHW"
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "trueIndex"
|
||
|
|
int64Value: 3
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "falseIndex"
|
||
|
|
int64Value: 2
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
transformerArgs {
|
||
|
|
name: "attributeNameOfListAttribute"
|
||
|
|
argIndex: 1
|
||
|
|
stringValue: "ksize"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "MaxPoolV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "cholesky"
|
||
|
|
inputFrameworkOpName: "Cholesky"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Cholesky"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "random_crop"
|
||
|
|
inputFrameworkOpName: "RandomCrop"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "image"
|
||
|
|
inputTensorName: "size"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "shape"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "image"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "shape"
|
||
|
|
value: "size"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "RandomCrop"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "seed"
|
||
|
|
outputIntName: "seed"
|
||
|
|
inputToOutput {
|
||
|
|
key: "seed"
|
||
|
|
value: "seed"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomCrop"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "batch_to_space_nd"
|
||
|
|
inputFrameworkOpName: "BatchToSpaceND"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "crops"
|
||
|
|
inputTensorName: "block_shape"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "crop"
|
||
|
|
outputTensorName: "blockShape"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "crop"
|
||
|
|
value: "crops"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "blockShape"
|
||
|
|
value: "block_shape"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BatchToSpaceND"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
outputIntName: "blocks"
|
||
|
|
inputToOutput {
|
||
|
|
key: "blocks"
|
||
|
|
value: "block_shape"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "BatchToSpaceND"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchToSpaceND"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "reduce_mean"
|
||
|
|
inputFrameworkOpName: "Mean"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "reduction_indices"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Mean"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputBooleanName: "keep_dims"
|
||
|
|
outputBooleanName: "keepDims"
|
||
|
|
inputToOutput {
|
||
|
|
key: "keepDims"
|
||
|
|
value: "keep_dims"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Mean"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraytointattributevalue"
|
||
|
|
functionName: "ndarraytointattributevalue"
|
||
|
|
outputIntName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Mean"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "cosh"
|
||
|
|
inputFrameworkOpName: "Cosh"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Cosh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Cosh"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Cosh"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "identity"
|
||
|
|
inputFrameworkOpName: "Variable"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Variable"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Variable"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Variable"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "log_softmax"
|
||
|
|
inputFrameworkOpName: "LogSoftmax"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "logits"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "logits"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "LogSoftmax"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "cross"
|
||
|
|
inputFrameworkOpName: "Cross"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "a"
|
||
|
|
inputTensorName: "b"
|
||
|
|
outputTensorName: "a"
|
||
|
|
outputTensorName: "b"
|
||
|
|
inputToOutput {
|
||
|
|
key: "a"
|
||
|
|
value: "a"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "b"
|
||
|
|
value: "b"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Cross"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "matrix_set_diag"
|
||
|
|
inputFrameworkOpName: "BatchMatrixSetDiag"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "input"
|
||
|
|
inputTensorName: "diagonal"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "diagonal"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "diagonal"
|
||
|
|
value: "diagonal"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BatchMatrixSetDiag"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BatchMatrixSetDiag"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "non_max_suppression_overlaps"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionWithOverlaps"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "scores"
|
||
|
|
inputTensorName: "overlaps"
|
||
|
|
outputTensorName: "scales"
|
||
|
|
outputTensorName: "boxes"
|
||
|
|
inputToOutput {
|
||
|
|
key: "scales"
|
||
|
|
value: "scores"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "boxes"
|
||
|
|
value: "overlaps"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionWithOverlaps"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "maxOutputSize"
|
||
|
|
outputDoubleName: "overlapThreshold"
|
||
|
|
outputDoubleName: "scoreThreshold"
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxOutputSize"
|
||
|
|
value: "max_output_size"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "overlapThreshold"
|
||
|
|
value: "overlap_threshold"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "scoreThreshold"
|
||
|
|
value: "score_threshold"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "NonMaxSuppressionWithOverlaps"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "concat"
|
||
|
|
inputFrameworkOpName: "ConcatV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ConcatV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarrayinputtonumericalattribute"
|
||
|
|
functionName: "ndarrayinputtonumericalattribute"
|
||
|
|
outputIntName: "concatDimension"
|
||
|
|
inputToOutput {
|
||
|
|
key: "concatDimension"
|
||
|
|
value: "axis"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "ConcatV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "isDynamicAxis"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "isDynamicAxis"
|
||
|
|
boolValue: true
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ConcatV2"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "truncatediv"
|
||
|
|
inputFrameworkOpName: "TruncateDiv"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "TruncateDiv"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "TruncateDiv"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
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||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
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|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "TruncateDiv"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "any"
|
||
|
|
inputFrameworkOpName: "Any"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
outputTensorName: "dimensions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "input"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Any"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Any"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
inputToOutput {
|
||
|
|
key: "dimensions"
|
||
|
|
value: "reduction_indices"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Any"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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||
|
|
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|
||
|
|
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|
||
|
|
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|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
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|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "LogicalOr"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
inputFrameworkOpName: "Inv"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
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||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Inv"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "boolean_not"
|
||
|
|
inputFrameworkOpName: "LogicalNot"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "LogicalNot"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "igammac"
|
||
|
|
inputFrameworkOpName: "Igammac"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "a"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "a"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Igammac"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "extract_image_patches"
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "images"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "images"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "ksizeRows"
|
||
|
|
inputToOutput {
|
||
|
|
key: "ksizeRows"
|
||
|
|
value: "ksizes"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "ksizeRows"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "ksizeCols"
|
||
|
|
inputToOutput {
|
||
|
|
key: "ksizeCols"
|
||
|
|
value: "ksizes"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "ksizeCols"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 2
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 1
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "kstrideRows"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kstrideRows"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kstrideRows"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 2
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "kstrideCols"
|
||
|
|
inputToOutput {
|
||
|
|
key: "kstrideCols"
|
||
|
|
value: "strides"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "kstrideCols"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 2
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 3
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "krateRows"
|
||
|
|
inputToOutput {
|
||
|
|
key: "krateRows"
|
||
|
|
value: "rates"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "krateRows"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 1
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 4
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "listattributevaluelookuptoindex"
|
||
|
|
functionName: "listattributevaluelookuptoindex"
|
||
|
|
inputIntName: "index"
|
||
|
|
outputIntName: "krateCols"
|
||
|
|
inputToOutput {
|
||
|
|
key: "krateCols"
|
||
|
|
value: "rates"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "krateCols"
|
||
|
|
transformerArgs {
|
||
|
|
name: "index"
|
||
|
|
int64Value: 2
|
||
|
|
argType: INT64
|
||
|
|
argIndex: 5
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "stringequals"
|
||
|
|
functionName: "stringequals"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
inputStringAttrName: "padding"
|
||
|
|
outputIntName: "isSameMode"
|
||
|
|
inputToOutput {
|
||
|
|
key: "isSameMode"
|
||
|
|
value: "padding"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "isSameMode"
|
||
|
|
transformerArgs {
|
||
|
|
name: "padding"
|
||
|
|
argType: STRING
|
||
|
|
stringValue: "SAME"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "ExtractImagePatches"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "fake_quant_with_min_max_vars"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxVars"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "inputs"
|
||
|
|
inputTensorName: "min"
|
||
|
|
inputTensorName: "max"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "min"
|
||
|
|
outputTensorName: "max"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "inputs"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "min"
|
||
|
|
value: "min"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "max"
|
||
|
|
value: "max"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxVars"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "num_bits"
|
||
|
|
outputIntName: "numBits"
|
||
|
|
inputBooleanName: "narrow_range"
|
||
|
|
outputBooleanName: "narrowed"
|
||
|
|
inputToOutput {
|
||
|
|
key: "numBits"
|
||
|
|
value: "num_bits"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "narrowed"
|
||
|
|
value: "narrow_range"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "FakeQuantWithMinMaxVars"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "round"
|
||
|
|
inputFrameworkOpName: "Round"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Round"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Round"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Round"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "dynamic_stitch"
|
||
|
|
inputFrameworkOpName: "ParallelDynamicStitch"
|
||
|
|
rule {
|
||
|
|
ruleName: "passthrough"
|
||
|
|
functionName: "passthrough"
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ParallelDynamicStitch"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputIntName: "N"
|
||
|
|
outputIntName: "numPartitions"
|
||
|
|
inputToOutput {
|
||
|
|
key: "numPartitions"
|
||
|
|
value: "N"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "ParallelDynamicStitch"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "sigmoid"
|
||
|
|
inputFrameworkOpName: "Sigmoid"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Sigmoid"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Sigmoid"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Sigmoid"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "lstmBlock"
|
||
|
|
inputFrameworkOpName: "BlockLSTMV2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "seq_len_max"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "cs_prev"
|
||
|
|
inputTensorName: "h_prev"
|
||
|
|
inputTensorName: "w"
|
||
|
|
inputTensorName: "wci"
|
||
|
|
inputTensorName: "wcf"
|
||
|
|
inputTensorName: "wco"
|
||
|
|
inputTensorName: "b"
|
||
|
|
outputTensorName: "maxTSLength"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "cLast"
|
||
|
|
outputTensorName: "yLast"
|
||
|
|
outputTensorName: "W"
|
||
|
|
outputTensorName: "Wci"
|
||
|
|
outputTensorName: "Wcf"
|
||
|
|
outputTensorName: "Wco"
|
||
|
|
outputTensorName: "b"
|
||
|
|
inputToOutput {
|
||
|
|
key: "maxTSLength"
|
||
|
|
value: "seq_len_max"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "cLast"
|
||
|
|
value: "cs_prev"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "yLast"
|
||
|
|
value: "h_prev"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "W"
|
||
|
|
value: "w"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wci"
|
||
|
|
value: "wci"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wcf"
|
||
|
|
value: "wcf"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "Wco"
|
||
|
|
value: "wco"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "b"
|
||
|
|
value: "b"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "BlockLSTMV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputFloatName: "cell_clip"
|
||
|
|
outputDoubleName: "clippingCellValue"
|
||
|
|
inputToOutput {
|
||
|
|
key: "clippingCellValue"
|
||
|
|
value: "cell_clip"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "BlockLSTMV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "invertbooleannumber"
|
||
|
|
functionName: "invertbooleannumber"
|
||
|
|
outputIntName: "peephole"
|
||
|
|
inputBooleanName: "use_peephole"
|
||
|
|
inputToOutput {
|
||
|
|
key: "peephole"
|
||
|
|
value: "use_peephole"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "BlockLSTMV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputFloatName: "forgetBias"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "forgetBias"
|
||
|
|
doubleValue: 3.0
|
||
|
|
argType: DOUBLE
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "BlockLSTMV2"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputIntName: "dataFormat"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "dataFormat"
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
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|
|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
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|
|
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|
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|
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|
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|
|
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|
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|
|
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|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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mappings {
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|
|
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|
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|
|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
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|
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|
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|
|
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|
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|
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|
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|
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|
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|
|
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|
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|
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|
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transformerArgs {
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
|
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|
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|
|
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|
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|
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|
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|
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|
|
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|
|
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mappings {
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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rule {
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|
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transformerArgs {
|
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|
|
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transformerArgs {
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|
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|
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|
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|
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|
|
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|
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rule {
|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
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|
|
rule {
|
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
mappings {
|
||
|
|
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|
||
|
|
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|
|
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|
|
rule {
|
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
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|
|
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|
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|
|
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|
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|
|
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|
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|
|
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|
||
|
|
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|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "ListDiff"
|
||
|
|
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|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
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|
|
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|
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|
|
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||
|
|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
|
rule {
|
||
|
|
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|
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|
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|
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|
|
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|
|
transformerArgs {
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|
|
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|
|
transformerArgs {
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|
|
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|
|
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|
|
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|
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|
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|
|
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|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
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|
||
|
|
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|
||
|
|
rule {
|
||
|
|
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|
|
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|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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transformerArgs {
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|
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|
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|
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|
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|
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|
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|
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|
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|
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transformerArgs {
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|
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|
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|
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|
|
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|
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|
|
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|
|
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|
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|
|
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|
|
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|
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|
|
mappings {
|
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|
|
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||
|
|
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|
||
|
|
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|
|
rule {
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|
|
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|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
key: "exclusive"
|
||
|
|
value: "exclusive"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
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|
||
|
|
value: "reverse"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Cumprod"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "mergesum"
|
||
|
|
inputFrameworkOpName: "AddN"
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
inputTensorName: "inputs"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "inputs"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "AddN"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "random_normal"
|
||
|
|
inputFrameworkOpName: "RandomStandardNormal"
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
inputTensorName: "shape"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "shape"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "RandomStandardNormal"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
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|
||
|
|
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|
||
|
|
inputDataTypeName: "dtype"
|
||
|
|
outputDataTypeName: "dtype"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dtype"
|
||
|
|
value: "dtype"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "RandomStandardNormal"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "sign"
|
||
|
|
inputFrameworkOpName: "Sign"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Sign"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Sign"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Sign"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "greater"
|
||
|
|
inputFrameworkOpName: "Greater"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
inputTensorName: "y"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "y"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "y"
|
||
|
|
value: "y"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Greater"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Greater"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Greater"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "exp"
|
||
|
|
inputFrameworkOpName: "Exp"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "x"
|
||
|
|
outputTensorName: "input"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "x"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "Exp"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "valuemapping"
|
||
|
|
functionName: "valuemapping"
|
||
|
|
inputDataTypeName: "T"
|
||
|
|
outputDataTypeName: "dataType"
|
||
|
|
inputToOutput {
|
||
|
|
key: "dataType"
|
||
|
|
value: "T"
|
||
|
|
}
|
||
|
|
ruleType: "attribute"
|
||
|
|
inputFrameworkOpName: "Exp"
|
||
|
|
}
|
||
|
|
rule {
|
||
|
|
ruleName: "argdescriptorconstant"
|
||
|
|
functionName: "argdescriptorconstant"
|
||
|
|
inputBooleanName: "inPlace"
|
||
|
|
ruleType: "attribute"
|
||
|
|
transformerArgs {
|
||
|
|
key: "value"
|
||
|
|
transformerArgs {
|
||
|
|
name: "inPlace"
|
||
|
|
argType: BOOL
|
||
|
|
}
|
||
|
|
}
|
||
|
|
inputFrameworkOpName: "Exp"
|
||
|
|
}
|
||
|
|
}
|
||
|
|
mappings {
|
||
|
|
frameworkName: "tensorflow"
|
||
|
|
opName: "adjust_contrast_v2"
|
||
|
|
inputFrameworkOpName: "AdjustContrastv2"
|
||
|
|
rule {
|
||
|
|
ruleName: "ndarraymapping"
|
||
|
|
functionName: "ndarraymapping"
|
||
|
|
inputTensorName: "images"
|
||
|
|
inputTensorName: "contrast_factor"
|
||
|
|
outputTensorName: "input"
|
||
|
|
outputTensorName: "factor"
|
||
|
|
inputToOutput {
|
||
|
|
key: "input"
|
||
|
|
value: "images"
|
||
|
|
}
|
||
|
|
inputToOutput {
|
||
|
|
key: "factor"
|
||
|
|
value: "contrast_factor"
|
||
|
|
}
|
||
|
|
ruleType: "tensor"
|
||
|
|
inputFrameworkOpName: "AdjustContrastv2"
|
||
|
|
}
|
||
|
|
}
|