m53297601
/
Paddle
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

format code

Browse Source
release/0.11.0
sweetsky0901 7 years ago
parent bd561384bc
commit c52ed8de37
6 changed files with 54 additions and 82 deletions
Show Stats Download Patch File Download Diff File

22
paddle/operators/math/unpooling.cc
Unescape View File

@ -13,17 +13,15 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/math/unpooling.h"
namespace paddle {
namespace operators {
namespace math {
// All tensors are in NCHW format
template <typename T>
class Unpool2dMaxFunctor<platform::CPUPlace, T> {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices, framework::Tensor* output) {
public:
void operator()(
const platform::DeviceContext& context, const framework::Tensor& input,
const framework::Tensor& indices, framework::Tensor* output) {
const int batch_size = input.dims()[0];
const int input_height = input.dims()[2];
const int input_width = input.dims()[3];
@ -51,13 +49,11 @@ public:
};
template <class T>
class Unpool2dMaxGradFunctor<platform::CPUPlace, T> {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices,
const framework::Tensor& output,
const framework::Tensor& output_grad,
framework::Tensor* input_grad) {
public:
void operator()(
const platform::DeviceContext& context, const framework::Tensor& input,
const framework::Tensor& indices, const framework::Tensor& output,
const framework::Tensor& output_grad, framework::Tensor* input_grad) {
const int batch_size = input.dims()[0];
const int input_height = input.dims()[2];
const int input_width = input.dims()[3];

59
paddle/operators/math/unpooling.cu
Unescape View File

@ -19,14 +19,10 @@ namespace paddle {
namespace operators {
namespace math {
template <typename T>
__global__ void KernelUnpool2dMax(const int nthreads, const T* input_data,
const int* indices_data,
const int input_height,
const int input_width,
const int channels,
T* output_data,
const int output_height,
const int output_width) {
__global__ void KernelUnpool2dMax(
const int nthreads, const T* input_data, const int* indices_data,
const int input_height, const int input_width, const int channels,
T* output_data, const int output_height, const int output_width) {
int in_n_stride = input_height * input_width * channels;
int in_c_stride = input_height * input_width;
int out_n_stride = output_height * output_width * channels;
@ -44,16 +40,11 @@ __global__ void KernelUnpool2dMax(const int nthreads, const T* input_data,
}
}
template <typename T>
__global__ void KernelUnpool2dMaxGrad(const int nthreads, const T* input_data,
const int* indices_data,
const int input_height,
const int input_width,
const int channels,
const T* output_data,
const T* output_grad,
const int output_height,
const int output_width,
T* input_grad) {
__global__ void KernelUnpool2dMaxGrad(
const int nthreads, const T* input_data, const int* indices_data,
const int input_height, const int input_width, const int channels,
const T* output_data, const T* output_grad, const int output_height,
const int output_width, T* input_grad) {
int in_n_stride = input_height * input_width * channels;
int in_c_stride = input_height * input_width;
int out_n_stride = output_height * output_width * channels;
@ -75,11 +66,10 @@ __global__ void KernelUnpool2dMaxGrad(const int nthreads, const T* input_data,
*/
template <typename T>
class Unpool2dMaxFunctor<platform::GPUPlace, T> {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices,
framework::Tensor* output) {
public:
void operator()(
const platform::DeviceContext& context, const framework::Tensor& input,
const framework::Tensor& indices, framework::Tensor* output) {
const int batch_size = input.dims()[0];
const int input_height = input.dims()[2];
const int input_width = input.dims()[3];
@ -91,12 +81,11 @@ public:
T* output_data = output->mutable_data<T>(context.GetPlace());
int threads = 1024;
int grid = (input.numel() + threads - 1) / threads;
KernelUnpool2dMax<
T><<<grid, threads, 0,
KernelUnpool2dMax<T><<<grid, threads, 0,
reinterpret_cast<const platform::CUDADeviceContext&>(context)
.stream()>>>(input.numel(), input_data, indices_data,
input_height, input_width, output_channels,
output_data, output_height, output_width);
.stream()>>>(input.numel(), input_data, indices_data,
input_height, input_width, output_channels,
output_data, output_height, output_width);
}
};
/*
@ -104,7 +93,7 @@ public:
*/
template <typename T>
class Unpool2dMaxGradFunctor<platform::GPUPlace, T> {
public:
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices,
@ -124,13 +113,11 @@ public:
T* input_grad_data = input_grad->mutable_data<T>(context.GetPlace());
int threads = 1024;
int grid = (input.numel() + threads - 1) / threads;
KernelUnpool2dMaxGrad<
T><<<grid, threads, 0,
reinterpret_cast<const platform::CUDADeviceContext&>(context)
.stream()>>>(input.numel(), input_data, indices_data,
input_height, input_width, output_channels,
output_data, output_grad_data,
output_height, output_width, input_grad_data);
KernelUnpool2dMaxGrad<T><<<grid, threads, 0,
reinterpret_cast<const platform::CUDADeviceContext&>(context)
.stream()>>>(input.numel(), input_data, indices_data,
input_height, input_width, output_channels, output_data,
output_grad_data, output_height, output_width, input_grad_data);
}
};
template class Unpool2dMaxGradFunctor<platform::GPUPlace, float>;

23
paddle/operators/math/unpooling.h
Unescape View File

@ -18,25 +18,20 @@ limitations under the License. */
namespace paddle {
namespace operators {
namespace math {
template <typename Place, typename T>
class Unpool2dMaxFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices, framework::Tensor* output);
public:
void operator()(
const platform::DeviceContext& context, const framework::Tensor& input,
const framework::Tensor& indices, framework::Tensor* output);
};
template <typename Place, class T>
class Unpool2dMaxGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices,
const framework::Tensor& output,
const framework::Tensor& output_grad,
framework::Tensor* input_grad);
public:
void operator()(
const platform::DeviceContext& context, const framework::Tensor& input,
const framework::Tensor& indices, const framework::Tensor& output,
const framework::Tensor& output_grad, framework::Tensor* input_grad);
};
} // namespace math
} // namespace operators

15
paddle/operators/unpool_op.cc
Unescape View File

@ -31,13 +31,12 @@ class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
"(Tensor) The input tensor of the indices given out by MaxPool2d. "
"The format of input tensor is NCHW. Where N is batch size, C is the "
"number of channels, H and W is the height and width of feature.");
AddOutput(
"Out",
"(Tensor) The output tensor of unpool operator."
"The format of output tensor is also NCHW."
"Where N is batch size, C is "
"the number of channels, H and W is the height and "
"width of feature.");
AddOutput("Out",
"(Tensor) The output tensor of unpool operator."
"The format of output tensor is also NCHW."
"Where N is batch size, C is "
"the number of channels, H and W is the height and "
"width of feature.");
AddAttr<std::vector<int>>(
"ksize",
"(vector), the unpooling window size(height, width) "
@ -138,7 +137,7 @@ namespace ops = paddle::operators;
REGISTER_OP(unpool, ops::UnpoolOp, ops::Unpool2dOpMaker, unpool_grad,
ops::UnpoolOpGrad);
REGISTER_OP_CPU_KERNEL(
unpool,ops::UnpoolKernel<paddle::platform::CPUPlace, float>,
unpool, ops::UnpoolKernel<paddle::platform::CPUPlace, float>,
ops::UnpoolKernel<paddle::platform::CPUPlace, double>);
REGISTER_OP_CPU_KERNEL(
unpool_grad, ops::UnpoolGradKernel<paddle::platform::CPUPlace, float>,

14
paddle/operators/unpool_op.cu.cc
Unescape View File

@ -15,11 +15,9 @@ limitations under the License. */
#include "paddle/operators/unpool_op.h"
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(unpool,
ops::UnpoolKernel<paddle::platform::GPUPlace, float>,
ops::UnpoolKernel<paddle::platform::GPUPlace, double>);
REGISTER_OP_GPU_KERNEL(unpool_grad,
ops::UnpoolGradKernel<paddle::platform::GPUPlace,
float>,
ops::UnpoolGradKernel<paddle::platform::GPUPlace,
double>);
REGISTER_OP_GPU_KERNEL(
unpool, ops::UnpoolKernel<paddle::platform::GPUPlace, float>,
ops::UnpoolKernel<paddle::platform::GPUPlace, double>);
REGISTER_OP_GPU_KERNEL(
unpool_grad, ops::UnpoolGradKernel<paddle::platform::GPUPlace, float>,
ops::UnpoolGradKernel<paddle::platform::GPUPlace, double>);

3
paddle/operators/unpool_op.h
Unescape View File

@ -20,7 +20,6 @@ limitations under the License. */
namespace paddle {
namespace operators {
template <typename Place, typename T>
class UnpoolKernel : public framework::OpKernel<T> {
public:
@ -41,7 +40,6 @@ class UnpoolKernel : public framework::OpKernel<T> {
unpool2d_max_forward(context.device_context(), *in_x, *in_y, out);
}
};
template <typename Place, typename T>
class UnpoolGradKernel : public framework::OpKernel<T> {
public:
@ -69,6 +67,5 @@ class UnpoolGradKernel : public framework::OpKernel<T> {
*out_grad, in_x_grad);
}
};
} // namespace operators
} // namespace paddle

Write Preview
Loading…
Cancel
Save