im2col_test.cc

/* 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 {
    TensorCopySync(input_tmp, *place, &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 {
    TensorCopySync(output_cfo, paddle::platform::CPUPlace(), &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 {
    TensorCopySync(output_ocf, paddle::platform::CPUPlace(), &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 {
    TensorCopySync(input_tmp, *place, &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 {
    TensorCopySync(input, paddle::platform::CPUPlace(), &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 {
    TensorCopySync(input_tmp, *place, &input);
  }

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

  if (paddle::platform::is_cpu_place(*place)) {
    in_ptr = input.data<float>();
  } else {
    TensorCopySync(input, paddle::platform::CPUPlace(), &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;
}

void testIm2colCPU() {
  paddle::framework::Tensor input;
  paddle::framework::Tensor output;
  int input_height = 3;
  int input_width = 4;
  int filter_size = 2;
  int ic = 2;
  std::vector<int> stride({1, 1});  // stride_y, stride_x
  std::vector<int> padding({0, 0});
  std::vector<int> dilation({1, 1});  // dilation_y, dilation_x
  int output_height =
      (input_height - filter_size + padding[0] * 2) / stride[0] + 1;
  int output_width =
      (input_width - filter_size + padding[1] * 2) / stride[1] + 1;
  float* input_ptr = input.mutable_data<float>({ic, input_height, input_width},
                                               paddle::platform::CPUPlace());
  for (int i = 0; i < input.numel(); ++i) {
    input_ptr[i] = static_cast<float>(i);
  }

  paddle::platform::CPUPlace place;
  paddle::platform::CPUDeviceContext context(place);
  output.mutable_data<float>(
      {ic, filter_size, filter_size, output_height, output_width}, place);
  paddle::operators::math::Im2ColFunctor<
      paddle::operators::math::ColFormat::kCFO,
      paddle::platform::CPUDeviceContext, float>
      im2col;
  im2col(context, input, dilation, stride, padding, &output);
  auto ref_im2col = [&](
      const paddle::framework::Tensor& im, const std::vector<int>& dilation,
      const std::vector<int>& stride, const std::vector<int>& padding,
      paddle::framework::Tensor* col) {
    int im_channels = im.dims()[0];
    int im_height = im.dims()[1];
    int im_width = im.dims()[2];
    int filter_height = col->dims()[1];
    int filter_width = col->dims()[2];
    int output_height = col->dims()[3];
    int output_width = col->dims()[4];

    int channels_col = im_channels * filter_height * filter_width;

    const float* im_data = im.data<float>();
    float* col_data = col->data<float>();
    for (int c = 0; c < channels_col; ++c) {
      int w_offset = c % filter_width;
      int h_offset = (c / filter_width) % filter_height;
      int c_im = c / (filter_width * filter_height);
      for (int h = 0; h < output_height; ++h) {
        int im_row_idx = h * stride[0] - padding[0] + h_offset * dilation[0];
        for (int w = 0; w < output_width; ++w) {
          int im_col_idx = w * stride[1] - padding[1] + w_offset * dilation[1];
          int col_idx = (c * output_height + h) * output_width + w;
          int im_idx = (im_row_idx + c_im * im_height) * im_width + im_col_idx;

          col_data[col_idx] = (im_row_idx < 0 || im_row_idx >= im_height ||
                               im_col_idx < 0 || im_col_idx >= im_width)
                                  ? 0.f
                                  : im_data[im_idx];
        }
      }
    }
  };

  paddle::framework::Tensor ref_output;
  ref_output.mutable_data<float>(
      {ic, filter_size, filter_size, output_height, output_width}, place);
  ref_im2col(input, dilation, stride, padding, &ref_output);

  float* out_cfo_ptr = output.data<float>();
  for (int i = 0; i < ic * filter_size * filter_size; ++i) {
    for (int j = 0; j < output_height * output_width; ++j) {
      std::cout << out_cfo_ptr[i * output_height * output_width + j] << ",";
    }
    std::cout << std::endl;
  }

  float* out_ref_ptr = ref_output.data<float>();
  for (int i = 0; i < output.numel(); ++i) {
    EXPECT_EQ(out_cfo_ptr[i], out_ref_ptr[i]);
  }
}

TEST(math, im2col) {
  testIm2col<paddle::platform::CPUDeviceContext, paddle::platform::CPUPlace>();
  testIm2colCPU();
#ifdef PADDLE_WITH_CUDA
  testIm2col<paddle::platform::CUDADeviceContext,
             paddle::platform::CUDAPlace>();
#endif
}