org.nd4j.linalg.api.ops.impl.reduce.floating.Norm2 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.reduce.floating;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.BaseReduceFloatOp;
import org.nd4j.linalg.ops.transforms.Transforms;
import java.util.Collections;
import java.util.List;
/**
* Sum of squared values (real)
* Sum of squared complex modulus (complex)
*
* @author Adam Gibson
*/
public class Norm2 extends BaseReduceFloatOp {
public Norm2(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions) {
super(sameDiff, i_v, dimensions, keepDims);
}
public Norm2() {
}
public Norm2(INDArray x, INDArray z, int... dimensions) {
super(x, null, z, dimensions);
}
public Norm2(INDArray x, int... dimensions) {
super(x, dimensions);
}
public Norm2(INDArray x, boolean keepDims, int... dimensions) {
super(x, keepDims, dimensions);
}
@Override
public INDArray noOp() {
return Transforms.abs(x());
}
@Override
public int opNum() {
return 3;
}
@Override
public String opName() {
return "reduce_norm2";
}
@Override
public List doDiff(List grad) {
//d norm2(in)/dx = x / norm2(in)
return Collections.singletonList(f().norm2Bp(arg(), grad.get(0), keepDims, dimensions));
}
@Override
public String onnxName() {
return "Norm";
}
@Override
public String tensorflowName() {
return "norm";
}
}