chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,465 @@
|
||||
/* 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/phi/kernels/funcs/im2col.h"
|
||||
|
||||
#include <gtest/gtest.h>
|
||||
#include <array>
|
||||
|
||||
#include "paddle/fluid/framework/tensor_util.h"
|
||||
#include "paddle/phi/common/place.h"
|
||||
#include "paddle/phi/core/platform/device_context.h"
|
||||
#include "paddle/phi/kernels/funcs/im2col_cfo_cpu.h"
|
||||
|
||||
template <typename DeviceContext, typename Place>
|
||||
void testIm2col() {
|
||||
phi::DenseTensor input_tmp;
|
||||
phi::DenseTensor input;
|
||||
phi::DenseTensor output_cfo;
|
||||
phi::DenseTensor output_ocf;
|
||||
phi::DenseTensor 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}, phi::CPUPlace());
|
||||
std::array<float, 6> arr = {0, 1, 2, 3, 4, 5};
|
||||
memcpy(input_ptr, arr.data(), 6 * sizeof(float));
|
||||
|
||||
auto* place = new Place();
|
||||
DeviceContext* context = new DeviceContext(*place);
|
||||
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
input = input_tmp;
|
||||
} else {
|
||||
paddle::framework::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
|
||||
phi::funcs::Im2ColFunctor<phi::funcs::ColFormat::CFO, DeviceContext, float>
|
||||
im2col;
|
||||
phi::funcs::Im2ColFunctor<phi::funcs::ColFormat::OCF, DeviceContext, float>
|
||||
im2col_ocf;
|
||||
|
||||
im2col(*context, input, dilation, stride, padding, &output_cfo);
|
||||
im2col_ocf(*context, input, dilation, stride, padding, &output_ocf);
|
||||
|
||||
std::array<float, 8> out_cfo_data = {0, 1, 1, 2, 3, 4, 4, 5};
|
||||
std::array<float, 8> out_ocf_data = {0, 1, 3, 4, 1, 2, 4, 5};
|
||||
|
||||
float* out_cfo_ptr = nullptr;
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
out_cfo_ptr = output_cfo.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(output_cfo, phi::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 = nullptr;
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
out_ocf_ptr = output_ocf.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(output_ocf, phi::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: CFO
|
||||
phi::funcs::Col2ImFunctor<phi::funcs::ColFormat::CFO, DeviceContext, float>
|
||||
col2im;
|
||||
phi::funcs::Col2ImFunctor<phi::funcs::ColFormat::OCF, DeviceContext, float>
|
||||
col2im_ocf;
|
||||
std::array<float, 6> col2im_data = {0, 2, 2, 3, 8, 5};
|
||||
|
||||
memset(input_ptr, 0, 6 * sizeof(float));
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
input = input_tmp;
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input_tmp, *place, &input);
|
||||
}
|
||||
|
||||
col2im(*context, output_cfo, dilation, stride, padding, &input);
|
||||
|
||||
float* in_ptr = nullptr;
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
in_ptr = input.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input, phi::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: OCF
|
||||
memset(input_ptr, 0, 6 * sizeof(float));
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
input = input_tmp;
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input_tmp, *place, &input);
|
||||
}
|
||||
|
||||
col2im_ocf(*context, output_ocf, dilation, stride, padding, &input);
|
||||
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
in_ptr = input.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input, phi::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;
|
||||
}
|
||||
|
||||
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
|
||||
template <>
|
||||
void testIm2col<phi::GPUContext, phi::GPUPlace>() {
|
||||
phi::DenseTensor input_tmp;
|
||||
phi::DenseTensor input;
|
||||
phi::DenseTensor output_cfo;
|
||||
phi::DenseTensor output_ocf;
|
||||
phi::DenseTensor 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}, phi::CPUPlace());
|
||||
std::array<float, 6> arr = {0, 1, 2, 3, 4, 5};
|
||||
memcpy(input_ptr, arr.data(), 6 * sizeof(float));
|
||||
|
||||
auto* place = new phi::GPUPlace();
|
||||
auto* context = new phi::GPUContext(*place);
|
||||
context->SetAllocator(paddle::memory::allocation::AllocatorFacade::Instance()
|
||||
.GetAllocator(*place, context->stream())
|
||||
.get());
|
||||
context->PartialInitWithAllocator();
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
input = input_tmp;
|
||||
} else {
|
||||
paddle::framework::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
|
||||
phi::funcs::Im2ColFunctor<phi::funcs::ColFormat::CFO, phi::GPUContext, float>
|
||||
im2col;
|
||||
phi::funcs::Im2ColFunctor<phi::funcs::ColFormat::OCF, phi::GPUContext, float>
|
||||
im2col_ocf;
|
||||
|
||||
im2col(*context, input, dilation, stride, padding, &output_cfo);
|
||||
im2col_ocf(*context, input, dilation, stride, padding, &output_ocf);
|
||||
|
||||
std::array<float, 8> out_cfo_data = {0, 1, 1, 2, 3, 4, 4, 5};
|
||||
std::array<float, 8> out_ocf_data = {0, 1, 3, 4, 1, 2, 4, 5};
|
||||
|
||||
float* out_cfo_ptr;
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
out_cfo_ptr = output_cfo.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(output_cfo, phi::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 (phi::is_cpu_place(*place)) {
|
||||
out_ocf_ptr = output_ocf.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(output_ocf, phi::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: CFO
|
||||
phi::funcs::Col2ImFunctor<phi::funcs::ColFormat::CFO, phi::GPUContext, float>
|
||||
col2im;
|
||||
phi::funcs::Col2ImFunctor<phi::funcs::ColFormat::OCF, phi::GPUContext, float>
|
||||
col2im_ocf;
|
||||
std::array<float, 6> col2im_data = {0, 2, 2, 3, 8, 5};
|
||||
|
||||
memset(input_ptr, 0, 6 * sizeof(float));
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
input = input_tmp;
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input_tmp, *place, &input);
|
||||
}
|
||||
|
||||
col2im(*context, output_cfo, dilation, stride, padding, &input);
|
||||
|
||||
float* in_ptr;
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
in_ptr = input.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input, phi::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: OCF
|
||||
memset(input_ptr, 0, 6 * sizeof(float));
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
input = input_tmp;
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input_tmp, *place, &input);
|
||||
}
|
||||
|
||||
col2im_ocf(*context, output_ocf, dilation, stride, padding, &input);
|
||||
|
||||
if (phi::is_cpu_place(*place)) {
|
||||
in_ptr = input.data<float>();
|
||||
} else {
|
||||
paddle::framework::TensorCopySync(input, phi::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;
|
||||
}
|
||||
#endif
|
||||
|
||||
TEST(math, im2col) {
|
||||
testIm2col<phi::CPUContext, phi::CPUPlace>();
|
||||
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
|
||||
testIm2col<phi::GPUContext, phi::GPUPlace>();
|
||||
#endif
|
||||
}
|
||||
|
||||
#define PREPARE_IM2COL_CPU \
|
||||
phi::CPUPlace place; \
|
||||
phi::CPUContext context(place); \
|
||||
phi::DenseTensor input; \
|
||||
phi::DenseTensor out; \
|
||||
phi::DenseTensor 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); \
|
||||
phi::funcs:: \
|
||||
Im2ColFunctor<phi::funcs::ColFormat::CFO, phi::CPUContext, float> \
|
||||
im2col
|
||||
|
||||
void testIm2colCPU(int ic, int ih, int iw, int fh, int fw, int ph, int pw) {
|
||||
PREPARE_IM2COL_CPU;
|
||||
|
||||
im2col(context, input, dilation, stride, padding, &out);
|
||||
phi::funcs::im2col_common<float>(input, dilation, stride, padding, &ref);
|
||||
|
||||
float* ref_data = ref.data<float>();
|
||||
float* out_data = out.data<float>();
|
||||
for (int i = 0; i < out.numel(); ++i) {
|
||||
EXPECT_EQ(out_data[i], ref_data[i]);
|
||||
}
|
||||
}
|
||||
|
||||
void benchIm2col(int ic, int ih, int iw, int fh, int fw, int ph, int pw) {
|
||||
PREPARE_IM2COL_CPU;
|
||||
constexpr int repeat = 100;
|
||||
auto GetCurrentMs = []() -> double {
|
||||
struct timeval time = {0, 0};
|
||||
gettimeofday(&time, nullptr);
|
||||
return 1e+3 * time.tv_sec + 1e-3 * time.tv_usec; // NOLINT
|
||||
};
|
||||
auto t1 = GetCurrentMs();
|
||||
for (int i = 0; i < repeat; ++i) {
|
||||
im2col(context, input, dilation, stride, padding, &out);
|
||||
}
|
||||
auto t2 = GetCurrentMs();
|
||||
|
||||
for (int i = 0; i < repeat; ++i) {
|
||||
phi::funcs::im2col_common<float>(input, dilation, stride, padding, &ref);
|
||||
}
|
||||
auto t3 = GetCurrentMs();
|
||||
|
||||
LOG(INFO) << "before: " << (t3 - t2) / repeat
|
||||
<< ",after: " << (t2 - t1) / repeat
|
||||
<< ",boost: " << ((t3 - t2) / (t2 - t1) - 1) * 100 << "%";
|
||||
}
|
||||
|
||||
TEST(math, im2col_cputest) {
|
||||
// padding_h == padding_w
|
||||
for (int p = 0; p < 4; ++p) {
|
||||
// width == height
|
||||
testIm2colCPU(/*ic*/ 2,
|
||||
/*ih*/ 5,
|
||||
/*iw*/ 5,
|
||||
/*fh*/ 4,
|
||||
/*fw*/ 4,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
testIm2colCPU(/*ic*/ 2,
|
||||
/*ih*/ 4,
|
||||
/*iw*/ 4,
|
||||
/*fh*/ 3,
|
||||
/*fw*/ 3,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
testIm2colCPU(/*ic*/ 2,
|
||||
/*ih*/ 4,
|
||||
/*iw*/ 4,
|
||||
/*fh*/ 2,
|
||||
/*fw*/ 2,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
|
||||
// height != width
|
||||
testIm2colCPU(/*ic*/ 2,
|
||||
/*ih*/ 5,
|
||||
/*iw*/ 4,
|
||||
/*fh*/ 2,
|
||||
/*fw*/ 3,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
testIm2colCPU(/*ic*/ 2,
|
||||
/*ih*/ 5,
|
||||
/*iw*/ 4,
|
||||
/*fh*/ 1,
|
||||
/*fw*/ 3,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
testIm2colCPU(/*ic*/ 2,
|
||||
/*ih*/ 4,
|
||||
/*iw*/ 5,
|
||||
/*fh*/ 3,
|
||||
/*fw*/ 1,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
|
||||
// filter == 1
|
||||
testIm2colCPU(/*ic*/ 3,
|
||||
/*ih*/ 4,
|
||||
/*iw*/ 4,
|
||||
/*fh*/ 1,
|
||||
/*fw*/ 1,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
testIm2colCPU(/*ic*/ 3,
|
||||
/*ih*/ 3,
|
||||
/*iw*/ 4,
|
||||
/*fh*/ 1,
|
||||
/*fw*/ 1,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
}
|
||||
|
||||
// padding_h != padding_w
|
||||
testIm2colCPU(/*ic*/ 2,
|
||||
/*ih*/ 4,
|
||||
/*iw*/ 4,
|
||||
/*fh*/ 2,
|
||||
/*fw*/ 3,
|
||||
/*ph*/ 1,
|
||||
/*pw*/ 2);
|
||||
|
||||
// benchmark
|
||||
for (int p : {0, 1}) {
|
||||
for (int k : {1, 3, 5}) {
|
||||
LOG(INFO) << "padding == " << p << ", filter == " << k;
|
||||
benchIm2col(/*ic*/ 3,
|
||||
/*ih*/ 224,
|
||||
/*iw*/ 224,
|
||||
/*fh*/ k,
|
||||
/*fw*/ k,
|
||||
/*ph*/ p,
|
||||
/*pw*/ p);
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user