org.nd4j.linalg.api.ops.custom.RandomCrop Maven / Gradle / Ivy
/* ******************************************************************************
* Copyright (c) 2019 Konduit K.K.
*
* 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.custom;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.rng.Random;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
public class RandomCrop extends DynamicCustomOp {
public RandomCrop() {}
public RandomCrop(@NonNull INDArray input, @NonNull INDArray shape) {
Preconditions.checkArgument(shape.isVector(),"RandomCrop:Shape tensor should be a vector");
Preconditions.checkArgument(input.rank() == shape.length(), "RandomCrop:The length of the shape vector is not match input rank");
addInputArgument(input, shape);
}
public RandomCrop(@NonNull SameDiff sameDiff, @NonNull SDVariable input, @NonNull SDVariable shape) {
super("", sameDiff, new SDVariable[]{input, shape});
}
@Override
public String opName() {
return "random_crop";
}
@Override
public String tensorflowName() {
return "RandomCrop";
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
Preconditions.checkState(inputDataTypes != null /*&& inputDataTypes.size() == 4*/,
"Expected 4 input datatypes for %s, got %s", getClass(), inputDataTypes);
return Collections.singletonList(DataType.FLOAT); //TF import: always returns float32...
}
}