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PaddleDetection
提交 225c11a9 编写于 作者: D dzhwinter 提交者： Jiabin Yang
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polish cudnn related code and fix bug. (#15164) 

* staged.

* polish code

* polish code. test=develop

* polish code. test=develop

* api change. test=develop

* fix default value. test=develop

* fix default value. test=develop
上级 6e362444
隐藏空白更改
内联 并排
Showing with 543 addition and 128 deletion
cmake/operators.cmake
浏览文件 @ 225c11a9
...@@ -153,7 +153,11 @@ function(op_library TARGET) ...@@ -153,7 +153,11 @@ function(op_library TARGET)
# pybind USE_OP_DEVICE_KERNEL for CUDNN # pybind USE_OP_DEVICE_KERNEL for CUDNN
list(LENGTH cudnn_cu_cc_srcs cudnn_cu_cc_srcs_len) list(LENGTH cudnn_cu_cc_srcs cudnn_cu_cc_srcs_len)
if (WITH_GPU AND ${cudnn_cu_cc_srcs_len} GREATER 0) if (WITH_GPU AND ${cudnn_cu_cc_srcs_len} GREATER 0)
if(${TARGET} STREQUAL "activation")
file(APPEND ${pybind_file} "USE_OP_DEVICE_KERNEL(relu, CUDNN);\n")
else()
file(APPEND ${pybind_file} "USE_OP_DEVICE_KERNEL(${TARGET}, CUDNN);\n") file(APPEND ${pybind_file} "USE_OP_DEVICE_KERNEL(${TARGET}, CUDNN);\n")
endif()
endif() endif()
# pybind USE_OP_DEVICE_KERNEL for MIOPEN # pybind USE_OP_DEVICE_KERNEL for MIOPEN
......
paddle/fluid/framework/executor.cc
浏览文件 @ 225c11a9
...@@ -20,6 +20,7 @@ limitations under the License. */ ...@@ -20,6 +20,7 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_tensor_array.h" #include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/reader.h" #include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/framework/threadpool.h"
#include "paddle/fluid/framework/transfer_scope_cache.h" #include "paddle/fluid/framework/transfer_scope_cache.h"
#include "paddle/fluid/framework/variable_helper.h" #include "paddle/fluid/framework/variable_helper.h"
#include "paddle/fluid/operators/distributed/distributed.h" #include "paddle/fluid/operators/distributed/distributed.h"
......
paddle/fluid/operators/activation_cudnn.cu.cc 0 → 100644
浏览文件 @ 225c11a9
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/platform/cudnn_desc.h"
namespace paddle {
namespace operators {
using framework::Tensor;
using platform::ActivationDescriptor;
using platform::TensorDescriptor;
template <typename Functor>
class CudnnActivationKernel
: public framework::OpKernel<Functor::ElEWISE_TYPE> {
public:
void Compute(const framework::ExecutionContext& context) const override {
framework::Tensor *X, *Out;
ExtractActivationTensor(context, X, Out);
ActivationDescriptor act_desc;
TensorDescriptor x_desc, out_desc;
x_desc.set(detail::Ref(X));
out_desc.set(detail::Ref(Out));
}
};
} // namespace operators
} // namespace paddle
paddle/fluid/operators/activation_cudnn_op.cu.cc 0 → 100644
浏览文件 @ 225c11a9
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/platform/cudnn_desc.h"
namespace paddle {
namespace operators {
using framework::Tensor;
using platform::ActivationDescriptor;
using platform::TensorDescriptor;
using platform::CUDADeviceContext;
template <typename T>
struct CudnnActivationFunctor {
using ELEMENT_TYPE = T;
CudnnActivationFunctor(const CUDADeviceContext& ctx, const T& c,
const cudnnActivationMode_t& m)
: ctx_(ctx), coef_(c), mode_(m) {}
void operator()(const Tensor& x, Tensor* out) {
ActivationDescriptor act_desc;
act_desc.set(mode_, coef_);
TensorDescriptor x_desc, out_desc;
x_desc.set(x);
out_desc.set(detail::Ref(out));
PADDLE_ENFORCE(platform::dynload::cudnnActivationForward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), x_desc.desc(), x.data<T>(),
platform::CudnnDataType<T>::kZero(), out_desc.desc(),
out->mutable_data<T>(ctx_.GetPlace())));
}
const CUDADeviceContext& ctx_;
const T coef_;
const cudnnActivationMode_t mode_;
};
template <typename T>
struct CudnnActivationGradFunctor {
using ELEMENT_TYPE = T;
CudnnActivationGradFunctor(const CUDADeviceContext& ctx, const T& c,
const cudnnActivationMode_t& m)
: ctx_(ctx), coef_(c), mode_(m) {}
void operator()(const Tensor& x, const Tensor& out, const Tensor dout,
Tensor* dx) {
ActivationDescriptor act_desc;
act_desc.set(mode_, coef_);
TensorDescriptor x_desc, out_desc, dout_desc, dx_desc;
x_desc.set(x);
out_desc.set(out);
dout_desc.set(dout);
dx_desc.set(detail::Ref(dx));
PADDLE_ENFORCE(platform::dynload::cudnnActivationBackward(
ctx_.cudnn_handle(), act_desc.desc(),
platform::CudnnDataType<T>::kOne(), out_desc.desc(), out.data<T>(),
dout_desc.desc(), dout.data<T>(), x_desc.desc(), x.data<T>(),
platform::CudnnDataType<T>::kZero(), dx_desc.desc(),
dx->mutable_data<T>(ctx_.GetPlace())));
}
const CUDADeviceContext& ctx_;
const T coef_;
const cudnnActivationMode_t mode_;
};
template <typename T>
struct CudnnReluFunctor : public CudnnActivationFunctor<T> {
explicit CudnnReluFunctor(const CUDADeviceContext& ctx)
: CudnnActivationFunctor<T>(ctx, 0.0, CUDNN_ACTIVATION_RELU) {}
};
template <typename T>
struct CudnnReluGradFunctor : public CudnnActivationGradFunctor<T> {
explicit CudnnReluGradFunctor(const CUDADeviceContext& ctx)
: CudnnActivationGradFunctor<T>(ctx, 0.0, CUDNN_ACTIVATION_RELU) {}
};
template <typename T>
struct CudnnRelu6Functor : public CudnnActivationFunctor<T> {
explicit CudnnRelu6Functor(const CUDADeviceContext& ctx)
: CudnnActivationFunctor<T>(ctx, 6.0, CUDNN_ACTIVATION_CLIPPED_RELU) {}
};
template <typename T>
struct CudnnRelu6GradFunctor : public CudnnActivationGradFunctor<T> {
explicit CudnnRelu6GradFunctor(const CUDADeviceContext& ctx)
: CudnnActivationGradFunctor<T>(ctx, 6.0, CUDNN_ACTIVATION_CLIPPED_RELU) {
}
};
template <typename T>
struct CudnnSigmoidFunctor : public CudnnActivationFunctor<T> {
explicit CudnnSigmoidFunctor(const CUDADeviceContext& ctx)
: CudnnActivationFunctor<T>(ctx, 0.0, CUDNN_ACTIVATION_SIGMOID) {}
};
template <typename T>
struct CudnnSigmoidGradFunctor : public CudnnActivationGradFunctor<T> {
explicit CudnnSigmoidGradFunctor(const CUDADeviceContext& ctx)
: CudnnActivationGradFunctor<T>(ctx, 0.0, CUDNN_ACTIVATION_SIGMOID) {}
};
template <typename T>
struct CudnnTanhFunctor : public CudnnActivationFunctor<T> {
explicit CudnnTanhFunctor(const CUDADeviceContext& ctx)
: CudnnActivationFunctor<T>(ctx, 0.0, CUDNN_ACTIVATION_TANH) {}
};
template <typename T>
struct CudnnTanhGradFunctor : public CudnnActivationGradFunctor<T> {
explicit CudnnTanhGradFunctor(const CUDADeviceContext& ctx)
: CudnnActivationGradFunctor<T>(ctx, 0.0, CUDNN_ACTIVATION_TANH) {}
};
template <typename Functor>
class CudnnActivationKernel
: public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
public:
using T = typename Functor::ELEMENT_TYPE;
void Compute(const framework::ExecutionContext& context) const override {
const framework::Tensor* X = nullptr;
framework::Tensor* Out = nullptr;
ExtractActivationTensor(context, &X, &Out);
Out->mutable_data<T>(context.GetPlace());
auto& dev_ctx = context.template device_context<CUDADeviceContext>();
Functor functor(dev_ctx);
functor(detail::Ref(X), Out);
}
};
template <typename Functor>
class CudnnActivationGradKernel
: public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
public:
using T = typename Functor::ELEMENT_TYPE;
void Compute(const framework::ExecutionContext& context) const override {
const framework::Tensor *X, *Out, *dOut;
X = Out = dOut = nullptr;
framework::Tensor* dX = nullptr;
ExtractActivationGradTensor(context, &X, &Out, &dOut, &dX);
dX->mutable_data<T>(context.GetPlace());
auto& dev_ctx = context.template device_context<CUDADeviceContext>();
Functor functor(dev_ctx);
functor(detail::Ref(X), detail::Ref(Out), detail::Ref(dOut), dX);
}
};
} // namespace operators
} // namespace paddle
namespace plat = paddle::platform;
namespace ops = paddle::operators;
#define FOR_EACH_CUDNN_OP_FUNCTOR(__macro) \
__macro(relu, CudnnReluFunctor, CudnnReluGradFunctor); \
__macro(relu6, CudnnRelu6Functor, CudnnRelu6GradFunctor); \
__macro(sigmoid, CudnnTanhFunctor, CudnnTanhGradFunctor); \
__macro(tanh, CudnnTanhFunctor, CudnnTanhGradFunctor)
#define REGISTER_ACTIVATION_CUDNN_KERNEL(act_type, functor, grad_functor) \
REGISTER_OP_KERNEL(act_type, CUDNN, plat::CUDAPlace, \
ops::CudnnActivationKernel<ops::functor<float>>, \
ops::CudnnActivationKernel<ops::functor<double>>); \
REGISTER_OP_KERNEL( \
act_type##_grad, CUDNN, plat::CUDAPlace, \
ops::CudnnActivationGradKernel<ops::grad_functor<float>>, \
ops::CudnnActivationGradKernel<ops::grad_functor<double>>);
FOR_EACH_CUDNN_OP_FUNCTOR(REGISTER_ACTIVATION_CUDNN_KERNEL);
paddle/fluid/operators/activation_op.cc
浏览文件 @ 225c11a9
...@@ -16,29 +16,36 @@ limitations under the License. */ ...@@ -16,29 +16,36 @@ limitations under the License. */
#include <string> #include <string>
#include "paddle/fluid/operators/mkldnn/mkldnn_activation_op.h" #include "paddle/fluid/operators/mkldnn/mkldnn_activation_op.h"
#include "paddle/fluid/platform/port.h" #include "paddle/fluid/platform/port.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/cudnn_helper.h"
#endif
namespace paddle { namespace paddle {
namespace operators { namespace operators {
using paddle::framework::Tensor; using paddle::framework::Tensor;
#define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT) \ #define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT) \
class OP_NAME##OpMaker \ class OP_NAME##OpMaker \
: public ::paddle::framework::OpProtoAndCheckerMaker { \ : public ::paddle::framework::OpProtoAndCheckerMaker { \
public: \ public: \
void Make() override { \ void Make() override { \
AddInput("X", "Input of " #OP_NAME " operator"); \ AddInput("X", "Input of " #OP_NAME " operator"); \
AddOutput("Out", "Output of " #OP_NAME " operator"); \ AddOutput("Out", "Output of " #OP_NAME " operator"); \
AddAttr<bool>("use_mkldnn", \ AddAttr<bool>("use_mkldnn", \
"(bool, default false) Only used in mkldnn kernel") \ "(bool, default false) Only used in mkldnn kernel") \
.SetDefault(false); \ .SetDefault(false); \
AddAttr<bool>( \ AddAttr<bool>("use_cudnn", \
"is_test", \ "(bool, default false) Only used in cudnn kernel, need " \
"(bool, default false) Set to true for inference only, false " \ "install cudnn") \
"for training. Some layers may run faster when this is true.") \ .SetDefault(false); \
.SetDefault(false); \ AddAttr<bool>( \
AddComment(OP_COMMENT); \ "is_test", \
} \ "(bool, default false) Set to true for inference only, false " \
"for training. Some layers may run faster when this is true.") \
.SetDefault(false); \
AddComment(OP_COMMENT); \
} \
} }
#define REGISTER_ACTIVATION_OP_GRAD_MAKER(OP_NAME, KERNEL_TYPE) \ #define REGISTER_ACTIVATION_OP_GRAD_MAKER(OP_NAME, KERNEL_TYPE) \
...@@ -67,6 +74,12 @@ framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx, ...@@ -67,6 +74,12 @@ framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx,
const std::string& name) { const std::string& name) {
framework::LibraryType library{framework::LibraryType::kPlain}; framework::LibraryType library{framework::LibraryType::kPlain};
framework::DataLayout layout = framework::DataLayout::kAnyLayout; framework::DataLayout layout = framework::DataLayout::kAnyLayout;
#ifdef PADDLE_WITH_CUDA
auto it1 = oper.Attrs().find("use_cudnn");
if (it1 != oper.Attrs().end() && platform::CanCUDNNBeUsed(ctx)) {
library = framework::LibraryType::kCUDNN;
}
#endif
#ifdef PADDLE_WITH_MKLDNN #ifdef PADDLE_WITH_MKLDNN
auto it = oper.Attrs().find("use_mkldnn"); auto it = oper.Attrs().find("use_mkldnn");
if (library == framework::LibraryType::kPlain && it != oper.Attrs().end() && if (library == framework::LibraryType::kPlain && it != oper.Attrs().end() &&
......
paddle/fluid/operators/activation_op.h
浏览文件 @ 225c11a9
...@@ -41,53 +41,115 @@ static std::unordered_set<std::string> InplaceOpSet = { ...@@ -41,53 +41,115 @@ static std::unordered_set<std::string> InplaceOpSet = {
"floor", "reciprocal", "relu6", "soft_relu", "hard_sigmoid", "floor", "reciprocal", "relu6", "soft_relu", "hard_sigmoid",
}; };
static bool IsInplace(const std::string& op) {
bool inplace = InplaceOpSet.count(op);
// for op_grad
const int kGradSuffixLen = 4;
if (op.size() > kGradSuffixLen &&
op.compare(op.size() - kGradSuffixLen - 1, kGradSuffixLen, "grad")) {
inplace =
InplaceOpSet.count(op.substr(0, op.size() - (kGradSuffixLen + 1)));
}
return inplace;
}
/* The following operator can be used to process SelectedRows, because the /* The following operator can be used to process SelectedRows, because the
* output of those operator for zero is zero too. * output of those operator for zero is zero too.
*/ */
static std::unordered_set<std::string> CanBeUsedBySelectedRows = { static std::unordered_set<std::string> CanBeUsedBySelectedRows = {
"abs", "abs_grad", "square", "square_grad", "sqrt", "sqrt_grad"}; "abs", "abs_grad", "square", "square_grad", "sqrt", "sqrt_grad"};
static bool IsInplace(std::string op) { return InplaceOpSet.count(op); } inline void ExtractActivationTensor(const framework::ExecutionContext& context,
const framework::Tensor** X,
template <typename DeviceContext, typename Functor> framework::Tensor** Out) {
class ActivationKernel auto x_var = context.InputVar("X");
: public framework::OpKernel<typename Functor::ELEMENT_TYPE> { auto out_var = context.OutputVar("Out");
public: PADDLE_ENFORCE(x_var != nullptr,
using T = typename Functor::ELEMENT_TYPE; "Cannot get input Variable X, variable name = %s",
context.op().Input("X"));
void Compute(const framework::ExecutionContext& context) const override { PADDLE_ENFORCE(out_var != nullptr,
"Cannot get output Variable Out, variable name = %s",
context.op().Output("Out"));
if (CanBeUsedBySelectedRows.count(context.op().Type())) {
*X = paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(*x_var);
*Out = paddle::framework::GetMutableLoDTensorOrSelectedRowsValueFromVar(
out_var);
} else {
*X = context.Input<framework::Tensor>("X");
*Out = context.Output<framework::Tensor>("Out");
}
PADDLE_ENFORCE(*Out != nullptr,
"Cannot get output tensor Out, variable name = %s",
context.op().Output("Out"));
}
inline void ExtractActivationGradTensor(
const framework::ExecutionContext& context, const framework::Tensor** X,
const framework::Tensor** Out, const framework::Tensor** dOut,
framework::Tensor** dX) {
auto out_var = context.InputVar("Out");
auto out_grad_var = context.InputVar(framework::GradVarName("Out"));
auto x_grad_var = context.OutputVar(framework::GradVarName("X"));
PADDLE_ENFORCE(out_var != nullptr,
"Cannot get input Variable Out, variable name = %s",
context.op().Input("Out"));
PADDLE_ENFORCE(out_grad_var != nullptr,
"Cannot get input Variable %s, variable name = %s",
framework::GradVarName("Out"),
context.op().Input(framework::GradVarName("Out")));
PADDLE_ENFORCE(x_grad_var != nullptr,
"Cannot get output Variable %s, variable name = %s",
framework::GradVarName("X"),
context.op().Output(framework::GradVarName("X")));
if (CanBeUsedBySelectedRows.count(context.op().Type())) {
*Out = paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(*out_var);
*dOut = paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(
*out_grad_var);
*dX = paddle::framework::GetMutableLoDTensorOrSelectedRowsValueFromVar(
x_grad_var);
} else {
*Out = context.Input<framework::Tensor>("Out");
*dOut = context.Input<framework::Tensor>(framework::GradVarName("Out"));
*dX = context.Output<framework::Tensor>(framework::GradVarName("X"));
}
PADDLE_ENFORCE(*dX != nullptr,
"Cannot get output tensor %s, variable name = %s",
framework::GradVarName("X"),
context.op().Output(framework::GradVarName("X")));
bool inplace = IsInplace(context.op().Type());
if (!inplace) {
auto x_var = context.InputVar("X"); auto x_var = context.InputVar("X");
auto out_var = context.OutputVar("Out");
PADDLE_ENFORCE(x_var != nullptr, PADDLE_ENFORCE(x_var != nullptr,
"Cannot get input Variable X, variable name = %s", "Cannot get input tensor X, variable name = %s",
context.op().Input("X")); context.op().Input("X"));
PADDLE_ENFORCE(out_var != nullptr,
"Cannot get output Variable Out, variable name = %s",
context.op().Output("Out"));
framework::Tensor X, *Out;
if (CanBeUsedBySelectedRows.count(context.op().Type())) { if (CanBeUsedBySelectedRows.count(context.op().Type())) {
X = detail::Ref( *X = paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(*x_var);
paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(*x_var),
"Cannot get input Tensor X, variable name = %s",
context.op().Input("X"));
Out = paddle::framework::GetMutableLoDTensorOrSelectedRowsValueFromVar(
out_var);
} else { } else {
X = detail::Ref(context.Input<framework::Tensor>("X"), *X = context.Input<framework::Tensor>("X");
"Cannot get input Tensor X, variable name = %s",
context.op().Input("X"));
Out = context.Output<framework::Tensor>("Out");
} }
} else {
VLOG(10) << " Inplace activation of Op : " << context.op().Type();
*X = *dX;
}
}
PADDLE_ENFORCE(Out != nullptr, template <typename DeviceContext, typename Functor>
"Cannot get output tensor Out, variable name = %s", class ActivationKernel
context.op().Output("Out")); : public framework::OpKernel<typename Functor::ELEMENT_TYPE> {
public:
using T = typename Functor::ELEMENT_TYPE;
void Compute(const framework::ExecutionContext& context) const override {
const framework::Tensor* X = nullptr;
framework::Tensor* Out = nullptr;
ExtractActivationTensor(context, &X, &Out);
Out->mutable_data<T>(context.GetPlace()); Out->mutable_data<T>(context.GetPlace());
auto x = framework::EigenVector<T>::Flatten(X);
auto out = framework::EigenVector<T>::Flatten(*Out); auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto* place = auto* place =
context.template device_context<DeviceContext>().eigen_device(); context.template device_context<DeviceContext>().eigen_device();
Functor functor; Functor functor;
...@@ -106,55 +168,15 @@ class ActivationGradKernel ...@@ -106,55 +168,15 @@ class ActivationGradKernel
public: public:
using T = typename Functor::ELEMENT_TYPE; using T = typename Functor::ELEMENT_TYPE;
void Compute(const framework::ExecutionContext& context) const override { void Compute(const framework::ExecutionContext& context) const override {
auto out_var = context.InputVar("Out"); const framework::Tensor *X, *Out, *dOut;
auto out_grad_var = context.InputVar(framework::GradVarName("Out")); framework::Tensor* dX = nullptr;
auto x_grad_var = context.OutputVar(framework::GradVarName("X")); X = Out = dOut = nullptr;
PADDLE_ENFORCE(out_var != nullptr, ExtractActivationGradTensor(context, &X, &Out, &dOut, &dX);
"Cannot get input Variable Out, variable name = %s",
context.op().Input("Out"));
PADDLE_ENFORCE(out_grad_var != nullptr,
"Cannot get input Variable %s, variable name = %s",
framework::GradVarName("Out"),
context.op().Input(framework::GradVarName("Out")));
PADDLE_ENFORCE(x_grad_var != nullptr,
"Cannot get output Variable %s, variable name = %s",
framework::GradVarName("X"),
context.op().Output(framework::GradVarName("X")));
framework::Tensor Out, dOut, *dX;
if (CanBeUsedBySelectedRows.count(context.op().Type())) {
Out = detail::Ref(
paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(*out_var),
"Cannot get input Tensor Out, variable name = %s",
context.op().Input("Out"));
dOut =
detail::Ref(paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(
*out_grad_var),
"Cannot get input Tensor %s, variable name = %s",
framework::GradVarName("Out"),
context.op().Input(framework::GradVarName("Out")));
dX = paddle::framework::GetMutableLoDTensorOrSelectedRowsValueFromVar(
x_grad_var);
} else {
Out = detail::Ref(context.Input<framework::Tensor>("Out"),
"Cannot get input Tensor Out, variable name = %s",
context.op().Input("Out"));
dOut = detail::Ref(
context.Input<framework::Tensor>(framework::GradVarName("Out")),
"Cannot get input Tensor %s, variable name = %s",
framework::GradVarName("Out"),
context.op().Input(framework::GradVarName("Out")));
dX = context.Output<framework::Tensor>(framework::GradVarName("X"));
}
PADDLE_ENFORCE(dX != nullptr,
"Cannot get output tensor %s, variable name = %s",
framework::GradVarName("X"),
context.op().Output(framework::GradVarName("X")));
dX->mutable_data<T>(context.GetPlace()); dX->mutable_data<T>(context.GetPlace());
auto dout = framework::EigenVector<T>::Flatten(detail::Ref(dOut));
auto dout = framework::EigenVector<T>::Flatten(dOut); auto out = framework::EigenVector<T>::Flatten(detail::Ref(Out));
auto out = framework::EigenVector<T>::Flatten(Out); auto dx = framework::EigenVector<T>::Flatten(detail::Ref(dX));
auto dx = framework::EigenVector<T>::Flatten(*dX); auto x = framework::EigenVector<T>::Flatten(detail::Ref(X));
auto* place = auto* place =
context.template device_context<DeviceContext>().eigen_device(); context.template device_context<DeviceContext>().eigen_device();
Functor functor; Functor functor;
...@@ -162,27 +184,7 @@ class ActivationGradKernel ...@@ -162,27 +184,7 @@ class ActivationGradKernel
for (auto& attr : attrs) { for (auto& attr : attrs) {
*attr.second = context.Attr<float>(attr.first); *attr.second = context.Attr<float>(attr.first);
} }
bool inplace = functor.Inplace(); functor(*place, x, out, dout, dx);
if (!inplace) {
auto x_var = context.InputVar("X");
PADDLE_ENFORCE(x_var != nullptr,
"Cannot get input tensor X, variable name = %s",
context.op().Input("X"));
framework::Tensor X;
if (CanBeUsedBySelectedRows.count(context.op().Type())) {
X = detail::Ref(
paddle::framework::GetLoDTensorOrSelectedRowsValueFromVar(*x_var));
} else {
X = detail::Ref(context.Input<framework::Tensor>("X"));
}
auto x = framework::EigenVector<T>::Flatten(X);
functor(*place, x, out, dout, dx);
} else {
VLOG(10) << " Inplace activation ";
auto x = framework::EigenVector<T>::Flatten(*dX);
functor(*place, x, out, dout, dx);
}
} }
}; };
...@@ -214,7 +216,6 @@ struct SigmoidFunctor : public BaseActivationFunctor<T> { ...@@ -214,7 +216,6 @@ struct SigmoidFunctor : public BaseActivationFunctor<T> {
template <typename T> template <typename T>
struct SigmoidGradFunctor : public BaseActivationFunctor<T> { struct SigmoidGradFunctor : public BaseActivationFunctor<T> {
bool Inplace() const { return IsInplace("sigmoid"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -269,7 +270,6 @@ struct ExpFunctor : public BaseActivationFunctor<T> { ...@@ -269,7 +270,6 @@ struct ExpFunctor : public BaseActivationFunctor<T> {
template <typename T> template <typename T>
struct ExpGradFunctor : public BaseActivationFunctor<T> { struct ExpGradFunctor : public BaseActivationFunctor<T> {
bool Inplace() const { return IsInplace("exp"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -288,7 +288,6 @@ struct ReluFunctor : public BaseActivationFunctor<T> { ...@@ -288,7 +288,6 @@ struct ReluFunctor : public BaseActivationFunctor<T> {
template <typename T> template <typename T>
struct ReluGradFunctor : public BaseActivationFunctor<T> { struct ReluGradFunctor : public BaseActivationFunctor<T> {
bool Inplace() const { return IsInplace("relu"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -331,7 +330,6 @@ struct TanhFunctor : public BaseActivationFunctor<T> { ...@@ -331,7 +330,6 @@ struct TanhFunctor : public BaseActivationFunctor<T> {
template <typename T> template <typename T>
struct TanhGradFunctor : public BaseActivationFunctor<T> { struct TanhGradFunctor : public BaseActivationFunctor<T> {
bool Inplace() const { return IsInplace("tanh"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -437,7 +435,6 @@ struct SqrtFunctor : public BaseActivationFunctor<T> { ...@@ -437,7 +435,6 @@ struct SqrtFunctor : public BaseActivationFunctor<T> {
template <typename T> template <typename T>
struct SqrtGradFunctor : public BaseActivationFunctor<T> { struct SqrtGradFunctor : public BaseActivationFunctor<T> {
bool Inplace() const { return IsInplace("sqrt"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -456,7 +453,6 @@ struct CeilFunctor : public BaseActivationFunctor<T> { ...@@ -456,7 +453,6 @@ struct CeilFunctor : public BaseActivationFunctor<T> {
template <typename T> template <typename T>
struct ZeroGradFunctor : public BaseActivationFunctor<T> { struct ZeroGradFunctor : public BaseActivationFunctor<T> {
bool Inplace() const { return IsInplace("ceil"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -573,7 +569,6 @@ struct ReciprocalFunctor : public BaseActivationFunctor<T> { ...@@ -573,7 +569,6 @@ struct ReciprocalFunctor : public BaseActivationFunctor<T> {
template <typename T> template <typename T>
struct ReciprocalGradFunctor : public BaseActivationFunctor<T> { struct ReciprocalGradFunctor : public BaseActivationFunctor<T> {
bool Inplace() const { return IsInplace("reciprocal"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -673,7 +668,6 @@ struct Relu6GradFunctor : public BaseActivationFunctor<T> { ...@@ -673,7 +668,6 @@ struct Relu6GradFunctor : public BaseActivationFunctor<T> {
typename BaseActivationFunctor<T>::AttrPair GetAttrs() { typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
return {{"threshold", &threshold}}; return {{"threshold", &threshold}};
} }
bool Inplace() const { return IsInplace("relu6"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -755,7 +749,6 @@ struct SoftReluGradFunctor : public BaseActivationFunctor<T> { ...@@ -755,7 +749,6 @@ struct SoftReluGradFunctor : public BaseActivationFunctor<T> {
typename BaseActivationFunctor<T>::AttrPair GetAttrs() { typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
return {{"threshold", &threshold}}; return {{"threshold", &threshold}};
} }
bool Inplace() const { return IsInplace("soft_relu"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
...@@ -936,7 +929,6 @@ struct HardSigmoidGradFunctor : public BaseActivationFunctor<T> { ...@@ -936,7 +929,6 @@ struct HardSigmoidGradFunctor : public BaseActivationFunctor<T> {
typename BaseActivationFunctor<T>::AttrPair GetAttrs() { typename BaseActivationFunctor<T>::AttrPair GetAttrs() {
return {{"slope", &slope}, {"offset", &offset}}; return {{"slope", &slope}, {"offset", &offset}};
} }
bool Inplace() { return IsInplace("hard_sigmoid"); }
template <typename Device, typename X, typename Out, typename dOut, template <typename Device, typename X, typename Out, typename dOut,
typename dX> typename dX>
void operator()(Device d, X x, Out out, dOut dout, dX dx) const { void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
......
paddle/fluid/platform/CMakeLists.txt
浏览文件 @ 225c11a9
...@@ -82,6 +82,7 @@ nv_test(device_context_test SRCS device_context_test.cu DEPS device_context gpu_ ...@@ -82,6 +82,7 @@ nv_test(device_context_test SRCS device_context_test.cu DEPS device_context gpu_
cc_test(init_test SRCS init_test.cc DEPS device_context) cc_test(init_test SRCS init_test.cc DEPS device_context)
nv_test(cudnn_helper_test SRCS cudnn_helper_test.cc DEPS dynload_cuda) nv_test(cudnn_helper_test SRCS cudnn_helper_test.cc DEPS dynload_cuda)
nv_test(cudnn_desc_test SRCS cudnn_desc_test.cc DEPS dynload_cuda)
nv_test(transform_test SRCS transform_test.cu DEPS memory place device_context) nv_test(transform_test SRCS transform_test.cu DEPS memory place device_context)
cc_library(timer SRCS timer.cc) cc_library(timer SRCS timer.cc)
......
paddle/fluid/platform/cudnn_desc.h 0 → 100644
浏览文件 @ 225c11a9
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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.
#pragma once
#include <algorithm>
#include <functional>
#include <iostream>
#include <iterator>
#include <memory>
#include <numeric>
#include <string>
#include <vector>
#include "paddle/fluid/platform/cudnn_helper.h"
namespace paddle {
namespace platform {
using framework::Tensor;
template <typename T>
cudnnDataType_t ToCudnnDataType(const T& t) {
auto type = framework::ToDataType(t);
return ToCudnnDataType(type);
}
template <>
cudnnDataType_t ToCudnnDataType(const framework::proto::VarType::Type& t) {
cudnnDataType_t type = CUDNN_DATA_FLOAT;
switch (t) {
case framework::proto::VarType::FP16:
type = CUDNN_DATA_HALF;
break;
case framework::proto::VarType::FP32:
type = CUDNN_DATA_FLOAT;
break;
case framework::proto::VarType::FP64:
type = CUDNN_DATA_DOUBLE;
break;
default:
break;
}
return type;
}
class ActivationDescriptor {
public:
using T = cudnnActivationStruct;
struct Deleter {
void operator()(T* t) {
if (t != nullptr) {
PADDLE_ENFORCE(dynload::cudnnDestroyActivationDescriptor(t));
t = nullptr;
}
}
};
ActivationDescriptor() {
T* raw_ptr;
PADDLE_ENFORCE(dynload::cudnnCreateActivationDescriptor(&raw_ptr));
desc_.reset(raw_ptr);
}
template <typename T>
void set(cudnnActivationMode_t mode, const T& coef) {
CUDNN_ENFORCE(dynload::cudnnSetActivationDescriptor(
desc_.get(), mode, CUDNN_NOT_PROPAGATE_NAN, static_cast<double>(coef)));
}
T* desc() { return desc_.get(); }
T* desc() const { return desc_.get(); }
private:
std::unique_ptr<T, Deleter> desc_;
};
class TensorDescriptor {
public:
using T = cudnnTensorStruct;
struct Deleter {
void operator()(T* t) {
if (t != nullptr) {
PADDLE_ENFORCE(dynload::cudnnDestroyTensorDescriptor(t));
t = nullptr;
}
}
};
TensorDescriptor() {
T* raw_ptr;
PADDLE_ENFORCE(dynload::cudnnCreateTensorDescriptor(&raw_ptr));
desc_.reset(raw_ptr);
}
T* desc() { return desc_.get(); }
T* desc() const { return desc_.get(); }
void set(const Tensor& tensor, const int groups = 1) {
auto dims = framework::vectorize2int(tensor.dims());
std::vector<int> strides(dims.size());
strides[dims.size() - 1] = 1;
for (int i = dims.size() - 2; i >= 0; i--) {
strides[i] = dims[i + 1] * strides[i + 1];
}
std::vector<int> dims_with_group(dims.begin(), dims.end());
if (groups > 1) {
dims_with_group[1] = dims_with_group[1] / groups;
}
PADDLE_ENFORCE(dynload::cudnnSetTensorNdDescriptor(
desc_.get(), ToCudnnDataType(tensor.type()), dims_with_group.size(),
dims_with_group.data(), strides.data()));
}
private:
std::unique_ptr<T, Deleter> desc_;
};
} // namespace platform
} // namespace paddle
paddle/fluid/platform/cudnn_desc_test.cc 0 → 100644
浏览文件 @ 225c11a9
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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/fluid/platform/cudnn_desc.h"
#include <gtest/gtest.h>
namespace paddle {
namespace platform {
TEST(TensorDescriptor, Empty) {
ActivationDescriptor a;
TensorDescriptor t;
TensorDescriptor t1;
TensorDescriptor *t11 = new TensorDescriptor();
delete t11;
std::unique_ptr<TensorDescriptor> tt(new TensorDescriptor());
}
TEST(TensorDescriptor, Normal) {
framework::Tensor tt;
tt.Resize({2, 3, 4});
tt.mutable_data<float>(platform::CPUPlace());
TensorDescriptor desc;
desc.set(tt);
EXPECT_TRUE(desc.desc() != nullptr);
}
} // namespace platform
} // namespace paddle
paddle/fluid/platform/dynload/cudnn.h
浏览文件 @ 225c11a9
...@@ -99,6 +99,7 @@ extern void EnforceCUDNNLoaded(const char* fn_name); ...@@ -99,6 +99,7 @@ extern void EnforceCUDNNLoaded(const char* fn_name);
__macro(cudnnDestroy); \ __macro(cudnnDestroy); \
__macro(cudnnSetStream); \ __macro(cudnnSetStream); \
__macro(cudnnActivationForward); \ __macro(cudnnActivationForward); \
__macro(cudnnActivationBackward); \
__macro(cudnnConvolutionForward); \ __macro(cudnnConvolutionForward); \
__macro(cudnnConvolutionBackwardBias); \ __macro(cudnnConvolutionBackwardBias); \
__macro(cudnnGetConvolutionForwardWorkspaceSize); \ __macro(cudnnGetConvolutionForwardWorkspaceSize); \
......
python/paddle/fluid/tests/unittests/test_activation_op.py
浏览文件 @ 225c11a9
...@@ -26,6 +26,7 @@ class TestActivation(OpTest): ...@@ -26,6 +26,7 @@ class TestActivation(OpTest):
self.op_type = "exp" self.op_type = "exp"
self.dtype = np.float32 self.dtype = np.float32
self.init_dtype() self.init_dtype()
self.init_kernel_type()
x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype) x = np.random.uniform(0.1, 1, [11, 17]).astype(self.dtype)
out = np.exp(x) out = np.exp(x)
...@@ -44,6 +45,9 @@ class TestActivation(OpTest): ...@@ -44,6 +45,9 @@ class TestActivation(OpTest):
def init_dtype(self): def init_dtype(self):
self.dtype = np.float32 self.dtype = np.float32
def init_kernel_type(self):
pass
class TestSigmoid(TestActivation): class TestSigmoid(TestActivation):
def setUp(self): def setUp(self):
...@@ -601,6 +605,25 @@ class TestSwish(TestActivation): ...@@ -601,6 +605,25 @@ class TestSwish(TestActivation):
self.check_grad(['X'], 'Out', max_relative_error=0.008) self.check_grad(['X'], 'Out', max_relative_error=0.008)
#------------------ Test Cudnn Activation----------------------
def create_test_act_cudnn_class(parent, atol=1e-3, grad_atol=1e-3):
@unittest.skipIf(not core.is_compiled_with_cuda(),
"core is not compiled with CUDA")
class TestActCudnn(parent):
def init_kernel_type(self):
self.attrs = {"use_cudnn": True}
cls_name = "{0}_{1}".format(parent.__name__, "cudnn")
TestActCudnn.__name__ = cls_name
globals()[cls_name] = TestActCudnn
create_test_act_cudnn_class(TestRelu)
create_test_act_cudnn_class(TestRelu6)
create_test_act_cudnn_class(TestSigmoid)
create_test_act_cudnn_class(TestTanh)
#------------------ Test Fp16 ---------------------- #------------------ Test Fp16 ----------------------
def create_test_act_fp16_class(parent, def create_test_act_fp16_class(parent,
atol=1e-3, atol=1e-3,
......
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