add gtest

Author: tensor-tang

paddle/fluid/operators/math/im2col_test.cc

@@ -160,8 +160,93 @@ void testIm2col() {
   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>();