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提交 06db7038 编写于 作者: X xzl

../../../../../paddle/api

上级 3772d27d
...@@ -155,7 +155,8 @@ op_library(parallel_do_op DEPS executor) ...@@ -155,7 +155,8 @@ op_library(parallel_do_op DEPS executor)
# Regist multiple Kernel to pybind # Regist multiple Kernel to pybind
if (WITH_GPU) if (WITH_GPU)
op_library(conv_op SRCS conv_op.cc conv_op.cu.cc conv_cudnn_op.cu.cc DEPS vol2col) op_library(conv_op SRCS conv_op.cc conv_op.cu.cc conv_cudnn_op.cu.cc DEPS
vol2col depthwise_conv)
op_library(pool_op SRCS pool_op.cc pool_op.cu.cc pool_cudnn_op.cu.cc DEPS pooling) op_library(pool_op SRCS pool_op.cc pool_op.cu.cc pool_cudnn_op.cu.cc DEPS pooling)
op_library(conv_transpose_op SRCS conv_transpose_op.cc conv_transpose_op.cu.cc op_library(conv_transpose_op SRCS conv_transpose_op.cc conv_transpose_op.cu.cc
conv_transpose_cudnn_op.cu.cc DEPS vol2col) conv_transpose_cudnn_op.cu.cc DEPS vol2col)
......
...@@ -318,15 +318,20 @@ framework::OpKernelType ConvOpGrad::GetExpectedKernelType( ...@@ -318,15 +318,20 @@ framework::OpKernelType ConvOpGrad::GetExpectedKernelType(
namespace ops = paddle::operators; namespace ops = paddle::operators;
REGISTER_OP(conv2d, ops::ConvOp, ops::Conv2DOpMaker, conv2d_grad, REGISTER_OP(conv2d, ops::ConvOp, ops::Conv2DOpMaker, conv2d_grad,
ops::ConvOpGrad); ops::ConvOpGrad);
REGISTER_OP(depthwiseConv, ops::ConvOp, ops::Conv2DOpMaker, conv2d_grad, REGISTER_OP(depthwiseConv, ops::ConvOp, ops::Conv2DOpMaker, depthwiseConv_grad,
ops::ConvOpGrad); ops::ConvOpGrad);
REGISTER_OP(conv3d, ops::ConvOp, ops::Conv3DOpMaker, conv3d_grad, REGISTER_OP(conv3d, ops::ConvOp, ops::Conv3DOpMaker, conv3d_grad,
ops::ConvOpGrad); ops::ConvOpGrad);
REGISTER_OP_CPU_KERNEL( REGISTER_OP_CPU_KERNEL(
depthwiseConv, depthwiseConv,
ops::DepthwiseConvKernel<paddle::platform::CPUDeviceContext, float>, ops::GemmConvKernel<paddle::platform::CPUDeviceContext, float>,
ops::DepthwiseConvKernel<paddle::platform::CPUDeviceContext, double>); ops::GemmConvKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL(
depthwiseConv_grad,
ops::GemmConvGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::GemmConvGradKernel<paddle::platform::CPUDeviceContext, double>);
REGISTER_OP_CPU_KERNEL( REGISTER_OP_CPU_KERNEL(
conv2d, ops::GemmConvKernel<paddle::platform::CPUDeviceContext, float>, conv2d, ops::GemmConvKernel<paddle::platform::CPUDeviceContext, float>,
......
...@@ -364,18 +364,15 @@ class DepthwiseConvKernel : public framework::OpKernel<T> { ...@@ -364,18 +364,15 @@ class DepthwiseConvKernel : public framework::OpKernel<T> {
Tensor* output = context.Output<Tensor>("Output"); Tensor* output = context.Output<Tensor>("Output");
output->mutable_data<T>(context.GetPlace()); output->mutable_data<T>(context.GetPlace());
std::vector<int> ksize = context.Attr<std::vector<int>>("ksize");
std::vector<int> strides = context.Attr<std::vector<int>>("strides"); std::vector<int> strides = context.Attr<std::vector<int>>("strides");
std::vector<int> paddings = context.Attr<std::vector<int>>("paddings"); std::vector<int> paddings = context.Attr<std::vector<int>>("paddings");
std::vector<int> dilations = context.Attr<std::vector<int>>("dilations"); std::vector<int> dilations = context.Attr<std::vector<int>>("dilations");
framework::DDim filter_matrix_shape = {filter.dims()[0],
filter.numel() / filter.dims()[0]};
filter.Resize(filter_matrix_shape);
math::DepthwiseConvFunctor<DeviceContext, T> depthwiseConv; math::DepthwiseConvFunctor<DeviceContext, T> depthwiseConv;
auto& dev_ctx = context.template device_context<DeviceContext>(); auto& dev_ctx = context.template device_context<DeviceContext>();
depthwiseConv(dev_ctx, input, filter, filter_shape_vec, strides, paddings, depthwiseConv(dev_ctx, *input, filter, ksize, strides, paddings,
output); output);
} }
}; };
......
...@@ -8,6 +8,7 @@ if(WITH_GPU) ...@@ -8,6 +8,7 @@ if(WITH_GPU)
nv_library(softmax SRCS softmax.cc softmax.cu DEPS device_context) nv_library(softmax SRCS softmax.cc softmax.cu DEPS device_context)
nv_library(cross_entropy SRCS cross_entropy.cc cross_entropy.cu DEPS device_context) nv_library(cross_entropy SRCS cross_entropy.cc cross_entropy.cu DEPS device_context)
nv_library(pooling SRCS pooling.cc pooling.cu DEPS device_context) nv_library(pooling SRCS pooling.cc pooling.cu DEPS device_context)
nv_library(depthwise_conv SRCS depthwise_conv.cu DEPS device_context)
nv_library(sequence_pooling SRCS sequence_pooling.cc sequence_pooling.cu DEPS device_context math_function) nv_library(sequence_pooling SRCS sequence_pooling.cc sequence_pooling.cu DEPS device_context math_function)
nv_library(vol2col SRCS vol2col.cc vol2col.cu DEPS device_context tensor) nv_library(vol2col SRCS vol2col.cc vol2col.cu DEPS device_context tensor)
nv_library(context_project SRCS context_project.cc context_project.cu DEPS device_context math_function) nv_library(context_project SRCS context_project.cc context_project.cu DEPS device_context math_function)
......
...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include "paddle/operators/math/pooling.h" #include "paddle/operators/math/depthwise_conv.h"
#include "paddle/platform/cuda_helper.h" #include "paddle/platform/cuda_helper.h"
namespace paddle { namespace paddle {
...@@ -195,7 +195,7 @@ __global__ void KernelDepthwiseConvFilterGrad(const int num_i, ...@@ -195,7 +195,7 @@ __global__ void KernelDepthwiseConvFilterGrad(const int num_i,
* Ksize, strides, paddings are two elements. These two elements represent * Ksize, strides, paddings are two elements. These two elements represent
* height and width, respectively. * height and width, respectively.
*/ */
template <typename T> template <class T>
class DepthwiseConvFunctor<platform::CUDADeviceContext, T> { class DepthwiseConvFunctor<platform::CUDADeviceContext, T> {
public: public:
void operator()(const platform::CUDADeviceContext& context, void operator()(const platform::CUDADeviceContext& context,
...@@ -226,7 +226,7 @@ class DepthwiseConvFunctor<platform::CUDADeviceContext, T> { ...@@ -226,7 +226,7 @@ class DepthwiseConvFunctor<platform::CUDADeviceContext, T> {
dim3 threads(1024, 1); dim3 threads(1024, 1);
dim3 grid(blocks, 1); dim3 grid(blocks, 1);
KernelDepthwiseConv<T><<<grid, threads, 0, STREAM_DEFAULT>>>( KernelDepthwiseConv<T><<<grid, threads, 0, context.stream()>>>(
nthreads, input_data, filter_data, batch_size, output_channels, nthreads, input_data, filter_data, batch_size, output_channels,
output_height, output_width, input_channels, input_height, input_width, output_height, output_width, input_channels, input_height, input_width,
output_channels / input_channels, ksize_height, ksize_width, output_channels / input_channels, ksize_height, ksize_width,
...@@ -236,7 +236,6 @@ class DepthwiseConvFunctor<platform::CUDADeviceContext, T> { ...@@ -236,7 +236,6 @@ class DepthwiseConvFunctor<platform::CUDADeviceContext, T> {
}; };
/* /*
template <typename T> template <typename T>
class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext, PoolProcess, T> class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext, PoolProcess, T>
{ {
...@@ -254,8 +253,7 @@ class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext, PoolProcess, T> ...@@ -254,8 +253,7 @@ class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext, PoolProcess, T>
const int output_height = output.dims()[2]; const int output_height = output.dims()[2];
const int output_width = output.dims()[3]; const int output_width = output.dims()[3];
const int ksize_height = ksize[0]; const int ksize_height = ksize[0];
const int ksize_width = ksize[1]; const int ksize_width = ksize[1]; const int stride_height = strides[0];
const int stride_height = strides[0];
const int stride_width = strides[1]; const int stride_width = strides[1];
const int padding_height = paddings[0]; const int padding_height = paddings[0];
const int padding_width = paddings[1]; const int padding_width = paddings[1];
...@@ -321,24 +319,20 @@ class DepthwiseConvdFilterGradFunctor<platform::CUDADeviceContext, T> { ...@@ -321,24 +319,20 @@ class DepthwiseConvdFilterGradFunctor<platform::CUDADeviceContext, T> {
*/ */
template class DepthwiseConvFunctor<platform::CUDADeviceContext, template class DepthwiseConvFunctor<platform::CUDADeviceContext,
paddle::operators::math::MaxPool<float>,
float>; float>;
template class DepthwiseConvFunctor<platform::CUDADeviceContext,
double>;
/* /*
template class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext, template class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext,
paddle::operators::math::MaxPoolGrad<float>,
float>; float>;
template class DepthwiseConvFilterGradFunctor<platform::CUDADeviceContext, template class DepthwiseConvFilterGradFunctor<platform::CUDADeviceContext,
paddle::operators::math::MaxPoolGrad<float>,
float>; float>;
template class DepthwiseConvFunctor<platform::CUDADeviceContext, template class DepthwiseConvFunctor<platform::CUDADeviceContext,
paddle::operators::math::MaxPool<double>, double>;
template class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext, template class DepthwiseConvInputGradFunctor<platform::CUDADeviceContext,
paddle::operators::math::MaxPoolGrad<double>,
double>; double>;
template class DepthwiseConvFilterGradFunctor<platform::CUDADeviceContext, template class DepthwiseConvFilterGradFunctor<platform::CUDADeviceContext,
paddle::operators::math::MaxPoolGrad<double>,
double>; double>;
*/ */
......
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