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 Yurii Shyrma (iuriish@yahoo.com), created on 22.01.2018
//
#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_eye)

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

namespace sd {
namespace ops {

CUSTOM_OP_IMPL(eye, -2, 1, false, -2, -2) {
  helpers::eye(block.launchContext(), *OUTPUT_VARIABLE(0));

  return sd::Status::OK;
}

DECLARE_TYPES(eye) {
  getOpDescriptor()->setAllowedInputTypes(0, {ALL_INTS});
  getOpDescriptor()->setAllowedInputTypes(1, {DataType::INT32, DataType::INT64});
  getOpDescriptor()->setAllowedOutputTypes(0, {ALL_FLOATS});
}

DECLARE_SHAPE_FN(eye) {
  std::vector<LongType> params;

  sd::DataType dtype = block.getTArguments()->empty() ? sd::DataType::FLOAT32 : sd::DataTypeUtils::fromInt(T_ARG(0));

  if (block.width() == 0) {
    params = *block.getIArguments();
  } else {
    for (int i = 0; i < block.width(); i++) {
      auto input = INPUT_VARIABLE(i);
      REQUIRE_TRUE(input->rankOf() == 1, 0, "Inputs to eye should be 1D");

      for (int e = 0; e < input->lengthOf(); e++) params.emplace_back(input->e<int>(e));
    }
  }

  REQUIRE_TRUE(params.size() > 0, 0, "Size is not provided for eye op.");

  const bool ordered = (params[0] == -99 || params[0] == -102);  // -99 :'c', -102 : 'f'
  if (!ordered) params.insert(params.begin(), -99);

  REQUIRE_TRUE(params.size() > 1, 0, "Size is not provided for eye op.");

  sd::LongType* outShapeInfo(nullptr);

  const int size = params.size();

  switch (size) {
    case 2:
      ALLOCATE(outShapeInfo, block.getWorkspace(), shape::shapeInfoLength(2), sd::LongType);
      outShapeInfo[0] = 2;
      outShapeInfo[1] = params[1];
      outShapeInfo[2] = params[1];
      break;

    case 3:
      ALLOCATE(outShapeInfo, block.getWorkspace(), shape::shapeInfoLength(2), sd::LongType);
      outShapeInfo[0] = 2;
      outShapeInfo[1] = params[1];
      outShapeInfo[2] = params[2];
      break;

    default:
      int rank = size - 1;
      ALLOCATE(outShapeInfo, block.getWorkspace(), shape::shapeInfoLength(rank), sd::LongType);
      outShapeInfo[0] = rank;
      outShapeInfo[rank - 1] = params[1];
      outShapeInfo[rank] = params[2];
      for (int i = 1; i < rank - 1; ++i) outShapeInfo[i] = params[i + 2];
      break;
  }

  shape::updateStrides(outShapeInfo, static_cast<char>(-params[0]));
  auto desc = new ShapeDescriptor(outShapeInfo, dtype);
  auto result = ConstantShapeHelper::getInstance().createShapeInfo(desc);
  RELEASE(outShapeInfo, block.getWorkspace());
  auto ret =  SHAPELIST(result);
  delete desc;
  return ret;
}

}  // namespace ops
}  // namespace sd

#endif