org.nd4j.linalg.api.ops.custom.BitCast Maven / Gradle / Ivy
/*
* ******************************************************************************
* *
* *
* * 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.linalg.api.ops.custom;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
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.shape.options.ArrayOptionsHelper;
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;
public class BitCast extends DynamicCustomOp {
public BitCast() {}
private DataType dtype;
public BitCast(INDArray in, DataType dataType, INDArray out) {
this(in, dataType.toInt(), out);
}
public BitCast(INDArray in, int dataType, INDArray out) {
inputArguments.add(in);
outputArguments.add(out);
iArguments.add(Long.valueOf(dataType));
dtype = DataType.fromInt(dataType);
}
public BitCast(INDArray in, DataType dataType) {
this(in, dataType.toInt());
}
public BitCast(INDArray in, int dataType) {
inputArguments.add(in);
iArguments.add(Long.valueOf(dataType));
dtype = DataType.fromInt(dataType);
}
public BitCast(SameDiff sameDiff, SDVariable in, SDVariable dataType) {
super("", sameDiff, new SDVariable[]{in, dataType});
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
TFGraphMapper.initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
val t = nodeDef.getAttrOrDefault("type", null);
val type = ArrayOptionsHelper.convertToDataType(t.getType());
addIArgument(type.toInt());
dtype = type;
}
@Override
public String opName() {
return "bitcast";
}
@Override
public String tensorflowName() {
return "Bitcast";
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
int n = args().length;
Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), inputDataTypes);
if(dtype == null) {
if(!iArguments.isEmpty()) {
dtype = DataType.fromInt(iArguments.get(0).intValue());
}
}
return Collections.singletonList(dtype);
}
}