org.nd4j.linalg.api.ops.impl.layers.convolution.LocalResponseNormalization 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.convolution;
import lombok.Builder;
import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import onnx.OnnxProto3;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.ops.impl.layers.convolution.config.LocalResponseNormalizationConfig;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.*;
/**
* LocalResponseNormalization operation
*/
@Slf4j
@Getter
@NoArgsConstructor
public class LocalResponseNormalization extends DynamicCustomOp {
protected LocalResponseNormalizationConfig config;
@Builder(builderMethodName = "builder")
public LocalResponseNormalization(SameDiff sameDiff, SDVariable[] inputFunctions,
INDArray[] inputs, INDArray[] outputs,boolean inPlace,
LocalResponseNormalizationConfig config) {
super(null,sameDiff, inputFunctions, inPlace);
this.config = config;
if(inputs != null) {
addInputArgument(inputs);
}
if(outputs!= null) {
addOutputArgument(outputs);
}
addArgs();
}
@Override
public Map propertiesForFunction() {
return config.toProperties();
}
private void addArgs() {
addTArgument(config.getBias());
addTArgument(config.getAlpha());
addTArgument(config.getBeta());
addIArgument(config.getDepth());
}
@Override
public String opName() {
return "lrn";
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
val aAlpha = nodeDef.getAttrOrThrow("alpha");
val aBeta = nodeDef.getAttrOrThrow("beta");
val aBias = nodeDef.getAttrOrThrow("bias");
val aDepth = nodeDef.getAttrOrThrow("depth_radius");
val alpha = aAlpha.getF();
val beta = aBeta.getF();
val bias = aBias.getF();
val depth = aDepth.getF();
LocalResponseNormalizationConfig localResponseNormalizationConfig = LocalResponseNormalizationConfig.builder()
.alpha(alpha)
.beta(beta)
.bias(bias)
.depth((int) depth)
.build();
this.config = localResponseNormalizationConfig;
addArgs();
}
@Override
public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map attributesForNode, OnnxProto3.GraphProto graph) {
val aAlpha = attributesForNode.get("alpha");
val aBeta = attributesForNode.get("beta");
val aBias = attributesForNode.get("bias");
val aDepth = attributesForNode.get("size");
val alpha = aAlpha.getF();
val beta = aBeta.getF();
val bias = aBias.getF();
val depth = aDepth.getF();
LocalResponseNormalizationConfig localResponseNormalizationConfig = LocalResponseNormalizationConfig.builder()
.alpha(alpha)
.beta(beta)
.bias(bias)
.depth((int) depth)
.build();
this.config = localResponseNormalizationConfig;
addArgs();
}
@Override
public Map> mappingsForFunction() {
Map> ret = new HashMap<>();
val depthMapping = PropertyMapping.builder()
.tfAttrName("depth_radius")
.propertyNames(new String[]{"depth"})
.onnxAttrName("size")
.build();
val alphaMapping = PropertyMapping.builder()
.tfAttrName("alpha")
.onnxAttrName("alpha")
.propertyNames(new String[]{"alpha"})
.build();
val betaMapping = PropertyMapping.builder()
.tfAttrName("beta")
.onnxAttrName("beta")
.propertyNames(new String[]{"beta"})
.build();
val biasMapping = PropertyMapping.builder()
.tfAttrName("bias")
.onnxAttrName("bias")
.propertyNames(new String[]{"bias"})
.build();
Map map = new HashMap<>();
map.put("depth",depthMapping);
map.put("alpha",alphaMapping);
map.put("beta",betaMapping);
map.put("bias",biasMapping);
ret.put(tensorflowName(),map);
ret.put(onnxName(),map);
return ret;
}
@Override
public List doDiff(List f1) {
SDVariable[] gradFnInputs = new SDVariable[]{arg(), f1.get(0)};
LocalResponseNormalizationDerivative lrnGrad = LocalResponseNormalizationDerivative.derivativeBuilder()
.inPlace(inPlace)
.sameDiff(sameDiff)
.inputFunctions(gradFnInputs)
.config(config)
.build();
return Collections.singletonList(lrnGrad.outputVariable());
}
@Override
public String onnxName() {
return "LRN";
}
@Override
public String tensorflowName() {
return "LRN";
}
}