deeplearning4j/deeplearning4j

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libnd4j/include/ops/declarable/generic/nn/activations/thresholdedrelu.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
 ******************************************************************************/

//
// @author Yurii Shyrma, created on 24.07.2018
//

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

#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/activations.h>
#include <ops/declarable/helpers/legacy_helpers.h>
namespace sd {
namespace ops {

////////////////////////////////////////////////////////////////////////
CONFIGURABLE_OP_IMPL(thresholdedrelu, 1, 1, true, 0, 0) {
  auto input = INPUT_VARIABLE(0);
  auto output = OUTPUT_VARIABLE(0);

  auto scalar = block.numT() > 0 ? block.getTArguments()->at(0) : 0.0;

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

  return sd::Status::OK;
}

DECLARE_TYPES(thresholdedrelu) { getOpDescriptor()->setAllowedInputTypes(0, DataType::ANY)->setSameMode(true); }

////////////////////////////////////////////////////////////////////////
CONFIGURABLE_OP_IMPL(thresholdedrelu_bp, 2, 1, true, 0, 0) {
  auto input = INPUT_VARIABLE(0);
  auto dLdO = INPUT_VARIABLE(1);

  auto dLdI = OUTPUT_VARIABLE(0);
  auto threshold = block.numT() > 0 ? block.getTArguments()->at(0) : 0.0;

  helpers::thresholdReluDerivative(block.launchContext(), input, threshold, dLdO, dLdI);

  return sd::Status::OK;
}

DECLARE_TYPES(thresholdedrelu_bp) {
  getOpDescriptor()
      ->setAllowedInputTypes(0, DataType::ANY)
      ->setAllowedInputTypes(1, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF})
      ->setAllowedOutputTypes(0, {DataType::FLOAT32, DataType ::DOUBLE, DataType::HALF});
}

}  // namespace ops
}  // namespace sd

#endif