/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

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. */

#include "paddle/utils/Logging.h"

#include "SequencePoolLayer.h"
#include "paddle/math/Matrix.h"
#include "paddle/utils/Stat.h"

namespace paddle {

/**
 * A layer for extracting the last instance of the input sequence.
 * Input: a sequence
 * If SequenceLevel = kNonseq:
 *   Output: a sequence containing only the last instance of the input sequence
 * If SequenceLevel = kSeq:
 *   Check input sequence must has sub-sequence
 *   Output: a sequence containing only the last instance of each sub-sequence
 *           of the input sequence
 *
 * The config file api is last_seq and first_seq.
 */

class SequenceLastInstanceLayer : public SequencePoolLayer {
protected:
  MatrixPtr tmpSrc_;
  MatrixPtr tmpDest_;

public:
  explicit SequenceLastInstanceLayer(const LayerConfig& config)
      : SequencePoolLayer(config) {}

  ~SequenceLastInstanceLayer() {}

  bool init(const LayerMap& layerMap, const ParameterMap& parameterMap);

  void forward(PassType passType);
  void backward(const UpdateCallback& callback = nullptr);
};

REGISTER_LAYER(seqlastins, SequenceLastInstanceLayer);

bool SequenceLastInstanceLayer::init(const LayerMap& layerMap,
                                     const ParameterMap& parameterMap) {
  SequencePoolLayer::init(layerMap, parameterMap);

  tmpSrc_ =
      Matrix::create(nullptr, /* height= */ 1, 1, /* trans= */ false, useGpu_);
  tmpDest_ =
      Matrix::create(nullptr, /* height= */ 1, 1, /* trans= */ false, useGpu_);

  return true;
}

void SequenceLastInstanceLayer::forward(PassType passType) {
  SequencePoolLayer::forward(passType);

  const int* starts = startPositions_->getData(false);
  MatrixPtr inputValue = getInputValue(0);
  MatrixPtr outputValue = getOutputValue();

  {
    AsyncGpuBlock asyncGpuBlock;
    REGISTER_TIMER_INFO("SequenceLastInstanceLayerForward", getName().c_str());

    for (size_t seqId = 0; seqId < newBatchSize_; ++seqId) {
      int insId =
          config_.select_first() ? starts[seqId] : starts[seqId + 1] - 1;

      outputValue->subMatrix(seqId, 1, tmpDest_)
          ->assign(*(inputValue->subMatrix(insId, 1, tmpSrc_)));
    }
  }

  if (biases_.get() != NULL) {
    outputValue->addBias(*(biases_->getW()), 1);
  }

  /*  activation, should set to 'linear' in most cases */
  forwardActivation();
}

void SequenceLastInstanceLayer::backward(const UpdateCallback& callback) {
  SequencePoolLayer::backward(callback);

  MatrixPtr inputGrad = getInputGrad(0);
  MatrixPtr outputGrad = getOutputGrad();
  const int* starts = startPositions_->getData(false);
  size_t numSequences = startPositions_->getSize() - 1;

  if (inputGrad) {
    AsyncGpuBlock asyncGpuBlock;
    REGISTER_TIMER_INFO("SequenceLastInstanceLayerBackward", getName().c_str());

    for (size_t seqId = 0; seqId < numSequences; ++seqId) {
      int insId =
          config_.select_first() ? starts[seqId] : starts[seqId + 1] - 1;

      inputGrad->subMatrix(insId, 1, tmpDest_)
          ->add(*(outputGrad->subMatrix(seqId, 1, tmpSrc_)));
    }
  }
}

}  // namespace paddle