org.nd4j.linalg.api.ops.impl.loss.WeightedCrossEntropyLoss Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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* * information regarding copyright ownership.
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.api.ops.impl.loss;
import lombok.NoArgsConstructor;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.Op;
import java.util.Collections;
import java.util.List;
@NoArgsConstructor
public class WeightedCrossEntropyLoss extends DynamicCustomOp {
public WeightedCrossEntropyLoss(SameDiff sameDiff, SDVariable targets, SDVariable inputs, SDVariable weights) {
super(null, sameDiff, new SDVariable[]{targets, inputs, weights}, false);
this.sameDiff = sameDiff;
}
public WeightedCrossEntropyLoss(@NonNull INDArray targets, @NonNull INDArray inputs, @NonNull INDArray weights){
super(new INDArray[] {targets, inputs, weights}, null);
}
@Override
public String opName() {
return "weighted_cross_entropy_with_logits";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No TensorFlow op opName found for " + opName());
}
@Override
public Op.Type opType() {
return Op.Type.CUSTOM;
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == 3, "Expected exactly 3 input datatypes for %s, got %s", getClass(), inputDataTypes);
return Collections.singletonList(inputDataTypes.get(0)); //Same as predictions
}
}