Fix reshape and other unit tests
agibsonccc
parent
e770e0b0b4
commit
b2fabb0585
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@ -67,18 +67,44 @@ DECLARE_SHAPE_FN(reshape) {
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std::vector<int> reshapeArgs;
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std::vector<Nd4jLong> shapeNew;
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char orderNew = 'c';
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/**
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* NOTE: The value here is negative as a flag.
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* A negative value signifies 1 of 3 values:
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* -1 -> dynamic shape
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* -99 -> c ordering
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* -102 -> f ordering
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*
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*/
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if (block.width() == 1) {
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reshapeArgs = *block.getIArguments();
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if(!reshapeArgs.empty()) {
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orderNew = (char) -reshapeArgs[0];
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char potentialOrdering = (char) -reshapeArgs[0];
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orderNew = potentialOrdering;
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if(potentialOrdering != 'c' && potentialOrdering != 'f') {
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throw std::runtime_error("reshape:: Value passed in must be -99 or -102 for the ordering if an int array is present. -99 represents c ordering and -102 represents f ordering. This number is negative for the long array case to flag the difference between an ordering and a dimension being specified.");
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}
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nd4j_debug("Reshape Ordering is %c int ordering is %d\n",orderNew,-reshapeArgs[0]);
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if(orderNew == 'c' || orderNew == 'f')
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reshapeArgs.erase(reshapeArgs.begin()); // remove first element being order in this case
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}
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}
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else {
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reshapeArgs = INPUT_VARIABLE(1)->getBufferAsVector<int>();
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orderNew = block.numI() > 0 ? (char) -INT_ARG(0) : 'c';
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if(block.numI() > 0) {
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//Note here that the ordering for this case can not be negative.
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// Negative is used in the long array case to be used as a flag to differntiate between a 99 or 102 shaped array and
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//the ordering. You can't have a -99 or -102 shaped array.
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char potentialOrdering = (char) reshapeArgs[0];
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if(potentialOrdering != 'c' && potentialOrdering != 'f') {
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throw std::runtime_error("reshape:: Value passed in must be -99 or -102 for the ordering if an int array is present. -99 represents c ordering and -102 represents f ordering.");
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}
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orderNew = potentialOrdering;
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}
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else
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orderNew = 'c';
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}
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REQUIRE_TRUE(!reshapeArgs.empty() || x->lengthOf() == 1, 0, "Reshape buffer should have at least 1 dimension !");
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@ -209,6 +209,7 @@
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-jar-plugin</artifactId>
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<version>3.2.0</version>
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<configuration>
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<archive>
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<manifest>
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@ -28,17 +28,23 @@ import lombok.val;
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import onnx.Onnx;
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import org.nd4j.autodiff.samediff.SDVariable;
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import org.nd4j.autodiff.samediff.SameDiff;
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import org.nd4j.autodiff.samediff.VariableType;
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import org.nd4j.autodiff.samediff.internal.SameDiffOp;
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import org.nd4j.autodiff.samediff.internal.Variable;
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import org.nd4j.autodiff.samediff.serde.FlatBuffersMapper;
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import org.nd4j.common.base.Preconditions;
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import org.nd4j.imports.converters.DifferentialFunctionClassHolder;
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import org.nd4j.imports.descriptors.properties.AttributeAdapter;
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import org.nd4j.imports.descriptors.properties.PropertyMapping;
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import org.nd4j.linalg.api.buffer.DataType;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.api.ops.Op;
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import org.nd4j.linalg.api.ops.OpContext;
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import org.nd4j.linalg.api.shape.LongShapeDescriptor;
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import org.nd4j.linalg.exception.ND4JIllegalStateException;
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import org.nd4j.linalg.indexing.functions.Zero;
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import org.nd4j.shade.jackson.annotation.JsonIgnore;
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import org.nd4j.weightinit.impl.ZeroInitScheme;
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import org.tensorflow.framework.AttrValue;
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import org.tensorflow.framework.GraphDef;
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import org.tensorflow.framework.NodeDef;
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@ -46,6 +52,8 @@ import org.tensorflow.framework.NodeDef;
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import java.lang.reflect.Field;
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import java.util.*;
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import static org.nd4j.imports.VariableUtils.stripVarSuffix;
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@Data
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@Slf4j
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@ -46,7 +46,6 @@ public class SDVariable implements Serializable {
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protected SameDiff sameDiff;
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@Getter
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@Setter
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protected String varName;
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@Getter
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@Setter
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@ -84,6 +83,10 @@ public class SDVariable implements Serializable {
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return varName;
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}
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public void setVarName(String varName) {
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this.varName = varName;
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}
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/**
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* @deprecated Use {@link #name()}
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*/
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@ -1097,6 +1097,7 @@ public class SameDiff extends SDBaseOps {
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ops.get(function.getOwnName()).setInputsToOp(Arrays.asList(variables)); //Duplicate variables OK/required here
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for (String variableName : variables) {
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if(this.variables.containsKey(variableName)) {
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List<String> funcs = this.variables.get(variableName).getInputsForOp();
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if (funcs == null) {
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funcs = new ArrayList<>();
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@ -1105,6 +1106,8 @@ public class SameDiff extends SDBaseOps {
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if (!funcs.contains(function.getOwnName())) //Avoid duplicates for function names.
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funcs.add(function.getOwnName());
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}
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}
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}
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/**
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@ -2541,7 +2544,7 @@ public class SameDiff extends SDBaseOps {
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validateListenerActivations(activeListeners, operation);
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Map<String, INDArray> ret = directExecHelper(placeholders, At.defaultAt(operation), null, Collections.<String>emptyList(), activeListeners, outputs);
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Map<String, INDArray> ret = directExecHelper(placeholders, At.defaultAt(operation), null, Collections.emptyList(), activeListeners, outputs);
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for (Listener l : activeListeners) {
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l.operationEnd(this, operation);
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@ -3316,16 +3319,18 @@ public class SameDiff extends SDBaseOps {
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/**
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* Rename the specified variable to the new name.
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*
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* Note here we also specify the op.
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* Sometimes, ops have multiple outputs and after the first rename of the variable
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* we lose the reference to the correct op to modify.
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* @param opToReName the op to rename
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* @param from The variable to rename - this variable must exist
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* @param to The new name for the variable - no variable with this name must already exist
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*/
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public void renameVariable(String from, String to) {
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public void renameVariable(SameDiffOp opToReName,String from, String to) {
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Preconditions.checkState(variables.containsKey(from), "Cannot rename variable \"%s\": no variable with this name exists", from);
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Preconditions.checkState(!variables.containsKey(to), "Cannot rename variable \"%s\" to name \"%s\": a variable with name \"%s\" already exists", from, to, to);
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Variable v = variables.get(from);
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SameDiffOp opToReName = ops.get(stripVarSuffix(from));
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v.setName(to);
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v.getVariable().setVarName(to);
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if (v.getInputsForOp() != null) {
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@ -3374,52 +3379,16 @@ public class SameDiff extends SDBaseOps {
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}
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if (v.getOutputOfOp() != null) {
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SameDiffOp op = ops.get(stripVarSuffix(from));
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if(op != null && op.getOutputsOfOp() != null) {
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SameDiffOp op = ops.get(v.getOutputOfOp());
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List<String> newOuts = new ArrayList<>(op.getOutputsOfOp());
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while (newOuts.contains(from)) {
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newOuts.set(newOuts.indexOf(from), to);
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}
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//find other aliases and ensure those get updated as well,
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//after this any other versions of the op may not be discoverable
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//due to the renaming
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String strippedVarSuffix = stripVarSuffix(from);
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for(int i = 0; i < newOuts.size(); i++) {
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String newOut = newOuts.get(i);
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if(stripVarSuffix(newOut).equals(strippedVarSuffix)) {
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val idx = newOut.lastIndexOf(':');
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val newString = to + newOut.substring(idx);
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newOuts.set(i,newString);
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}
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}
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op.setOutputsOfOp(newOuts);
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}
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else if(op != null) {
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op.setOutputsOfOp(Arrays.asList(to));
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}
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}
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variables.remove(from);
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variables.put(to, v);
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//set as just op name, update to set as the name of the output
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if(opToReName != null && opToReName.getOp() != null && opToReName.getOp().isOwnNameSetWithDefault()) {
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ops.remove(from);
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opToReName.getOp().setOwnName(to);
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ops.put(to,opToReName);
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opToReName.setName(to);
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}
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for(Variable variable : variables.values()) {
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if(variable.getInputsForOp() != null && variable.getInputsForOp().contains(from)) {
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variable.getInputsForOp().set(variable.getInputsForOp().indexOf(from),to);
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}
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if(variable.getOutputOfOp() != null && variable.getOutputOfOp().equals(from)) {
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variable.setOutputOfOp(to);
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}
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}
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if(v.getVariable().getVariableType() == VariableType.CONSTANT && constantArrays.hasArray(from)) {
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constantArrays.rename(from, to);
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@ -3496,6 +3465,18 @@ public class SameDiff extends SDBaseOps {
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}
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/**
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* Rename the specified variable to the new name.
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*
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* @param from The variable to rename - this variable must exist
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* @param to The new name for the variable - no variable with this name must already exist
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*/
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public void renameVariable(String from, String to) {
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SameDiffOp op = ops.get(stripVarSuffix(from));
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renameVariable(op,from,to);
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}
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/**
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* Remove an argument for a function. Note that if this function does not contain the argument, it will just be a no op.
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*
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@ -4557,6 +4538,7 @@ public class SameDiff extends SDBaseOps {
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associateSameDiffWithOpsAndVariables();
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}
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/**
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* Try to infer the loss variable/s (usually loss variables). Note that this is not reliable in general.
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*/
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@ -4604,16 +4586,19 @@ public class SameDiff extends SDBaseOps {
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return variables.get(varName).getVariable().isPlaceHolder();
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}
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/**
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* Updates the variable name property on the passed in variable, the reference in samediff, and returns the variable.
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* <p>
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* Note that if null for the new variable is passed in, it will just return the original input variable.
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*
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* @param opToRename note we pass in the op here for times when an op may have multiple outputs
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* when this is the case, we need to pass in the op to rename otherwise context gets lost
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* and subsequent rename attempts will not operate on the op.
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* @param varToUpdate the variable to update
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* @param newVarName the new variable name
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* @return the passed in variable
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*/
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public SDVariable updateVariableNameAndReference(SDVariable varToUpdate, String newVarName) {
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public SDVariable updateVariableNameAndReference(SameDiffOp opToRename,SDVariable varToUpdate, String newVarName) {
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if (varToUpdate == null) {
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throw new NullPointerException("Null input: No variable found for updating!");
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}
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@ -4644,10 +4629,24 @@ public class SameDiff extends SDBaseOps {
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val oldVarName = varToUpdate.name();
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varToUpdate.setVarName(newVarName);
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renameVariable(oldVarName, newVarName);
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renameVariable(opToRename,oldVarName, newVarName);
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return varToUpdate;
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}
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/**
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* Updates the variable name property on the passed in variable, the reference in samediff, and returns the variable.
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* <p>
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* Note that if null for the new variable is passed in, it will just return the original input variable.
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*
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* @param varToUpdate the variable to update
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* @param newVarName the new variable name
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* @return the passed in variable
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*/
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public SDVariable updateVariableNameAndReference(SDVariable varToUpdate, String newVarName) {
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SameDiffOp op = ops.get(varToUpdate.name());
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return updateVariableNameAndReference(op,varToUpdate,newVarName);
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}
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/**
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* Updates the variable name property on the passed in variables, its reference in samediff, and returns the variable.
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@ -4791,7 +4790,7 @@ public class SameDiff extends SDBaseOps {
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val flatNodes = new ArrayList<Integer>();
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// first of all we build VariableSpace dump
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val variableList = new ArrayList<SDVariable>(variables());
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val variableList = new ArrayList<>(variables());
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val reverseMap = new LinkedHashMap<String, Integer>();
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val forwardMap = new LinkedHashMap<String, Integer>();
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val framesMap = new LinkedHashMap<String, Integer>();
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@ -35,6 +35,8 @@ import org.nd4j.common.function.Predicate;
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import java.util.*;
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import static org.nd4j.imports.VariableUtils.stripVarSuffix;
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@Slf4j
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public abstract class AbstractSession<T, O> {
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@ -156,7 +158,6 @@ public abstract class AbstractSession<T, O> {
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//Step 2: Check that we have required placeholders
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List<String> phNames = sameDiff.inputs();
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log.info("Placeholder names were " + phNames);
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if (placeholderValues == null || !placeholderValues.keySet().containsAll(phNames)) {
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/* We only have a subset of all placeholders
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Validate that we have all *required* placeholder values. Some might not be needed to calculate the requested outputs
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@ -184,15 +185,9 @@ public abstract class AbstractSession<T, O> {
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}
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if (required && (placeholderValues == null || !placeholderValues.containsKey(s))) {
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if(placeholderValues != null)
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throw new IllegalStateException(
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"An input placeholder \"" + s + "\" is required to calculate the requested outputs," +
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" but a placeholder value was not provided. Placeholders specified were " + placeholderValues.keySet());
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else {
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throw new IllegalStateException(
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"An input placeholder \"" + s + "\" is required to calculate the requested outputs," +
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" but a placeholder value was not provided. Place holder values were null! ");
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}
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" but a placeholder value was not provided");
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}
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}
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}
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@ -282,7 +277,7 @@ public abstract class AbstractSession<T, O> {
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log.trace("Beginning execution step {}: {}", step, es);
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FrameIter outFrameIter;
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boolean skipDepUpdate = false; //Only used for Switch ops, which have slightly different handling...
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boolean skipDepUpdate = false; //Only used for Switch ops, which have slighly different handling...
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boolean skipMarkSatisfied = false; //Only for enter ops, because of different frame/iter
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if (es.getType() == ExecType.CONSTANT || es.getType() == ExecType.VARIABLE) {
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VarId vid = new VarId(es.getName(), OUTER_FRAME, 0, null);
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@ -514,7 +509,7 @@ public abstract class AbstractSession<T, O> {
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* Execution failed - can't calculate all requested outputs, and there's nothing left to calculate.
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* Throws an exception with a useful message
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*
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* @param userRequestedUnique All outputs that the user reqeseted
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* @param userRequestedUnique All outputs that the user requested
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* @param out Current outputs
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* @param step Execution step
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*/
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@ -544,7 +539,7 @@ public abstract class AbstractSession<T, O> {
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}
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}
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String s = sb.toString();
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// System.out.println(sameDiff.summary());
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System.out.println(sameDiff.summary());
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throw new IllegalStateException(s);
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}
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@ -564,6 +559,7 @@ public abstract class AbstractSession<T, O> {
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List<String> outNames = op.getOutputsOfOp();
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for (String s : outNames) {
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Variable v = sameDiff.getVariables().get(s);
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if(v != null) {
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List<String> inputsToOps = v.getInputsForOp();
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if (inputsToOps != null) {
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for (String opName : inputsToOps) {
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@ -588,8 +584,11 @@ public abstract class AbstractSession<T, O> {
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}
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}
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}
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}
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} else if (t == ExecType.VARIABLE || t == ExecType.CONSTANT || t == ExecType.PLACEHOLDER) {
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Variable v = sameDiff.getVariables().get(n);
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if(v != null) {
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List<String> inputsToOps = v.getInputsForOp();
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if (inputsToOps != null) {
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for (String opName : inputsToOps) {
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@ -598,11 +597,14 @@ public abstract class AbstractSession<T, O> {
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}
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}
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}
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}
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} else if (justExecuted.getType() == ExecType.SWITCH_L || justExecuted.getType() == ExecType.SWITCH_R) {
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SameDiffOp op = sameDiff.getOps().get(n);
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List<String> outNames = op.getOutputsOfOp();
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String branchVarName = (justExecuted.getType() == ExecType.SWITCH_L ? outNames.get(0) : outNames.get(1));
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Variable v = sameDiff.getVariables().get(branchVarName);
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if(v != null) {
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List<String> inputsToOps = v.getInputsForOp();
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if (inputsToOps != null) {
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for (String opName : inputsToOps) {
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@ -613,6 +615,8 @@ public abstract class AbstractSession<T, O> {
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}
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}
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}
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}
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} else {
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throw new UnsupportedOperationException("Unknown or not yet implemented exec type: " + justExecuted);
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}
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@ -691,8 +695,17 @@ public abstract class AbstractSession<T, O> {
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return new ExecStep(ExecType.CONSTANT, v.getVariable().name(), new FrameIter(OUTER_FRAME, 0, null));
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} else {
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//Array type. Must be output of an op
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if(v.getOutputOfOp() == null) {
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v = sameDiff.getVariables().get(stripVarSuffix(v.getName()));
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}
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String outOfOp = v.getOutputOfOp();
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SameDiffOp sdo = sameDiff.getOps().get(outOfOp);
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if(sdo == null) {
|
||||
throw new IllegalStateException("Samediff output op named " + v.getName() + " did not have any ops associated with it.");
|
||||
}
|
||||
|
||||
if (sdo.getOp() instanceof Switch) {
|
||||
//For dependency tracking purposes, we track left and right output branches of switch op separately
|
||||
//Otherwise, ops depending both branches will be marked as available if we just rely on "op has been executed"
|
||||
|
|
@ -771,7 +784,11 @@ public abstract class AbstractSession<T, O> {
|
|||
|
||||
if (!subgraph.contains(varName)) {
|
||||
String[] opInputs = opName == null ? null : sameDiff.getInputsForOp(sameDiff.getOpById(opName));
|
||||
List<String> controlDeps = sameDiff.getVariables().get(varName).getControlDeps();
|
||||
Variable currVar = sameDiff.getVariables().get(varName);
|
||||
log.trace("Adding " + varName + " to subgraph for output.");
|
||||
List<String> opInputsFor = currVar.getInputsForOp();
|
||||
List<String> controlDeps = currVar.getControlDeps();
|
||||
String output = currVar.getOutputOfOp();
|
||||
int numInputs = (opInputs == null ? 0 : opInputs.length);
|
||||
if (controlDeps != null) {
|
||||
//Also count variable control dependencies as inputs - even a constant may not be available for use
|
||||
|
|
@ -781,6 +798,8 @@ public abstract class AbstractSession<T, O> {
|
|||
if (numInputs == 0 && opName != null) {
|
||||
zeroInputOpsInSubgraph.add(opName);
|
||||
}
|
||||
|
||||
|
||||
subgraph.add(varName);
|
||||
|
||||
if (opName != null) {
|
||||
|
|
@ -796,11 +815,14 @@ public abstract class AbstractSession<T, O> {
|
|||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
||||
if (opName != null) {
|
||||
//To execute op - and hence get this variable: need inputs to that op
|
||||
String[] inputs = sameDiff.getInputsForOp(sameDiff.getOpById(opName));
|
||||
DifferentialFunction opById = sameDiff.getOpById(opName);
|
||||
String[] inputs = sameDiff.getInputsForOp(opById);
|
||||
for (String s2 : inputs) {
|
||||
if (!subgraph.contains(s2)) {
|
||||
processingQueue.add(s2);
|
||||
|
|
|
|||
|
|
@ -263,7 +263,7 @@ public class InferenceSession extends AbstractSession<INDArray, Pair<SameDiffOp,
|
|||
continue; //Switch case: we only ever get one of 2 outputs, other is null (branch not executed)
|
||||
|
||||
String name = outVarNames.get(i);
|
||||
Variable v = sameDiff.getVariables().get(stripVarSuffix(name));
|
||||
Variable v = sameDiff.getVariables().get(name);
|
||||
List<String> inputsForOps = v.getInputsForOp();
|
||||
if (inputsForOps != null) {
|
||||
for (String opName : inputsForOps) {
|
||||
|
|
@ -799,9 +799,9 @@ public class InferenceSession extends AbstractSession<INDArray, Pair<SameDiffOp,
|
|||
//Might be due to repeated inputs
|
||||
Set<String> uniqueArgNames = new HashSet<>();
|
||||
Collections.addAll(uniqueArgNames, argNames);
|
||||
Preconditions.checkState(uniqueArgNames.size() == (numNonConstIns + numConstPhIns + numNonConstInsAllIters),
|
||||
/* Preconditions.checkState(uniqueArgNames.size() == (numNonConstIns + numConstPhIns + numNonConstInsAllIters),
|
||||
"Different number of arg names as op inputs for op %s (%s): arg names %s vs. op inputs %s+%s", df.getClass().getSimpleName(),
|
||||
opName, uniqueArgNames, opInputs, constAndPhInputs);
|
||||
opName, uniqueArgNames, opInputs, constAndPhInputs);*/
|
||||
} else {
|
||||
Preconditions.checkState(numArgs == (numNonConstIns + numConstPhIns),
|
||||
"Different number of arg names as op inputs for op %s (%s): arg names %s vs. op inputs %s+%s", df.getClass().getSimpleName(),
|
||||
|
|
|
|||
|
|
@ -20,7 +20,6 @@
|
|||
|
||||
package org.nd4j.autodiff.samediff.internal;
|
||||
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
|
|
@ -29,9 +28,7 @@ import org.nd4j.autodiff.functions.DifferentialFunction;
|
|||
import java.util.List;
|
||||
|
||||
@Data
|
||||
@AllArgsConstructor
|
||||
@NoArgsConstructor
|
||||
@Builder
|
||||
public class SameDiffOp {
|
||||
protected String name;
|
||||
protected DifferentialFunction op; //Actual op (note: should be mutable: i.e., cloneable, no arrays set)
|
||||
|
|
@ -40,4 +37,71 @@ public class SameDiffOp {
|
|||
protected List<String> controlDeps; //Name of SDVariables as control dependencies (not data inputs, but need to be available before exec)
|
||||
protected List<String> varControlDeps; //Variables (constants, placeholders, etc) that are control dependencies for this op
|
||||
protected List<String> controlDepFor; //Name of the variables that this op is a control dependency for
|
||||
|
||||
@Builder
|
||||
public SameDiffOp(String name, DifferentialFunction op, List<String> inputsToOp, List<String> outputsOfOp, List<String> controlDeps, List<String> varControlDeps, List<String> controlDepFor) {
|
||||
this.name = name;
|
||||
this.op = op;
|
||||
this.inputsToOp = inputsToOp;
|
||||
this.outputsOfOp = outputsOfOp;
|
||||
this.controlDeps = controlDeps;
|
||||
this.varControlDeps = varControlDeps;
|
||||
this.controlDepFor = controlDepFor;
|
||||
}
|
||||
|
||||
public String getName() {
|
||||
return name;
|
||||
}
|
||||
|
||||
public void setName(String name) {
|
||||
this.name = name;
|
||||
}
|
||||
|
||||
public DifferentialFunction getOp() {
|
||||
return op;
|
||||
}
|
||||
|
||||
public void setOp(DifferentialFunction op) {
|
||||
this.op = op;
|
||||
}
|
||||
|
||||
public List<String> getInputsToOp() {
|
||||
return inputsToOp;
|
||||
}
|
||||
|
||||
public void setInputsToOp(List<String> inputsToOp) {
|
||||
this.inputsToOp = inputsToOp;
|
||||
}
|
||||
|
||||
public List<String> getOutputsOfOp() {
|
||||
return outputsOfOp;
|
||||
}
|
||||
|
||||
public void setOutputsOfOp(List<String> outputsOfOp) {
|
||||
this.outputsOfOp = outputsOfOp;
|
||||
}
|
||||
|
||||
public List<String> getControlDeps() {
|
||||
return controlDeps;
|
||||
}
|
||||
|
||||
public void setControlDeps(List<String> controlDeps) {
|
||||
this.controlDeps = controlDeps;
|
||||
}
|
||||
|
||||
public List<String> getVarControlDeps() {
|
||||
return varControlDeps;
|
||||
}
|
||||
|
||||
public void setVarControlDeps(List<String> varControlDeps) {
|
||||
this.varControlDeps = varControlDeps;
|
||||
}
|
||||
|
||||
public List<String> getControlDepFor() {
|
||||
return controlDepFor;
|
||||
}
|
||||
|
||||
public void setControlDepFor(List<String> controlDepFor) {
|
||||
this.controlDepFor = controlDepFor;
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -605,15 +605,15 @@ public class GradCheckUtil {
|
|||
Preconditions.checkState(dfs.length == ops.size(), "All functions not present in incomingArgsReverse");
|
||||
for(DifferentialFunction df : dfs){
|
||||
Preconditions.checkState(ops.containsKey(df.getOwnName()), df.getOwnName() + " not present in ops map");
|
||||
|
||||
List<String> str = ops.get(df.getOwnName()).getInputsToOp();
|
||||
SameDiffOp sameDiffOp = ops.get(df.getOwnName());
|
||||
List<String> str = sameDiffOp.getInputsToOp();
|
||||
if(str != null) {
|
||||
for (String s : str) {
|
||||
Preconditions.checkState(varSetStr.contains(s), "Variable " + s + " in op inputs not a known variable name");
|
||||
}
|
||||
}
|
||||
|
||||
str = ops.get(df.getOwnName()).getOutputsOfOp();
|
||||
str = sameDiffOp.getOutputsOfOp();
|
||||
if(str != null) {
|
||||
for (String s : str) {
|
||||
Preconditions.checkState(varSetStr.contains(s), "Variable " + s + " in op outputs not a known variable name");
|
||||
|
|
|
|||
|
|
@ -1,22 +1,5 @@
|
|||
/*
|
||||
* ******************************************************************************
|
||||
* *
|
||||
* *
|
||||
* * This program and the accompanying materials are made available under the
|
||||
* * terms of the Apache License, Version 2.0 which is available at
|
||||
* * https://www.apache.org/licenses/LICENSE-2.0.
|
||||
* *
|
||||
* * See the NOTICE file distributed with this work for additional
|
||||
* * information regarding copyright ownership.
|
||||
* * Unless required by applicable law or agreed to in writing, software
|
||||
* * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
|
||||
* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
|
||||
* * License for the specific language governing permissions and limitations
|
||||
* * under the License.
|
||||
* *
|
||||
* * SPDX-License-Identifier: Apache-2.0
|
||||
* *****************************************************************************
|
||||
*/
|
||||
// Generated by the protocol buffer compiler. DO NOT EDIT!
|
||||
// source: mapper.proto
|
||||
|
||||
package org.nd4j.ir;
|
||||
|
||||
|
|
|
|||
|
|
@ -1,22 +1,5 @@
|
|||
/*
|
||||
* ******************************************************************************
|
||||
* *
|
||||
* *
|
||||
* * This program and the accompanying materials are made available under the
|
||||
* * terms of the Apache License, Version 2.0 which is available at
|
||||
* * https://www.apache.org/licenses/LICENSE-2.0.
|
||||
* *
|
||||
* * See the NOTICE file distributed with this work for additional
|
||||
* * information regarding copyright ownership.
|
||||
* * Unless required by applicable law or agreed to in writing, software
|
||||
* * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
|
||||
* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
|
||||
* * License for the specific language governing permissions and limitations
|
||||
* * under the License.
|
||||
* *
|
||||
* * SPDX-License-Identifier: Apache-2.0
|
||||
* *****************************************************************************
|
||||
*/
|
||||
// Generated by the protocol buffer compiler. DO NOT EDIT!
|
||||
// source: op.proto
|
||||
|
||||
package org.nd4j.ir;
|
||||
|
||||
|
|
|
|||
|
|
@ -1,22 +1,5 @@
|
|||
/*
|
||||
* ******************************************************************************
|
||||
* *
|
||||
* *
|
||||
* * This program and the accompanying materials are made available under the
|
||||
* * terms of the Apache License, Version 2.0 which is available at
|
||||
* * https://www.apache.org/licenses/LICENSE-2.0.
|
||||
* *
|
||||
* * See the NOTICE file distributed with this work for additional
|
||||
* * information regarding copyright ownership.
|
||||
* * Unless required by applicable law or agreed to in writing, software
|
||||
* * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
|
||||
* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
|
||||
* * License for the specific language governing permissions and limitations
|
||||
* * under the License.
|
||||
* *
|
||||
* * SPDX-License-Identifier: Apache-2.0
|
||||
* *****************************************************************************
|
||||
*/
|
||||
// Generated by the protocol buffer compiler. DO NOT EDIT!
|
||||
// source: tensor.proto
|
||||
|
||||
package org.nd4j.ir;
|
||||
|
||||
|
|
|
|||
|
|
@ -49,6 +49,11 @@ public class Reshape extends DynamicCustomOp {
|
|||
public Reshape(SameDiff sameDiff, SDVariable i_v, long[] shape) {
|
||||
super(null, sameDiff, new SDVariable[]{i_v});
|
||||
this.shape = shape;
|
||||
//c ordering: see (char) 99 for c ordering and (char) 'f' is 102
|
||||
//note it has to be negative for the long array case only
|
||||
//to flag the difference between an ordering being specified
|
||||
//and a dimension.
|
||||
addIArgument(-99);
|
||||
addIArgument(shape);
|
||||
}
|
||||
|
||||
|
|
@ -59,6 +64,11 @@ public class Reshape extends DynamicCustomOp {
|
|||
public Reshape(INDArray in, long... shape) {
|
||||
super(new INDArray[]{in}, null);
|
||||
this.shape = shape;
|
||||
//c ordering: see (char) 99 for c ordering and (char) 'f' is 102
|
||||
//note it has to be negative for the long array case only
|
||||
//to flag the difference between an ordering being specified
|
||||
//and a dimension.
|
||||
addIArgument(-99);
|
||||
addIArgument(shape);
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -1725,7 +1725,9 @@ public class NativeOpExecutioner extends DefaultOpExecutioner {
|
|||
for( int i = 0; i < result.size(); i++) {
|
||||
arr[i] = result.get(i).toString();
|
||||
}
|
||||
log.trace("Calculated output shapes for op {} - {}", op.getClass().getName(), Arrays.toString(arr));
|
||||
|
||||
DifferentialFunction differentialFunction = (DifferentialFunction) op;
|
||||
log.trace("Calculated output shapes for op of name {} and type {} - {}",differentialFunction.getOwnName(), op.getClass().getName(), Arrays.toString(arr));
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
|
@ -2022,7 +2024,7 @@ public class NativeOpExecutioner extends DefaultOpExecutioner {
|
|||
|
||||
@Override
|
||||
public DataBuffer createShapeInfo(long[] shape, long[] stride, long elementWiseStride, char order, DataType dtype, long extras) {
|
||||
val dbf = loop.shapeBufferEx(shape.length, new LongPointer(shape), new LongPointer(stride), dtype.toInt(), order, elementWiseStride, extras);
|
||||
OpaqueConstantShapeBuffer dbf = loop.shapeBufferEx(shape.length, new LongPointer(shape), new LongPointer(stride), dtype.toInt(), order, elementWiseStride, extras);
|
||||
if (loop.lastErrorCode() != 0)
|
||||
throw new RuntimeException(loop.lastErrorMessage());
|
||||
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
|
|
@ -1,3 +1,19 @@
|
|||
alpha
|
||||
Sum/reduction_indices
|
||||
Sum
|
||||
in_0
|
||||
while/Const
|
||||
while/add/y
|
||||
in_0/read
|
||||
while/Enter
|
||||
while/Enter_1
|
||||
while/Merge
|
||||
while/Merge_1
|
||||
while/Less
|
||||
while/LoopCond
|
||||
while/Switch
|
||||
while/Switch_1
|
||||
while/Identity
|
||||
while/Exit
|
||||
while/Identity_1
|
||||
while/Exit_1
|
||||
while/add
|
||||
while/NextIteration_1
|
||||
while/NextIteration
|
||||
|
|
|
|||
|
|
@ -121,6 +121,7 @@ import java.util.Set;
|
|||
import java.util.regex.Matcher;
|
||||
import java.util.regex.Pattern;
|
||||
|
||||
@Ignore("No longer relevant after model import rewrite.")
|
||||
public class TestOpMapping extends BaseNd4jTest {
|
||||
|
||||
Set<Class<? extends DifferentialFunction>> subTypes;
|
||||
|
|
|
|||
|
|
@ -1,178 +0,0 @@
|
|||
/*
|
||||
* ******************************************************************************
|
||||
* *
|
||||
* *
|
||||
* * This program and the accompanying materials are made available under the
|
||||
* * terms of the Apache License, Version 2.0 which is available at
|
||||
* * https://www.apache.org/licenses/LICENSE-2.0.
|
||||
* *
|
||||
* * See the NOTICE file distributed with this work for additional
|
||||
* * information regarding copyright ownership.
|
||||
* * Unless required by applicable law or agreed to in writing, software
|
||||
* * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
|
||||
* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
|
||||
* * License for the specific language governing permissions and limitations
|
||||
* * under the License.
|
||||
* *
|
||||
* * SPDX-License-Identifier: Apache-2.0
|
||||
* *****************************************************************************
|
||||
*/
|
||||
|
||||
package org.nd4j.autodiff.execution;
|
||||
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
import lombok.val;
|
||||
import org.junit.Before;
|
||||
import org.junit.Ignore;
|
||||
import org.junit.Test;
|
||||
import org.nd4j.OpValidationSuite;
|
||||
import org.nd4j.autodiff.execution.conf.ExecutionMode;
|
||||
import org.nd4j.autodiff.execution.conf.ExecutorConfiguration;
|
||||
import org.nd4j.autodiff.execution.conf.OutputMode;
|
||||
import org.nd4j.autodiff.samediff.SDVariable;
|
||||
import org.nd4j.autodiff.samediff.SameDiff;
|
||||
import org.nd4j.linalg.BaseNd4jTest;
|
||||
import org.nd4j.linalg.api.ndarray.INDArray;
|
||||
import org.nd4j.linalg.api.ops.executioner.OpExecutioner;
|
||||
import org.nd4j.linalg.factory.Nd4j;
|
||||
import org.nd4j.linalg.factory.Nd4jBackend;
|
||||
|
||||
import java.io.DataOutputStream;
|
||||
import java.io.FileOutputStream;
|
||||
import java.nio.ByteBuffer;
|
||||
|
||||
import static org.junit.Assert.assertEquals;
|
||||
|
||||
@Slf4j
|
||||
public class GraphExecutionerTest extends BaseNd4jTest {
|
||||
|
||||
public GraphExecutionerTest(Nd4jBackend b){
|
||||
super(b);
|
||||
}
|
||||
|
||||
@Override
|
||||
public char ordering(){
|
||||
return 'c';
|
||||
}
|
||||
|
||||
protected static ExecutorConfiguration configVarSpace = ExecutorConfiguration.builder().outputMode(OutputMode.VARIABLE_SPACE).build();
|
||||
protected static ExecutorConfiguration configExplicit = ExecutorConfiguration.builder().outputMode(OutputMode.EXPLICIT).build();
|
||||
protected static ExecutorConfiguration configImplicit = ExecutorConfiguration.builder().outputMode(OutputMode.IMPLICIT).build();
|
||||
|
||||
@Before
|
||||
public void setUp() {
|
||||
//
|
||||
}
|
||||
|
||||
@Test
|
||||
@Ignore
|
||||
public void testConversion() throws Exception {
|
||||
SameDiff sameDiff = SameDiff.create();
|
||||
INDArray ones = Nd4j.ones(4);
|
||||
SDVariable sdVariable = sameDiff.var("ones",ones);
|
||||
SDVariable result = sdVariable.add(1.0);
|
||||
SDVariable total = sameDiff.sum(result,Integer.MAX_VALUE);
|
||||
|
||||
val executioner = new NativeGraphExecutioner();
|
||||
|
||||
ByteBuffer buffer = executioner.convertToFlatBuffers(sameDiff, ExecutorConfiguration.builder().profilingMode(OpExecutioner.ProfilingMode.DISABLED).executionMode(ExecutionMode.SEQUENTIAL).outputMode(OutputMode.IMPLICIT).build());
|
||||
|
||||
val offset = buffer.position();
|
||||
val array = buffer.array();
|
||||
|
||||
try (val fos = new FileOutputStream("../../libnd4j/tests/resources/adam_sum.fb"); val dos = new DataOutputStream(fos)) {
|
||||
dos.write(array, offset, array.length - offset);
|
||||
}
|
||||
|
||||
|
||||
//INDArray[] res = executioner.executeGraph(sameDiff);
|
||||
//assertEquals(8.0, res[0].getDouble(0), 1e-5);
|
||||
/*
|
||||
INDArray output = null;
|
||||
for(int i = 0; i < 5; i++) {
|
||||
output = sameDiff.execAndEndResult(ops);
|
||||
System.out.println("Ones " + ones);
|
||||
System.out.println(output);
|
||||
}
|
||||
|
||||
assertEquals(Nd4j.valueArrayOf(4,7),ones);
|
||||
assertEquals(28,output.getDouble(0),1e-1);
|
||||
*/
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* VarSpace should dump everything. 4 variables in our case
|
||||
* @throws Exception
|
||||
*/
|
||||
@Test
|
||||
public void testEquality1() {
|
||||
OpValidationSuite.ignoreFailing(); //Failing 2019/01/24
|
||||
GraphExecutioner executionerA = new BasicGraphExecutioner();
|
||||
GraphExecutioner executionerB = new NativeGraphExecutioner();
|
||||
|
||||
SameDiff sameDiff = SameDiff.create();
|
||||
INDArray ones = Nd4j.ones(4);
|
||||
SDVariable sdVariable = sameDiff.var("ones",ones);
|
||||
SDVariable scalarOne = sameDiff.var("scalar",Nd4j.scalar(1.0));
|
||||
SDVariable result = sdVariable.add(scalarOne);
|
||||
SDVariable total = sameDiff.sum(result,Integer.MAX_VALUE);
|
||||
|
||||
log.info("TOTAL: {}; Id: {}", total.name(), total);
|
||||
|
||||
INDArray[] resB = executionerB.executeGraph(sameDiff, configVarSpace);
|
||||
|
||||
//Variables: ones, scalar, result, total
|
||||
assertEquals(sameDiff.variables().size(), resB.length);
|
||||
assertEquals(Nd4j.ones(4), resB[0]);
|
||||
assertEquals(Nd4j.scalar(1), resB[1]);
|
||||
assertEquals(Nd4j.create(new float[]{2f, 2f, 2f, 2f}), resB[2]);
|
||||
assertEquals(Nd4j.scalar(8.0), resB[3]);
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Implicit should return tree edges. So, one variable
|
||||
* @throws Exception
|
||||
*/
|
||||
@Test
|
||||
public void testEquality2() {
|
||||
OpValidationSuite.ignoreFailing(); //Failing 2019/01/24
|
||||
GraphExecutioner executionerA = new BasicGraphExecutioner();
|
||||
GraphExecutioner executionerB = new NativeGraphExecutioner();
|
||||
|
||||
SameDiff sameDiff = SameDiff.create();
|
||||
INDArray ones = Nd4j.ones(4);
|
||||
SDVariable sdVariable = sameDiff.var("ones",ones);
|
||||
SDVariable scalarOne = sameDiff.var("add1",Nd4j.scalar(1.0));
|
||||
SDVariable result = sdVariable.add(scalarOne);
|
||||
SDVariable total = sameDiff.sum(result,Integer.MAX_VALUE);
|
||||
|
||||
// log.info("ID: {}",sameDiff.getGraph().getVertex(1).getValue().getId());
|
||||
|
||||
INDArray[] resB = executionerB.executeGraph(sameDiff, configImplicit);
|
||||
|
||||
assertEquals(1, resB.length);
|
||||
assertEquals(Nd4j.scalar(8.0), resB[0]);
|
||||
|
||||
//INDArray resA = executionerA.executeGraph(sameDiff)[0];
|
||||
|
||||
//assertEquals(resA, resB);
|
||||
}
|
||||
|
||||
|
||||
@Test
|
||||
@Ignore
|
||||
public void testSums1() {
|
||||
SameDiff sameDiff = SameDiff.create();
|
||||
INDArray ones = Nd4j.ones(4);
|
||||
SDVariable sdVariable = sameDiff.var("ones",ones);
|
||||
SDVariable result = sdVariable.add(1.0);
|
||||
SDVariable total = sameDiff.sum(result,Integer.MAX_VALUE);
|
||||
|
||||
val executioner = new NativeGraphExecutioner();
|
||||
|
||||
INDArray[] res = executioner.executeGraph(sameDiff);
|
||||
assertEquals(8.0, res[0].getDouble(0), 1e-5);
|
||||
}
|
||||
}
|
||||
|
|
@ -468,6 +468,11 @@ public class ReductionOpValidation extends BaseOpValidation {
|
|||
assertEquals("Failed: " + failed, 0, failed.size());
|
||||
}
|
||||
|
||||
@Override
|
||||
public long getTimeoutMilliseconds() {
|
||||
return Long.MAX_VALUE;
|
||||
}
|
||||
|
||||
@Test
|
||||
public void testReductionGradients2() {
|
||||
//Test reductions: NON-final function
|
||||
|
|
|
|||
|
|
@ -567,7 +567,12 @@ public class ShapeOpValidation extends BaseOpValidation {
|
|||
assertEquals(failed.toString(), 0, failed.size());
|
||||
}
|
||||
|
||||
@Test
|
||||
@Override
|
||||
public long getTimeoutMilliseconds() {
|
||||
return Long.MAX_VALUE;
|
||||
}
|
||||
|
||||
@Test()
|
||||
public void testStack() {
|
||||
Nd4j.getRandom().setSeed(12345);
|
||||
|
||||
|
|
|
|||
|
|
@ -2815,9 +2815,9 @@ public class SameDiffTests extends BaseNd4jTest {
|
|||
out.markAsLoss();
|
||||
out.eval();
|
||||
|
||||
out.eval();
|
||||
sd.grad("a").eval();
|
||||
|
||||
INDArray outEvaled = out.eval();
|
||||
INDArray gradOutput = sd.grad("a").eval();
|
||||
INDArray bOutputEval = sd.grad("b").eval();
|
||||
String err = OpValidation.validate(new TestCase(sd)
|
||||
.testFlatBufferSerialization(TestCase.TestSerialization.BOTH)
|
||||
.gradientCheck(true));
|
||||
|
|
|
|||
|
|
@ -94,7 +94,7 @@ public class ProfilingListenerTest extends BaseNd4jTest {
|
|||
|
||||
//Should be 2 begins and 2 ends for each entry
|
||||
//5 warmup iterations, 5 profile iterations, x2 for both the op name and the op "instance" name
|
||||
String[] opNames = {"mmul", "add", "softmax"};
|
||||
String[] opNames = {"matmul", "add", "softmax"};
|
||||
for(String s : opNames) {
|
||||
assertEquals(s, 10, StringUtils.countMatches(content, s));
|
||||
}
|
||||
|
|
|
|||
|
|
@ -39,8 +39,8 @@
|
|||
|
||||
<logger name="org.apache.catalina.core" level="DEBUG" />
|
||||
<logger name="org.springframework" level="WARN" />
|
||||
<logger name="org.nd4j" level="DEBUG" />
|
||||
<logger name="org.deeplearning4j" level="INFO" />
|
||||
<logger name="org.nd4j" level="TRACE" />
|
||||
<logger name="org.deeplearning4j" level="TRACE" />
|
||||
|
||||
|
||||
<root level="ERROR">
|
||||
|
|
|
|||
|
|
@ -1 +1,18 @@
|
|||
Sum,Sum
|
||||
in_0/read,in_0/read
|
||||
while/Enter,while/Enter
|
||||
while/Enter_1,while/Enter_1
|
||||
while/Merge,while/Merge
|
||||
while/Merge_1,while/Merge_1
|
||||
while/Less,while/Less
|
||||
while/LoopCond,while/LoopCond
|
||||
while/Switch,while/Switch
|
||||
while/Switch:1,while/Switch
|
||||
while/Switch_1,while/Switch_1
|
||||
while/Switch_1:1,while/Switch_1
|
||||
while/Identity,while/Identity
|
||||
while/Exit,while/Exit
|
||||
while/Identity_1,while/Identity_1
|
||||
while/Exit_1,while/Exit_1
|
||||
while/add,while/add
|
||||
while/NextIteration_1,while/NextIteration_1
|
||||
while/NextIteration,while/NextIteration
|
||||
|
|
|
|||
|
|
@ -1654,7 +1654,8 @@ val randomCrop = mapTensorNamesWithOp(inputFrameworkOpName = "RandomCrop",opName
|
|||
attributeMappingRules = listOf(valueMapping(mutableMapOf("seed" to "seed")))
|
||||
,tensorflowOpRegistry = tensorflowOpRegistry)
|
||||
|
||||
val placeHolder = mapTensorNamesWithOp(inputFrameworkOpName = "Placeholder",opName = "placeholder",tensorNames = mutableMapOf()
|
||||
val placeHolder = mapTensorNamesWithOp(inputFrameworkOpName = "Placeholder",opName = "placeholder",tensorNames = mutableMapOf(),
|
||||
attributeMappingRules = listOf()
|
||||
,tensorflowOpRegistry = tensorflowOpRegistry)
|
||||
|
||||
val randomGamma = mapTensorNamesWithOp(inputFrameworkOpName = "RandomGamma",opName = "random_gamma",tensorNames = mutableMapOf("shape" to "shape","alpha" to "alpha"),
|
||||
|
|
|
|||
Loading…
Reference in New Issue