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Add ctc loss to TF import

master
agibsonccc 2021-03-13 09:17:36 +09:00
parent 0c81654567
commit df1be4a116
4 changed files with 52 additions and 1 deletions
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6
nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/impl/loss/CtcLoss.java
View File

@ -22,6 +22,7 @@ package org.nd4j.linalg.api.ops.impl.loss;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.impl.loss.bp.CtcLossBp;
@ -30,6 +31,11 @@ import java.util.List;
public class CtcLoss extends DynamicCustomOp {
public CtcLoss(INDArray targetLabels, INDArray logitInputs, INDArray targetLabelLengths, INDArray logitInputLengths) {
super(new INDArray[]{targetLabels,logitInputs,targetLabelLengths,logitInputLengths},null);
}
public CtcLoss(SameDiff sameDiff, SDVariable targetLabels,SDVariable logitInputs,SDVariable targetLabelLengths,SDVariable logitInputLengths){
super(sameDiff,new SDVariable[]{targetLabels,logitInputs,targetLabelLengths,logitInputLengths});
}

10
nd4j/samediff-import/samediff-import-tensorflow/src/main/kotlin/org/nd4j/samediff/frameworkimport/tensorflow/definitions/TensorflowOpDeclarations.kt
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@ -419,6 +419,16 @@ val checkNumerics = TensorflowMappingProcess(
tensorMappingRules = listOf(mappingNDArrayInputs(mutableMapOf("input" to "tensor")))
)
val ctcLoss = TensorflowMappingProcess(
opName = "ctc_loss",
inputFrameworkOpName = "CTCLoss",
opMappingRegistry = tensorflowOpRegistry,
attributeMappingRules = listOf(),
tensorMappingRules = listOf(mappingNDArrayInputs(mutableMapOf("logitInput" to "inputs","targetLabels" to "labels_values",
"targetLabelLengths" to "labels_indices","logitInputLengths" to "sequence_length")))
)
//only exists in tf2, tf-java can't run it
val checkNumericsV2 = TensorflowMappingProcess(

35
nd4j/samediff-import/samediff-import-tensorflow/src/main/resources/tensorflow-mapping-ruleset.pbtxt
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@ -10307,6 +10307,41 @@ mappings {
inputFrameworkOpName: "UniqueWithCounts"
}
}
mappings {
frameworkName: "tensorflow"
opName: "ctc_loss"
inputFrameworkOpName: "CTCLoss"
rule {
ruleName: "ndarraymapping"
functionName: "ndarraymapping"
inputTensorName: "inputs"
inputTensorName: "labels_values"
inputTensorName: "labels_indices"
inputTensorName: "sequence_length"
outputTensorName: "logitInput"
outputTensorName: "targetLabels"
outputTensorName: "targetLabelLengths"
outputTensorName: "logitInputLengths"
inputToOutput {
key: "logitInput"
value: "inputs"
}
inputToOutput {
key: "targetLabels"
value: "labels_values"
}
inputToOutput {
key: "targetLabelLengths"
value: "labels_indices"
}
inputToOutput {
key: "logitInputLengths"
value: "sequence_length"
}
ruleType: "tensor"
inputFrameworkOpName: "CTCLoss"
}
}
mappings {
frameworkName: "tensorflow"
opName: "randomuniform"