org.nd4j.linalg.api.ops.impl.shape.Squeeze 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.shape;
import lombok.val;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.*;
/**
*
*/
public class Squeeze extends DynamicCustomOp {
private int[] squeezeDims;
public Squeeze() {
}
public Squeeze(SameDiff sameDiff, SDVariable arg, int[] squeezeDims) {
super(null, sameDiff, new SDVariable[]{arg});
this.squeezeDims = squeezeDims;
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
super.initFromTensorFlow(nodeDef, initWith, attributesForNode, graph);
if (squeezeDims != null)
addIArgument(squeezeDims);
}
@Override
public void resolvePropertiesFromSameDiffBeforeExecution() {
super.resolvePropertiesFromSameDiffBeforeExecution();
if (squeezeDims != null && numIArguments() < squeezeDims.length) {
addIArgument(squeezeDims);
}
}
@Override
public String opName() {
return "squeeze";
}
@Override
public String tensorflowName() {
return "Squeeze";
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
Map mapping = new LinkedHashMap<>();
val squeezeDims = PropertyMapping.builder()
.tfAttrName("squeeze_dims")
.propertyNames(new String[]{"squeezeDims"})
.build();
mapping.put("squeezeDims", squeezeDims);
ret.put(tensorflowName(), mapping);
return ret;
}
@Override
public List doDiff(List i_v) {
if (squeezeDims == null) {
//TODO Strictly speaking this *is* possible by inspecting the input array
throw new IllegalStateException("Cannot do Squeeze backprop with no dimensions");
}
SDVariable ret = i_v.get(0);
for (int d : squeezeDims) {
ret = sameDiff.expandDims(ret, d);
}
;
return Arrays.asList(ret);
}
}