/* ******************************************************************************
 *
 *
 * 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 GS <sgazeos@gmail.com> on 4/6/2018.
//
#include <array/ResultSet.h>
#include <ops/declarable/helpers/diag.h>
#if NOT_EXCLUDED(OP_diag)
namespace sd {
namespace ops {
namespace helpers {

//////////////////////////////////////////////////////////////////////////
// Returns a batched matrix tensor with new batched diagonal values.
// for detailed explanations please take a look on web page:
// https://www.tensorflow.org/api_docs/python/tf/matrix_set_diag
template <typename T>
static void _diagFunctor(NDArray* input, NDArray* output) {
  const int inLength = input->isScalar() ? 1 : input->lengthOf();

  for (int i = 0; i < inLength; ++i) output->p<T>(i * (inLength + 1), (*input).e<T>(i));
}

void diagFunctor(sd::LaunchContext* context, NDArray* input, NDArray* output) {
  auto xType = input->dataType();

  BUILD_SINGLE_SELECTOR(xType, _diagFunctor, (input, output), SD_COMMON_TYPES);
}

BUILD_SINGLE_TEMPLATE( void _diagFunctor, (NDArray* input, NDArray* output);, SD_COMMON_TYPES);

void diagPartFunctor(sd::LaunchContext* context, NDArray * input, NDArray* output) {
  const int outLen = output->lengthOf();
  const int inLen = input->lengthOf();
  int i(0), j(0);
  while (j < outLen) {
    auto currE = input->e(i);
    output->p(j, &currE);
    i += outLen + 1;
    ++j;
  }
}

}  // namespace helpers
}  // namespace ops
}  // namespace sd
#endif