提交 b163e601 编写于 作者: T tensor-tang

add gtest

上级 aae994fd
......@@ -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>();
......
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