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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.transforms.custom;
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.ops.impl.transforms.BaseDynamicTransformOp;
import java.util.Collections;
import java.util.List;
public class Zeta extends BaseDynamicTransformOp {
public Zeta(SameDiff sameDiff, SDVariable x, SDVariable q) {
super(sameDiff, new SDVariable[] {x, q} ,false);
}
public Zeta() {}
@Override
public String opName() {
return "zeta";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op opName found for " + opName());
}
@Override
public String tensorflowName() {
return "Zeta";
}
@Override
public List doDiff(List i_v) {
throw new UnsupportedOperationException("Not yet implemented: " + opName());
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 2, "Expected exactly 2 input datatypes for %s, got %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.get(0).isFPType(), "Input 0 datatype must be a floating point type, got %s", dataTypes.get(0));
Preconditions.checkState(dataTypes.get(1).isFPType(), "Input 1 datatype must be a floating point type, got %s", dataTypes.get(1));
Preconditions.checkState(dataTypes.get(0) == dataTypes.get(1), "Input datatypes must be equal, type, got %s", dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}