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PaddleDetection
提交 60d6348e 编写于 作者: Y Yu Yang
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Revert develop

上级 86af6bdc
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Showing with 30 addition and 52 deletion
paddle/fluid/operators/math/pooling.cu
浏览文件 @ 60d6348e
......@@ -12,8 +12,6 @@ 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 <algorithm>
#include <vector>
#include "paddle/fluid/operators/math/pooling.h"
#include "paddle/fluid/platform/cuda_primitives.h"
......@@ -22,7 +20,7 @@ namespace operators {
namespace math {
template <typename PoolProcess, typename T>
__global__ void KernelPool2D(const int nthreads, const T* input_data, // NOLINT
__global__ void KernelPool2D(const int nthreads, const T* input_data,
const int channels, const int input_height,
const int input_width, const int output_height,
const int output_width, const int ksize_height,
......@@ -60,8 +58,8 @@ __global__ void KernelPool2D(const int nthreads, const T* input_data, // NOLINT
template <typename PoolProcess, typename T>
__global__ void KernelPool2DGrad(
const int nthreads, const T* input_data, const T* output_data, // NOLINT
const T* output_grad, const int channels, const int input_height, // NOLINT
const int nthreads, const T* input_data, const T* output_data,
const T* output_grad, const int channels, const int input_height,
const int input_width, const int output_height, const int output_width,
const int ksize_height, const int ksize_width, const int stride_height,
const int stride_width, const int padding_height, const int padding_width,
......@@ -108,8 +106,8 @@ __global__ void KernelPool2DGrad(
template <typename T>
__global__ void KernelMaxPool2DGrad(
const int nthreads, const T* input_data, const T* output_data, // NOLINT
const T* output_grad, const int channels, const int input_height, // NOLINT
const int nthreads, const T* input_data, const T* output_data,
const T* output_grad, const int channels, const int input_height,
const int input_width, const int output_height, const int output_width,
const int ksize_height, const int ksize_width, const int stride_height,
const int stride_width, const int padding_height, const int padding_width,
......@@ -160,10 +158,8 @@ template <typename PoolProcess, typename T>
class Pool2dFunctor<platform::CUDADeviceContext, PoolProcess, T> {
public:
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_process, framework::Tensor* output) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -205,10 +201,8 @@ class Pool2dGradFunctor<platform::CUDADeviceContext, PoolProcess, T> {
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_process, framework::Tensor* input_grad) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -252,10 +246,8 @@ class MaxPool2dGradFunctor<platform::CUDADeviceContext, T> {
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -314,7 +306,7 @@ template class Pool2dGradFunctor<platform::CUDADeviceContext,
double>;
template <typename PoolProcess, typename T>
__global__ void KernelPool3D(const int nthreads, const T* input_data, // NOLINT
__global__ void KernelPool3D(const int nthreads, const T* input_data,
const int channels, const int input_depth,
const int input_height, const int input_width,
const int output_depth, const int output_height,
......@@ -360,8 +352,8 @@ __global__ void KernelPool3D(const int nthreads, const T* input_data, // NOLINT
template <typename PoolProcess, typename T>
__global__ void KernelPool3DGrad(
const int nthreads, const T* input_data, const T* output_data, // NOLINT
const T* output_grad, const int channels, const int input_depth, // NOLINT
const int nthreads, const T* input_data, const T* output_data,
const T* output_grad, const int channels, const int input_depth,
const int input_height, const int input_width, const int output_depth,
const int output_height, const int output_width, const int ksize_depth,
const int ksize_height, const int ksize_width, const int stride_depth,
......@@ -424,8 +416,8 @@ __global__ void KernelPool3DGrad(
template <typename T>
__global__ void KernelMaxPool3DGrad(
const int nthreads, const T* input_data, const T* output_data, // NOLINT
const T* output_grad, const int channels, const int input_depth, // NOLINT
const int nthreads, const T* input_data, const T* output_data,
const T* output_grad, const int channels, const int input_depth,
const int input_height, const int input_width, const int output_depth,
const int output_height, const int output_width, const int ksize_depth,
const int ksize_height, const int ksize_width, const int stride_depth,
......@@ -482,10 +474,8 @@ template <typename PoolProcess, class T>
class Pool3dFunctor<platform::CUDADeviceContext, PoolProcess, T> {
public:
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_process, framework::Tensor* output) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -535,10 +525,8 @@ class Pool3dGradFunctor<platform::CUDADeviceContext, PoolProcess, T> {
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
PoolProcess pool_process, framework::Tensor* input_grad) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -590,10 +578,8 @@ class MaxPool3dGradFunctor<platform::CUDADeviceContext, T> {
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& output,
const framework::Tensor& output_grad,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& output_grad, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -750,10 +736,8 @@ template <typename T1, typename T2>
class MaxPool2dWithIndexFunctor<platform::CUDADeviceContext, T1, T2> {
public:
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* output, framework::Tensor* mask) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -795,10 +779,8 @@ class MaxPool2dWithIndexGradFunctor<platform::CUDADeviceContext, T1, T2> {
public:
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& output_grad,
const framework::Tensor& mask,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& mask, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad) {
const int batch_size = input_grad->dims()[0];
const int input_channels = input_grad->dims()[1];
......@@ -955,10 +937,8 @@ template <typename T1, typename T2>
class MaxPool3dWithIndexFunctor<platform::CUDADeviceContext, T1, T2> {
public:
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& input,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& input, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* output, framework::Tensor* mask) {
const int batch_size = input.dims()[0];
const int input_channels = input.dims()[1];
......@@ -1007,10 +987,8 @@ class MaxPool3dWithIndexGradFunctor<platform::CUDADeviceContext, T1, T2> {
public:
void operator()(const platform::CUDADeviceContext& context,
const framework::Tensor& output_grad,
const framework::Tensor& mask,
std::vector<int>& ksize, // NOLINT
std::vector<int>& strides, // NOLINT
std::vector<int>& paddings, // NOLINT
const framework::Tensor& mask, std::vector<int>& ksize,
std::vector<int>& strides, std::vector<int>& paddings,
framework::Tensor* input_grad) {
const int batch_size = input_grad->dims()[0];
const int input_channels = input_grad->dims()[1];
......
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