org.nd4j.linalg.api.ops.impl.transforms.custom.MirrorPad 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.transforms.custom;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.imports.descriptors.properties.AttributeAdapter;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
import org.nd4j.imports.descriptors.properties.adapters.StringEqualsAdapter;
import org.nd4j.imports.descriptors.properties.adapters.StringNotEqualsAdapter;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.buffer.DataType;
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.*;
@Slf4j
public class MirrorPad extends DynamicCustomOp {
protected boolean isSymmetric = false;
public MirrorPad() {
//
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
TFGraphMapper.getInstance().initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
iArguments.add(isSymmetric ? 1L : 0L);
}
@Override
public String opName() {
return "mirror_pad";
}
@Override
public String tensorflowName() {
return "MirrorPad";
}
@Override
public Map> attributeAdaptersForFunction() {
Map> ret = new HashMap<>();
Map tfMappings = new LinkedHashMap<>();
// :)
tfMappings.put("isSymmetric", new StringNotEqualsAdapter("REFLECT"));
ret.put(tensorflowName(), tfMappings);
return ret;
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
Map map = new HashMap<>();
val symmetric = PropertyMapping.builder()
.tfAttrName("mode")
.propertyNames(new String[]{"isSymmetric"})
.build();
map.put("isSymmetric", symmetric);
ret.put(tensorflowName(), map);
return ret;
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 2, "Expected exactly 2 input datatypes for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}