提交 8d6be4fb 编写于 作者: T tensor-tang

refine im2col test and add benchmark

上级 507c1430
...@@ -14,7 +14,9 @@ limitations under the License. */ ...@@ -14,7 +14,9 @@ limitations under the License. */
#include "paddle/fluid/operators/math/im2col.h" #include "paddle/fluid/operators/math/im2col.h"
#include <gtest/gtest.h> #include <gtest/gtest.h>
#include <sys/time.h>
#include <vector> #include <vector>
#include "paddle/fluid/operators/math/im2col_cfo_cpu.h"
template <typename DeviceContext, typename Place> template <typename DeviceContext, typename Place>
void testIm2col() { void testIm2col() {
...@@ -160,82 +162,86 @@ void testIm2col() { ...@@ -160,82 +162,86 @@ void testIm2col() {
delete context; delete context;
} }
TEST(math, im2col) {
testIm2col<paddle::platform::CPUDeviceContext, paddle::platform::CPUPlace>();
#ifdef PADDLE_WITH_CUDA
testIm2col<paddle::platform::CUDADeviceContext,
paddle::platform::CUDAPlace>();
#endif
}
#define PREPARE_IM2COL_CPU \
paddle::platform::CPUPlace place; \
paddle::platform::CPUDeviceContext context(place); \
paddle::framework::Tensor input; \
paddle::framework::Tensor out; \
paddle::framework::Tensor ref; \
std::vector<int> padding({ph, pw}); \
std::vector<int> stride({1, 1}); \
std::vector<int> dilation({1, 1}); \
float* input_ptr = input.mutable_data<float>({ic, ih, iw}, place); \
for (int i = 0; i < input.numel(); ++i) { \
input_ptr[i] = static_cast<float>(i + 1); \
} \
int output_height = (ih - fh + padding[0] * 2) / stride[0] + 1; \
int output_width = (iw - fw + padding[1] * 2) / stride[1] + 1; \
out.mutable_data<float>({ic, fh, fw, output_height, output_width}, place); \
ref.mutable_data<float>({ic, fh, fw, output_height, output_width}, place); \
paddle::operators::math::Im2ColFunctor< \
paddle::operators::math::ColFormat::kCFO, \
paddle::platform::CPUDeviceContext, float> \
im2col
void testIm2colCPU(int ic, int ih, int iw, int fh, int fw, int ph, int pw) { void testIm2colCPU(int ic, int ih, int iw, int fh, int fw, int ph, int pw) {
paddle::framework::Tensor input; PREPARE_IM2COL_CPU;
paddle::framework::Tensor output;
paddle::framework::Tensor ref_output;
std::vector<int> padding({ph, pw});
std::vector<int> stride({1, 1}); // stride_y, stride_x
std::vector<int> dilation({1, 1}); // dilation_y, dilation_x
int output_height = (ih - fh + padding[0] * 2) / stride[0] + 1;
int output_width = (iw - fw + padding[1] * 2) / stride[1] + 1;
float* input_ptr =
input.mutable_data<float>({ic, ih, iw}, paddle::platform::CPUPlace());
for (int i = 0; i < input.numel(); ++i) {
input_ptr[i] = static_cast<float>(i + 1);
}
paddle::platform::CPUPlace place; im2col(context, input, dilation, stride, padding, &out);
paddle::platform::CPUDeviceContext context(place); paddle::operators::math::im2col_common<float>(input, dilation, stride,
output.mutable_data<float>({ic, fh, fw, output_height, output_width}, place); padding, &ref);
ref_output.mutable_data<float>({ic, fh, fw, output_height, output_width},
place); float* ref_data = ref.data<float>();
paddle::operators::math::Im2ColFunctor< float* out_data = out.data<float>();
paddle::operators::math::ColFormat::kCFO, for (int i = 0; i < out.numel(); ++i) {
paddle::platform::CPUDeviceContext, float> EXPECT_EQ(out_data[i], ref_data[i]);
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];
}
}
} }
}; }
ref_im2col(input, dilation, stride, padding, &ref_output); void benchIm2col(int ic, int ih, int iw, int fh, int fw, int ph, int pw) {
PREPARE_IM2COL_CPU;
constexpr int repeat = 30;
auto GetCurrentMs = []() -> double {
struct timeval time;
gettimeofday(&time, NULL);
return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec;
};
auto t1 = GetCurrentMs();
for (int i = 0; i < repeat; ++i) {
im2col(context, input, dilation, stride, padding, &out);
}
auto t2 = GetCurrentMs();
float* out_cfo_ptr = output.data<float>(); for (int i = 0; i < repeat; ++i) {
float* out_ref_ptr = ref_output.data<float>(); paddle::operators::math::im2col_common<float>(input, dilation, stride,
for (int i = 0; i < output.numel(); ++i) { padding, &ref);
EXPECT_EQ(out_cfo_ptr[i], out_ref_ptr[i]);
} }
auto t3 = GetCurrentMs();
LOG(INFO) << "before: " << (t3 - t2) / repeat
<< ",after: " << (t2 - t1) / repeat;
} }
TEST(math, im2col) { TEST(math, im2col_cputest) {
testIm2col<paddle::platform::CPUDeviceContext, paddle::platform::CPUPlace>(); testIm2colCPU(/*ic*/ 2, /*ih*/ 5, /*iw*/ 4, /*fh*/ 3, /*fw*/ 3, /*ph*/ 0,
testIm2colCPU(/*ic*/ 3, /*ih*/ 5, /*iw*/ 5, /*fh*/ 3, /*fw*/ 2, /*ph*/ 0,
/*pw*/ 0); /*pw*/ 0);
testIm2colCPU(/*ic*/ 2, /*ih*/ 5, /*iw*/ 4, /*fh*/ 3, /*fw*/ 3, /*ph*/ 1, testIm2colCPU(/*ic*/ 2, /*ih*/ 5, /*iw*/ 4, /*fh*/ 3, /*fw*/ 3, /*ph*/ 1,
/*pw*/ 1); /*pw*/ 1);
#ifdef PADDLE_WITH_CUDA
testIm2col<paddle::platform::CUDADeviceContext, benchIm2col(/*ic*/ 3, /*ih*/ 224, /*iw*/ 224, /*fh*/ 3, /*fw*/ 3, /*ph*/ 1,
paddle::platform::CUDAPlace>(); /*pw*/ 1);
#endif benchIm2col(/*ic*/ 3, /*ih*/ 224, /*iw*/ 224, /*fh*/ 3, /*fw*/ 3, /*ph*/ 0,
/*pw*/ 0);
benchIm2col(/*ic*/ 3, /*ih*/ 224, /*iw*/ 224, /*fh*/ 5, /*fw*/ 5, /*ph*/ 1,
/*pw*/ 1);
benchIm2col(/*ic*/ 3, /*ih*/ 224, /*iw*/ 224, /*fh*/ 5, /*fw*/ 5, /*ph*/ 0,
/*pw*/ 0);
} }
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