deeplearning4j/deeplearning4j

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libnd4j/include/ops/declarable/generic/tensor/zeros_as.cpp

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/* ******************************************************************************
 *
 *
 * 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.
 *
 *  See the NOTICE file distributed with this work for additional
 *  information regarding copyright ownership.
 * 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
 ******************************************************************************/

//
// Created by raver119 on 12.10.2017.
//

#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_zeros_as)

#include <ops/declarable/CustomOperations.h>

namespace sd {
namespace ops {
CUSTOM_OP_IMPL(zeros_as, 1, 1, false, 0, 0) {
  auto out = OUTPUT_VARIABLE(0);

  out->assign(0);  // output is filled by zero by default

  return sd::Status::OK;
}
DECLARE_SYN(zeroslike, zeros_as);
DECLARE_SYN(zeros_like, zeros_as);

DECLARE_SHAPE_FN(zeros_as) {
  auto in = inputShape->at(0);
  auto dtype = block.numD() ? D_ARG(0) : ArrayOptions::dataType(in);
  auto shape = sd::ConstantShapeHelper::getInstance().createShapeInfo(dtype, in);

  return SHAPELIST(shape);
}

DECLARE_TYPES(zeros_as) {
  getOpDescriptor()
      ->setAllowedInputTypes(sd::DataType::ANY)
      ->setAllowedOutputTypes(sd::DataType::ANY)
      ->setSameMode(false);
}
}  // namespace ops
}  // namespace sd

#endif