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P
Paddle
提交 64305b3f 编写于 作者: Y yuyang18
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Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into... 

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into feature/polish_visit_data_type
上级 9f705a4b 8c7d2e29
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README.md
浏览文件 @ 64305b3f
......@@ -62,9 +62,9 @@ Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddl
## Installation
It is recommended to check out the
[Docker installation guide](http://www.paddlepaddle.org/docs/develop/documentation/en/getstarted/build_and_install/docker_install_en.html)
[Docker installation guide](http://www.paddlepaddle.org/docs/develop/documentation/fluid/en/build_and_install/docker_install_en.html)
before looking into the
[build from source guide](http://www.paddlepaddle.org/docs/develop/documentation/en/getstarted/build_and_install/build_from_source_en.html).
[build from source guide](http://www.paddlepaddle.org/docs/develop/documentation/fluid/en/build_and_install/build_from_source_en.html).
## Documentation
......
cmake/external/mkldnn.cmake
浏览文件 @ 64305b3f
......@@ -45,9 +45,9 @@ IF(${CBLAS_PROVIDER} STREQUAL "MKLML")
ELSE()
MESSAGE(FATAL_ERROR "Should enable MKLML when build MKLDNN")
ENDIF()
SET(MKLDNN_CFLAG "${CMAKE_C_FLAGS} -Wno-error=strict-overflow")
SET(MKLDNN_CXXFLAG "${CMAKE_CXX_FLAGS} -Wno-error=strict-overflow")
SET(MKLDNN_FLAG "-Wno-error=strict-overflow -Wno-error=unused-result -Wno-unused-result")
SET(MKLDNN_CFLAG "${CMAKE_C_FLAGS} ${MKLDNN_FLAG}")
SET(MKLDNN_CXXFLAG "${CMAKE_CXX_FLAGS} ${MKLDNN_FLAG}")
ExternalProject_Add(
${MKLDNN_PROJECT}
${EXTERNAL_PROJECT_LOG_ARGS}
......@@ -61,6 +61,7 @@ ExternalProject_Add(
CMAKE_ARGS -DMKLROOT=${MKLML_ROOT}
CMAKE_ARGS -DCMAKE_C_FLAGS=${MKLDNN_CFLAG}
CMAKE_ARGS -DCMAKE_CXX_FLAGS=${MKLDNN_CXXFLAG}
CMAKE_ARGS -DWITH_TEST=OFF -DWITH_EXAMPLE=OFF
CMAKE_CACHE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${MKLDNN_INSTALL_DIR}
-DMKLROOT:PATH=${MKLML_ROOT}
)
......
cmake/external/mklml.cmake
浏览文件 @ 64305b3f
......@@ -27,7 +27,7 @@ ENDIF()
INCLUDE(ExternalProject)
SET(MKLML_PROJECT "extern_mklml")
SET(MKLML_VER "mklml_lnx_2018.0.1.20171007")
SET(MKLML_VER "mklml_lnx_2018.0.3.20180406")
SET(MKLML_URL "http://paddlepaddledeps.bj.bcebos.com/${MKLML_VER}.tgz")
SET(MKLML_SOURCE_DIR "${THIRD_PARTY_PATH}/mklml")
SET(MKLML_DOWNLOAD_DIR "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}")
......
doc/fluid/design/concepts/lod_tensor.md
浏览文件 @ 64305b3f
......@@ -155,7 +155,7 @@ into offsets
3 2+3 4+5 1+9 2+10 3+12
```
so we know that the first sentence is from word 0 to word 3, and the second sentence from work 3 to word 5.
so we know that the first sentence is from word 0 to word 3, and the second sentence from word 3 to word 5.
Similarly, the lengths in the top level LoD
......
paddle/fluid/framework/CMakeLists.txt
浏览文件 @ 64305b3f
......@@ -57,7 +57,7 @@ cc_library(data_transform SRCS data_transform.cc DEPS math_function tensor
cc_library(attribute SRCS attribute.cc DEPS framework_proto boost)
cc_test(program_desc_test SRCS program_desc_test.cc DEPS proto_desc
device_context)
cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute)
cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute glog)
cc_test(op_proto_maker_test SRCS op_proto_maker_test.cc DEPS op_proto_maker)
cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute device_context)
......
paddle/fluid/framework/data_device_transform_test.cu
浏览文件 @ 64305b3f
......@@ -32,8 +32,7 @@ struct AddFunctor {
class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("input", "input1 of test op");
AddOutput("output", "output of test op");
AddAttr<bool>("use_gpu", "force to use gpu kernel").SetDefault(false);
......
paddle/fluid/framework/details/computation_op_handle.h
浏览文件 @ 64305b3f
......@@ -36,7 +36,7 @@ struct ComputationOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
virtual bool NeedWait(VarHandleBase *in_var);
bool NeedWait(VarHandleBase *in_var) override;
private:
std::unique_ptr<OperatorBase> op_;
......
paddle/fluid/framework/details/fetch_op_handle.h
浏览文件 @ 64305b3f
......@@ -42,7 +42,7 @@ struct FetchOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
virtual void WaitInputVarGenerated(const platform::Place &place);
void WaitInputVarGenerated(const platform::Place &place) override;
private:
FeedFetchList *data_;
......
paddle/fluid/framework/details/multi_devices_graph_builder.cc
浏览文件 @ 64305b3f
......@@ -37,20 +37,26 @@ MultiDevSSAGraphBuilder::MultiDevSSAGraphBuilder(
const std::string &loss_var_name,
const std::unordered_set<std::string> &params,
const std::vector<Scope *> &local_scopes,
platform::NCCLContextMap *nccl_ctxs, bool use_default_grad_scale)
platform::NCCLContextMap *nccl_ctxs, bool use_default_grad_scale,
bool balance_parameter_opt_between_cards)
: loss_var_name_(loss_var_name),
places_(places),
local_scopes_(local_scopes),
nccl_ctxs_(nccl_ctxs) {
nccl_ctxs_(nccl_ctxs),
balance_parameter_opt_between_cards_(
balance_parameter_opt_between_cards) {
#else
MultiDevSSAGraphBuilder::MultiDevSSAGraphBuilder(
const std::vector<platform::Place> &places,
const std::string &loss_var_name,
const std::unordered_set<std::string> &params,
const std::vector<Scope *> &local_scopes, bool use_default_grad_scale)
const std::vector<Scope *> &local_scopes, bool use_default_grad_scale,
bool balance_parameter_opt_between_cards)
: loss_var_name_(loss_var_name),
places_(places),
local_scopes_(local_scopes) {
local_scopes_(local_scopes),
balance_parameter_opt_between_cards_(
balance_parameter_opt_between_cards) {
#endif
for (auto &p : params) {
grad_names_.insert(GradVarName(p));
......@@ -124,6 +130,12 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
// Find "send" op first for split is in front of send.
OpDesc *send_op = GetSendOpDesc(program);
size_t cur_device_id = 0;
std::vector<std::unordered_set<std::string>> var_name_on_devices;
std::vector<std::unordered_set<std::string>> bcast_var_name_set;
var_name_on_devices.resize(places_.size());
bcast_var_name_set.resize(places_.size());
bool is_forwarding = true;
for (auto *op : program.Block(0).AllOps()) {
if (op->Type() == "send") {
......@@ -139,12 +151,27 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
}
is_forwarding = false;
} else {
int op_dev_id = GetOpDeviceID(var_name_on_devices, *op);
if (op_dev_id == -1) { // var on all device
CreateComputationalOps(&result, *op, places_.size());
} else {
CreateComputationalOp(&result, *op, op_dev_id);
for (auto &var_name : op->OutputArgumentNames()) {
var_name_on_devices[op_dev_id].emplace(var_name);
}
}
if (!is_forwarding && places_.size() > 1) {
// Currently, we assume that once gradient is generated, it can be
// broadcast, and each gradient is only broadcast once.
for (auto &og : op->OutputArgumentNames()) {
if (IsParameterGradientOnce(og, &og_has_been_broadcast)) {
if (balance_parameter_opt_between_cards_) {
CreateReduceOp(&result, og, cur_device_id);
var_name_on_devices[cur_device_id].emplace(og);
bcast_var_name_set[cur_device_id].emplace(
og.substr(0, og.size() - strlen(kGradVarSuffix)));
cur_device_id = (cur_device_id + 1) % places_.size();
} else {
if (IsSparseGradient(var_types, og)) {
CreateReduceOp(&result, og, 0);
CreateBroadcastOp(&result, og, 0);
......@@ -156,7 +183,15 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
}
}
}
}
// Insert BCast Ops
for (size_t dev_id = 0; dev_id < bcast_var_name_set.size(); ++dev_id) {
auto &to_bcast_set = bcast_var_name_set[dev_id];
for (auto &bcast_name : to_bcast_set) {
CreateBroadcastOp(&result, bcast_name, dev_id);
}
}
/*
Dependency graph has been constructed. However, there are still data
harzaeds need to be handled.
......@@ -265,6 +300,26 @@ bool MultiDevSSAGraphBuilder::IsParameterGradientOnce(
return is_pg_once;
}
int MultiDevSSAGraphBuilder::GetOpDeviceID(
const std::vector<std::unordered_set<std::string>> &var_name_on_devices,
const OpDesc &op) const {
if (!balance_parameter_opt_between_cards_) {
return -1;
}
int var_dev_id = -1;
for (auto &var_name : op.InputArgumentNames()) {
if (var_dev_id != -1) break;
for (size_t i = 0; i < var_name_on_devices.size(); ++i) {
if (var_name_on_devices[i].count(var_name)) {
var_dev_id = static_cast<int>(i);
break;
}
}
}
return var_dev_id;
}
void MultiDevSSAGraphBuilder::CreateScaleLossGradOp(SSAGraph *result) const {
for (size_t i = 0; i < places_.size(); ++i) {
// Insert ScaleCost OpHandle
......
paddle/fluid/framework/details/multi_devices_graph_builder.h
浏览文件 @ 64305b3f
......@@ -36,13 +36,15 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
const std::unordered_set<std::string> &params,
const std::vector<Scope *> &local_scopes,
platform::NCCLContextMap *nccl_ctxs,
bool use_default_grad_scale);
bool use_default_grad_scale,
bool balance_parameter_opt_between_cards);
#else
MultiDevSSAGraphBuilder(const std::vector<platform::Place> &places,
const std::string &loss_var_name,
const std::unordered_set<std::string> &params,
const std::vector<Scope *> &local_scopes,
bool use_default_grad_scale);
bool use_default_grad_scale,
bool balance_parameter_opt_between_cards);
#endif
std::unique_ptr<SSAGraph> Build(const ProgramDesc &program) const override;
......@@ -60,6 +62,7 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
#ifdef PADDLE_WITH_CUDA
platform::NCCLContextMap *nccl_ctxs_;
#endif
bool balance_parameter_opt_between_cards_;
bool use_default_grad_scale_;
bool IsScaleLossOp(const OpDesc &op) const;
......@@ -84,6 +87,10 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
const std::string &og,
std::unordered_set<std::string> *og_has_been_broadcast) const;
int GetOpDeviceID(
const std::vector<std::unordered_set<std::string>> &var_name_on_devices,
const OpDesc &op) const;
void InsertNCCLAllReduceOp(SSAGraph *result, const std::string &og) const;
void CreateBroadcastOp(SSAGraph *result, const std::string &p_name,
......
paddle/fluid/framework/details/op_registry.h
浏览文件 @ 64305b3f
......@@ -95,7 +95,10 @@ struct OpInfoFiller<T, kOpProtoAndCheckerMaker> {
void operator()(const char* op_type, OpInfo* info) const {
info->proto_ = new proto::OpProto;
info->checker_ = new OpAttrChecker();
auto maker = T(info->proto_, info->checker_);
T maker;
maker.SetProto(info->proto_);
maker.SetChecker(info->checker_);
maker.Make();
maker.Validate();
info->proto_->set_type(op_type);
PADDLE_ENFORCE(
......
paddle/fluid/framework/op_proto_maker.h
浏览文件 @ 64305b3f
......@@ -14,56 +14,57 @@ limitations under the License. */
#pragma once
#include <string>
#include "glog/logging.h"
#include "paddle/fluid/framework/attribute.h"
#include "paddle/fluid/framework/framework.pb.h"
namespace paddle {
namespace framework {
// this class not only make proto but also init attribute checkers.
class OpProtoAndCheckerMaker {
public:
using OpProto = proto::OpProto;
using OpAttrChecker = framework::OpAttrChecker;
OpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: proto_(proto), op_checker_(op_checker) {}
virtual void Make() = 0;
virtual ~OpProtoAndCheckerMaker() {
PADDLE_ENFORCE(validated_, "should call Validate after build");
CHECK(validated_) << "should call Validate after build";
}
void SetProto(proto::OpProto *proto) { proto_ = proto; }
void SetChecker(OpAttrChecker *attr_checker) { op_checker_ = attr_checker; }
void Validate();
protected:
struct VariableBuilder {
OpProto::Var* var_;
proto::OpProto::Var *var_;
VariableBuilder& AsDuplicable() {
VariableBuilder &AsDuplicable() {
var_->set_duplicable(true);
return *this;
}
VariableBuilder& AsIntermediate() {
VariableBuilder &AsIntermediate() {
var_->set_intermediate(true);
return *this;
}
VariableBuilder& AsDispensable() {
VariableBuilder &AsDispensable() {
var_->set_dispensable(true);
return *this;
}
};
VariableBuilder AddInput(const std::string& name, const std::string& comment);
VariableBuilder AddInput(const std::string &name, const std::string &comment);
VariableBuilder AddOutput(const std::string& name,
const std::string& comment);
VariableBuilder AddOutput(const std::string &name,
const std::string &comment);
template <typename T>
TypedAttrChecker<T>& AddAttr(const std::string& name,
const std::string& comment,
TypedAttrChecker<T> &AddAttr(const std::string &name,
const std::string &comment,
bool generated = false) {
auto* attr = proto_->add_attrs();
auto *attr = proto_->add_attrs();
attr->set_name(name);
attr->set_comment(comment);
attr->set_generated(generated);
......@@ -71,21 +72,14 @@ class OpProtoAndCheckerMaker {
return op_checker_->AddAttrChecker<T>(name);
}
void AddComment(const std::string& comment) { proto_->set_comment(comment); }
void AddComment(const std::string &comment) { proto_->set_comment(comment); }
private:
void CheckNoDuplicatedInOutAttrs();
OpProto* proto_;
OpAttrChecker* op_checker_;
proto::OpProto *proto_;
OpAttrChecker *op_checker_;
bool validated_{false};
};
class NOPMaker : public OpProtoAndCheckerMaker {
public:
NOPMaker(OpProto* proto, framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {}
};
} // namespace framework
} // namespace paddle
paddle/fluid/framework/op_proto_maker_test.cc
浏览文件 @ 64305b3f
......@@ -18,9 +18,7 @@ limitations under the License. */
class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
public:
TestAttrProtoMaker(paddle::framework::proto::OpProto* proto,
paddle::framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddAttr<float>("scale", "scale of test op");
AddAttr<float>("scale", "scale of test op");
}
......@@ -29,15 +27,16 @@ class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
TEST(ProtoMaker, DuplicatedAttr) {
paddle::framework::proto::OpProto op_proto;
paddle::framework::OpAttrChecker op_checker;
auto proto_maker = TestAttrProtoMaker(&op_proto, &op_checker);
TestAttrProtoMaker proto_maker;
proto_maker.SetProto(&op_proto);
proto_maker.SetChecker(&op_checker);
proto_maker.Make();
ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
}
class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
public:
TestInOutProtoMaker(paddle::framework::proto::OpProto* proto,
paddle::framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("input", "input of test op");
AddInput("input", "input of test op");
}
......@@ -46,6 +45,9 @@ class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
TEST(ProtoMaker, DuplicatedInOut) {
paddle::framework::proto::OpProto op_proto;
paddle::framework::OpAttrChecker op_checker;
auto proto_maker = TestInOutProtoMaker(&op_proto, &op_checker);
TestAttrProtoMaker proto_maker;
proto_maker.SetProto(&op_proto);
proto_maker.SetChecker(&op_checker);
proto_maker.Make();
ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
}
paddle/fluid/framework/op_registry_test.cc
浏览文件 @ 64305b3f
......@@ -33,8 +33,7 @@ class CosineOp : public OperatorBase {
class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("input", "input of cosine op");
AddOutput("output", "output of cosine op");
AddAttr<float>("scale", "scale of cosine op")
......@@ -55,8 +54,7 @@ class MyTestOp : public OperatorBase {
class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("input", "input of cosine op").AsDuplicable();
AddOutput("output", "output of cosine op").AsIntermediate();
auto my_checker = [](int i) {
......@@ -212,10 +210,7 @@ namespace framework {
class OpKernelTestMaker : public OpProtoAndCheckerMaker {
public:
OpKernelTestMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddComment("NoGradOp, same input output. no Grad");
}
void Make() { AddComment("NoGradOp, same input output. no Grad"); }
};
class OpWithKernelTest : public OperatorWithKernel {
......@@ -275,9 +270,9 @@ TEST(OperatorRegistrar, CUDA) {
static int op_test_value = 0;
using paddle::platform::DeviceContext;
using paddle::platform::CPUDeviceContext;
using paddle::platform::CUDADeviceContext;
using paddle::platform::DeviceContext;
namespace paddle {
namespace framework {
......
paddle/fluid/framework/operator_test.cc
浏览文件 @ 64305b3f
......@@ -46,8 +46,7 @@ class OpWithoutKernelTest : public OperatorBase {
class OpWithoutKernelCheckerMaker : public OpProtoAndCheckerMaker {
public:
OpWithoutKernelCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("input", "input of test op");
AddOutput("output", "output of test op");
AddAttr<float>("scale", "scale of cosine op");
......@@ -98,8 +97,7 @@ namespace framework {
class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("x", "input of test op");
AddOutput("y", "output of test op");
AddAttr<float>("scale", "scale of cosine op")
......@@ -137,9 +135,7 @@ class CPUKernelTest : public OpKernel<float> {
class OpKernelTestMultiInputsProtoAndCheckerMaker
: public OpProtoAndCheckerMaker {
public:
OpKernelTestMultiInputsProtoAndCheckerMaker(OpProto* proto,
OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("xs", "inputs of test op").AsDuplicable();
AddInput("k", "input of test op");
AddOutput("ys", "outputs of test op").AsDuplicable();
......
paddle/fluid/framework/parallel_executor.cc
浏览文件 @ 64305b3f
......@@ -58,7 +58,7 @@ ParallelExecutor::ParallelExecutor(
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
Scope *scope, const std::vector<Scope *> &local_scopes, bool allow_op_delay,
bool use_default_grad_scale)
bool use_default_grad_scale, bool balance_parameter_opt_between_cards)
: member_(new ParallelExecutorPrivate(places)) {
member_->global_scope_ = scope;
......@@ -93,11 +93,12 @@ ParallelExecutor::ParallelExecutor(
#ifdef PADDLE_WITH_CUDA
details::MultiDevSSAGraphBuilder builder(
member_->places_, loss_var_name, params, member_->local_scopes_,
member_->nccl_ctxs_.get(), use_default_grad_scale);
member_->nccl_ctxs_.get(), use_default_grad_scale,
balance_parameter_opt_between_cards);
#else
details::MultiDevSSAGraphBuilder builder(member_->places_, loss_var_name,
params, member_->local_scopes_,
use_default_grad_scale);
details::MultiDevSSAGraphBuilder builder(
member_->places_, loss_var_name, params, member_->local_scopes_,
use_default_grad_scale, balance_parameter_opt_between_cards);
#endif
auto graph = builder.Build(main_program);
......
paddle/fluid/framework/parallel_executor.h
浏览文件 @ 64305b3f
......@@ -40,7 +40,8 @@ class ParallelExecutor {
const ProgramDesc& main_program,
const std::string& loss_var_name, Scope* scope,
const std::vector<Scope*>& local_scopes,
bool allow_op_delay, bool use_default_grad_scale);
bool allow_op_delay, bool use_default_grad_scale,
bool balance_parameter_opt_between_cards);
~ParallelExecutor();
......
paddle/fluid/framework/var_type_inference_test.cc
浏览文件 @ 64305b3f
......@@ -24,8 +24,7 @@ namespace framework {
class SumOpMaker : public OpProtoAndCheckerMaker {
public:
SumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("X", "").AsDuplicable();
AddOutput("Out", "");
AddComment("");
......
paddle/fluid/operators/CMakeLists.txt
浏览文件 @ 64305b3f
......@@ -166,6 +166,8 @@ function(op_library TARGET)
# NOTE(*): activation use macro to regist the kernels, set use_op manually.
if(${TARGET} STREQUAL "activation")
file(APPEND ${pybind_file} "USE_OP(relu);\n")
elseif(${TARGET} STREQUAL "reduce")
file(APPEND ${pybind_file} "USE_OP(reduce_sum);\n")
else()
file(APPEND ${pybind_file} "USE_OP(${TARGET});\n")
endif()
......@@ -268,6 +270,11 @@ foreach(src ${READER_LIBRARY})
set(OP_LIBRARY ${src} ${OP_LIBRARY})
endforeach()
add_subdirectory(detection)
foreach(src ${DETECTION_LIBRARY})
set(OP_LIBRARY ${src} ${OP_LIBRARY})
endforeach()
set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library")
cc_test(gather_test SRCS gather_test.cc DEPS tensor)
......
paddle/fluid/operators/accuracy_op.cc
浏览文件 @ 64305b3f
......@@ -63,8 +63,7 @@ class AccuracyOp : public framework::OperatorWithKernel {
class AccuracyOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AccuracyOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
// TODO(typhoonzero): support both inference value and indices.
AddInput("Out", "The network output of topk (inferences)");
AddInput("Indices", "The the network output of topk (indices)");
......
paddle/fluid/operators/activation_op.cc
浏览文件 @ 64305b3f
......@@ -23,8 +23,7 @@ namespace operators {
class OP_NAME##OpMaker \
: public ::paddle::framework::OpProtoAndCheckerMaker { \
public: \
OP_NAME##OpMaker(OpProto *proto, OpAttrChecker *op_checker) \
: ::paddle::framework::OpProtoAndCheckerMaker(proto, op_checker) { \
void Make() override { \
AddInput("X", "Input of " #OP_NAME "operator"); \
AddOutput("Out", "Output of" #OP_NAME "operator"); \
AddAttr<bool>("use_mkldnn", \
......@@ -204,8 +203,7 @@ $$out = \frac{x}{1 + |x|}$$
class LeakyReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LeakyReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of LeakyRelu operator");
AddOutput("Out", "Output of LeakyRelu operator");
AddAttr<float>("alpha", "The small negative slope").SetDefault(0.02f);
......@@ -220,8 +218,7 @@ $out = \max(x, \alpha * x)$
class SoftShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SoftShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of Softshrink operator");
AddOutput("Out", "Output of Softshrink operator");
AddAttr<float>("lambda", "non-negative offset").SetDefault(0.5f);
......@@ -242,8 +239,7 @@ $$
class HardShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
public:
HardShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of HardShrink operator");
AddOutput("Out", "Output of HardShrink operator");
AddAttr<float>("threshold", "The value of threshold for HardShrink")
......@@ -265,8 +261,7 @@ $$
class BReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of BRelu operator");
AddOutput("Out", "Output of BRelu operator");
AddAttr<float>("t_min", "The min marginal value of BRelu")
......@@ -284,8 +279,7 @@ $out = \max(\min(x, t_{min}), t_{max})$
class SoftReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SoftReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of SoftRelu operator");
AddOutput("Out", "Output of SoftRelu operator");
AddAttr<float>("threshold", "The threshold value of SoftRelu")
......@@ -301,8 +295,7 @@ $out = \ln(1 + \exp(\max(\min(x, threshold), threshold))$
class ELUOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ELUOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of ELU operator");
AddOutput("Out", "Output of ELU operator");
AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f);
......@@ -320,8 +313,7 @@ $out = \max(0, x) + \min(0, \alpha * (e^x - 1))$
class Relu6OpMaker : public framework::OpProtoAndCheckerMaker {
public:
Relu6OpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of Relu6 operator");
AddOutput("Out", "Output of Relu6 operator");
AddAttr<float>("threshold", "The threshold value of Relu6")
......@@ -337,8 +329,7 @@ $out = \min(\max(0, x), 6)$
class PowOpMaker : public framework::OpProtoAndCheckerMaker {
public:
PowOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of Pow operator");
AddOutput("Out", "Output of Pow operator");
AddAttr<float>("factor", "The exponential factor of Pow").SetDefault(1.0f);
......@@ -353,8 +344,7 @@ $out = x^{factor}$
class STanhOpMaker : public framework::OpProtoAndCheckerMaker {
public:
STanhOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of STanh operator");
AddOutput("Out", "Output of STanh operator");
AddAttr<float>("scale_a", "The scale parameter of a for the input")
......@@ -372,8 +362,7 @@ $$out = b * \frac{e^{a * x} - e^{-a * x}}{e^{a * x} + e^{-a * x}}$$
class ThresholdedReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ThresholdedReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of ThresholdedRelu operator");
AddOutput("Out", "Output of ThresholdedRelu operator");
AddAttr<float>("threshold", "The threshold location of activation")
......@@ -394,8 +383,7 @@ $$
class HardSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
public:
HardSigmoidOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of HardSigmoid operator");
AddOutput("Out", "Output of HardSigmoid operator");
AddAttr<float>("slope", "Slope for linear approximation of sigmoid")
......@@ -420,8 +408,7 @@ It is recommended to use the defaults for this activation.
class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SwishOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of Swish operator");
AddOutput("Out", "Output of Swish operator");
AddAttr<float>("beta", "Constant beta of swish operator").SetDefault(1.0f);
......
paddle/fluid/operators/adadelta_op.cc
浏览文件 @ 64305b3f
......@@ -66,8 +66,7 @@ class AdadeltaOp : public framework::OperatorWithKernel {
class AdadeltaOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AdadeltaOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("AvgSquaredGrad", "(Tensor) Input average of squared gradient");
......
paddle/fluid/operators/adagrad_op.cc
浏览文件 @ 64305b3f
......@@ -67,8 +67,7 @@ class AdagradOp : public framework::OperatorWithKernel {
class AdagradOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AdagradOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("Moment", "(Tensor) Second moment");
......
paddle/fluid/operators/adam_op.cc
浏览文件 @ 64305b3f
......@@ -80,8 +80,7 @@ class AdamOp : public framework::OperatorWithKernel {
class AdamOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AdamOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("LearningRate", "(Tensor) Learning rate");
......
paddle/fluid/operators/adamax_op.cc
浏览文件 @ 64305b3f
......@@ -74,8 +74,7 @@ class AdamaxOp : public framework::OperatorWithKernel {
class AdamaxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AdamaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("LearningRate", "(Tensor) Learning rate");
......
paddle/fluid/operators/array_to_lod_tensor_op.cc
浏览文件 @ 64305b3f
......@@ -123,8 +123,7 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
class ArrayToLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
ArrayToLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(std::vector<LodTensor>) A vector of tensors that is going to "
"be casted to a big LoDTensor.");
......
paddle/fluid/operators/assign_op.cc
浏览文件 @ 64305b3f
......@@ -94,8 +94,7 @@ class AssignOp : public framework::OperatorBase {
class AssignOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
AssignOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor, SelectedRows or LoDTensorArray) The input variable "
"could be LoDTensor, SelectedRows or LoDTensorArray.")
......
paddle/fluid/operators/assign_value_op.cc
浏览文件 @ 64305b3f
......@@ -45,8 +45,7 @@ class AssignValueOp : public framework::OperatorWithKernel {
class AssignValueOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AssignValueOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddOutput("Out", "(Tensor) Output tensor of assign_value operator.");
AddAttr<std::vector<int>>("shape",
"(vector<int>) "
......
paddle/fluid/operators/auc_op.cc
浏览文件 @ 64305b3f
......@@ -50,8 +50,7 @@ class AucOp : public framework::OperatorWithKernel {
class AucOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AucOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Out",
"A floating point 2D tensor, values are in the range [0, 1]."
"Each row is sorted in descending order. This input should be the"
......
paddle/fluid/operators/average_accumulates_op.cc
浏览文件 @ 64305b3f
......@@ -111,8 +111,7 @@ class AverageAccumulatesOp : public framework::OperatorWithKernel {
class AverageAccumulatesOpMaker : public framework::OpProtoAndCheckerMaker {
public:
AverageAccumulatesOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("param", "(Tensor), The parameter to be accumulated.");
AddInput("in_sum_1",
"(Tensor), A tensor used to store the parameter "
......
paddle/fluid/operators/batch_norm_op.cc
浏览文件 @ 64305b3f
......@@ -126,8 +126,7 @@ class BatchNormOp : public framework::OperatorWithKernel {
class BatchNormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BatchNormOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddAttr<bool>("is_test", "").SetDefault(false);
AddAttr<float>("momentum", "").SetDefault(0.9);
AddAttr<float>("epsilon", "")
......
paddle/fluid/operators/batch_size_like.h
浏览文件 @ 64305b3f
......@@ -53,8 +53,7 @@ class BatchSizeLikeOp : public framework::OperatorWithKernel {
class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() final {
AddInput("Input",
"(Tensor) Tensor "
"whose input_dim_idx'th dimension specifies the batch_size");
......@@ -68,7 +67,11 @@ class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
AddAttr<int>("output_dim_idx",
"(int, default 0) The index of output's batch size dimension")
.SetDefault(0);
Apply();
}
protected:
virtual void Apply() = 0;
};
} // namespace operators
......
paddle/fluid/operators/beam_search_decode_op.cc
浏览文件 @ 64305b3f
......@@ -134,8 +134,7 @@ class BeamSearchDecodeOp : public framework::OperatorBase {
class BeamSearchDecodeOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
BeamSearchDecodeOpProtoMaker(OpProto* proto, OpAttrChecker* op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Ids",
"(LodTensorArray)"
"score of the candidate words in each step");
......
paddle/fluid/operators/beam_search_op.cc
浏览文件 @ 64305b3f
......@@ -197,8 +197,7 @@ std::string ItemToString(const BeamSearch::Item &item) {
class BeamSearchOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BeamSearchOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
// inputs and outputs stored in proto
AddInput("pre_ids", "ids in previous step");
AddInput("ids", "a LoDTensor of shape of [None,k]");
......
paddle/fluid/operators/bilinear_interp_op.cc
浏览文件 @ 64305b3f
......@@ -41,8 +41,7 @@ class BilinearInterpOp : public framework::OperatorWithKernel {
class BilinearInterpOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BilinearInterpOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor) The input tensor of bilinear interpolation, "
"This is a 4-D tensor with shape of (N x C x h x w)");
......
paddle/fluid/operators/bilinear_tensor_product_op.cc
浏览文件 @ 64305b3f
......@@ -65,8 +65,7 @@ class BilinearTensorProductOp : public framework::OperatorWithKernel {
class BilinearTensorProductOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BilinearTensorProductOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The first input of bilinear_tensor_product operator.");
AddInput("Y", "The second input of bilinear_tensor_product operator.");
AddInput("Weight",
......
paddle/fluid/operators/cast_op.cc
浏览文件 @ 64305b3f
......@@ -21,8 +21,7 @@ namespace operators {
class CastOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
CastOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input tensor of cast op");
AddOutput("Out", "The output tensor of cast op");
AddAttr<int>("out_dtype", "output data type");
......
paddle/fluid/operators/channel_close_op.cc
浏览文件 @ 64305b3f
......@@ -50,8 +50,7 @@ class ChannelCloseOpOpInferShape : public framework::InferShapeBase {
class ChannelCloseOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ChannelCloseOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kChannel,
"The Channel Variable that should be closed by"
" the ChannelClose Op.");
......
paddle/fluid/operators/channel_create_op.cc
浏览文件 @ 64305b3f
......@@ -91,8 +91,7 @@ class ChannelCreateOpOpInferShape : public framework::InferShapeBase {
class ChannelCreateOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ChannelCreateOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddOutput(kOutput,
"The object of a Channel type created by ChannelCreate Op.");
AddAttr<int>("capacity", "The size of the buffer of Channel.")
......
paddle/fluid/operators/channel_recv_op.cc
浏览文件 @ 64305b3f
......@@ -72,8 +72,7 @@ class ChannelRecvOp : public framework::OperatorBase {
class ChannelRecvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ChannelRecvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(Channel,
"(Channel) A variable which \"receives\" the a value sent"
"to it by a channel_send op.")
......
paddle/fluid/operators/channel_send_op.cc
浏览文件 @ 64305b3f
......@@ -57,8 +57,7 @@ class ChannelSendOp : public framework::OperatorBase {
class ChannelSendOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ChannelSendOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(Channel,
"(Channel) A variable which \"sends\" the passed in value to "
"a listening receiver.")
......
paddle/fluid/operators/chunk_eval_op.cc
浏览文件 @ 64305b3f
......@@ -66,8 +66,7 @@ class ChunkEvalOp : public framework::OperatorWithKernel {
class ChunkEvalOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ChunkEvalOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Inference",
"(Tensor, default: Tensor<int64_t>). "
"Predictions from the network.");
......
paddle/fluid/operators/clip_by_norm_op.cc
浏览文件 @ 64305b3f
......@@ -37,8 +37,7 @@ class ClipByNormOp : public framework::OperatorWithKernel {
class ClipByNormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ClipByNormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor) The input of clip_by_norm op."
"The number of dimensions must be between [1, 9].");
......
paddle/fluid/operators/clip_op.cc
浏览文件 @ 64305b3f
......@@ -38,8 +38,7 @@ class ClipOp : public framework::OperatorWithKernel {
template <typename AttrType>
class ClipOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ClipOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor)The input of clip op."
"The number of dimensions must be between [1, 9].");
......
paddle/fluid/operators/compare_op.cc
浏览文件 @ 64305b3f
......@@ -21,8 +21,7 @@ namespace operators {
template <typename OpComment>
class CompareOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
CompareOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
OpComment comment;
AddInput("X",
string::Sprintf("(LoDTensor) the left hand operand of %s operator",
......
paddle/fluid/operators/concat_op.cc
浏览文件 @ 64305b3f
......@@ -63,8 +63,7 @@ class ConcatOp : public framework::OperatorWithKernel {
class ConcatOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ConcatOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input tensors of concat operator.").AsDuplicable();
AddOutput("Out", "Output tensor of concat operator.");
AddAttr<int>("axis",
......
paddle/fluid/operators/conditional_block_op.cc
浏览文件 @ 64305b3f
......@@ -108,8 +108,7 @@ class ConditionalBlockOp : public ConditionalOp {
class ConditionalBlockOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
ConditionalBlockOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"The conditional variable of this operator. If X is empty, the "
"whole sub-block will not be executed.")
......
paddle/fluid/operators/conv_op.cc
浏览文件 @ 64305b3f
......@@ -106,8 +106,7 @@ framework::OpKernelType ConvOp::GetExpectedKernelType(
library);
}
Conv2DOpMaker::Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Conv2DOpMaker::Make() {
AddInput(
"Input",
"(Tensor) The input tensor of convolution operator. "
......@@ -200,8 +199,7 @@ $$
)DOC");
}
Conv3DOpMaker::Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Conv3DOpMaker::Make() {
AddInput(
"Input",
"(Tensor) The input tensor of convolution operator. "
......
paddle/fluid/operators/conv_op.h
浏览文件 @ 64305b3f
......@@ -60,12 +60,12 @@ inline bool IsExpand(const std::vector<int64_t>& filter_dim,
// operator implementations can reuse the code.
class Conv2DOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
void Make() override;
};
class Conv3DOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
void Make() override;
};
class ConvOp : public framework::OperatorWithKernel {
......
paddle/fluid/operators/conv_shift_op.cc
浏览文件 @ 64305b3f
......@@ -75,8 +75,7 @@ class ConvShiftGradOp : public framework::OperatorWithKernel {
class ConvShiftOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ConvShiftOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>), a 2-D tensor with shape B x M, "
"where B is the batch size and M is the data dimension.");
......
paddle/fluid/operators/conv_transpose_op.cc
浏览文件 @ 64305b3f
......@@ -84,9 +84,7 @@ framework::OpKernelType ConvTransposeOp::GetExpectedKernelType(
layout_, library_);
}
Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(OpProto* proto,
OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Conv2DTransposeOpMaker::Make() {
AddInput(
"Input",
"(Tensor) The input tensor of convolution transpose operator. "
......@@ -168,9 +166,7 @@ Example:
)DOC");
}
Conv3DTransposeOpMaker::Conv3DTransposeOpMaker(OpProto* proto,
OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Conv3DTransposeOpMaker::Make() {
AddInput("Input",
"(Tensor) The input tensor of convolution transpose operator."
"The format of input tensor is NCDHW. Where N is batch size, C is "
......
paddle/fluid/operators/conv_transpose_op.h
浏览文件 @ 64305b3f
......@@ -30,12 +30,12 @@ using DDim = framework::DDim;
// operator implementations can reuse the code.
class Conv2DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Conv2DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
void Make() override;
};
class Conv3DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Conv3DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
void Make() override;
};
class ConvTransposeOp : public framework::OperatorWithKernel {
......
paddle/fluid/operators/cos_sim_op.cc
浏览文件 @ 64305b3f
......@@ -62,8 +62,7 @@ class CosSimOp : public framework::OperatorWithKernel {
class CosSimOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CosSimOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The 1st input of cos_sim op.");
AddInput("Y", "The 2nd input of cos_sim op.");
AddOutput("Out", "The output of cos_sim op.");
......
paddle/fluid/operators/crf_decoding_op.cc
浏览文件 @ 64305b3f
......@@ -18,8 +18,7 @@ namespace paddle {
namespace operators {
class CRFDecodingOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CRFDecodingOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Emission",
"(LoDTensor, default: LoDTensor<float>). A LoDTensor with shape "
"[N x D] where N is the size of the mini-batch and D is the total "
......
paddle/fluid/operators/crop_op.cc
浏览文件 @ 64305b3f
......@@ -52,8 +52,7 @@ class CropOp : public framework::OperatorWithKernel {
class CropOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CropOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"The input of pad op. "
"The input should be a k-D tensor(k > 0 and k < 7).");
......
paddle/fluid/operators/cross_entropy_op.cc
浏览文件 @ 64305b3f
......@@ -111,8 +111,7 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
class CrossEntropyOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>), a 2-D tensor with shape [N x D],"
" where N is the batch size and D is the number of classes. "
......
paddle/fluid/operators/ctc_align_op.cc
浏览文件 @ 64305b3f
......@@ -44,8 +44,7 @@ class CTCAlignOp : public framework::OperatorWithKernel {
class CTCAlignOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CTCAlignOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Input",
"(LodTensor, default: LoDTensor<int>), Its shape is "
"[Lp, 1], where Lp is the sum of all input sequences' length.");
......
paddle/fluid/operators/cumsum_op.cc
浏览文件 @ 64305b3f
......@@ -29,8 +29,7 @@ class CumOp : public framework::OperatorWithKernel {
class CumsumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
CumsumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "Input of Cumsum operator");
AddOutput("Out", "Output of Cumsum operator");
AddAttr<int>("axis",
......
paddle/fluid/operators/decayed_adagrad_op.cc
浏览文件 @ 64305b3f
......@@ -62,8 +62,7 @@ class DecayedAdagradOp : public framework::OperatorWithKernel {
class DecayedAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
public:
DecayedAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("Moment", "(Tensor) Second moment");
......
paddle/fluid/operators/delete_var_op.cc
浏览文件 @ 64305b3f
......@@ -34,8 +34,7 @@ class DeleteVarOp : public framework::OperatorBase {
class DeleteVarOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
DeleteVarOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of delete op").AsDuplicable();
AddComment(R"DOC(
Delete Operator.
......
paddle/fluid/operators/detection/CMakeLists.txt 0 → 100644
浏览文件 @ 64305b3f
set(LOCAL_DETECTION_LIBS)
function(detection_library TARGET_NAME)
set(oneValueArgs "")
set(multiValueArgs SRCS DEPS)
set(options "")
set(common_deps op_registry)
set(pybind_flag 0)
cmake_parse_arguments(detection_library "${options}" "${oneValueArgs}"
"${multiValueArgs}" ${ARGN})
op_library(${TARGET_NAME} SRCS ${detection_library_SRCS} DEPS ${common_deps} ${detection_library_DEPS})
set(LOCAL_DETECTION_LIBS
${TARGET_NAME}
${LOCAL_DETECTION_LIBS}
PARENT_SCOPE)
endfunction()
detection_library(bipartite_match_op SRCS bipartite_match_op.cc)
detection_library(box_coder_op SRCS box_coder_op.cc box_coder_op.cu)
detection_library(iou_similarity_op SRCS iou_similarity_op.cc
iou_similarity_op.cu)
detection_library(mine_hard_examples_op SRCS mine_hard_examples_op.cc)
detection_library(multiclass_nms_op SRCS multiclass_nms_op.cc)
detection_library(prior_box_op SRCS prior_box_op.cc prior_box_op.cu)
detection_library(target_assign_op SRCS target_assign_op.cc
target_assign_op.cu)
# Export local libraries to parent
set(DETECTION_LIBRARY ${LOCAL_DETECTION_LIBS} PARENT_SCOPE)
paddle/fluid/operators/bipartite_match_op.cc → paddle/fluid/operators/detection/bipartite_match_op.cc
浏览文件 @ 64305b3f
......@@ -182,8 +182,7 @@ class BipartiteMatchKernel : public framework::OpKernel<T> {
class BipartiteMatchOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BipartiteMatchOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"DistMat",
"(LoDTensor or Tensor) this input is a 2-D LoDTensor with shape "
......
paddle/fluid/operators/box_coder_op.cc → paddle/fluid/operators/detection/box_coder_op.cc
浏览文件 @ 64305b3f
......@@ -9,7 +9,7 @@ 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/fluid/operators/box_coder_op.h"
#include "paddle/fluid/operators/detection/box_coder_op.h"
namespace paddle {
namespace operators {
......@@ -60,8 +60,7 @@ class BoxCoderOp : public framework::OperatorWithKernel {
class BoxCoderOpMaker : public framework::OpProtoAndCheckerMaker {
public:
BoxCoderOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"PriorBox",
"(Tensor, default Tensor<float>) "
......
paddle/fluid/operators/box_coder_op.cu → paddle/fluid/operators/detection/box_coder_op.cu
浏览文件 @ 64305b3f
......@@ -9,7 +9,7 @@ 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/fluid/operators/box_coder_op.h"
#include "paddle/fluid/operators/detection/box_coder_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
namespace paddle {
......
paddle/fluid/operators/iou_similarity_op.cc → paddle/fluid/operators/detection/iou_similarity_op.cc
浏览文件 @ 64305b3f
......@@ -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/fluid/operators/iou_similarity_op.h"
#include "paddle/fluid/operators/detection/iou_similarity_op.h"
namespace paddle {
namespace operators {
......@@ -42,8 +42,7 @@ class IOUSimilarityOp : public framework::OperatorWithKernel {
class IOUSimilarityOpMaker : public framework::OpProtoAndCheckerMaker {
public:
IOUSimilarityOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor, default LoDTensor<float>) "
"Box list X is a 2-D LoDTensor with shape [N, 4] holds N boxes, "
......
paddle/fluid/operators/iou_similarity_op.cu → paddle/fluid/operators/detection/iou_similarity_op.cu
浏览文件 @ 64305b3f
......@@ -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/fluid/operators/iou_similarity_op.h"
#include "paddle/fluid/operators/detection/iou_similarity_op.h"
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
......
paddle/fluid/operators/mine_hard_examples_op.cc → paddle/fluid/operators/detection/mine_hard_examples_op.cc
浏览文件 @ 64305b3f
......@@ -253,8 +253,7 @@ class MineHardExamplesOp : public framework::OperatorWithKernel {
class MineHardExamplesOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MineHardExamplesOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"ClsLoss",
"(Tensor, default Tensor<float>), The classification loss with shape "
......
paddle/fluid/operators/multiclass_nms_op.cc → paddle/fluid/operators/detection/multiclass_nms_op.cc
浏览文件 @ 64305b3f
......@@ -309,8 +309,7 @@ class MultiClassNMSKernel : public framework::OpKernel<T> {
class MultiClassNMSOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MultiClassNMSOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("BBoxes",
"(Tensor) A 3-D Tensor with shape [N, M, 4] represents the "
"predicted locations of M bounding bboxes, N is the batch size. "
......
paddle/fluid/operators/prior_box_op.cc → paddle/fluid/operators/detection/prior_box_op.cc
浏览文件 @ 64305b3f
......@@ -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/fluid/operators/prior_box_op.h"
#include "paddle/fluid/operators/detection/prior_box_op.h"
namespace paddle {
namespace operators {
......@@ -79,8 +79,7 @@ class PriorBoxOp : public framework::OperatorWithKernel {
class PriorBoxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
PriorBoxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Input",
"(Tensor, default Tensor<float>), "
"the input feature data of PriorBoxOp, The layout is NCHW.");
......
paddle/fluid/operators/prior_box_op.cu → paddle/fluid/operators/detection/prior_box_op.cu
浏览文件 @ 64305b3f
......@@ -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/fluid/operators/prior_box_op.h"
#include "paddle/fluid/operators/detection/prior_box_op.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/target_assign_op.cc → paddle/fluid/operators/detection/target_assign_op.cc
浏览文件 @ 64305b3f
......@@ -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/fluid/operators/target_assign_op.h"
#include "paddle/fluid/operators/detection/target_assign_op.h"
namespace paddle {
namespace operators {
......@@ -65,8 +65,7 @@ class TargetAssignOp : public framework::OperatorWithKernel {
class TargetAssignOpMaker : public framework::OpProtoAndCheckerMaker {
public:
TargetAssignOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor), This input is a 3D LoDTensor with shape [M, P, K]. "
"Some elements in X will be assigned to Out based on the "
......
paddle/fluid/operators/target_assign_op.cu → paddle/fluid/operators/detection/target_assign_op.cu
浏览文件 @ 64305b3f
......@@ -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/fluid/operators/target_assign_op.h"
#include "paddle/fluid/operators/detection/target_assign_op.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/detection_map_op.cc
浏览文件 @ 64305b3f
......@@ -78,8 +78,7 @@ class DetectionMAPOp : public framework::OperatorWithKernel {
class DetectionMAPOpMaker : public framework::OpProtoAndCheckerMaker {
public:
DetectionMAPOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("DetectRes",
"(LoDTensor) A 2-D LoDTensor with shape [M, 6] represents the "
"detections. Each row has 6 values: "
......
paddle/fluid/operators/dropout_op.cc
浏览文件 @ 64305b3f
......@@ -37,8 +37,7 @@ class DropoutOp : public framework::OperatorWithKernel {
class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {
public:
DropoutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of dropout op.");
AddOutput("Out", "The output of dropout op.");
AddOutput("Mask", "The random sampled dropout mask.").AsIntermediate();
......
paddle/fluid/operators/edit_distance_op.cc
浏览文件 @ 64305b3f
......@@ -49,8 +49,7 @@ class EditDistanceOp : public framework::OperatorWithKernel {
class EditDistanceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
EditDistanceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Hyps",
"(2-D LoDTensor<int64_t>, 2nd dim. equal to 1) "
"The indices for hypothesis strings.");
......
paddle/fluid/operators/elementwise_add_op.cc
浏览文件 @ 64305b3f
......@@ -14,26 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_add_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwiseAddOpMaker : public ElementwiseOpMaker {
public:
ElementwiseAddOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: ElementwiseOpMaker(proto, op_checker) {
SetComment("Add", "Out = X + Y");
AddComment(comment_);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(elementwise_add, ops::ElementwiseOp,
ops::ElementwiseAddOpMaker, ops::ElementwiseOpInferVarType,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(elementwise_add_grad, ops::ElementwiseOpGrad);
REGISTER_ELEMWISE_OP(elementwise_add, "Add", "Out = X + Y");
REGISTER_OP_CPU_KERNEL(
elementwise_add,
ops::ElementwiseAddKernel<paddle::platform::CPUDeviceContext, float>,
......
paddle/fluid/operators/elementwise_div_op.cc
浏览文件 @ 64305b3f
......@@ -14,26 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_div_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwiseDivOpMaker : public ElementwiseOpMaker {
public:
ElementwiseDivOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: ElementwiseOpMaker(proto, op_checker) {
SetComment("Div", "Out = X / Y");
AddComment(comment_);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(elementwise_div, ops::ElementwiseOp,
ops::ElementwiseDivOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(elementwise_div_grad, ops::ElementwiseOpGrad);
REGISTER_ELEMWISE_OP(elementwise_div, "Div", "Out = X / Y");
REGISTER_OP_CPU_KERNEL(
elementwise_div,
ops::ElementwiseDivKernel<paddle::platform::CPUDeviceContext, float>,
......
paddle/fluid/operators/elementwise_max_op.cc
浏览文件 @ 64305b3f
......@@ -14,25 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_max_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwiseMaxOpMaker : public ElementwiseOpMaker {
public:
ElementwiseMaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: ElementwiseOpMaker(proto, op_checker) {
SetComment("Max", "Out = max(X, Y)");
AddComment(comment_);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(elementwise_max, ops::ElementwiseOp,
ops::ElementwiseMaxOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(elementwise_max_grad, ops::ElementwiseOpGrad);
REGISTER_ELEMWISE_OP(elementwise_max, "Max", "Out = max(X, Y)");
REGISTER_OP_CPU_KERNEL(
elementwise_max,
ops::ElementwiseMaxKernel<paddle::platform::CPUDeviceContext, float>,
......
paddle/fluid/operators/elementwise_min_op.cc
浏览文件 @ 64305b3f
......@@ -14,25 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_min_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwiseMinOpMaker : public ElementwiseOpMaker {
public:
ElementwiseMinOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: ElementwiseOpMaker(proto, op_checker) {
SetComment("Max", "Out = min(X, Y)");
AddComment(comment_);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(elementwise_min, ops::ElementwiseOp,
ops::ElementwiseMinOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(elementwise_min_grad, ops::ElementwiseOpGrad);
REGISTER_ELEMWISE_OP(elementwise_min, "Min", "Out = min(X, Y)");
REGISTER_OP_CPU_KERNEL(
elementwise_min,
ops::ElementwiseMinKernel<paddle::platform::CPUDeviceContext, float>,
......
paddle/fluid/operators/elementwise_mul_op.cc
浏览文件 @ 64305b3f
......@@ -14,27 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_mul_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwiseMulOpMaker : public ElementwiseOpMaker {
public:
ElementwiseMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: ElementwiseOpMaker(proto, op_checker) {
SetComment("Mul", "Out = X \\odot\\ Y");
AddComment(comment_);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(elementwise_mul, ops::ElementwiseOp,
ops::ElementwiseMulOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(elementwise_mul_grad, ops::ElementwiseOpGrad);
REGISTER_ELEMWISE_OP(elementwise_mul, "Mul", "Out = X \\odot\\ Y");
REGISTER_OP_CPU_KERNEL(
elementwise_mul,
ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext, float>,
......
paddle/fluid/operators/elementwise_op.h
浏览文件 @ 64305b3f
......@@ -54,8 +54,7 @@ class ElementwiseOpInferVarType : public framework::VarTypeInference {
class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ElementwiseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() final {
AddInput("X", "(Tensor), The first input tensor of elementwise op.");
AddInput("Y", "(Tensor), The second input tensor of elementwise op.");
AddOutput("Out", "The output of elementwise op.");
......@@ -64,12 +63,12 @@ class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
"for broadcasting Y onto X.")
.SetDefault(-1)
.EqualGreaterThan(-1);
comment_ = R"DOC(
Limited Elementwise {name} Operator.
AddComment(string::Sprintf(R"DOC(
Limited Elementwise %s Operator.
The equation is:
$${equation}$$
$$%s$$
$X$ is a tensor of any dimension and the dimensions of tensor $Y$ must be
smaller than or equal to the dimensions of $X$.
......@@ -100,26 +99,13 @@ For example
Either of the inputs $X$ and $Y$ or none can carry the LoD (Level of Details)
information. However, the output only shares the LoD information with input $X$.
)DOC";
AddComment(comment_);
)DOC",
GetName(), GetEquation()));
}
protected:
std::string comment_;
void Replace(std::string* src, std::string from, std::string to) {
std::size_t len_from = std::strlen(from.c_str());
std::size_t len_to = std::strlen(to.c_str());
for (std::size_t pos = src->find(from); pos != std::string::npos;
pos = src->find(from, pos + len_to)) {
src->replace(pos, len_from, to);
}
}
void SetComment(std::string name, std::string equation) {
Replace(&comment_, "{name}", name);
Replace(&comment_, "{equation}", equation);
}
virtual std::string GetName() const = 0;
virtual std::string GetEquation() const = 0;
};
class ElementwiseOpGrad : public framework::OperatorWithKernel {
......@@ -152,3 +138,16 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
};
} // namespace operators
} // namespace paddle
#define REGISTER_ELEMWISE_OP(op_type, op_name, equation) \
class __ElemwiseOp##op_type##Maker__ \
: public ::paddle::operators::ElementwiseOpMaker { \
protected: \
virtual std::string GetName() const { return op_name; } \
virtual std::string GetEquation() const { return equation; } \
}; \
REGISTER_OPERATOR(op_type, ::paddle::operators::ElementwiseOp, \
__ElemwiseOp##op_type##Maker__, \
::paddle::operators::ElementwiseOpInferVarType, \
::paddle::framework::DefaultGradOpDescMaker<true>); \
REGISTER_OPERATOR(op_type##_grad, ::paddle::operators::ElementwiseOpGrad)
paddle/fluid/operators/elementwise_pow_op.cc
浏览文件 @ 64305b3f
......@@ -13,17 +13,15 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/elementwise_pow_op.h"
#include <string>
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwisePowOpMaker : public ElementwiseOpMaker {
public:
ElementwisePowOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: ElementwiseOpMaker(proto, op_checker) {
SetComment("Pow", "Out = X ^ Y");
AddComment(comment_);
}
protected:
std::string GetName() const override { return "Pow"; }
std::string GetEquation() const override { return "Out = X ^ Y"; }
};
} // namespace operators
} // namespace paddle
......
paddle/fluid/operators/elementwise_sub_op.cc
浏览文件 @ 64305b3f
......@@ -14,25 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_sub_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwiseSubOpMaker : public ElementwiseOpMaker {
public:
ElementwiseSubOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: ElementwiseOpMaker(proto, op_checker) {
SetComment("Sub", "Out = X - Y");
AddComment(comment_);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(elementwise_sub, ops::ElementwiseOp,
ops::ElementwiseSubOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(elementwise_sub_grad, ops::ElementwiseOpGrad);
REGISTER_ELEMWISE_OP(elementwise_sub, "Sub", "Out = X - Y");
REGISTER_OP_CPU_KERNEL(
elementwise_sub,
ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, float>,
......
paddle/fluid/operators/expand_op.cc
浏览文件 @ 64305b3f
......@@ -56,8 +56,7 @@ class ExpandOp : public framework::OperatorWithKernel {
class ExpandOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>). A tensor with rank in [1, 6]."
"X is the input to be expanded.");
......
paddle/fluid/operators/fc_op.cc
浏览文件 @ 64305b3f
......@@ -72,8 +72,7 @@ framework::OpKernelType FCOpGrad::GetExpectedKernelType(
layout, library);
}
FCOpMaker::FCOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void FCOpMaker::Make() {
AddInput("Input", "(Tensor) The input tensor of fully connected operator. ");
AddInput("W", "(Tensor), The second input tensor of fc op.");
AddOutput("Out", "(Tensor) The output tensor of fully connected operator. ");
......
paddle/fluid/operators/fc_op.h
浏览文件 @ 64305b3f
......@@ -45,7 +45,7 @@ class FCOpGrad : public framework::OperatorWithKernel {
class FCOpMaker : public framework::OpProtoAndCheckerMaker {
public:
FCOpMaker(OpProto* proto, OpAttrChecker* op_checker);
void Make() override;
};
} // namespace operators
......
paddle/fluid/operators/feed_op.cc
浏览文件 @ 64305b3f
......@@ -66,8 +66,7 @@ class FeedOp : public framework::OperatorBase {
class FeedOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
FeedOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of feed op");
AddOutput("Out", "The output of feed op");
AddAttr<int>("col", "(int) The column of feed");
......
paddle/fluid/operators/fetch_op.cc
浏览文件 @ 64305b3f
......@@ -66,8 +66,7 @@ class FetchOp : public framework::OperatorBase {
class FetchOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
FetchOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of fetch op");
AddOutput("Out", "The output of fetch op");
AddAttr<int>("col", "(int) The column of fetch");
......
paddle/fluid/operators/fill_constant_batch_size_like_op.cc
浏览文件 @ 64305b3f
......@@ -30,9 +30,8 @@ class FillConstantBatchSizeLikeOp : public BatchSizeLikeOp {
};
class FillConstantBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
public:
FillConstantBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: BatchSizeLikeOpMaker(proto, op_checker) {
protected:
void Apply() override {
AddAttr<int>("dtype",
"(int, default 5 (FP32)) "
"Output data type")
......
paddle/fluid/operators/fill_constant_op.cc
浏览文件 @ 64305b3f
......@@ -59,8 +59,7 @@ class FillConstantOp : public framework::OperatorBase {
class FillConstantOpMaker : public framework::OpProtoAndCheckerMaker {
public:
FillConstantOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddAttr<int>("dtype",
"(int, default 5 (FP32)) "
"Output data type")
......
paddle/fluid/operators/fill_op.cc
浏览文件 @ 64305b3f
......@@ -82,8 +82,7 @@ class FillOp : public framework::OperatorBase {
class FillOpMaker : public framework::OpProtoAndCheckerMaker {
public:
FillOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddComment(R"DOC(Fill operator
Fill an tensor with `value` and `shape`. The type of the tensor is specify by
......
paddle/fluid/operators/fill_zeros_like_op.cc
浏览文件 @ 64305b3f
......@@ -33,8 +33,7 @@ class FillZerosLikeOp : public framework::OperatorWithKernel {
class FillZerosLikeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
FillZerosLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of fill-zeros-like op.");
AddOutput("Out", "The variable will be filled up with zeros.");
AddComment(R"DOC(
......
paddle/fluid/operators/ftrl_op.cc
浏览文件 @ 64305b3f
......@@ -64,8 +64,7 @@ class FTRLOp : public framework::OperatorWithKernel {
class FTRLOpMaker : public framework::OpProtoAndCheckerMaker {
public:
FTRLOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter value that has to be updated.");
......
paddle/fluid/operators/gather_op.cc
浏览文件 @ 64305b3f
......@@ -67,8 +67,7 @@ class GatherGradOp : public framework::OperatorWithKernel {
class GatherOpMaker : public framework::OpProtoAndCheckerMaker {
public:
GatherOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The source input of gather op");
AddInput("Index", "The index input of gather op");
AddOutput("Out", "The output of gather op");
......
paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
浏览文件 @ 64305b3f
......@@ -32,9 +32,8 @@ class GaussianRandomBatchSizeLikeOp : public BatchSizeLikeOp {
};
class GaussianRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
public:
GaussianRandomBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: BatchSizeLikeOpMaker(proto, op_checker) {
protected:
void Apply() override {
AddAttr<float>("mean",
"(float, default 0.0) "
"mean of random tensor.")
......
paddle/fluid/operators/gaussian_random_op.cc
浏览文件 @ 64305b3f
......@@ -70,8 +70,7 @@ class GaussianRandomOp : public framework::OperatorWithKernel {
class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
public:
GaussianRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddOutput("Out", "Output matrix of gaussian random op");
AddAttr<std::vector<int>>("shape",
......
paddle/fluid/operators/get_places_op.cc
浏览文件 @ 64305b3f
......@@ -78,8 +78,7 @@ class GetPlacesOp : public framework::OperatorBase {
class GetPlacesOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
GetPlacesOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddOutput("Out", "vector of Place");
AddAttr<int>("device_count", "device count").SetDefault(0);
AddAttr<std::string>("device_type", "device type")
......
paddle/fluid/operators/go_op.cc
浏览文件 @ 64305b3f
......@@ -89,8 +89,7 @@ class GoOp : public framework::OperatorBase {
class GoOpMaker : public framework::OpProtoAndCheckerMaker {
public:
GoOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kX,
"A set of variables, which are required by operators inside the "
"block of Go Op.")
......
paddle/fluid/operators/gru_op.cc
浏览文件 @ 64305b3f
......@@ -71,8 +71,7 @@ class GRUOp : public framework::OperatorWithKernel {
class GRUOpMaker : public framework::OpProtoAndCheckerMaker {
public:
GRUOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Input",
"(LoDTensor) The first input is a LodTensor, which supports "
"variable-time length input sequence. The underlying tensor in "
......
paddle/fluid/operators/gru_unit_op.cc
浏览文件 @ 64305b3f
......@@ -71,8 +71,7 @@ class GRUUnitOp : public framework::OperatorWithKernel {
class GRUUnitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
GRUUnitOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Input",
"(Tensor) Matrix with shape [batch_size, frame_size * 3] for the "
"input.");
......
paddle/fluid/operators/hinge_loss_op.cc
浏览文件 @ 64305b3f
......@@ -46,8 +46,7 @@ class HingeLossOp : public framework::OperatorWithKernel {
template <typename AttrType>
class HingeLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
HingeLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Logits",
"The input value (Logits) of Hinge loss op."
"Logits is a 2-D tensor with shape [batch_size, 1].");
......
paddle/fluid/operators/huber_loss_op.cc
浏览文件 @ 64305b3f
......@@ -45,8 +45,7 @@ class HuberLossOp : public framework::OperatorWithKernel {
template <typename AttrType>
class HuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
HuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"The input value of huber loss op."
"X is a 2-D tensor with shape [batch_size, 1].");
......
paddle/fluid/operators/im2sequence_op.cc
浏览文件 @ 64305b3f
......@@ -54,8 +54,7 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
class Im2SequenceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Im2SequenceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor) The input tensor has NCHW format."
"N: batch size"
......
paddle/fluid/operators/increment_op.cc
浏览文件 @ 64305b3f
......@@ -47,8 +47,7 @@ class IncrementOp : public framework::OperatorWithKernel {
class IncrementOpMaker : public framework::OpProtoAndCheckerMaker {
public:
IncrementOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) The input tensor of increment operator");
AddOutput("Out", "(Tensor) The output tensor of increment operator.");
AddAttr<float>("step",
......
paddle/fluid/operators/is_empty_op.cc
浏览文件 @ 64305b3f
......@@ -48,8 +48,7 @@ class IsEmptyOp : public framework::OperatorBase {
class IsEmptyOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
IsEmptyOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kInput, "(Tensor) Tensor which is to be checked.");
AddOutput(kOutput, "(Tensor) a boolean Tensor that indicate empty or not.");
AddComment(R"DOC(
......
paddle/fluid/operators/l1_norm_op.cc
浏览文件 @ 64305b3f
......@@ -48,8 +48,7 @@ class L1NormGradOp : public framework::OperatorWithKernel {
class L1NormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
L1NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) The input of l1_norm op.");
AddOutput("Out", "(Scalar) The output of l1_norm op.");
AddComment(R"DOC(
......
paddle/fluid/operators/label_smooth_op.cc
浏览文件 @ 64305b3f
......@@ -47,8 +47,7 @@ class LabelSmoothOp : public framework::OperatorWithKernel {
class LabelSmoothOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LabelSmoothOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor) The input labels of LabelSmooth operator. This "
"input can be batched labels in one-hot encoding or output from "
......
paddle/fluid/operators/layer_norm_op.cc
浏览文件 @ 64305b3f
......@@ -61,8 +61,7 @@ class LayerNormOp : public framework::OperatorWithKernel {
class LayerNormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LayerNormOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(LoDTensor) The input tensor.");
AddInput("Scale",
"(Tensor, optional) Scale is a 1-dimensional tensor of size "
......
paddle/fluid/operators/linear_chain_crf_op.cc
浏览文件 @ 64305b3f
......@@ -19,8 +19,7 @@ namespace operators {
class LinearChainCRFOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LinearChainCRFOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Emission",
"(LoDTensor, default LoDTensor<float>) "
"A 2-D LoDTensor with shape [N x D], where N is the size of the "
......
paddle/fluid/operators/listen_and_serv_op.cc
浏览文件 @ 64305b3f
......@@ -343,8 +343,7 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
class ListenAndServOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ListenAndServOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("X", "(Tensor) Variables that server recv.").AsDuplicable();
AddComment(R"DOC(
ListenAndServ operator
......
paddle/fluid/operators/load_combine_op.cc
浏览文件 @ 64305b3f
......@@ -77,8 +77,7 @@ class LoadCombineOp : public framework::OperatorBase {
class LoadCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
LoadCombineOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddOutput(
"Out",
"(vector) The output LoDTensors that will be read from the input file.")
......
paddle/fluid/operators/load_op.cc
浏览文件 @ 64305b3f
......@@ -73,8 +73,7 @@ class LoadOp : public framework::OperatorBase {
class LoadOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
LoadOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddOutput("Out", "(Tensor) The tensor need to be loaded");
AddAttr<bool>(
"load_as_fp16",
......
paddle/fluid/operators/lod_array_length_op.cc
浏览文件 @ 64305b3f
......@@ -40,8 +40,7 @@ class LoDArrayLengthOp : public framework::OperatorBase {
class LoDArrayLengthProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
LoDArrayLengthProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(LoDTensorArray) The input tensor array.");
AddOutput("Out", "(Tensor) 1x1 CPU Tensor of length, int64_t");
AddComment(R"DOC(
......
paddle/fluid/operators/lod_rank_table_op.cc
浏览文件 @ 64305b3f
......@@ -38,8 +38,7 @@ class LoDRankTableOp : public framework::OperatorBase {
class LoDRankTableOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
LoDRankTableOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor) input lod tensor, must contain lod information.");
AddOutput("Out", "(LoDRankTable) The rank table of specific level.");
......
paddle/fluid/operators/lod_reset_op.cc
浏览文件 @ 64305b3f
......@@ -47,8 +47,7 @@ class LoDResetOp : public framework::OperatorWithKernel {
class LoDResetOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LoDResetOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor, LoDTensor) Input variable of LoDResetOp which "
"could be a Tensor or LoDTensor, where the data of output "
......
paddle/fluid/operators/lod_tensor_to_array_op.cc
浏览文件 @ 64305b3f
......@@ -105,8 +105,7 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
class LoDTensorToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
LoDTensorToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "");
AddInput("RankTable", "");
AddOutput("Out", "");
......
paddle/fluid/operators/log_loss_op.cc
浏览文件 @ 64305b3f
......@@ -46,8 +46,7 @@ class LogLossOp : public framework::OperatorWithKernel {
template <typename AttrType>
class LogLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LogLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Predicted",
"The input value (Predicted) of Log loss op."
"Predicted is a 2-D tensor with shape [batch_size, 1].");
......
paddle/fluid/operators/logical_op.cc
浏览文件 @ 64305b3f
......@@ -21,8 +21,7 @@ namespace operators {
template <typename OpComment>
class BinaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
BinaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
OpComment comment;
AddInput("X",
string::Sprintf("(LoDTensor) Left hand operand of %s operator",
......@@ -45,8 +44,7 @@ Each element of Out is calculated by %s
template <typename OpComment>
class UnaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
UnaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
OpComment comment;
AddInput("X", string::Sprintf("(LoDTensor) Operand of %s operator",
comment.type));
......
paddle/fluid/operators/lookup_sparse_table_op.cc
浏览文件 @ 64305b3f
......@@ -105,8 +105,7 @@ class LookupSparseTableOp : public framework::OperatorBase {
class LookupSparseTableOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LookupSparseTableOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("W",
"(SelectedRows) The input represents embedding table, "
"which is a learnable parameter.");
......
paddle/fluid/operators/lookup_table_op.cc
浏览文件 @ 64305b3f
......@@ -58,8 +58,7 @@ class LookupTableOp : public framework::OperatorWithKernel {
class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LookupTableOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("W",
"(Tensor) The input represents embedding tensors, "
"which is a learnable parameter.");
......
paddle/fluid/operators/lrn_op.cc
浏览文件 @ 64305b3f
......@@ -169,8 +169,7 @@ class LRNOp : public framework::OperatorWithKernel {
template <typename T>
class LRNOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LRNOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor) The input of LRN operator. "
"It must be a 4D tenor with NCHW format.");
......
paddle/fluid/operators/lstm_op.cc
浏览文件 @ 64305b3f
......@@ -103,8 +103,7 @@ class LSTMOp : public framework::OperatorWithKernel {
class LSTMOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LSTMOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Input",
"(LoDTensor) the first input is a LodTensor, which support "
"variable-time length input sequence. The underlying tensor in "
......
paddle/fluid/operators/lstm_unit_op.cc
浏览文件 @ 64305b3f
......@@ -48,8 +48,7 @@ class LstmUnitOp : public framework::OperatorWithKernel {
class LstmUnitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LstmUnitOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"Lstm unit only applies non-linear activations, please make sure"
"that linear tranformation has already been applied to `X`. "
......
paddle/fluid/operators/lstmp_op.cc
浏览文件 @ 64305b3f
......@@ -120,8 +120,7 @@ class LSTMPOp : public framework::OperatorWithKernel {
class LSTMPOpMaker : public framework::OpProtoAndCheckerMaker {
public:
LSTMPOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Input",
"(LoDTensor) the input for sequence data, which supports "
"variable-time length input sequence. The underlying tensor in "
......
paddle/fluid/operators/margin_rank_loss_op.cc
浏览文件 @ 64305b3f
......@@ -42,8 +42,7 @@ class MarginRankLossOp : public framework::OperatorWithKernel {
template <typename T>
class MarginRankLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MarginRankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X1",
"(2-D tensor with shape [batch_size x 1]) The score for "
"one item X1 to be ranked, from pairwise ranking model.");
......
paddle/fluid/operators/math/blas_impl.cu.h
浏览文件 @ 64305b3f
......@@ -96,10 +96,22 @@ struct CUBlas<platform::float16> {
reinterpret_cast<__half *>(C), ldc));
}
template <typename... ARGS>
static void GEMM_BATCH(ARGS... args) {
static void GEMM_BATCH(cublasHandle_t handle, cublasOperation_t transa,
cublasOperation_t transb, int m, int n, int k,
const float16 *alpha, const float16 *A, int lda,
long long int strideA, const float16 *B, // NOLINT
int ldb, long long int strideB, // NOLINT
const float16 *beta, float16 *C, int ldc,
long long int strideC, // NOLINT
int batchCount) {
#if CUDA_VERSION >= 8000
PADDLE_ENFORCE(platform::dynload::cublasHgemmStridedBatched(args...));
PADDLE_ENFORCE(platform::dynload::cublasHgemmStridedBatched(
handle, transa, transb, m, n, k,
reinterpret_cast<const __half *>(alpha),
reinterpret_cast<const __half *>(A), lda, strideA,
reinterpret_cast<const __half *>(B), ldb, strideB,
reinterpret_cast<const __half *>(beta), reinterpret_cast<__half *>(C),
ldc, strideC, batchCount));
#else
PADDLE_THROW("HgemmStridedBatched is not supported on cuda <= 7.5");
#endif
......
paddle/fluid/operators/math/blas_impl.h
浏览文件 @ 64305b3f
......@@ -172,9 +172,9 @@ void Blas<platform::CPUDeviceContext>::BatchedGEMM(
c_array.data(), &ldc, 1 /* group_count */, &batchCount);
#else
for (int k = 0; k < batchCount; ++k) {
const float *Ak = &A[k * strideA];
const float *Bk = &B[k * strideB];
float *Ck = &C[k * M * N];
auto *Ak = &A[k * strideA];
auto *Bk = &B[k * strideB];
auto *Ck = &C[k * M * N];
this->template GEMM<T>(transA, transB, M, N, K, alpha, Ak, Bk, beta, Ck);
}
#endif
......
paddle/fluid/operators/math/math_function.cu
浏览文件 @ 64305b3f
......@@ -35,7 +35,8 @@ template struct SetConstant<platform::CUDADeviceContext, bool>;
#define DEFINE_GPU_TRANS(RANK) \
template struct Transpose<platform::CUDADeviceContext, float, RANK>; \
template struct Transpose<platform::CUDADeviceContext, double, RANK>;
template struct Transpose<platform::CUDADeviceContext, double, RANK>; \
template struct Transpose<platform::CUDADeviceContext, float16, RANK>;
DEFINE_GPU_TRANS(1);
DEFINE_GPU_TRANS(2);
......
paddle/fluid/operators/matmul_op.cc
浏览文件 @ 64305b3f
......@@ -25,7 +25,7 @@ namespace operators {
* Get row matrix shape from a vector shape. If the rank of x_dim > 1, the
* original x_dim is returned.
*/
static framework::DDim RowMatrixFromVector(const framework::DDim& x_dim) {
static framework::DDim RowMatrixFromVector(const framework::DDim &x_dim) {
if (x_dim.size() > 1) {
return x_dim;
}
......@@ -36,7 +36,7 @@ static framework::DDim RowMatrixFromVector(const framework::DDim& x_dim) {
* Get column matrix shape from a vector shape. If the ran of y_dim > 1, the
* original y_dim is returned.
*/
static framework::DDim ColumnMatrixFromVector(const framework::DDim& y_dim) {
static framework::DDim ColumnMatrixFromVector(const framework::DDim &y_dim) {
if (y_dim.size() > 1) {
return y_dim;
}
......@@ -46,12 +46,12 @@ static framework::DDim ColumnMatrixFromVector(const framework::DDim& y_dim) {
template <typename DeviceContext, typename T>
class MatMulKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto& x =
void Compute(const framework::ExecutionContext &context) const override {
auto &x =
detail::Ref(context.Input<framework::Tensor>("X"), "Cannot find X");
auto& y =
auto &y =
detail::Ref(context.Input<framework::Tensor>("Y"), "Cannot find Y");
auto* out = context.Output<framework::Tensor>("Out");
auto *out = context.Output<framework::Tensor>("Out");
out->mutable_data<T>(context.GetPlace());
auto blas = math::GetBlas<DeviceContext, T>(context);
......@@ -65,7 +65,7 @@ class MatMulKernel : public framework::OpKernel<T> {
// Reshape a rank-3 tensor from P x M x N to (P * M) x N.
// Identity op if the tensor is not of rank 3.
static framework::Tensor FoldInitDims(const framework::Tensor& input) {
static framework::Tensor FoldInitDims(const framework::Tensor &input) {
auto output = input;
auto in_dims = input.dims();
if (in_dims.size() == 3) {
......@@ -78,8 +78,8 @@ static framework::Tensor FoldInitDims(const framework::Tensor& input) {
// (Warning: This requires transposing data and writes into new memory.)
// Identity op if the tensor is not of rank 3.
template <typename DeviceContext, typename T>
static framework::Tensor FoldHeadAndLastDims(const DeviceContext& context,
const framework::Tensor& input) {
static framework::Tensor FoldHeadAndLastDims(const DeviceContext &context,
const framework::Tensor &input) {
auto in_dims = input.dims();
if (in_dims.size() != 3) {
return input;
......@@ -102,7 +102,7 @@ static framework::Tensor FoldHeadAndLastDims(const DeviceContext& context,
* If transposed, `H,W` will be swapped.
*/
static void ReshapeTensorIntoMatrixSequence(
framework::Tensor* x, const math::MatDescriptor& descriptor) {
framework::Tensor *x, const math::MatDescriptor &descriptor) {
int64_t h, w;
h = descriptor.height_;
w = descriptor.width_;
......@@ -130,9 +130,9 @@ static void ReshapeTensorIntoMatrixSequence(
* If any of `X` and `Y` has batch size BatchSize, the out will have the
* BatchSize.
*/
static void ReshapeXYOutIntoMatrixSequence(framework::Tensor* x,
framework::Tensor* y,
framework::Tensor* out, bool trans_x,
static void ReshapeXYOutIntoMatrixSequence(framework::Tensor *x,
framework::Tensor *y,
framework::Tensor *out, bool trans_x,
bool trans_y) {
auto x_dim = RowMatrixFromVector(x->dims());
auto y_dim = ColumnMatrixFromVector(y->dims());
......@@ -177,10 +177,10 @@ static void ReshapeXYOutIntoMatrixSequence(framework::Tensor* x,
template <typename DeviceContext, typename T>
class MatMulGradKernel : public framework::OpKernel<T> {
public:
void MatMul(const framework::ExecutionContext& context,
const framework::Tensor& a, bool trans_a,
const framework::Tensor& b, bool trans_b,
framework::Tensor* out) const {
void MatMul(const framework::ExecutionContext &context,
const framework::Tensor &a, bool trans_a,
const framework::Tensor &b, bool trans_b,
framework::Tensor *out) const {
out->mutable_data<T>(context.GetPlace());
auto blas = math::GetBlas<DeviceContext, T>(context);
auto mat_dim_a = math::CreateMatrixDescriptor(a.dims(), 0, trans_a);
......@@ -188,18 +188,18 @@ class MatMulGradKernel : public framework::OpKernel<T> {
blas.MatMul(a, mat_dim_a, b, mat_dim_b, T(1), out, T(0));
}
void CalcInputGrad(const framework::ExecutionContext& context,
const framework::Tensor& a, bool trans_a,
bool is_fold_init_dims_a, const framework::Tensor& b,
void CalcInputGrad(const framework::ExecutionContext &context,
const framework::Tensor &a, bool trans_a,
bool is_fold_init_dims_a, const framework::Tensor &b,
bool trans_b, bool is_fold_init_dims_b,
framework::Tensor* out) const {
framework::Tensor *out) const {
if (out == nullptr) return;
bool need_combine = (a.dims().size() == 3 || b.dims().size() == 3) &&
out->dims().size() == 2;
if (!need_combine) {
MatMul(context, a, trans_a, b, trans_b, out);
} else {
auto& ctx = context.template device_context<DeviceContext>();
auto &ctx = context.template device_context<DeviceContext>();
MatMul(context, is_fold_init_dims_a
? FoldInitDims(a)
: FoldHeadAndLastDims<DeviceContext, T>(ctx, a),
......@@ -210,13 +210,13 @@ class MatMulGradKernel : public framework::OpKernel<T> {
}
}
void Compute(const framework::ExecutionContext& context) const override {
void Compute(const framework::ExecutionContext &context) const override {
auto x = *context.Input<framework::Tensor>("X");
auto y = *context.Input<framework::Tensor>("Y");
auto dout =
*context.Input<framework::Tensor>(framework::GradVarName("Out"));
auto* dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
auto* dy = context.Output<framework::Tensor>(framework::GradVarName("Y"));
auto *dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
auto *dy = context.Output<framework::Tensor>(framework::GradVarName("Y"));
bool transpose_x = context.Attr<bool>("transpose_X");
bool transpose_y = context.Attr<bool>("transpose_Y");
......@@ -269,7 +269,7 @@ class MatMulOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
protected:
void InferShape(framework::InferShapeContext* context) const override {
void InferShape(framework::InferShapeContext *context) const override {
PADDLE_ENFORCE(context->HasInput("X"),
"Input(X) of MatMulOp should not be null.");
PADDLE_ENFORCE(context->HasInput("Y"),
......@@ -322,8 +322,7 @@ class MatMulOp : public framework::OperatorWithKernel {
class MatMulOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MatMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The first input of MatMul op");
AddInput("Y", "The second input of MatMul op");
AddOutput("Out", "The output of MatMul op");
......@@ -376,7 +375,7 @@ class MatMulOpGrad : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
protected:
void InferShape(framework::InferShapeContext* context) const override {
void InferShape(framework::InferShapeContext *context) const override {
PADDLE_ENFORCE(context->HasInput("X"), "Input(X) should not be null");
PADDLE_ENFORCE(context->HasInput("Y"), "Input(Y) should not be null");
PADDLE_ENFORCE(context->HasInput(framework::GradVarName("Out")),
......@@ -402,7 +401,7 @@ class MatMulOpGradMaker : public framework::SingleGradOpDescMaker {
protected:
std::unique_ptr<framework::OpDesc> Apply() const override {
auto* retv = new framework::OpDesc();
auto *retv = new framework::OpDesc();
retv->SetType("matmul_grad");
retv->SetInput("X", Input("X"));
retv->SetInput("Y", Input("Y"));
......@@ -421,15 +420,27 @@ REGISTER_OPERATOR(matmul, ops::MatMulOp, ops::MatMulOpMaker,
ops::MatMulOpGradMaker);
REGISTER_OPERATOR(matmul_grad, ops::MatMulOpGrad);
REGISTER_OP_CPU_KERNEL(
matmul, ops::MatMulKernel<paddle::platform::CPUDeviceContext, float>);
matmul, ops::MatMulKernel<paddle::platform::CPUDeviceContext, float>,
ops::MatMulKernel<paddle::platform::CPUDeviceContext, double>,
ops::MatMulKernel<paddle::platform::CPUDeviceContext,
paddle::platform::float16>);
REGISTER_OP_CPU_KERNEL(
matmul_grad,
ops::MatMulGradKernel<paddle::platform::CPUDeviceContext, float>);
ops::MatMulGradKernel<paddle::platform::CPUDeviceContext, float>,
ops::MatMulGradKernel<paddle::platform::CPUDeviceContext, double>,
ops::MatMulGradKernel<paddle::platform::CPUDeviceContext,
paddle::platform::float16>);
#ifdef PADDLE_WITH_CUDA
REGISTER_OP_CUDA_KERNEL(
matmul, ops::MatMulKernel<paddle::platform::CUDADeviceContext, float>);
matmul, ops::MatMulKernel<paddle::platform::CUDADeviceContext, float>,
ops::MatMulKernel<paddle::platform::CUDADeviceContext, double>,
ops::MatMulKernel<paddle::platform::CUDADeviceContext,
paddle::platform::float16>);
REGISTER_OP_CUDA_KERNEL(
matmul_grad,
ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, float>);
ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, float>,
ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, double>,
ops::MatMulGradKernel<paddle::platform::CUDADeviceContext,
paddle::platform::float16>);
#endif
paddle/fluid/operators/max_sequence_len_op.cc
浏览文件 @ 64305b3f
......@@ -41,8 +41,7 @@ class MaxSeqenceLenOp : public framework::OperatorBase {
class MaxSeqenceLenOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
MaxSeqenceLenOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("RankTable", "The lod_rank_table.");
AddOutput("Out", "The max sequence length.");
AddComment(
......
paddle/fluid/operators/maxout_op.cc
浏览文件 @ 64305b3f
......@@ -22,8 +22,7 @@ using framework::Tensor;
class MaxOutOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MaxOutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of maxout operator. "
......
paddle/fluid/operators/mean_op.cc
浏览文件 @ 64305b3f
......@@ -32,8 +32,7 @@ class MeanOp : public framework::OperatorWithKernel {
class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MeanOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of mean op");
AddOutput("Out", "The output of mean op");
AddComment(R"DOC(
......
paddle/fluid/operators/merge_lod_tensor_op.cc
浏览文件 @ 64305b3f
......@@ -121,8 +121,7 @@ class MergeLoDTensorOp : public framework::OperatorBase {
class MergeLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
MergeLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"The input LoDTensor, contains complete lod information to "
"construct the output");
......
paddle/fluid/operators/minus_op.cc
浏览文件 @ 64305b3f
......@@ -48,8 +48,7 @@ class MinusOp : public framework::OperatorWithKernel {
class MinusOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MinusOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The left tensor of minus operator.");
AddInput("Y", "The right tensor of minus operator.");
AddOutput("Out", "The output tensor of minus operator.");
......
paddle/fluid/operators/modified_huber_loss_op.cc
浏览文件 @ 64305b3f
......@@ -39,8 +39,7 @@ class ModifiedHuberLossOp : public framework::OperatorWithKernel {
class ModifiedHuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ModifiedHuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"The input tensor of modified huber loss op. "
"X is 2-D tensor with shape [batch_size, 1].");
......
paddle/fluid/operators/momentum_op.cc
浏览文件 @ 64305b3f
......@@ -62,8 +62,7 @@ class MomentumOp : public framework::OperatorWithKernel {
class MomentumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MomentumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter that has to be updated");
......
paddle/fluid/operators/mul_op.cc
浏览文件 @ 64305b3f
......@@ -96,8 +96,7 @@ class MulOp : public framework::OperatorWithKernel {
class MulOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor), The first input tensor of mul op.");
AddInput("Y", "(Tensor), The second input tensor of mul op.");
AddOutput("Out", "(Tensor), The output tensor of mul op.");
......
paddle/fluid/operators/multiplex_op.cc
浏览文件 @ 64305b3f
......@@ -61,8 +61,7 @@ class MultiplexOp : public framework::OperatorWithKernel {
class MultiplexOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MultiplexOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Ids", "The index tensor of multiplex operator.");
AddInput("X", "The candidate tensors of multiplex operator.")
.AsDuplicable();
......
paddle/fluid/operators/nccl_op.cc
浏览文件 @ 64305b3f
......@@ -76,8 +76,7 @@ class NCCLInitOpShapeInference : public framework::InferShapeBase {
class NCCLInitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
NCCLInitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kParallelScopes, "The working place of parallel do.");
AddOutput("Communicator",
"Create Communicator for communicating between gpus");
......@@ -118,8 +117,7 @@ class NCCLAllReduceOp : public framework::OperatorWithKernel {
// AllReduceOp
class NCCLAllReduceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
NCCLAllReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of AllReduce op");
AddInput("Communicator", "Communicator for communicating between gpus");
AddOutput("Out", "The output of AllReduce op");
......@@ -165,8 +163,7 @@ class NCCLReduceOp : public framework::OperatorWithKernel {
// ReduceOp
class NCCLReduceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
NCCLReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of Reduce op");
AddInput("Communicator", "Communicator for communicating between gpus");
AddOutput("Out", "The output of Reduce op");
......@@ -214,8 +211,7 @@ class NCCLBcastOp : public framework::OperatorWithKernel {
// BcastOp
class NCCLBcastOpMaker : public framework::OpProtoAndCheckerMaker {
public:
NCCLBcastOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input of BcastSend op");
AddInput("Communicator", "Communicator for communicating between gpus");
AddOutput("Out", "The output of Bcast");
......
paddle/fluid/operators/nce_op.cc
浏览文件 @ 64305b3f
......@@ -75,8 +75,7 @@ class NCEOp : public framework::OperatorWithKernel {
class NCEOpMaker : public framework::OpProtoAndCheckerMaker {
public:
NCEOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Input", "(Tensor) A tensor of shape [batch_size, dim].");
AddInput(
"Label",
......
paddle/fluid/operators/norm_op.cc
浏览文件 @ 64305b3f
......@@ -19,8 +19,7 @@ namespace operators {
template <typename AttrType>
class NormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of norm operator. "
......
paddle/fluid/operators/one_hot_op.cc
浏览文件 @ 64305b3f
......@@ -46,8 +46,7 @@ class OneHotOp : public framework::OperatorWithKernel {
class OneHotOpMaker : public framework::OpProtoAndCheckerMaker {
public:
OneHotOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor, LoDTensor<int>) Input variable with rank at least 2. "
"The last dimension of X should be 1. Each value of X is an index "
......
paddle/fluid/operators/pad_op.cc
浏览文件 @ 64305b3f
......@@ -48,8 +48,7 @@ class PadOp : public framework::OperatorWithKernel {
class PadOpMaker : public framework::OpProtoAndCheckerMaker {
public:
PadOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"The input of pad op. "
"The input should be a k-D tensor(k > 0 and k < 7)");
......
paddle/fluid/operators/parallel_do_op.cc
浏览文件 @ 64305b3f
......@@ -196,8 +196,7 @@ class ParallelDoOp : public framework::OperatorBase {
class ParallelDoOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
ParallelDoOpProtoMaker(OpProto *proto, framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kInputs, "").AsDuplicable();
AddInput(kParameters, "").AsDuplicable();
AddInput(kPlaces, "");
......
paddle/fluid/operators/pool_op.cc
浏览文件 @ 64305b3f
......@@ -135,8 +135,7 @@ framework::OpKernelType PoolOpGrad::GetExpectedKernelType(
library_);
}
Pool2dOpMaker::Pool2dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Pool2dOpMaker::Make() {
AddInput(
"X",
"(Tensor) The input tensor of pooling operator. "
......@@ -229,8 +228,7 @@ Example:
)DOC");
}
Pool3dOpMaker::Pool3dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Pool3dOpMaker::Make() {
AddInput("X",
"(Tensor) The input tensor of pooling operator. "
"The format of input tensor is NCDHW, where N is batch size, C is "
......
paddle/fluid/operators/pool_op.h
浏览文件 @ 64305b3f
......@@ -50,12 +50,12 @@ class PoolOpGrad : public framework::OperatorWithKernel {
class Pool2dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Pool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
void Make() override;
};
class Pool3dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Pool3dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
void Make() override;
};
template <typename DeviceContext, typename T>
......
paddle/fluid/operators/pool_with_index_op.cc
浏览文件 @ 64305b3f
......@@ -100,8 +100,7 @@ class MaxPoolWithIndexOpGrad : public framework::OperatorWithKernel {
class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MaxPool2dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of pooling operator. "
......@@ -177,8 +176,7 @@ Example:
class MaxPool3dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MaxPool3dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor) The input tensor of pooling operator. "
"The format of input tensor is NCDHW, where N is batch size, C is "
......
paddle/fluid/operators/positive_negative_pair_op.cc
浏览文件 @ 64305b3f
......@@ -95,8 +95,7 @@ class PositiveNegativePairOp : public framework::OperatorWithKernel {
class PositiveNegativePairOpMaker : public framework::OpProtoAndCheckerMaker {
public:
PositiveNegativePairOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Score",
"(Tensor, float) Model Score on an item (with "
"respect to QueryID). It's a 2-D tensor with shape [batch_size, "
......
paddle/fluid/operators/precision_recall_op.cc
浏览文件 @ 64305b3f
......@@ -90,8 +90,7 @@ class PrecisionRecallOp : public framework::OperatorWithKernel {
class PrecisionRecallOpMaker : public framework::OpProtoAndCheckerMaker {
public:
PrecisionRecallOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("MaxProbs",
"(Tensor, default Tensor<float>) A 2-D tensor with shape N x 1, "
"where N is the batch size. Each row contains the max probability "
......
paddle/fluid/operators/prefetch_op.cc
浏览文件 @ 64305b3f
......@@ -64,8 +64,7 @@ class PrefetchOp : public framework::OperatorBase {
class PrefetchOpMaker : public framework::OpProtoAndCheckerMaker {
public:
PrefetchOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("X", "(LoDTensor) Input Id variables to be sent").AsDuplicable();
AddOutput("RPCClient",
"(RPCClient) The RPC client object which will be"
......
paddle/fluid/operators/prelu_op.cc
浏览文件 @ 64305b3f
......@@ -38,8 +38,7 @@ class PReluOp : public framework::OperatorWithKernel {
class PReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
PReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input tensor of prelu operator.");
AddInput("Alpha", "The alpha weight of prelu operator.");
AddOutput("Out", "The output tensor of prelu operator.");
......
paddle/fluid/operators/print_op.cc
浏览文件 @ 64305b3f
......@@ -209,8 +209,7 @@ class TensorPrintOp : public framework::OperatorBase {
class PrintOpProtoAndCheckMaker : public framework::OpProtoAndCheckerMaker {
public:
PrintOpProtoAndCheckMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("In", "Input tensor to be displayed.");
AddAttr<int>("first_n", "Only log `first_n` number of times.");
AddAttr<std::string>("message", "A string message to print as a prefix.");
......
paddle/fluid/operators/proximal_adagrad_op.cc
浏览文件 @ 64305b3f
......@@ -66,8 +66,7 @@ class ProximalAdagradOp : public framework::OperatorWithKernel {
class ProximalAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ProximalAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter that has to be updated.");
......
paddle/fluid/operators/proximal_gd_op.cc
浏览文件 @ 64305b3f
......@@ -54,8 +54,7 @@ class ProximalGDOp : public framework::OperatorWithKernel {
class ProximalGDOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ProximalGDOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter value that has to be updated.");
......
paddle/fluid/operators/rank_loss_op.cc
浏览文件 @ 64305b3f
......@@ -46,8 +46,7 @@ class RankLossOp : public framework::OperatorWithKernel {
class RankLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
RankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Label",
"(2-D Tensor with shape [batch_size x 1]) "
"The label indicating A ranked higher than B or not.");
......
paddle/fluid/operators/read_op.cc
浏览文件 @ 64305b3f
......@@ -79,8 +79,7 @@ class ReadOp : public framework::OperatorBase {
class ReadOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ReadOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
void Make() override {
AddInput("Reader", "(ReaderHolder) The executed reader.");
AddOutput("Out", "(LoDTensor) The output data.").AsDuplicable();
AddComment(R"DOC(
......
paddle/fluid/operators/reader/create_batch_reader_op.cc
浏览文件 @ 64305b3f
......@@ -52,9 +52,8 @@ class CreateBatchReaderOp : public framework::OperatorBase {
};
class CreateBatchReaderOpMaker : public DecoratedReaderMakerBase {
public:
CreateBatchReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: DecoratedReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddAttr<int>("batch_size",
"How many instances the batch reader yields each time.")
.GreaterThan(0);
......
paddle/fluid/operators/reader/create_double_buffer_reader_op.cc
浏览文件 @ 64305b3f
......@@ -113,9 +113,8 @@ class CreateDoubleBufferReaderOp : public framework::OperatorBase {
};
class CreateDoubleBufferReaderOpMaker : public DecoratedReaderMakerBase {
public:
CreateDoubleBufferReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: DecoratedReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddComment(R"DOC(
CreateDoubleBufferReader Operator
......
paddle/fluid/operators/reader/create_multi_pass_reader_op.cc
浏览文件 @ 64305b3f
......@@ -65,9 +65,8 @@ class CreateMultiPassReaderOp : public framework::OperatorBase {
};
class CreateMultiPassReaderOpMaker : public DecoratedReaderMakerBase {
public:
CreateMultiPassReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: DecoratedReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddAttr<int>("pass_num", "The number of pass to run.").GreaterThan(0);
AddComment(R"DOC(
CreateMultiPassReader Operator
......
paddle/fluid/operators/reader/create_random_data_generator_op.cc
浏览文件 @ 64305b3f
......@@ -84,9 +84,8 @@ class CreateRandomDataGeneratorOp : public framework::OperatorBase {
};
class CreateRandomDataGeneratorOpMaker : public FileReaderMakerBase {
public:
CreateRandomDataGeneratorOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: FileReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddAttr<float>("min", "The lower bound of reader's uniform distribution.");
AddAttr<float>("max", "The upper bound of reader's uniform distribution.");
AddComment(R"DOC(
......
paddle/fluid/operators/reader/create_recordio_file_reader_op.cc
浏览文件 @ 64305b3f
......@@ -76,9 +76,8 @@ class CreateRecordIOReaderOp : public framework::OperatorBase {
};
class CreateRecordIOReaderOpMaker : public FileReaderMakerBase {
public:
CreateRecordIOReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: FileReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddAttr<std::string>("filename", "The filename of record io reader");
AddComment(R"DOC(
CreateRecordIOReader Operator
......
paddle/fluid/operators/reader/create_shuffle_reader_op.cc
浏览文件 @ 64305b3f
......@@ -92,9 +92,8 @@ class CreateShuffleReaderOp : public framework::OperatorBase {
};
class CreateShuffleReaderOpMaker : public DecoratedReaderMakerBase {
public:
CreateShuffleReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: DecoratedReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddAttr<int>("buffer_size", "The shuffle buffer size.").GreaterThan(0);
AddComment(R"DOC(
CreateShuffleReader Operator
......
paddle/fluid/operators/reader/create_threaded_reader_op.cc
浏览文件 @ 64305b3f
......@@ -53,9 +53,8 @@ class CreateThreadedReaderOp : public framework::OperatorBase {
};
class CreateThreadedReaderOpMaker : public DecoratedReaderMakerBase {
public:
CreateThreadedReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: DecoratedReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddComment(R"DOC(
CreateThreadedReader Operator
......
paddle/fluid/operators/reader/open_files_op.cc
浏览文件 @ 64305b3f
......@@ -185,9 +185,8 @@ class OpenFilesOp : public framework::OperatorBase {
};
class OpenFilesOpMaker : public FileReaderMakerBase {
public:
OpenFilesOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
: FileReaderMakerBase(op_proto, op_checker) {
protected:
void Apply() override {
AddAttr<std::vector<std::string>>("file_names", "Files to be read.");
AddAttr<int>("thread_num", "The maximal concurrent prefetch thread number.")
.GreaterThan(0);
......
paddle/fluid/operators/reader/reader_op_registry.cc
浏览文件 @ 64305b3f
......@@ -53,10 +53,7 @@ std::unique_ptr<framework::ReaderBase> CreateReaderByFileName(
return std::unique_ptr<framework::ReaderBase>(reader);
}
FileReaderMakerBase::FileReaderMakerBase(
framework::OpProtoAndCheckerMaker::OpProto* op_proto,
framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
void FileReaderMakerBase::Make() {
AddOutput("Out", "(ReaderHolder) The created random reader.").AsDuplicable();
AddAttr<std::vector<int>>("shape_concat", "The concat of all data's shapes.");
AddAttr<std::vector<int>>(
......@@ -68,6 +65,7 @@ FileReaderMakerBase::FileReaderMakerBase(
"It means the reader will generate two data each time,"
"whose shapes are [2,3,4] and [5,6] respectively.");
AddAttr<std::vector<int>>("lod_levels", "The LoD levels of each data.");
Apply();
}
void FileReaderInferShape::operator()(framework::InferShapeContext* ctx) const {
......@@ -127,13 +125,11 @@ void DecoratedReaderInferVarType::operator()(
out_reader->SetDataTypes(in_reader->GetDataTypes());
}
DecoratedReaderMakerBase::DecoratedReaderMakerBase(
framework::OpProtoAndCheckerMaker::OpProto* op_proto,
framework::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(op_proto, op_checker) {
void DecoratedReaderMakerBase::Make() {
AddInput("UnderlyingReader",
"(ReaderHolder) The underlying reader for creating a batch reader.");
AddOutput("Out", "(ReaderHolder) The created batch reader.");
Apply();
}
} // namespace reader
......
paddle/fluid/operators/reader/reader_op_registry.h
浏览文件 @ 64305b3f
......@@ -47,7 +47,10 @@ extern std::vector<framework::DDim> RestoreShapes(
class FileReaderMakerBase : public framework::OpProtoAndCheckerMaker {
public:
FileReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
void Make() final;
protected:
virtual void Apply() = 0;
};
class FileReaderInferShape : public framework::InferShapeBase {
......@@ -76,7 +79,10 @@ class DecoratedReaderInferVarType : public framework::VarTypeInference {
class DecoratedReaderMakerBase : public framework::OpProtoAndCheckerMaker {
public:
DecoratedReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
void Make() final;
protected:
virtual void Apply() = 0;
};
} // namespace reader
......
paddle/fluid/operators/recurrent_op.cc
浏览文件 @ 64305b3f
......@@ -508,8 +508,7 @@ class RecurrentGradOp : public RecurrentBase {
class RecurrentOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
RecurrentOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kInputs, "rnn inputs").AsDuplicable();
AddInput(kInitialStates, "rnn initial states").AsDuplicable();
AddInput(kParameters,
......
paddle/fluid/operators/recv_op.cc
浏览文件 @ 64305b3f
......@@ -53,8 +53,7 @@ class RecvOp : public framework::OperatorBase {
class RecvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
RecvOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddOutput("Out", "(Tensor) Variables to get from server.").AsDuplicable();
AddComment(R"DOC(
Recv operator
......
paddle/fluid/operators/reduce_op.cc
浏览文件 @ 64305b3f
......@@ -90,8 +90,7 @@ class ReduceGradOp : public framework::OperatorWithKernel {
class ReduceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() final {
AddInput("X",
"(Tensor) The input tensor. Tensors with rank at most 6 are "
"supported.");
......@@ -111,78 +110,20 @@ class ReduceOpMaker : public framework::OpProtoAndCheckerMaker {
"(bool, default false) "
"If true, output a scalar reduced along all dimensions.")
.SetDefault(false);
comment_ = R"DOC(
{ReduceOp} Operator.
AddComment(string::Sprintf(R"DOC(
%s Operator.
This operator computes the {reduce} of input tensor along the given dimension.
This operator computes the %s of input tensor along the given dimension.
The result tensor has 1 fewer dimension than the input unless keep_dim is true.
If reduce_all is true, just reduce along all dimensions and output a scalar.
)DOC";
AddComment(comment_);
)DOC",
GetOpType(), GetName()));
}
protected:
std::string comment_;
void Replace(std::string *src, std::string from, std::string to) {
std::size_t len_from = std::strlen(from.c_str());
std::size_t len_to = std::strlen(to.c_str());
for (std::size_t pos = src->find(from); pos != std::string::npos;
pos = src->find(from, pos + len_to)) {
src->replace(pos, len_from, to);
}
}
void SetComment(std::string name, std::string op) {
Replace(&comment_, "{ReduceOp}", name);
Replace(&comment_, "{reduce}", op);
}
};
class ReduceSumOpMaker : public ReduceOpMaker {
public:
ReduceSumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: ReduceOpMaker(proto, op_checker) {
SetComment("ReduceSum", "sum");
AddComment(comment_);
}
};
class ReduceMeanOpMaker : public ReduceOpMaker {
public:
ReduceMeanOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: ReduceOpMaker(proto, op_checker) {
SetComment("ReduceMean", "mean");
AddComment(comment_);
}
};
class ReduceMaxOpMaker : public ReduceOpMaker {
public:
ReduceMaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: ReduceOpMaker(proto, op_checker) {
SetComment("ReduceMax", "max");
AddComment(comment_);
}
};
class ReduceMinOpMaker : public ReduceOpMaker {
public:
ReduceMinOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: ReduceOpMaker(proto, op_checker) {
SetComment("ReduceMin", "min");
AddComment(comment_);
}
};
class ReduceProdOpMaker : public ReduceOpMaker {
public:
ReduceProdOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: ReduceOpMaker(proto, op_checker) {
SetComment("ReduceProd", "production");
AddComment(comment_);
}
virtual std::string GetName() const = 0;
virtual std::string GetOpType() const = 0;
};
} // namespace operators
......@@ -190,25 +131,21 @@ class ReduceProdOpMaker : public ReduceOpMaker {
namespace ops = paddle::operators;
REGISTER_OPERATOR(reduce_sum, ops::ReduceOp, ops::ReduceSumOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(reduce_sum_grad, ops::ReduceGradOp);
REGISTER_OPERATOR(reduce_mean, ops::ReduceOp, ops::ReduceMeanOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(reduce_mean_grad, ops::ReduceGradOp);
REGISTER_OPERATOR(reduce_max, ops::ReduceOp, ops::ReduceMaxOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(reduce_max_grad, ops::ReduceGradOp);
REGISTER_OPERATOR(reduce_min, ops::ReduceOp, ops::ReduceMinOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(reduce_min_grad, ops::ReduceGradOp);
REGISTER_OPERATOR(reduce_prod, ops::ReduceOp, ops::ReduceProdOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(reduce_prod_grad, ops::ReduceGradOp);
#define REGISTER_REDUCE_OP(op_name) \
class __##op_name##Maker__ : public ops::ReduceOpMaker { \
protected: \
virtual std::string GetName() const { return #op_name; } \
virtual std::string GetOpType() const { return "Reduce " #op_name; } \
}; \
REGISTER_OPERATOR(reduce_##op_name, ops::ReduceOp, __##op_name##Maker__, \
paddle::framework::DefaultGradOpDescMaker<true>); \
REGISTER_OPERATOR(reduce_##op_name##_grad, ops::ReduceGradOp)
REGISTER_REDUCE_OP(sum);
REGISTER_REDUCE_OP(mean);
REGISTER_REDUCE_OP(max);
REGISTER_REDUCE_OP(min);
REGISTER_REDUCE_OP(prod);
#define REGISTER_REDUCE_CPU_KERNEL(reduce_type, functor, grad_functor) \
REGISTER_OP_CPU_KERNEL(reduce_type, \
......
paddle/fluid/operators/reorder_lod_tensor_by_rank_op.cc
浏览文件 @ 64305b3f
......@@ -23,9 +23,7 @@ namespace operators {
class ReorderLoDTensorByRankTableOpProtoMaker
: public framework::OpProtoAndCheckerMaker {
public:
ReorderLoDTensorByRankTableOpProtoMaker(OpProto *proto,
OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor), the input lod tensor to be reordered according to "
"Input(RankTable).");
......
paddle/fluid/operators/reshape_op.cc
浏览文件 @ 64305b3f
......@@ -22,8 +22,7 @@ namespace operators {
class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ReshapeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor). The input tensor of reshape operator.");
AddInput("Shape",
"(Tensor<int32>, optional). If provided, reshape according to "
......
paddle/fluid/operators/rmsprop_op.cc
浏览文件 @ 64305b3f
......@@ -63,8 +63,7 @@ class RmspropOp : public framework::OperatorWithKernel {
class RmspropOpMaker : public framework::OpProtoAndCheckerMaker {
public:
RmspropOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter value that has to be updated.");
......
paddle/fluid/operators/rnn_memory_helper_op.cc
浏览文件 @ 64305b3f
......@@ -59,8 +59,7 @@ class RNNMemoryHelperOpShapeInference : public framework::InferShapeBase {
class RNNMemoryHelperOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
RNNMemoryHelperOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "");
AddOutput("Out", "");
AddAttr<int>("dtype",
......@@ -117,8 +116,7 @@ class RNNMemoryHelperGradOp : public framework::OperatorBase {
class RNNMemoryHelperGradOpInfoMaker
: public framework::OpProtoAndCheckerMaker {
public:
RNNMemoryHelperGradOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(framework::GradVarName("Out"), "");
AddInput("X", "");
AddInput("Out", "");
......
paddle/fluid/operators/roi_pool_op.cc
浏览文件 @ 64305b3f
......@@ -98,8 +98,7 @@ class ROIPoolGradOp : public framework::OperatorWithKernel {
class ROIPoolOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ROIPoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor), "
"the input of ROIPoolOp. "
......
paddle/fluid/operators/row_conv_op.cc
浏览文件 @ 64305b3f
......@@ -76,8 +76,7 @@ class RowConvGradOp : public framework::OperatorWithKernel {
class RowConvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
RowConvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor), the input(X) is a LodTensor, which supports "
"variable time-length input sequences. The underlying tensor "
......
paddle/fluid/operators/save_combine_op.cc
浏览文件 @ 64305b3f
......@@ -127,8 +127,7 @@ class SaveCombineOp : public framework::OperatorBase {
class SaveCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
SaveCombineOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(vector) Input LoDTensors that need to be saved together in a file.")
......
paddle/fluid/operators/save_op.cc
浏览文件 @ 64305b3f
......@@ -117,8 +117,7 @@ class SaveOp : public framework::OperatorBase {
class SaveOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
SaveOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor ) Input tensor to be saved");
AddComment(R"DOC(
Save operator
......
paddle/fluid/operators/scale_op.cc
浏览文件 @ 64305b3f
......@@ -37,8 +37,7 @@ class ScaleOp : public framework::OperatorWithKernel {
class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ScaleOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) Input tensor of scale operator.");
AddOutput("Out", "(Tensor) Output tensor of scale operator.");
AddComment(R"DOC(
......
paddle/fluid/operators/scatter_op.cc
浏览文件 @ 64305b3f
......@@ -78,8 +78,7 @@ class ScatterGradOp : public framework::OperatorWithKernel {
class ScatterOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ScatterOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The source input of scatter op");
AddInput("Ids", "The index input of scatter op where X will be updated");
AddInput("Updates", "The updated value of updates op");
......
paddle/fluid/operators/select_op.cc
浏览文件 @ 64305b3f
......@@ -380,8 +380,7 @@ class SelectOp : public framework::OperatorBase {
class SelectOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SelectOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kX,
"A set of variables, which are required by operators inside the "
"cases of Select Op")
......
paddle/fluid/operators/send_barrier_op.cc
浏览文件 @ 64305b3f
......@@ -57,8 +57,7 @@ class SendBarrierOp : public framework::OperatorBase {
class SendBarrierOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SendBarrierOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddOutput("RPCClient",
"(RPCClient) The RPC client object which is"
"initialized at most once.");
......
paddle/fluid/operators/send_op.cc
浏览文件 @ 64305b3f
......@@ -92,8 +92,7 @@ class SendOp : public framework::OperatorBase {
class SendOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SendOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("X", "(Tensor) Input tensor to be sent").AsDuplicable();
AddOutput("Out", "(Tensor) Output tensor to be received from server")
.AsDuplicable();
......
paddle/fluid/operators/send_vars_op.cc
浏览文件 @ 64305b3f
......@@ -66,8 +66,7 @@ class SendVarsOp : public framework::OperatorBase {
class SendVarsOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SendVarsOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() {
AddInput("X", "(Tensor, SelectedRows) Input variables to be sent")
.AsDuplicable();
AddOutput("RPCClient",
......
paddle/fluid/operators/sequence_concat_op.cc
浏览文件 @ 64305b3f
......@@ -43,8 +43,7 @@ class SequenceConcatOp : public framework::OperatorWithKernel {
class SequenceConcatOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequenceConcatOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LodTensorArray) Input is a vector of LoDTensor, "
"each of which is a variable-length sequence or nested sequence.")
......
paddle/fluid/operators/sequence_conv_op.cc
浏览文件 @ 64305b3f
......@@ -102,8 +102,7 @@ class SequenceConvGradOp : public framework::OperatorWithKernel {
class SequenceConvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequenceConvOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(LoDTensor) the input(X) is a LodTensor, which supports "
......
paddle/fluid/operators/sequence_erase_op.cc
浏览文件 @ 64305b3f
......@@ -37,8 +37,7 @@ class SequenceEraseOp : public framework::OperatorWithKernel {
class SequenceEraseOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequenceEraseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(2-D LoDTensor with the 2nd dim. equal to 1) "
"Input LoDTensor of SequenceEraseOp.");
......
paddle/fluid/operators/sequence_expand_op.cc
浏览文件 @ 64305b3f
......@@ -94,8 +94,7 @@ class SequenceExpandOp : public framework::OperatorWithKernel {
class SequenceExpandOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequenceExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor, default LoDTensor<float>) A 2-D LoDTensor whose lod "
"level is at most 1.");
......
paddle/fluid/operators/sequence_pool_op.cc
浏览文件 @ 64305b3f
......@@ -38,8 +38,7 @@ class SequencePoolOp : public framework::OperatorWithKernel {
class SequencePoolOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequencePoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(LoDTensor) The variable-length input of SequencePoolOp");
AddOutput("Out",
"(Tensor) The output of SequencePoolOp does not contain LoD "
......
paddle/fluid/operators/sequence_reshape_op.cc
浏览文件 @ 64305b3f
......@@ -42,8 +42,7 @@ class SequenceReshapeOp : public framework::OperatorWithKernel {
class SequenceReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequenceReshapeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor, default LoDTensor<float>) A 2-D LoDTensor with shape "
"being [N, M].");
......
paddle/fluid/operators/sequence_slice_op.cc
浏览文件 @ 64305b3f
......@@ -79,8 +79,7 @@ class SequenceSliceGradOp : public framework::OperatorWithKernel {
class SequenceSliceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequenceSliceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor), "
"the input of SequenceSliceOp.");
......
paddle/fluid/operators/sequence_softmax_op.cc
浏览文件 @ 64305b3f
......@@ -57,8 +57,7 @@ class SequenceSoftmaxOp : public framework::OperatorWithKernel {
class SequenceSoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SequenceSoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(LoDTensor) 1-D or 2-D input LoDTensor with the 2-nd dimension "
"of length 1.");
......
paddle/fluid/operators/sgd_op.cc
浏览文件 @ 64305b3f
......@@ -68,8 +68,7 @@ class SGDOpInferVarType : public framework::VarTypeInference {
class SGDOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SGDOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Param", "(Tensor or SelectedRows) Input parameter");
AddInput("LearningRate", "(Tensor) Learning rate of SGD");
AddInput("Grad", "(Tensor or SelectedRows) Input gradient");
......
paddle/fluid/operators/shrink_rnn_memory_op.cc
浏览文件 @ 64305b3f
......@@ -69,8 +69,7 @@ class ShrinkRNNMemoryOp : public ArrayOp {
class ShrinkRNNMemoryOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
ShrinkRNNMemoryOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(LoDTensor) The RNN step memory to be shrinked.");
AddInput("RankTable", "(LoDRankTable) The lod_rank_table of dynamic RNN.");
AddInput("I",
......
paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cc
浏览文件 @ 64305b3f
......@@ -86,9 +86,7 @@ class SigmoidCrossEntropyWithLogitsGradOp
class SigmoidCrossEntropyWithLogitsOpMaker
: public framework::OpProtoAndCheckerMaker {
public:
SigmoidCrossEntropyWithLogitsOpMaker(OpProto* proto,
OpAttrChecker* op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>), a 2-D tensor with shape N x D, "
"where N is the batch size and D is the number of classes. "
......
paddle/fluid/operators/sign_op.cc
浏览文件 @ 64305b3f
......@@ -34,8 +34,7 @@ class SignOp : public framework::OperatorWithKernel {
template <typename AttrType>
class SignOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SignOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) Input tensor of sign operator.");
AddOutput("Out", "(Tensor) Output tensor of sign operator.");
AddComment(R"DOC(
......
paddle/fluid/operators/smooth_l1_loss_op.cc
浏览文件 @ 64305b3f
......@@ -46,8 +46,7 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
class SmoothL1LossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SmoothL1LossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>) A tensor with rank at least 2. "
"The input value of smooth l1 loss op with shape "
......
paddle/fluid/operators/softmax_mkldnn_op.cc
浏览文件 @ 64305b3f
......@@ -53,25 +53,60 @@ class SoftmaxMKLDNNKernel : public paddle::framework::OpKernel<T> {
"Softmax input and output dimensions should match");
// Same memory descriptor to be used for input and output
memory::dims softmax_tz = {src_tz[0], src_tz[1]};
// Currently only supports NC data format
// TODO(jczaja-intel): support more formats
// Generate keys for storing/retriving primitives for this operator
// TODO(jczaja): Each MKLDNN operator may have diffrent hashing function
auto gethash = [](memory::dims& operand_dims) {
return std::string(std::to_string(operand_dims[0]) + "-" +
std::to_string(operand_dims[1]));
};
const std::string key = gethash(softmax_tz);
const std::string key_softmax_p = key + "@softmax_p";
const std::string key_softmax_src_mem_p = key + "@softmax_src_mem_p";
const std::string key_softmax_dst_mem_p = key + "@softmax_dst_mem_p";
std::shared_ptr<void> softmax_p = dev_ctx.GetBlob(key_softmax_p);
if (softmax_p == nullptr) {
// Currently only NC data format is supported
auto softmax_md =
MKLDNNMemDesc({softmax_tz}, memory::f32, memory::format::nc);
// Normalization is made after innermost dimension eg. C out of NC
auto softmax_desc = softmax_forward::desc(prop_kind::forward_scoring,
softmax_md, 1 /*dim: C*/);
// create memory primitives
auto softmax_src_memory =
memory({softmax_md, mkldnn_engine},
auto softmax_src_memory_p = std::make_shared<memory>(
memory::primitive_desc{softmax_md, mkldnn_engine},
static_cast<void*>(const_cast<T*>(input_data)));
auto softmax_dst_memory =
memory({softmax_md, mkldnn_engine},
static_cast<void*>(const_cast<T*>(output_data)));
auto softmax_prim_desc =
softmax_forward::primitive_desc(softmax_desc, mkldnn_engine);
auto softmax = softmax_forward(softmax_prim_desc, softmax_src_memory,
softmax_dst_memory);
std::vector<primitive> pipeline{softmax};
dev_ctx.SetBlob(key_softmax_src_mem_p, softmax_src_memory_p);
auto softmax_dst_memory_p = std::make_shared<memory>(
memory::primitive_desc{softmax_md, mkldnn_engine},
static_cast<void*>(output_data));
dev_ctx.SetBlob(key_softmax_dst_mem_p, softmax_dst_memory_p);
auto softmax_forward_pd =
std::make_shared<softmax_forward::primitive_desc>(softmax_desc,
mkldnn_engine);
softmax_p = std::make_shared<softmax_forward>(
*(softmax_forward_pd.get()),
*(static_cast<memory*>(softmax_src_memory_p.get())),
*(static_cast<memory*>(softmax_dst_memory_p.get())));
dev_ctx.SetBlob(key_softmax_p, softmax_p);
} else {
// Primitives already exist
auto src_memory_p = std::static_pointer_cast<memory>(
dev_ctx.GetBlob(key_softmax_src_mem_p));
PADDLE_ENFORCE(src_memory_p != nullptr,
"Fail to find softmax src mem_p in device context");
auto dst_memory_p = std::static_pointer_cast<memory>(
dev_ctx.GetBlob(key_softmax_dst_mem_p));
PADDLE_ENFORCE(dst_memory_p != nullptr,
"Fail to find softmax dst mem_p in device context");
src_memory_p->set_data_handle(
reinterpret_cast<void*>(const_cast<T*>(input_data)));
dst_memory_p->set_data_handle(output_data);
}
std::vector<primitive> pipeline{
*(static_cast<softmax_forward::primitive*>(softmax_p.get()))};
stream(stream::kind::eager).submit(pipeline).wait();
const bool is_test = ctx.Attr<bool>("is_test");
......
paddle/fluid/operators/softmax_op.cc
浏览文件 @ 64305b3f
......@@ -77,8 +77,7 @@ class SoftmaxOp : public framework::OperatorWithKernel {
class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X",
"The input tensor of softmax. "
"2-D with shape [batch_size, input_feature_dimensions].");
......
paddle/fluid/operators/softmax_with_cross_entropy_op.cc
浏览文件 @ 64305b3f
......@@ -20,8 +20,7 @@ namespace operators {
class SoftmaxWithCrossEntropyOpMaker
: public framework::OpProtoAndCheckerMaker {
public:
SoftmaxWithCrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Logits",
"(Tensor, default: Tensor<float>), The unscaled log probabilities "
"which is a 2-D tensor with shape [N x K]. N is the batch_size, "
......
paddle/fluid/operators/split_byref_op.cc
浏览文件 @ 64305b3f
......@@ -64,8 +64,7 @@ class SplitByrefOp : public framework::OperatorWithKernel {
class SplitByrefOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SplitByrefOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) Input tensor of the split operator.");
AddOutput("Out", "(Tensor) Output tensors of the split operator.")
.AsDuplicable();
......
paddle/fluid/operators/split_ids_op.cc
浏览文件 @ 64305b3f
......@@ -19,8 +19,7 @@ namespace operators {
class SplitIdsOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SplitIdsOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Ids", "(LoDTensor) the input ids with shape{batch_num, 1}");
AddOutput("Out", "(LoDTensor) The outputs of the input Ids.")
.AsDuplicable();
......
paddle/fluid/operators/split_lod_tensor_op.cc
浏览文件 @ 64305b3f
......@@ -125,8 +125,7 @@ class SplitLoDTensorOp : public framework::OperatorBase {
class SplitLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
SplitLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input LoDTensor");
AddInput("Mask", "A bool column vector which mask the input");
AddOutput("OutTrue", "True branch of input LoDTensor");
......
paddle/fluid/operators/split_op.cc
浏览文件 @ 64305b3f
......@@ -70,8 +70,7 @@ class SplitOp : public framework::OperatorWithKernel {
class SplitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SplitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) Input tensor of the split operator.");
AddOutput("Out", "(Tensor) Output tensors of the split operator.")
.AsDuplicable();
......
paddle/fluid/operators/split_selected_rows_op.cc
浏览文件 @ 64305b3f
......@@ -19,8 +19,7 @@ namespace operators {
class SplitSelectedRowsOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SplitSelectedRowsOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "The input SelectedRows.");
AddOutput("Out", "The outputs of the input SelectedRows.").AsDuplicable();
AddAttr<std::vector<int>>("height_sections",
......
paddle/fluid/operators/spp_op.cc
浏览文件 @ 64305b3f
......@@ -20,8 +20,7 @@ namespace operators {
class SppOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SppOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of spp operator. "
......
paddle/fluid/operators/squared_l2_distance_op.cc
浏览文件 @ 64305b3f
......@@ -56,8 +56,7 @@ class SquaredL2DistanceOp : public framework::OperatorWithKernel {
class SquaredL2DistanceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SquaredL2DistanceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) Input of SquaredL2DistanceOp.");
AddInput("Y", "(Tensor) Target of SquaredL2DistanceOp.");
AddOutput("sub_result",
......
paddle/fluid/operators/squared_l2_norm_op.cc
浏览文件 @ 64305b3f
......@@ -48,8 +48,7 @@ class SquaredL2NormGradOp : public framework::OperatorWithKernel {
class SquaredL2NormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SquaredL2NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) The input of squared_l2_norm op.");
AddOutput("Out", "(Scalar) The output of squared_l2_norm op.");
AddComment(R"DOC(
......
paddle/fluid/operators/sum_op.cc
浏览文件 @ 64305b3f
......@@ -112,8 +112,7 @@ class SumOp : public framework::OperatorWithKernel {
class SumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
SumOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(vector<Tensor>) The input tensors of sum operator.")
.AsDuplicable();
AddOutput("Out", "(Tensor) The output tensor of sum operator.");
......
paddle/fluid/operators/tensor_array_read_write_op.cc
浏览文件 @ 64305b3f
......@@ -57,8 +57,7 @@ class WriteToArrayOp : public ArrayOp {
class WriteToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
WriteToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(LoDTensor) the tensor will be written to tensor array");
AddInput(
"I",
......@@ -148,8 +147,7 @@ class ReadFromArrayOp : public ArrayOp {
class ReadFromArrayProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
ReadFromArrayProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(TensorArray) the array will be read from.");
AddInput("I",
"(Tensor) the subscript index in tensor array. The number of "
......
paddle/fluid/operators/top_k_op.cc
浏览文件 @ 64305b3f
......@@ -48,8 +48,7 @@ class TopkOp : public framework::OperatorWithKernel {
class TopkOpMaker : public framework::OpProtoAndCheckerMaker {
public:
TopkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("X", "(Tensor) The input of Topk op");
AddOutput("Out", "(Tensor) The output tensor of Topk op");
AddOutput("Indices", "(Tensor) The indices of Topk elements of input");
......
paddle/fluid/operators/transpose_op.cc
浏览文件 @ 64305b3f
......@@ -56,8 +56,7 @@ class TransposeOp : public framework::OperatorWithKernel {
class TransposeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
TransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(Tensor) The input tensor, tensors with rank up to 6 are supported.");
......
paddle/fluid/operators/uniform_random_batch_size_like_op.cc
浏览文件 @ 64305b3f
......@@ -32,9 +32,8 @@ class UniformRandomBatchSizeLikeOp : public BatchSizeLikeOp {
};
class UniformRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
public:
UniformRandomBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: BatchSizeLikeOpMaker(proto, op_checker) {
protected:
void Apply() override {
AddComment(R"DOC(
Uniform random operator
......
paddle/fluid/operators/uniform_random_op.cc
浏览文件 @ 64305b3f
......@@ -85,8 +85,7 @@ class UniformRandomOp : public framework::OperatorWithKernel {
class UniformRandomOpMaker : public framework::OpProtoAndCheckerMaker {
public:
UniformRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: framework::OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddOutput("Out", "(Tensor) The output tensor of uniform random op");
AddComment(R"DOC(
Uniform random operator.
......
paddle/fluid/operators/unpool_op.cc
浏览文件 @ 64305b3f
......@@ -20,8 +20,7 @@ namespace operators {
class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
Unpool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of unpool operator. "
......
paddle/fluid/operators/warpctc_op.cc
浏览文件 @ 64305b3f
......@@ -53,8 +53,7 @@ class WarpCTCOp : public framework::OperatorWithKernel {
class WarpCTCOpMaker : public framework::OpProtoAndCheckerMaker {
public:
WarpCTCOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput("Logits",
"(LodTensor, default: LoDTensor<float>), the unscaled "
"probabilities of variable-length sequences, which is a 2-D "
......
paddle/fluid/operators/while_op.cc
浏览文件 @ 64305b3f
......@@ -68,8 +68,7 @@ class WhileOp : public framework::OperatorBase {
class WhileOpMaker : public framework::OpProtoAndCheckerMaker {
public:
WhileOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
void Make() override {
AddInput(kX,
"A set of variables, which are required by operators inside the "
"block of While Op.")
......
paddle/fluid/pybind/pybind.cc
浏览文件 @ 64305b3f
......@@ -502,11 +502,13 @@ All parameter, weight, gradient are variables in Paddle.
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
Scope *scope, std::vector<Scope *> &local_scopes,
bool allow_op_delay, bool use_default_grad_scale) {
bool allow_op_delay, bool use_default_grad_scale,
bool balance_parameter_opt_between_cards) {
new (&self) ParallelExecutor(
num_threads, use_event, places, params, bcast_vars,
main_program, loss_var_name, scope, local_scopes,
allow_op_delay, use_default_grad_scale);
allow_op_delay, use_default_grad_scale,
balance_parameter_opt_between_cards);
})
.def("bcast_params", &ParallelExecutor::BCastParamsToGPUs)
// NOTE: even we return a vec<Scope*>* to Python use reference policy.
......
paddle/gserver/layers/PriorBox.cpp
浏览文件 @ 64305b3f
......@@ -28,7 +28,7 @@ namespace paddle {
*/
class PriorBoxLayer : public Layer {
public:
public: // NOLINT
explicit PriorBoxLayer(const LayerConfig& config) : Layer(config) {}
bool init(const LayerMap& layerMap,
const ParameterMap& parameterMap) override;
......@@ -36,7 +36,7 @@ public:
void forward(PassType passType) override;
void backward(const UpdateCallback& callback) override {}
protected:
protected: // NOLINT
int numPriors_;
std::vector<int> minSize_;
std::vector<int> maxSize_;
......@@ -109,18 +109,13 @@ void PriorBoxLayer::forward(PassType passType) {
real boxWidth = minSize;
real boxHeight = minSize;
// priors with different aspect ratios
for (size_t r = 0; r < aspectRatio_.size(); r++) {
real ar = aspectRatio_[r];
boxWidth = minSize * sqrt(ar);
boxHeight = minSize / sqrt(ar);
// first prior: aspect_ratio == 1.0, compatible to old logic
tmpPtr[idx++] = (centerX - boxWidth / 2.) / imageWidth;
tmpPtr[idx++] = (centerY - boxHeight / 2.) / imageHeight;
tmpPtr[idx++] = (centerX + boxWidth / 2.) / imageWidth;
tmpPtr[idx++] = (centerY + boxHeight / 2.) / imageHeight;
// set the variance.
for (int t = 0; t < 4; t++) tmpPtr[idx++] = variance_[t];
}
if (maxSize_.size() > 0) {
// square prior with size sqrt(minSize * maxSize)
......@@ -133,6 +128,22 @@ void PriorBoxLayer::forward(PassType passType) {
// set the variance.
for (int t = 0; t < 4; t++) tmpPtr[idx++] = variance_[t];
}
// priors with different aspect ratios
for (size_t r = 0; r < aspectRatio_.size(); r++) {
real ar = aspectRatio_[r];
if (fabs(ar - 1.0) < 1e-6) {
continue;
}
boxWidth = minSize * sqrt(ar);
boxHeight = minSize / sqrt(ar);
tmpPtr[idx++] = (centerX - boxWidth / 2.) / imageWidth;
tmpPtr[idx++] = (centerY - boxHeight / 2.) / imageHeight;
tmpPtr[idx++] = (centerX + boxWidth / 2.) / imageWidth;
tmpPtr[idx++] = (centerY + boxHeight / 2.) / imageHeight;
// set the variance.
for (int t = 0; t < 4; t++) tmpPtr[idx++] = variance_[t];
}
}
}
}
......
python/paddle/fluid/data_feeder.py
浏览文件 @ 64305b3f
......@@ -16,6 +16,7 @@ from __future__ import print_function
import core
import numpy
import six.moves as six
import multiprocessing
from framework import Variable, default_main_program
......@@ -116,3 +117,60 @@ class DataFeeder(object):
for each_name, each_converter in six.zip(self.feed_names, converter):
ret_dict[each_name] = each_converter.done()
return ret_dict
def feed_parallel(self, iterable, num_places=None):
if isinstance(self.place, core.CUDAPlace):
places = [
core.CUDAPlace(i)
for i in six.xrange(self._get_number_of_places_(num_places))
]
else:
places = [
core.CPUPlace()
for _ in six.xrange(self._get_number_of_places_(num_places))
]
if len(iterable) != len(places):
raise ValueError("feed_parallel takes multiple mini-batches. Each "
"mini-batch will be feed on each device. The "
"number of devices and number of mini-batches "
"must be same.")
place = self.place
for p, batch in six.zip(places, iterable):
self.place = p
yield self.feed(batch)
self.place = place
def _get_number_of_places_(self, num_places):
if num_places is not None:
return int(num_places)
elif isinstance(self.place, core.CUDAPlace):
return core.get_cuda_device_count()
else:
return multiprocessing.cpu_count()
def decorate_reader(self,
reader,
multi_devices,
num_places=None,
drop_last=True):
def __reader_creator__():
if not multi_devices:
for item in reader():
yield self.feed(item)
else:
num = self._get_number_of_places_(num_places)
item = []
for batch in reader():
item.append(batch)
if len(item) == num:
yield list(self.feed_parallel(item, num))
item = []
if not drop_last and len(item) != 0:
raise ValueError(
"The data batch which cannot fit for devices will be "
"dropped is not implementation. Other strategies are "
"not implemented")
return __reader_creator__
python/paddle/fluid/inferencer.py
浏览文件 @ 64305b3f
......@@ -16,31 +16,42 @@ import core
import framework
import executor
import io
from trainer import check_and_get_place
__all__ = ['Inferencer', ]
class Inferencer(object):
def __init__(self, network_func, param_path=None, place=None):
# 1. we need to generate a framework.Program by calling
# network_func. Reference: fluid.program_guard in test_word2vec.py
# 2. move the default_main_program to self.program.
# 3. run the default_startup program.
# 4. load params from param_path into scope
def __init__(self, param_path, place=None):
"""
:param param_path: the path where the inference model is saved by fluid.io.save_inference_model
:param place: place to do the inference
"""
self.param_path = param_path
self.scope = core.Scope()
self.place = place
self.startup_program = framework.Program()
# TODO: generate the startup_program with network_func
exe = executor.Executor(place)
exe.run(self.startup_program, scope=self.scope)
if param_path:
self.exe = executor.Executor(check_and_get_place(place))
with executor.scope_guard(self.scope):
# load params from param_path into scope
io.load_persistables(exe, dirname=param_path)
def infer(self, inputs):
# run self.program
pass
[self.inference_program, _,
self.fetch_targets] = io.load_inference_model(
executor=self.exe, dirname=param_path)
def infer(self, inputs, return_numpy=True):
"""
:param inputs: a map of {"input_name": input_var} that will be feed into the inference program
to get the predict value
:param return_numpy: if return numpy value for row tensor
:return: the predict value of the inference model
"""
if not isinstance(inputs, dict):
raise ValueError(
"inputs should be a map of {'input_name': input_var}")
with executor.scope_guard(self.scope):
results = self.exe.run(self.inference_program,
feed=inputs,
fetch_list=self.fetch_targets,
return_numpy=return_numpy)
return results
python/paddle/fluid/io.py
浏览文件 @ 64305b3f
......@@ -263,6 +263,9 @@ def get_inference_program(target_vars, main_program=None):
def prepend_feed_ops(inference_program,
feed_target_names,
feed_holder_name='feed'):
if len(feed_target_names) == 0:
return
global_block = inference_program.global_block()
feed_var = global_block.create_var(
name=feed_holder_name,
......@@ -323,6 +326,7 @@ def save_inference_model(dirname,
if isinstance(feeded_var_names, basestring):
feeded_var_names = [feeded_var_names]
else:
if len(feeded_var_names) > 0:
if not (bool(feeded_var_names) and all(
isinstance(name, basestring) for name in feeded_var_names)):
raise ValueError("'feed_var_names' should be a list of str.")
......
python/paddle/fluid/layers/layer_function_generator.py
浏览文件 @ 64305b3f
......@@ -113,7 +113,7 @@ def generate_layer_fn(op_type):
if len(not_intermediate_outputs) != 1:
raise ValueError("Only one non intermediate output operator can be",
"automatically generated.")
"automatically generated. {0}".format(op_type))
if not_intermediate_outputs[0].duplicable:
raise ValueError(
......
python/paddle/fluid/parallel_executor.py
浏览文件 @ 64305b3f
......@@ -30,7 +30,8 @@ class ParallelExecutor(object):
num_threads=None,
allow_op_delay=False,
share_vars_from=None,
use_default_grad_scale=True):
use_default_grad_scale=True,
balance_parameter_opt_between_cards=False):
"""
ParallelExecutor can run program in parallel.
......@@ -51,6 +52,9 @@ class ParallelExecutor(object):
gradients of each device and scaled gradients would be
aggregated. Otherwise, a customized scale value should be fed
to the network.
balance_parameter_opt_between_cards(bool, default True): Whether
updating different gradients on different cards. Currently, it
is not recommended.
Returns:
A ParallelExecutor object.
......@@ -129,7 +133,8 @@ class ParallelExecutor(object):
scope,
local_scopes,
allow_op_delay,
use_default_grad_scale)
use_default_grad_scale,
balance_parameter_opt_between_cards)
self.scope = scope
......
python/paddle/fluid/tests/book/CMakeLists.txt
浏览文件 @ 64305b3f
......@@ -5,3 +5,5 @@ string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
foreach(src ${TEST_OPS})
py_test(${src} SRCS ${src}.py)
endforeach()
add_subdirectory(high-level-api)
python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt 0 → 100644
浏览文件 @ 64305b3f
file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
# default test
foreach(src ${TEST_OPS})
py_test(${src} SRCS ${src}.py)
endforeach()
add_subdirectory(recognize_digits)
python/paddle/fluid/tests/book/high-level-api/recognize_digits/CMakeLists.txt 0 → 100644
浏览文件 @ 64305b3f
file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
# default test
foreach(src ${TEST_OPS})
py_test(${src} SRCS ${src}.py)
endforeach()
python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py → python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
浏览文件 @ 64305b3f
......@@ -21,7 +21,6 @@ import unittest
import math
import sys
import os
import paddle.v2.dataset as dataset
BATCH_SIZE = 64
......@@ -54,47 +53,65 @@ def train_program():
predict = inference_program()
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
acc = fluid.layers.accuracy(input=predict, label=label)
return avg_cost, acc
# acc = fluid.layers.accuracy(input=predict, label=label)
# return avg_cost, acc
return avg_cost
def train(use_cuda, save_dirname):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
trainer = fluid.Trainer(train_program, place=place, optimizer=optimizer)
trainer = fluid.Trainer(
train_func=train_program,
infer_func=inference_program,
place=place,
optimizer=optimizer)
def event_handler(event):
if isinstance(event, fluid.EndIteration):
avg_cost, acc = event.values
print("avg_cost: %s" % avg_cost)
print("acc : %s" % acc)
if (event.batch_id + 1) % 10 == 0:
test_metrics = trainer.test(reader=dataset.mnist.test())
avg_cost_set = test_metrics[0]
acc_set = test_metrics[1]
# get test acc and loss
acc = numpy.array(acc_set).mean()
avg_cost = numpy.array(avg_cost_set).mean()
if float(acc) > 0.2: # Smaller value to increase CI speed
trainer.save_params(save_dirname)
else:
print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
event.batch_id + 1, float(avg_cost), float(acc)))
if math.isnan(float(avg_cost)):
sys.exit("got NaN loss, training failed.")
if isinstance(event, fluid.EndEpochEvent):
# if (event.epoch + 1) % 10 == 0:
# trainer.save_params(save_dirname)
trainer.save_inference_model(save_dirname)
# TODO: Uncomment this part once we are sure that .train is working
# test_reader = paddle.batch(
# paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
# test_metrics = trainer.test(reader=test_reader)
# avg_cost_set = test_metrics[0]
# acc_set = test_metrics[1]
#
# # get test acc and loss
# acc = numpy.array(acc_set).mean()
# avg_cost = numpy.array(avg_cost_set).mean()
#
# print("avg_cost: %s" % avg_cost)
# print("acc : %s" % acc)
#
# if float(acc) > 0.2: # Smaller value to increase CI speed
# trainer.save_params(save_dirname)
# else:
# print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
# event.epoch + 1, float(avg_cost), float(acc)))
# if math.isnan(float(avg_cost)):
# sys.exit("got NaN loss, training failed.")
train_reader = paddle.batch(
paddle.reader.shuffle(
paddle.dataset.mnist.train(), buf_size=500),
batch_size=BATCH_SIZE)
trainer.train(
reader=dataset.mnist.train(), num_pass=100, event_handler=event_handler)
num_epochs=1,
event_handler=event_handler,
reader=train_reader,
feed_order=['img', 'label'])
def infer(use_cuda, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
inferencer = fluid.Inferencer(
inference_program, param_path=save_dirname, place=place)
inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
batch_size = 1
tensor_img = numpy.random.uniform(-1.0, 1.0,
......@@ -114,5 +131,5 @@ def main(use_cuda):
if __name__ == '__main__':
for use_cuda in (False, True):
main(use_cuda=use_cuda)
# for use_cuda in (False, True):
main(use_cuda=False)
python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py → python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
浏览文件 @ 64305b3f
......@@ -21,7 +21,6 @@ import unittest
import math
import sys
import os
import paddle.v2.dataset as dataset
BATCH_SIZE = 64
......@@ -41,47 +40,64 @@ def train_program():
predict = inference_program()
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
acc = fluid.layers.accuracy(input=predict, label=label)
return avg_cost, acc
# acc = fluid.layers.accuracy(input=predict, label=label)
# return avg_cost, acc
return avg_cost
def train(use_cuda, save_dirname):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
trainer = fluid.Trainer(train_program, place=place, optimizer=optimizer)
trainer = fluid.Trainer(
train_func=train_program,
infer_func=inference_program,
place=place,
optimizer=optimizer)
def event_handler(event):
if isinstance(event, fluid.EndIteration):
avg_cost, acc = event.values
print("avg_cost: %s" % avg_cost)
print("acc : %s" % acc)
if (event.batch_id + 1) % 10 == 0:
test_metrics = trainer.test(reader=dataset.mnist.test())
avg_cost_set = test_metrics[0]
acc_set = test_metrics[1]
# get test acc and loss
acc = numpy.array(acc_set).mean()
avg_cost = numpy.array(avg_cost_set).mean()
if float(acc) > 0.2: # Smaller value to increase CI speed
trainer.save_params(save_dirname)
else:
print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
event.batch_id + 1, float(avg_cost), float(acc)))
if math.isnan(float(avg_cost)):
sys.exit("got NaN loss, training failed.")
if isinstance(event, fluid.EndEpochEvent):
# if (event.epoch + 1) % 10 == 0:
trainer.save_inference_model(save_dirname)
# TODO: Uncomment this part once we are sure that .train is working
# test_reader = paddle.batch(
# paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
# test_metrics = trainer.test(reader=test_reader)
# avg_cost_set = test_metrics[0]
# acc_set = test_metrics[1]
#
# # get test acc and loss
# acc = numpy.array(acc_set).mean()
# avg_cost = numpy.array(avg_cost_set).mean()
#
# print("avg_cost: %s" % avg_cost)
# print("acc : %s" % acc)
#
# if float(acc) > 0.2: # Smaller value to increase CI speed
# trainer.save_params(save_dirname)
# else:
# print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
# event.epoch + 1, float(avg_cost), float(acc)))
# if math.isnan(float(avg_cost)):
# sys.exit("got NaN loss, training failed.")
train_reader = paddle.batch(
paddle.reader.shuffle(
paddle.dataset.mnist.train(), buf_size=500),
batch_size=BATCH_SIZE)
trainer.train(
reader=dataset.mnist.train(), num_pass=100, event_handler=event_handler)
num_epochs=1,
event_handler=event_handler,
reader=train_reader,
feed_order=['img', 'label'])
def infer(use_cuda, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
inferencer = fluid.Inferencer(
inference_program, param_path=save_dirname, place=place)
inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
batch_size = 1
tensor_img = numpy.random.uniform(-1.0, 1.0,
......@@ -101,5 +117,5 @@ def main(use_cuda):
if __name__ == '__main__':
for use_cuda in (False, True):
main(use_cuda=use_cuda)
# for use_cuda in (False, True):
main(use_cuda=False)
python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
浏览文件 @ 64305b3f
......@@ -99,45 +99,45 @@ def train(use_cuda, is_sparse, save_path):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
def event_handler(event):
# print type(event)
if isinstance(event, fluid.EndEpochEvent):
outs = trainer.test(reader=test_reader)
avg_cost = outs[0]
print("loss= ", avg_cost)
if avg_cost < 5.0:
trainer.save_params(save_path)
trainer.save_inference_model(save_path)
return
if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
trainer = fluid.Trainer(
partial(train_program, is_sparse),
partial(inference_program, is_sparse),
fluid.optimizer.SGD(learning_rate=0.001),
place=place)
trainer.train(
reader=train_reader, num_epochs=100, event_handler=event_handler)
reader=train_reader, num_epochs=1, event_handler=event_handler)
def infer(use_cuda, is_sparse, save_path):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
inferencer = fluid.Inferencer(
partial(inference_program, is_sparse),
param_path=save_path,
place=place)
inferencer = fluid.Inferencer(param_path=save_path, place=place)
lod = [0, 1]
first_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
second_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
third_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
fourth_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
result = inferencer.infer({
result = inferencer.infer(
{
'firstw': first_word,
'secondw': second_word,
'thirdw': third_word,
'forthw': fourth_word
})
print(result)
},
return_numpy=False)
print(np.array(result[0]))
def main(use_cuda, is_sparse):
......
python/paddle/fluid/tests/unittests/test_network_with_dtype.py
浏览文件 @ 64305b3f
......@@ -24,7 +24,7 @@ BATCH_SIZE = 20
class TestNetWithDtype(unittest.TestCase):
def setUp(self):
def set_network(self):
self.dtype = "float64"
self.init_dtype()
self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
......@@ -55,12 +55,14 @@ class TestNetWithDtype(unittest.TestCase):
pass
def test_cpu(self):
self.set_network()
place = fluid.CPUPlace()
self.run_net_on_place(place)
def test_gpu(self):
if not core.is_compiled_with_cuda():
return
self.set_network()
place = fluid.CUDAPlace(0)
self.run_net_on_place(place)
......
python/paddle/fluid/tests/unittests/test_parallel_executor.py
浏览文件 @ 64305b3f
......@@ -205,7 +205,8 @@ class TestParallelExecutorBase(unittest.TestCase):
allow_op_delay=False,
feed_dict=None,
seed=None,
use_parallel_executor=True):
use_parallel_executor=True,
balance_parameter_opt_between_cards=False):
def run_executor(exe, feed, fetch_list, program=None):
if isinstance(exe, fluid.ParallelExecutor):
res = exe.run(fetch_list=fetch_list, feed=feed)
......@@ -234,7 +235,11 @@ class TestParallelExecutorBase(unittest.TestCase):
if use_parallel_executor:
exe = fluid.ParallelExecutor(
True, loss_name=loss.name, allow_op_delay=allow_op_delay)
True,
loss_name=loss.name,
allow_op_delay=allow_op_delay,
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
else:
exe = fluid.Executor(place=place)
......@@ -280,20 +285,27 @@ class TestMNIST(TestParallelExecutorBase):
fluid.recordio_writer.convert_reader_to_recordio_file(
'./mnist.recordio', reader, feeder)
def check_simple_fc_convergence(self):
def check_simple_fc_convergence(self, balance_parameter_opt_between_cards):
self.check_network_convergence(simple_fc_net)
self.check_network_convergence(simple_fc_net, allow_op_delay=True)
img = np.zeros(shape=[32, 784], dtype='float32')
label = np.ones(shape=[32, 1], dtype='int64')
self.check_network_convergence(
simple_fc_net, feed_dict={"image": img,
"label": label})
simple_fc_net,
feed_dict={"image": img,
"label": label},
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
def test_simple_fc(self):
self.check_simple_fc_convergence()
self.check_simple_fc_convergence(False)
def test_simple_fc_with_new_strategy(self):
self.check_simple_fc_convergence(True)
def check_simple_fc_parallel_accuracy(self):
def check_simple_fc_parallel_accuracy(self,
balance_parameter_opt_between_cards):
img = np.zeros(shape=[32, 784], dtype='float32')
label = np.ones(shape=[32, 1], dtype='int64')
single_first_loss, single_last_loss = self.check_network_convergence(
......@@ -307,7 +319,9 @@ class TestMNIST(TestParallelExecutorBase):
seed=1000,
feed_dict={"image": img,
"label": label},
use_parallel_executor=True)
use_parallel_executor=True,
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
for p_f in parallel_first_loss:
self.assertAlmostEquals(p_f, single_first_loss[0], delta=1e-6)
......@@ -315,18 +329,28 @@ class TestMNIST(TestParallelExecutorBase):
self.assertAlmostEquals(p_l, single_last_loss[0], delta=1e-6)
def test_simple_fc_parallel_accuracy(self):
self.check_simple_fc_parallel_accuracy()
self.check_simple_fc_parallel_accuracy(False)
def check_batchnorm_fc_convergence(self):
def test_simple_fc_parallel_accuracy_with_new_strategy(self):
self.check_simple_fc_parallel_accuracy(True)
def check_batchnorm_fc_convergence(self,
balance_parameter_opt_between_cards):
self.check_network_convergence(fc_with_batchnorm)
img = np.zeros(shape=[32, 784], dtype='float32')
label = np.ones(shape=[32, 1], dtype='int64')
self.check_network_convergence(
fc_with_batchnorm, feed_dict={"image": img,
"label": label})
fc_with_batchnorm,
feed_dict={"image": img,
"label": label},
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
def test_batchnorm_fc(self):
self.check_batchnorm_fc_convergence()
self.check_batchnorm_fc_convergence(False)
def test_batchnorm_fc_with_new_strategy(self):
self.check_batchnorm_fc_convergence(True)
class TestResnet(TestParallelExecutorBase):
......@@ -348,17 +372,22 @@ class TestResnet(TestParallelExecutorBase):
# fluid.recordio_writer.convert_reader_to_recordio_file(
# "./flowers.recordio", reader, feeder, compressor=fluid.core.RecordIOWriter.Compressor.NoCompress)
def check_resnet_convergence(self):
def check_resnet_convergence(self, balance_parameter_opt_between_cards):
import functools
batch_size = 2
self.check_network_convergence(
functools.partial(
SE_ResNeXt50Small, batch_size=batch_size),
iter=20,
batch_size=batch_size)
batch_size=batch_size,
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
def test_resnet(self):
self.check_resnet_convergence()
self.check_resnet_convergence(False)
def test_resnet_with_new_strategy(self):
self.check_resnet_convergence(True)
class ModelHyperParams(object):
......@@ -519,7 +548,7 @@ class TestTransformer(TestParallelExecutorBase):
class ParallelExecutorTestingDuringTraining(unittest.TestCase):
def check_network_convergence(self):
def check_network_convergence(self, balance_parameter_opt_between_cards):
main = fluid.Program()
startup = fluid.Program()
with fluid.program_guard(main, startup):
......@@ -539,12 +568,18 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
feed_dict = {'image': image, 'label': label}
train_exe = fluid.ParallelExecutor(
use_cuda=True, loss_name=loss.name, main_program=main)
use_cuda=True,
loss_name=loss.name,
main_program=main,
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
test_exe = fluid.ParallelExecutor(
use_cuda=True,
main_program=test_program,
share_vars_from=train_exe)
share_vars_from=train_exe,
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
for i in xrange(5):
test_loss, = test_exe.run([loss.name], feed=feed_dict)
......@@ -558,8 +593,11 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
"Train loss: " + str(train_loss) + "\n Test loss:" +
str(test_loss))
def test_parallel(self):
self.check_network_convergence()
def test_parallel_testing(self):
self.check_network_convergence(False)
def test_parallel_testing_with_new_strategy(self):
self.check_network_convergence(True)
import paddle.dataset.conll05 as conll05
......@@ -579,7 +617,7 @@ embedding_name = 'emb'
def db_lstm(word, predicate, ctx_n2, ctx_n1, ctx_0, ctx_p1, ctx_p2, mark,
is_sparse, **ignored):
is_sparse, balance_parameter_opt_between_cards, **ignored):
# 8 features
predicate_embedding = fluid.layers.embedding(
input=predicate,
......@@ -648,7 +686,9 @@ def db_lstm(word, predicate, ctx_n2, ctx_n1, ctx_0, ctx_p1, ctx_p2, mark,
class TestCRFModel(unittest.TestCase):
def check_network_convergence(self, is_sparse):
def check_network_convergence(self,
is_sparse,
balance_parameter_opt_between_cards=False):
main = fluid.Program()
startup = fluid.Program()
with fluid.program_guard(main, startup):
......@@ -696,7 +736,11 @@ class TestCRFModel(unittest.TestCase):
exe = fluid.Executor(place)
exe.run(startup)
pe = fluid.ParallelExecutor(use_cuda=True, loss_name=avg_cost.name)
pe = fluid.ParallelExecutor(
use_cuda=True,
loss_name=avg_cost.name,
balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
)
feeder = fluid.DataFeeder(
feed_list=[
......@@ -718,6 +762,14 @@ class TestCRFModel(unittest.TestCase):
def test_update_dense_parameter(self):
self.check_network_convergence(is_sparse=False)
def test_update_sparse_parameter_with_new_strategy(self):
self.check_network_convergence(
is_sparse=False, balance_parameter_opt_between_cards=True)
def test_update_dense_parameter_with_new_strategy(self):
self.check_network_convergence(
is_sparse=False, balance_parameter_opt_between_cards=True)
# test fetch all the variables of global_block
......@@ -796,5 +848,42 @@ class TestFetchOp(unittest.TestCase):
self.parallel_exe(train_inputs, seed=1)
class TestFeedParallel(unittest.TestCase):
def test_main(self):
main = fluid.Program()
startup = fluid.Program()
startup.random_seed = 1
with fluid.scope_guard(fluid.core.Scope()):
with fluid.program_guard(main, startup):
data = fluid.layers.data(
name='image', shape=[3, 224, 224], dtype='float32')
label = fluid.layers.data(
name='label', shape=[1], dtype='int64')
out = Lenet(data, class_dim=102)
loss = fluid.layers.cross_entropy(input=out, label=label)
loss = fluid.layers.mean(loss)
opt = fluid.optimizer.Momentum(
learning_rate=0.1,
momentum=0.9,
regularization=fluid.regularizer.L2Decay(1e-4))
opt.minimize(loss)
place = fluid.CUDAPlace(0)
feeder = fluid.DataFeeder(place=place, feed_list=[data, label])
reader = feeder.decorate_reader(
paddle.batch(
flowers.train(), batch_size=16), multi_devices=True)
exe = fluid.Executor(place)
exe.run(startup)
pe = fluid.ParallelExecutor(
use_cuda=True, loss_name=loss.name, main_program=main)
for batch_id, data in enumerate(reader()):
loss_np = np.array(pe.run(feed=data, fetch_list=[loss.name])[0])
print batch_id, loss_np
if batch_id == 2:
break
if __name__ == '__main__':
unittest.main()
python/paddle/fluid/trainer.py
浏览文件 @ 64305b3f
......@@ -19,7 +19,7 @@ import executor
import data_feeder
import contextlib
import io
import transpiler
import unique_name
# optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module
import optimizer as opt_module
......@@ -56,26 +56,62 @@ class EndStepEvent(object):
self.step = step_id
def check_and_get_place(place):
"""
Check the type of place or get the default place
Args:
place(None|core.CUDAPlace|core.CPUPlace): the place that trainer will be executed on.
Raises:
TypeError if the type mismatched.
Returns:
the original place if it is not None.
if fluid is compiled with CUDA, returns CUDAPlace(0) by default.
Otherwise returns CPUPlace by default.
"""
if place is None:
if core.is_compiled_with_cuda():
return core.CUDAPlace(0)
else:
return core.CPUPlace()
else:
if not isinstance(place, core.CUDAPlace) and not isinstance(
place, core.CPUPlace):
raise TypeError("Place should be either CUDAPlace or CPUPlace")
return place
class Trainer(object):
"""
Args:
program_func(callable): A function which will return loss. The loss must be a scaler.
train_func(callable): A function which will return loss. The loss must be a scalar.
infer_func(callable): A function which will return predict, used to save inference model
optimizer(optimizer.Optimizer): The optimizer should be an instance of Optimizer
place: The device place of this trainer.
"""
def __init__(self, program_func, optimizer, param_path=None, place=None):
def __init__(self,
train_func,
infer_func,
optimizer,
param_path=None,
place=None):
# 1. we need to generate a framework.Program by calling
# program_func. Reference: fluid.program_guard in
# test_word2vec.py
if not isinstance(optimizer, opt_module.Optimizer):
raise TypeError("The optimizer should be an instance of Optimizer")
self.infer_func = infer_func
self.scope = core.Scope()
self.startup_program = framework.Program()
self.train_program = framework.Program()
with framework.program_guard(self.train_program, self.startup_program):
program_func_outs = program_func()
program_func_outs = train_func()
self.test_outputs = program_func_outs if isinstance(
program_func_outs, list) else [program_func_outs]
self.test_program = self.train_program.clone()
......@@ -86,9 +122,9 @@ class Trainer(object):
loss = self.test_outputs[0]
optimize_ops, params_grads = optimizer.minimize(loss)
self.place = Trainer._check_and_get_place(place)
self.place = check_and_get_place(place)
self.dist_transpile_if_necessary(optimize_ops, params_grads)
self._dist_transpile_if_necessary(optimize_ops, params_grads)
# 2. move the default_main_program to self.program and run the
# default_startup program on an empty core.Scope()
......@@ -101,7 +137,7 @@ class Trainer(object):
# load params from param_path into scope
io.load_persistables(exe, dirname=param_path)
def dist_transpile_if_necessary(self, optimize_ops, params_grads):
def _dist_transpile_if_necessary(self, optimize_ops, params_grads):
if "PADDLE_TRAINING_ROLE" not in os.environ:
return
......@@ -190,31 +226,14 @@ class Trainer(object):
exe = executor.Executor(self.place)
io.save_persistables(exe, dirname=param_path)
@staticmethod
def _check_and_get_place(place):
"""
Check the type of place or get the default place
Args:
place(None|core.CUDAPlace|core.CPUPlace): the place that trainer will be executed on.
Raises:
TypeError if the type mismatched.
Returns:
the original place if it is not None.
if fluid is compiled with CUDA, returns CUDAPlace(0) by default.
Otherwise returns CPUPlace by default.
"""
if place is None:
if core.is_compiled_with_cuda():
return core.CUDAPlace(0)
else:
return core.CPUPlace()
else:
if not isinstance(place, core.CUDAPlace) and not isinstance(
place, core.CPUPlace):
raise TypeError("Place should be either CUDAPlace or CPUPlace")
return place
def save_inference_model(self, model_path):
inference_program = framework.Program()
with framework.program_guard(inference_program):
with unique_name.guard():
predict_var = self.infer_func()
predict_var = self.train_program.block(0).var(predict_var.name)
exe = executor.Executor(self.place)
io.save_inference_model(model_path, [], [predict_var], exe)
@contextlib.contextmanager
def _prog_and_scope_guard(self):
......
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