org.nd4j.linalg.api.ops.impl.broadcast.BroadcastTo Maven / Gradle / Ivy
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* * 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.
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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.broadcast;
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.factory.Nd4j;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.Collections;
import java.util.List;
import java.util.Map;
@NoArgsConstructor
public class BroadcastTo extends DynamicCustomOp {
public BroadcastTo(SameDiff sameDiff, SDVariable input, SDVariable shape) {
super(null, sameDiff, new SDVariable[] {input,shape}, false);
}
public BroadcastTo(@NonNull INDArray input, @NonNull long[] shape, @NonNull INDArray output){
this(input, Nd4j.createFromArray(shape), output);
}
public BroadcastTo(@NonNull INDArray input, @NonNull INDArray shape, @NonNull INDArray output){
super(null, new INDArray[]{input, shape}, new INDArray[]{output});
}
@Override
public String opName() {
return "broadcast_to";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
super.initFromTensorFlow(nodeDef, initWith, attributesForNode, graph);
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx opName found for " + opName());
}
@Override
public String tensorflowName() {
return "BroadcastTo";
}
@Override
public List doDiff(List gradient){
throw new UnsupportedOperationException("Not yet implemented");
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 2, "Expected 2 input datatype for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}