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mv two function in conv op for good code style (#20116)

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* Delete PadFuntion, include padding.h instead. test=develop

* move function(IsSymmetricPadding) from conv_cudnn_op.cu/conv_transpose_cudnn_op.cu to padding.h, test=develop
API_fix
liym27 6 years ago committed by Aurelius84
parent 869cef6dc0
commit ad60b3b8ac
3 changed files with 27 additions and 65 deletions
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61
paddle/fluid/operators/conv_cudnn_op.cu
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@ -21,6 +21,7 @@ limitations under the License. */
#include "paddle/fluid/operators/conv_cudnn_helper.h"
#include "paddle/fluid/operators/conv_cudnn_op_cache.h"
#include "paddle/fluid/operators/conv_op.h"
#include "paddle/fluid/operators/math/padding.h"
#include "paddle/fluid/platform/cudnn_helper.h"
#include "paddle/fluid/platform/cudnn_workspace_helper.h"
#include "paddle/fluid/platform/float16.h"
@ -59,44 +60,6 @@ static inline void GetNCDHW(const framework::DDim& dims,
}
}
static inline bool IsSymmetricPadding(const std::vector<int>& paddings,
const int data_dim) {
bool is_sys_pad = true;
if (paddings.size() == data_dim * 2) {
for (size_t i = 0; i < data_dim; ++i) {
if (paddings[2 * i] != paddings[2 * i + 1]) {
is_sys_pad = false;
return is_sys_pad;
}
}
}
return is_sys_pad;
}
template <typename T, size_t D, int MajorType = Eigen::RowMajor,
typename IndexType = Eigen::DenseIndex>
using EigenTensor = framework::EigenTensor<T, D, MajorType, IndexType>;
template <typename DeviceContext, typename T, size_t D>
static void PadFunction(const framework::ExecutionContext& context,
const std::vector<int>& pads,
const framework::Tensor& src, T pad_value,
framework::Tensor* out) {
Eigen::array<std::pair<int, int>, D> paddings;
for (size_t i = 0; i < paddings.size(); ++i) {
paddings[i].first = pads[i * 2];
paddings[i].second = pads[i * 2 + 1];
}
auto src_tensor = EigenTensor<T, D>::From(src);
auto out_tensor = EigenTensor<T, D>::From(*out);
auto& place =
*context.template device_context<DeviceContext>().eigen_device();
out_tensor.device(place) = src_tensor.pad(paddings, pad_value);
}
template <typename DeviceContext, typename T, size_t D>
static void Slice_2(const framework::ExecutionContext& context,
const Tensor* input, Tensor* out,
@ -192,7 +155,7 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
in_data_dims, strides, ksize);
int data_dim = strides.size(); // 2d or 3d
bool is_sys_pad = IsSymmetricPadding(paddings, data_dim);
bool is_sys_pad = math::IsSymmetricPadding(paddings, data_dim);
Tensor transformed_input;
std::vector<int> padding_common(data_dim, 0);
@ -225,12 +188,12 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
T pad_value(0.0);
switch (rank) {
case 4: {
PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
ctx, input_pad, transformed_input_channel, pad_value,
&transformed_input);
} break;
case 5: {
PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
ctx, input_pad, transformed_input_channel, pad_value,
&transformed_input);
} break;
@ -404,7 +367,7 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
// cuDNN only supports padding the same amount on every dimension.
// So we create a new padded input tensor.
int data_dim = strides.size(); // 2d or 3d
bool is_sys_pad = IsSymmetricPadding(paddings, data_dim);
bool is_sys_pad = math::IsSymmetricPadding(paddings, data_dim);
Tensor transformed_input(input->type());
Tensor transformed_input_grad(input->type());
std::vector<int> padding_common(data_dim, 0);
@ -446,12 +409,12 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
T pad_value(0.0);
switch (rank) {
case 4: {
PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
ctx, input_pad, transformed_input_channel, pad_value,
&transformed_input);
} break;
case 5: {
PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
ctx, input_pad, transformed_input_channel, pad_value,
&transformed_input);
} break;
@ -737,7 +700,7 @@ class CUDNNConvDoubleGradOpKernel : public framework::OpKernel<T> {
in_data_dims, strides, ksize);
int data_dim = strides.size(); // 2d or 3d
bool is_sys_pad = IsSymmetricPadding(paddings, data_dim);
bool is_sys_pad = math::IsSymmetricPadding(paddings, data_dim);
Tensor transformed_X(X->type());
Tensor transformed_ddX(X->type());
@ -786,16 +749,16 @@ class CUDNNConvDoubleGradOpKernel : public framework::OpKernel<T> {
T pad_value(0.0);
switch (rank) {
case 4: {
PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
ctx, input_pad, transformed_X_channel, pad_value, &transformed_X);
PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 4>(
ctx, input_pad, transformed_ddX_channel, pad_value,
&transformed_ddX);
} break;
case 5: {
PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
ctx, input_pad, transformed_X_channel, pad_value, &transformed_X);
PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
math::PadFunction<paddle::platform::CUDADeviceContext, T, 5>(
ctx, input_pad, transformed_ddX_channel, pad_value,
&transformed_ddX);
} break;

18
paddle/fluid/operators/conv_transpose_cudnn_op.cu
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@ -51,20 +51,6 @@ static void DataTranspose(const framework::ExecutionContext& ctx,
transpose(dev_ctx, *input, output, axis);
}
static inline bool IsSymmetricPadding(const std::vector<int>& paddings,
const int data_dim) {
bool is_sys_pad = true;
if (paddings.size() == data_dim * 2) {
for (size_t i = 0; i < data_dim; ++i) {
if (paddings[2 * i] != paddings[2 * i + 1]) {
is_sys_pad = false;
return is_sys_pad;
}
}
}
return is_sys_pad;
}
template <typename T>
class CUDNNConvTransposeOpKernel : public framework::OpKernel<T> {
public:
@ -124,7 +110,7 @@ class CUDNNConvTransposeOpKernel : public framework::OpKernel<T> {
in_data_dims, strides, ksize);
int data_dim = strides.size(); // 2d or 3d
bool is_sys_pad = IsSymmetricPadding(paddings, data_dim);
bool is_sys_pad = math::IsSymmetricPadding(paddings, data_dim);
std::vector<int> input_pad(input_transpose.dims().size() * 2, 0);
Tensor transformed_input;
@ -373,7 +359,7 @@ class CUDNNConvTransposeGradOpKernel : public framework::OpKernel<T> {
in_data_dims, strides, ksize);
int data_dim = strides.size(); // 2d or 3d
bool is_sys_pad = IsSymmetricPadding(paddings, data_dim);
bool is_sys_pad = math::IsSymmetricPadding(paddings, data_dim);
std::vector<int> input_pad(input_transpose.dims().size() * 2, 0);
Tensor transformed_output_grad;

13
paddle/fluid/operators/math/padding.h
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@ -119,6 +119,19 @@ void PaddingGradFunctor(int rank, const framework::ExecutionContext& context,
}
}
inline bool IsSymmetricPadding(const std::vector<int>& pads,
const int data_dim) {
bool is_sys_pad = true;
if (pads.size() == data_dim * 2) {
for (size_t i = 0; i < data_dim; ++i) {
if (pads[2 * i] != pads[2 * i + 1]) {
is_sys_pad = false;
return is_sys_pad;
}
}
}
return is_sys_pad;
}
} // namespace math
} // namespace operators
} // namespace paddle

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