提交 3206094b 编写于 作者: S sweetsky0901

format code

上级 d2ee3c98
...@@ -21,7 +21,8 @@ namespace math { ...@@ -21,7 +21,8 @@ namespace math {
template <typename T> template <typename T>
__global__ void KernelUnpool2dMax(const int nthreads, const T* input_data, __global__ void KernelUnpool2dMax(const int nthreads, const T* input_data,
const int* indices_data, const int* indices_data,
const int input_height, const int input_width, const int input_height,
const int input_width,
const int channels, T* output_data, const int channels, T* output_data,
const int output_height, const int output_height,
const int output_width) { const int output_width) {
...@@ -42,11 +43,10 @@ __global__ void KernelUnpool2dMax(const int nthreads, const T* input_data, ...@@ -42,11 +43,10 @@ __global__ void KernelUnpool2dMax(const int nthreads, const T* input_data,
} }
} }
template <typename T> template <typename T>
__global__ void KernelUnpool2dMaxGrad(const int nthreads, const T* input_data, __global__ void KernelUnpool2dMaxGrad(
const int* indices_data, const int nthreads, const T* input_data, const int* indices_data,
const int input_height, const int input_width, const int input_height, const int input_width, const int channels,
const int channels, const T* output_data, const T* output_data, const T* output_grad, const int output_height,
const T* output_grad, const int output_height,
const int output_width, T* input_grad) { const int output_width, T* input_grad) {
int in_n_stride = input_height * input_width * channels; int in_n_stride = input_height * input_width * channels;
int in_c_stride = input_height * input_width; int in_c_stride = input_height * input_width;
...@@ -71,8 +71,8 @@ template <typename T> ...@@ -71,8 +71,8 @@ template <typename T>
class Unpool2dMaxFunctor<platform::GPUPlace, T> { class Unpool2dMaxFunctor<platform::GPUPlace, T> {
public: public:
void operator()(const platform::DeviceContext& context, void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, const framework::Tensor& indices, const framework::Tensor& input,
framework::Tensor* output) { const framework::Tensor& indices, framework::Tensor* output) {
const int batch_size = input.dims()[0]; const int batch_size = input.dims()[0];
const int input_height = input.dims()[2]; const int input_height = input.dims()[2];
const int input_width = input.dims()[3]; const int input_width = input.dims()[3];
...@@ -121,9 +121,9 @@ class Unpool2dMaxGradFunctor<platform::GPUPlace, T> { ...@@ -121,9 +121,9 @@ class Unpool2dMaxGradFunctor<platform::GPUPlace, T> {
T><<<grid, threads, 0, T><<<grid, threads, 0,
reinterpret_cast<const platform::CUDADeviceContext&>(context) reinterpret_cast<const platform::CUDADeviceContext&>(context)
.stream()>>>(input.numel(), input_data, indices_data, .stream()>>>(input.numel(), input_data, indices_data,
input_height, input_width, output_channels, output_data, input_height, input_width, output_channels,
output_grad_data, output_height, output_width, output_data, output_grad_data, output_height,
input_grad_data); output_width, input_grad_data);
} }
}; };
template class Unpool2dMaxGradFunctor<platform::GPUPlace, float>; template class Unpool2dMaxGradFunctor<platform::GPUPlace, float>;
......
...@@ -23,8 +23,7 @@ class Unpool2dMaxFunctor { ...@@ -23,8 +23,7 @@ class Unpool2dMaxFunctor {
public: public:
void operator()(const platform::DeviceContext& context, void operator()(const platform::DeviceContext& context,
const framework::Tensor& input, const framework::Tensor& input,
const framework::Tensor& indices, const framework::Tensor& indices, framework::Tensor* output);
framework::Tensor* output);
}; };
template <typename Place, class T> template <typename Place, class T>
class Unpool2dMaxGradFunctor { class Unpool2dMaxGradFunctor {
......
...@@ -84,16 +84,18 @@ class UnpoolOp : public framework::OperatorWithKernel { ...@@ -84,16 +84,18 @@ class UnpoolOp : public framework::OperatorWithKernel {
public: public:
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override { void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) of UnpoolOp" PADDLE_ENFORCE(ctx->HasInput("X"),
"Input(X) of UnpoolOp"
"should not be null."); "should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Indices"), "Input(Indices) of UnpoolOp" PADDLE_ENFORCE(ctx->HasInput("Indices"),
"Input(Indices) of UnpoolOp"
"should not be null."); "should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"), PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output(Out) of UnpoolOp should not be null."); "Output(Out) of UnpoolOp should not be null.");
auto in_x_dims = ctx->GetInputDim("X"); auto in_x_dims = ctx->GetInputDim("X");
auto in_y_dims = ctx->GetInputDim("Indices"); auto in_y_dims = ctx->GetInputDim("Indices");
std::string unpooling_type = std::string unpooling_type = ctx->Attrs()
ctx->Attrs().Get<std::string>("unpooling_type"); .Get<std::string>("unpooling_type");
std::vector<int> ksize = ctx->Attrs().Get<std::vector<int>>("ksize"); std::vector<int> ksize = ctx->Attrs().Get<std::vector<int>>("ksize");
std::vector<int> strides = ctx->Attrs().Get<std::vector<int>>("strides"); std::vector<int> strides = ctx->Attrs().Get<std::vector<int>>("strides");
std::vector<int> paddings = std::vector<int> paddings =
...@@ -134,8 +136,8 @@ class UnpoolOpGrad : public framework::OperatorWithKernel { ...@@ -134,8 +136,8 @@ class UnpoolOpGrad : public framework::OperatorWithKernel {
namespace ops = paddle::operators; namespace ops = paddle::operators;
REGISTER_OP(unpool, ops::UnpoolOp, ops::Unpool2dOpMaker, unpool_grad, REGISTER_OP(unpool, ops::UnpoolOp, ops::Unpool2dOpMaker, unpool_grad,
ops::UnpoolOpGrad); ops::UnpoolOpGrad);
REGISTER_OP_CPU_KERNEL( REGISTER_OP_CPU_KERNEL(unpool,
unpool, ops::UnpoolKernel<paddle::platform::CPUPlace, float>, ops::UnpoolKernel<paddle::platform::CPUPlace, float>,
ops::UnpoolKernel<paddle::platform::CPUPlace, double>); ops::UnpoolKernel<paddle::platform::CPUPlace, double>);
REGISTER_OP_CPU_KERNEL( REGISTER_OP_CPU_KERNEL(
unpool_grad, ops::UnpoolGradKernel<paddle::platform::CPUPlace, float>, unpool_grad, ops::UnpoolGradKernel<paddle::platform::CPUPlace, float>,
......
...@@ -15,8 +15,8 @@ limitations under the License. */ ...@@ -15,8 +15,8 @@ limitations under the License. */
#include "paddle/operators/unpool_op.h" #include "paddle/operators/unpool_op.h"
namespace ops = paddle::operators; namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL( REGISTER_OP_GPU_KERNEL(unpool,
unpool, ops::UnpoolKernel<paddle::platform::GPUPlace, float>, ops::UnpoolKernel<paddle::platform::GPUPlace, float>,
ops::UnpoolKernel<paddle::platform::GPUPlace, double>); ops::UnpoolKernel<paddle::platform::GPUPlace, double>);
REGISTER_OP_GPU_KERNEL( REGISTER_OP_GPU_KERNEL(
unpool_grad, ops::UnpoolGradKernel<paddle::platform::GPUPlace, float>, unpool_grad, ops::UnpoolGradKernel<paddle::platform::GPUPlace, float>,
......
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