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提交 45a8c9dd 编写于 作者: S sweetsky0901
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add unpool2d make ok

上级 f638f910
隐藏空白更改
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Showing with 59 addition and 45 deletion
paddle/operators/CMakeLists.txt
浏览文件 @ 45a8c9dd
......@@ -80,6 +80,13 @@ function(op_library TARGET)
file(APPEND ${pybind_file} "USE_OP(pool2d);\n")
endif()
# unpool_op contains several operators
if ("${TARGET}" STREQUAL "unpool_op")
set(pybind_flag 1)
# It's enough to just adding one operator to pybind
file(APPEND ${pybind_file} "USE_OP(unpool2d);\n")
endif()
# pool_cudnn_op contains several operators
if ("${TARGET}" STREQUAL "pool_cudnn_op")
set(pybind_flag 1)
......
paddle/operators/math/unpooling.cc
浏览文件 @ 45a8c9dd
......@@ -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
limitations under the License. */
#include "paddle/operators/math/maxouting.h"
#include "paddle/operators/math/unpooling.h"
namespace paddle {
namespace operators {
......@@ -20,7 +20,7 @@ namespace math {
// All tensors are in NCHW format
template <typename T>
class Unpool2d_Max_Functor<platform::CPUPlace, T> {
class Unpool2d_MaxFunctor<platform::CPUPlace, T> {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
......@@ -36,16 +36,14 @@ class Unpool2d_Max_Functor<platform::CPUPlace, T> {
int input_feasize = input_height * input_width;
int output_feasize = output_height * output_width;
const T* input_data = input.data<T>();
const T* indices_data = indices.data<T>();
const int * indices_data = indices.data<int>();
T* output_data = output->mutable_data<T>(context.GetPlace());
for (int b = 0; b < batch_size; ++b) {
for (int c = 0; c < output_channels; ++c) {
for (int i = 0; i < input_feasize; ++i) {
int index = indices_data[i];
if(index > output_feasize) {
//抛一个异常！
}
// PADDLE_ENFORCE(index < output_feasize, "err index in unpooling!");
output_data[index] = input_data[i];
}
input_data += input_feasize;
......@@ -70,26 +68,22 @@ public:
const int batch_size = input.dims()[0];
const int input_height = input.dims()[2];
const int input_width = input.dims()[3];
const int output_channels = output->dims()[1];
const int output_height = output->dims()[2];
const int output_width = output->dims()[3];
const int output_channels = output.dims()[1];
const int output_height = output.dims()[2];
const int output_width = output.dims()[3];
int input_feasize = input_height * input_width;
int output_feasize = output_height * output_width;
const T* input_data = input.data<T>();
const T* indices_data = indices.data<T>();
const T* output_data = output.data<T>();
const int* indices_data = indices.data<int>();
const T* output_grad_data = output_grad.data<T>();
T* input_grad_data = input_grad->mutable_data<T>(context.GetPlace());
for (int b = 0; b < batch_size; ++b) {
for (int c = 0; c < output_channels; ++c) {
for (int f = 0; f < input_feasize; ++f) {
for (int i = 0; i < input_feasize; ++i) {
int index = indices_data[i];
if(index > output_feasize) {
//抛一个异常！
}
// PADDLE_ENFORCE(index < output_feasize, "err index in unpooling!");
input_grad_data[i] = output_grad_data[index];
}
input_grad_data += input_feasize;
......
paddle/operators/math/unpooling.cu
浏览文件 @ 45a8c9dd
......@@ -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
limitations under the License. */
#include "paddle/operators/math/maxouting.h"
#include "paddle/operators/math/unpooling.h"
#include "paddle/platform/cuda_helper.h"
namespace paddle {
......@@ -22,7 +22,7 @@ namespace math {
template <typename T>
__global__ void KernelUnpool2dMax(const int nthreads,
const T* input_data,
const T* indices_data,
const int* indices_data,
const int input_height,
const int input_width,
T* output_data,
......@@ -30,16 +30,19 @@ __global__ void KernelUnpool2dMax(const int nthreads,
const int output_width) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
int offset = blockDim.x * gridDim.x;
// int output_feasize = output_height * output_width;
for (int i = index; i < nthreads; i += offset) {
int out_offset = i / (input_height * input_width) \
* output_height * output_width;
int out_index = indices_data[i];
// PADDLE_ENFORCE(out_index < output_feasize, "err index in unpooling!");
output_data[out_offset + out_index] = input_data[i];
}
}
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 T* output_data,
......@@ -49,10 +52,13 @@ __global__ void KernelUnpool2dMaxGrad(const int nthreads,
T* input_grad) {
int index = blockIdx.x * blockDim.x + threadIdx.x;
int offset = blockDim.x * gridDim.x;
// int output_feasize = output_height * output_width;
for (int i = index; i < nthreads; i += offset) {
int out_offset = i / (input_height * input_width) \
* output_height * output_width;
int out_index = indices_data[i];
// PADDLE_ENFORCE(out_index < output_feasize,
// "err index in unpooling!");
input_grad[i] = output_grad[out_offset + out_index];
}
}
......@@ -72,10 +78,8 @@ class Unpool2d_MaxFunctor<platform::GPUPlace, T> {
const int output_channels = output->dims()[1];
const int output_height = output->dims()[2];
const int output_width = output->dims()[3];
int input_feasize = input_height * input_width;
int output_feasize = output_height * output_width;
const T* input_data = input.data<T>();
const T* indices_data = indices.data<T>();
const int* indices_data = indices.data<int>();
T* output_data = output->mutable_data<T>(context.GetPlace());
int nthreads = output->numel();
......@@ -99,19 +103,18 @@ class Unpool2d_MaxGradFunctor<platform::GPUPlace, T> {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices,
framework::Tensor * input_grad,
const framework::Tensor& output,
const framework::Tensor& output_grad,
int groups) {
const framework::Tensor& output_grad) {
const int batch_size = input.dims()[0];
const int input_height = input.dims()[2];
const int input_width = input.dims()[3];
const int output_channels = output.dims()[1];
const int output_height = output.dims()[2];
const int output_width = output.dims()[3];
const T* input_data = input.data<T>();
const T* indices_data = indices.data<T>();
const int* indices_data = indices.data<int>();
const T* output_data = output.data<T>();
const T* output_grad_data = output_grad.data<T>();
T* input_grad_data = input_grad->mutable_data<T>(context.GetPlace());
......
paddle/operators/math/unpooling.h
浏览文件 @ 45a8c9dd
......@@ -26,7 +26,7 @@ namespace math {
template <typename Place, typename T>
class Unpool2d_Max_Functor {
class Unpool2d_MaxFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
......@@ -35,10 +35,11 @@ class Unpool2d_Max_Functor {
};
template <typename Place, class T>
class Unpool2d_Max_GradFunctor {
class Unpool2d_MaxGradFunctor {
public:
void operator()(const platform::DeviceContext& context,
const framework::Tensor& input,
const framework::Tensor& indices,
framework::Tensor * input_grad,
const framework::Tensor& output,
const framework::Tensor& output_grad);
......
paddle/operators/unpool_op.cc
浏览文件 @ 45a8c9dd
......@@ -20,7 +20,8 @@ using framework::Tensor;
class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
UnpoolOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
Unpool2dOpMaker(framework::OpProto* proto, \
framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("X",
"(Tensor) The input tensor of unpool operator. "
......@@ -39,10 +40,12 @@ class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
AddAttr<std::vector<int>>("ksize",
"(vector ), the unpooling window size(height, width) "
"of unpooling operator.");
AddAttr<std::vector<int>>("strides", "(vector, default:{1, 1}), "
AddAttr<std::vector<int>>("strides",
"(vector, default:{1, 1}), "
"strides(height, width) of unpooling operator.")
.SetDefault({1, 1});
AddAttr<std::vector<int>>("paddings", "(vector defalut:{0,0}), "
AddAttr<std::vector<int>>("paddings",
"(vector defalut:{0,0}), "
"paddings(height, width) of unpooling operator.")
.SetDefault({0, 0});
AddAttr<std::string>("unpoolingType",
......@@ -73,7 +76,8 @@ class UnpoolOp : public framework::OperatorWithKernel {
auto in_x_dims = ctx->GetInputDim("X");
auto in_y_dims = ctx->GetInputDim("Y");
std::string unpooling_type = ctx->Attrs().Get<std::string>("unpooling_type");
std::string unpooling_type = \
ctx->Attrs().Get<std::string>("unpooling_type");
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> paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
......@@ -95,7 +99,7 @@ class UnpoolOpGrad : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) must not be null.");
PADDLE_ENFORCE(ctx->HasInput("Y"), "Input(X) must not be null.");
PADDLE_ENFORCE(ctx->HasInput("Y"), "Input(Y) must not be null.");
PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
"Input(Out@GRAD) should not be null");
PADDLE_ENFORCE(ctx->HasOutput(framework::GradVarName("X")),
......@@ -109,8 +113,11 @@ class UnpoolOpGrad : public framework::OperatorWithKernel {
namespace ops = paddle::operators;
REGISTER_OP(unpool2d, ops::UnpoolOp, ops::Unpool2dOpMaker, unpool2d_grad,
ops::UnpoolOpGrad);
REGISTER_OP_CPU_KERNEL(unpool2d, ops::UnpoolKernel<paddle::platform::CPUPlace,
float>);
REGISTER_OP_CPU_KERNEL(unpool2d,
ops::UnpoolKernel<paddle::platform::CPUPlace, float>,
ops::UnpoolKernel<paddle::platform::CPUPlace, double>);
REGISTER_OP_CPU_KERNEL(unpool2d_grad,
ops::UnpoolGradKernel<paddle::platform::CPUPlace,
float>);
ops::UnpoolGradKernel<paddle::platform::CPUPlace,
float>,
ops::UnpoolGradKernel<paddle::platform::CPUPlace,
double>);
paddle/operators/unpool_op.cu.cc
浏览文件 @ 45a8c9dd
......@@ -16,7 +16,10 @@
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(unpool2d,
ops::UnpoolKernel<paddle::platform::GPUPlace, float>);
ops::UnpoolKernel<paddle::platform::GPUPlace, float>,
ops::UnpoolKernel<paddle::platform::GPUPlace, double>);
REGISTER_OP_GPU_KERNEL(unpool2d_grad,
ops::UnpoolGradKernel<paddle::platform::GPUPlace,
float>);
float>,
ops::UnpoolGradKernel<paddle::platform::GPUPlace,
double>);
paddle/operators/unpool_op.h
浏览文件 @ 45a8c9dd
......@@ -37,9 +37,8 @@ class UnpoolKernel : public framework::OpKernel<T> {
switch (ksize.size()) {
case 2: {
if (pooling_type == "max") {
math::Unpool2d_Max_Functor<Place, T> unpool2d_max_forward;
unpool2d_max_forward(context.device_context(), *in_x, *in_y,
ksize, strides, paddings, out);
math::Unpool2d_MaxFunctor<Place, T> unpool2d_max_forward;
unpool2d_max_forward(context.device_context(), *in_x, *in_y, out);
}
} break;
default: { PADDLE_THROW("Pool op only supports 2D input."); }
......@@ -71,12 +70,12 @@ class UnpoolGradKernel : public framework::OpKernel<T> {
switch (ksize.size()) {
case 2: {
if (pooling_type == "max") {
math::UnpoolGradFunctor<Place, T> maxout_backward;
maxout_backward(context.device_context(), *in_x, *in_y, in_x_grad, *out,
*out_grad, ksize, strides, paddings);
math::Unpool2d_MaxGradFunctor<Place, T> unpool2d_max_backward;
unpool2d_max_backward(context.device_context(), *in_x, *in_y, in_x_grad,
*out, *out_grad);
}
} break;
default: { PADDLE_THROW("Pool op only supports 2D input."); }
default: { PADDLE_THROW("Unpool op only supports 2D input."); }
}
}
};
......
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