org.nd4j.linalg.api.ops.impl.layers.recurrent.SRU Maven / Gradle / Ivy
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* Copyright (c) 2015-2018 Skymind, Inc.
*
* 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.
*
* 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.impl.layers.recurrent;
import java.util.Arrays;
import java.util.List;
import lombok.Getter;
import lombok.NonNull;
import onnx.Onnx;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.impl.layers.recurrent.weights.SRUWeights;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.Map;
/**
* Simple recurrent unit
*
* @author Adam Gibson
*/
public class SRU extends DynamicCustomOp {
@Getter
private SRUWeights weights;
@Getter
private SDVariable mask;
public SRU() { }
public SRU(@NonNull SameDiff sameDiff, @NonNull SDVariable x, @NonNull SDVariable initialC, SDVariable mask, @NonNull SRUWeights weights) {
super(null, sameDiff, wrapFilterNull(x, weights.getWeights(), weights.getBias(), initialC, mask));
this.mask = mask;
this.weights = weights;
}
@Override
public String opName() {
return "sru";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No onnx op name for " + opName());
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No tensorflow op name for " + opName());
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
super.initFromTensorFlow(nodeDef, initWith, attributesForNode, graph);
}
@Override
public void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map attributesForNode, Onnx.GraphProto graph) {
super.initFromOnnx(node, initWith, attributesForNode, graph);
}
}