deeplearning4j/deeplearning4j

/* ******************************************************************************
 *
 *
 * 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
 ******************************************************************************/

//
// @author raver119@gmail.com
//

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

#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/hashcode.h>
#include <ops/declarable/helpers/transforms.h>

namespace sd {
namespace ops {
CUSTOM_OP_IMPL(hashcode, 1, 1, false, 0, 0) {
  REQUIRE_TRUE(block.width() == 1, 0, "hashcode: this op can't be applied along dimension");

  auto input = INPUT_VARIABLE(0);
  auto output = OUTPUT_VARIABLE(0);

  REQUIRE_TRUE(output->isScalar(), 0, "hashcode: this op requires scalar output");

  helpers::hashCode(block.launchContext(), *input, *output);

  return sd::Status::OK;
};

DECLARE_SHAPE_FN(hashcode) {
  return SHAPELIST(ConstantShapeHelper::getInstance().scalarShapeInfo(sd::DataType::INT64));
}

DECLARE_TYPES(hashcode) {
  getOpDescriptor()
      ->setAllowedInputTypes(0, {ANY})
      ->setAllowedInputTypes(1, {ANY})
      ->setAllowedOutputTypes({sd::DataType::INT64});
};
}  // namespace ops
}  // namespace sd

#endif