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

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/fluid/operators/math/im2col.h"
#include <gtest/gtest.h>
#include <vector>

template <typename DeviceContext, typename Place>
void testIm2col() {
  paddle::framework::Tensor input_tmp;
  paddle::framework::Tensor input;
  paddle::framework::Tensor output_cfo;
  paddle::framework::Tensor output_ocf;
  paddle::framework::Tensor output_tmp;

  /**
   * input = [0, 1, 2,
   *          3, 4, 5]
   *
   * output_cfo = [0, 1
   *               1, 2
   *               3, 4
   *               4, 5]
   *
   * output_ocf = [0, 1, 3, 4
   *               1, 2, 4, 5]
   *
   * col2im_cfo = [0, 2, 2
   *               3, 4, 5]
   *
   * col2im_ocf = [0, 2, 2
   *               3, 4, 5]
   */
  int input_height = 2;
  int input_width = 3;
  int filter_size = 2;
  std::vector<int> stride({1, 1});  // stride_y, stride_x
  std::vector<int> padding(
      {0, 0, 0, 0});                  // up_pad, left_pad, down_pad, right_pad
  std::vector<int> dilation({1, 1});  // dilation_y, dilation_x
  int output_height =
      (input_height - filter_size + padding[0] + padding[1]) / stride[0] + 1;
  int output_width =
      (input_width - filter_size + padding[2] + padding[3]) / stride[1] + 1;
  float* input_ptr = input_tmp.mutable_data<float>(
      {1, input_height, input_width}, paddle::platform::CPUPlace());
  float arr[6] = {0, 1, 2, 3, 4, 5};
  memcpy(input_ptr, arr, 6 * sizeof(float));

  auto* place = new Place();
  DeviceContext* context = new DeviceContext(*place);
  if (paddle::platform::is_cpu_place(*place)) {
    input = input_tmp;
  } else {
    TensorCopy(input_tmp, *place, *context, &input);
  }
  output_cfo.mutable_data<float>(
      {1, filter_size, filter_size, output_height, output_width}, *place);
  output_ocf.mutable_data<float>(
      {output_height, output_width, 1, filter_size, filter_size}, *place);

  // Im2Col
  paddle::operators::math::Im2ColFunctor<
      paddle::operators::math::ColFormat::kCFO, DeviceContext, float>
      im2col;
  paddle::operators::math::Im2ColFunctor<
      paddle::operators::math::ColFormat::kOCF, DeviceContext, float>
      im2col_ocf;

  im2col(*context, input, dilation, stride, padding, &output_cfo);
  im2col_ocf(*context, input, dilation, stride, padding, &output_ocf);

  float out_cfo_data[] = {0, 1, 1, 2, 3, 4, 4, 5};
  float out_ocf_data[] = {0, 1, 3, 4, 1, 2, 4, 5};

  float* out_cfo_ptr;
  if (paddle::platform::is_cpu_place(*place)) {
    out_cfo_ptr = output_cfo.data<float>();
  } else {
    TensorCopy(output_cfo, paddle::platform::CPUPlace(), *context, &output_tmp);
    out_cfo_ptr = output_tmp.data<float>();
  }
  for (int i = 0; i < 6; ++i) {
    EXPECT_EQ(out_cfo_ptr[i], out_cfo_data[i]);
  }

  float* out_ocf_ptr;
  if (paddle::platform::is_cpu_place(*place)) {
    out_ocf_ptr = output_ocf.data<float>();
  } else {
    TensorCopy(output_ocf, paddle::platform::CPUPlace(), *context, &output_tmp);
    out_ocf_ptr = output_tmp.data<float>();
  }

  for (int i = 0; i < 6; ++i) {
    EXPECT_EQ(out_ocf_ptr[i], out_ocf_data[i]);
  }

  // Col2Im: kCFO
  paddle::operators::math::Col2ImFunctor<
      paddle::operators::math::ColFormat::kCFO, DeviceContext, float>
      col2im;
  paddle::operators::math::Col2ImFunctor<
      paddle::operators::math::ColFormat::kOCF, DeviceContext, float>
      col2im_ocf;
  float col2im_data[] = {0, 2, 2, 3, 8, 5};

  memset(input_ptr, 0, 6 * sizeof(float));
  if (paddle::platform::is_cpu_place(*place)) {
    input = input_tmp;
  } else {
    TensorCopy(input_tmp, *place, *context, &input);
  }

  col2im(*context, output_cfo, dilation, stride, padding, &input);

  float* in_ptr;
  if (paddle::platform::is_cpu_place(*place)) {
    in_ptr = input.data<float>();
  } else {
    TensorCopy(input, paddle::platform::CPUPlace(), *context, &input_tmp);
    in_ptr = input_tmp.data<float>();
  }
  for (int i = 0; i < 6; ++i) {
    EXPECT_EQ(in_ptr[i], col2im_data[i]);
  }

  // Col2Im: kOCF
  memset(input_ptr, 0, 6 * sizeof(float));
  if (paddle::platform::is_cpu_place(*place)) {
    input = input_tmp;
  } else {
    TensorCopy(input_tmp, *place, *context, &input);
  }

  col2im_ocf(*context, output_ocf, dilation, stride, padding, &input);

  if (paddle::platform::is_cpu_place(*place)) {
    in_ptr = input.data<float>();
  } else {
    TensorCopy(input, paddle::platform::CPUPlace(), *context, &input_tmp);
    in_ptr = input_tmp.data<float>();
  }
  for (int i = 0; i < 6; ++i) {
    EXPECT_EQ(in_ptr[i], col2im_data[i]);
  }

  delete place;
  delete context;
}

TEST(math, im2col) {
  testIm2col<paddle::platform::CPUDeviceContext, paddle::platform::CPUPlace>();
#ifdef PADDLE_WITH_CUDA
  testIm2col<paddle::platform::CUDADeviceContext,
             paddle::platform::CUDAPlace>();
#endif
}