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 Adam Gibson
//

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

#include <helpers/ShapeUtils.h>
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/choose.h>

namespace sd {
namespace ops {
CUSTOM_OP_IMPL(choose, -1, 2, false, -2, -1) {
  int mode = INT_ARG(0);
  auto result = OUTPUT_VARIABLE(0);
  auto numResults = OUTPUT_VARIABLE(1);

  if (block.width() > 1) {
    auto arg = INPUT_VARIABLE(0);
    auto comp = INPUT_VARIABLE(1);

    helpers::chooseFunctorArray(block.launchContext(), arg, comp, mode, result, numResults);

  }  // scalar case
  else {
    double scalar = T_ARG(0);
    auto arg = INPUT_VARIABLE(0);
    helpers::chooseFunctorScalar(block.launchContext(), arg, scalar, mode, result, numResults);
  }

  return sd::Status::OK;
}

DECLARE_TYPES(choose) {
  getOpDescriptor()
      ->setAllowedInputTypes(0, {ALL_FLOATS})
      ->setAllowedInputTypes(1, {ALL_FLOATS})
      ->setAllowedOutputTypes(0, {ALL_FLOATS})
      ->setAllowedOutputTypes(1, {ALL_INTS});
}

DECLARE_SHAPE_FN(choose) {
  sd::LongType const* shape;
  int rank;
  int mode = INT_ARG(0);
  auto numResults = NDArrayFactory::create<sd::LongType>(0L);
  if (block.width() > 1) {
    auto first = INPUT_VARIABLE(0);
    auto second = INPUT_VARIABLE(1);
    if (first->lengthOf() > second->lengthOf()) {
      shape = first->shapeInfo();
      rank = first->rankOf();
    } else {
      shape = second->shapeInfo();
      rank = second->rankOf();
    }

    helpers::chooseFunctorArray(block.launchContext(), first, second, mode, nullptr, &numResults);
  } else {
    auto first = INPUT_VARIABLE(0);
    shape = first->shapeInfo();
    rank = first->rankOf();
    double scalar = T_ARG(0);

    helpers::chooseFunctorScalar(block.launchContext(), first, scalar, mode, nullptr, &numResults);
  }

  auto newShape = ConstantShapeHelper::getInstance().vectorShapeInfo(numResults.e<sd::LongType>(0),
                                                                     ArrayOptions::dataType(inputShape->at(0)));

  auto shapeScalar = ConstantShapeHelper::getInstance().scalarShapeInfo(sd::DataType::INT64);
  return SHAPELIST(newShape, shapeScalar);
}

}  // namespace ops
}  // namespace sd

#endif