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3e4c671c
编写于
8月 07, 2017
作者:
D
dangqingqing
浏览文件
操作
浏览文件
下载
差异文件
Merge branch 'develop' of
https://github.com/PaddlePaddle/Paddle
into bn_infer
上级
bf08e5d9
dda4217c
变更
25
隐藏空白更改
内联
并排
Showing
25 changed file
with
317 addition
and
132 deletion
+317
-132
cmake/cpplint.cmake
cmake/cpplint.cmake
+10
-18
cmake/external/openblas.cmake
cmake/external/openblas.cmake
+7
-2
cmake/flags.cmake
cmake/flags.cmake
+2
-1
cmake/generic.cmake
cmake/generic.cmake
+13
-0
doc/design/mkldnn/README.MD
doc/design/mkldnn/README.MD
+110
-0
doc/design/mkldnn/image/overview.png
doc/design/mkldnn/image/overview.png
+0
-0
paddle/api/test/CMakeLists.txt
paddle/api/test/CMakeLists.txt
+6
-2
paddle/framework/operator.h
paddle/framework/operator.h
+5
-1
paddle/gserver/tests/CMakeLists.txt
paddle/gserver/tests/CMakeLists.txt
+0
-5
paddle/operators/add_op.cc
paddle/operators/add_op.cc
+2
-2
paddle/operators/mul_op.cc
paddle/operators/mul_op.cc
+9
-5
paddle/operators/recurrent_op.cc
paddle/operators/recurrent_op.cc
+19
-7
paddle/operators/rnn/recurrent_op_utils.cc
paddle/operators/rnn/recurrent_op_utils.cc
+15
-12
paddle/operators/sigmoid_op.cc
paddle/operators/sigmoid_op.cc
+4
-4
paddle/operators/sigmoid_op.cu
paddle/operators/sigmoid_op.cu
+2
-0
paddle/operators/sigmoid_op.h
paddle/operators/sigmoid_op.h
+19
-0
paddle/trainer/tests/simple_sparse_neural_network.py
paddle/trainer/tests/simple_sparse_neural_network.py
+2
-2
paddle/trainer/tests/simple_sparse_neural_network_dp.py
paddle/trainer/tests/simple_sparse_neural_network_dp.py
+4
-4
paddle/trainer/tests/test_TrainerOnePass.cpp
paddle/trainer/tests/test_TrainerOnePass.cpp
+4
-4
python/paddle/v2/framework/tests/CMakeLists.txt
python/paddle/v2/framework/tests/CMakeLists.txt
+23
-17
python/paddle/v2/framework/tests/test_recurrent_op.py
python/paddle/v2/framework/tests/test_recurrent_op.py
+48
-42
python/paddle/v2/framework/tests/test_sigmoid_op.py
python/paddle/v2/framework/tests/test_sigmoid_op.py
+3
-0
python/paddle/v2/plot/tests/CMakeLists.txt
python/paddle/v2/plot/tests/CMakeLists.txt
+1
-1
python/paddle/v2/reader/tests/CMakeLists.txt
python/paddle/v2/reader/tests/CMakeLists.txt
+2
-1
python/paddle/v2/tests/CMakeLists.txt
python/paddle/v2/tests/CMakeLists.txt
+7
-2
未找到文件。
cmake/cpplint.cmake
浏览文件 @
3e4c671c
...
...
@@ -42,29 +42,21 @@ macro(add_style_check_target TARGET_NAME)
if
(
WITH_STYLE_CHECK
)
set
(
SOURCES_LIST
${
ARGN
}
)
list
(
REMOVE_DUPLICATES SOURCES_LIST
)
list
(
SORT SOURCES_LIST
)
foreach
(
filename
${
SOURCES_LIST
}
)
set
(
LINT ON
)
foreach
(
pattern
${
IGNORE_PATTERN
}
)
if
(
filename MATCHES
${
pattern
}
)
message
(
STATUS
"DROP LINT
${
filename
}
"
)
set
(
LINT OFF
)
list
(
REMOVE_ITEM SOURCES_LIST
${
filename
}
)
endif
()
endforeach
()
if
(
LINT MATCHES ON
)
# cpplint code style
get_filename_component
(
base_filename
${
filename
}
NAME
)
set
(
CUR_GEN
${
CMAKE_CURRENT_BINARY_DIR
}
/
${
base_filename
}
.cpplint
)
add_custom_command
(
OUTPUT
${
CUR_GEN
}
PRE_BUILD
COMMAND
"
${
PYTHON_EXECUTABLE
}
"
"
${
PROJ_ROOT
}
/paddle/scripts/cpplint.py"
"--filter=
${
STYLE_FILTER
}
"
"--write-success=
${
CUR_GEN
}
"
${
filename
}
DEPENDS
${
filename
}
${
PROJ_ROOT
}
/paddle/scripts/cpplint.py
WORKING_DIRECTORY
${
CMAKE_CURRENT_SOURCE_DIR
}
)
add_custom_target
(
${
base_filename
}
.cpplint DEPENDS
${
CUR_GEN
}
)
add_dependencies
(
${
TARGET_NAME
}
${
base_filename
}
.cpplint
)
endif
()
endforeach
()
if
(
SOURCES_LIST
)
add_custom_command
(
TARGET
${
TARGET_NAME
}
POST_BUILD
COMMAND
"
${
PYTHON_EXECUTABLE
}
"
"
${
PROJ_ROOT
}
/paddle/scripts/cpplint.py"
"--filter=
${
STYLE_FILTER
}
"
${
SOURCES_LIST
}
COMMENT
"cpplint: Checking source code style"
WORKING_DIRECTORY
${
CMAKE_CURRENT_SOURCE_DIR
}
)
endif
()
endif
()
endmacro
()
cmake/external/openblas.cmake
浏览文件 @
3e4c671c
...
...
@@ -69,8 +69,13 @@ ENDIF(NOT ${CBLAS_FOUND})
MESSAGE
(
STATUS
"BLAS library:
${
CBLAS_LIBRARIES
}
"
)
INCLUDE_DIRECTORIES
(
${
CBLAS_INC_DIR
}
)
ADD_LIBRARY
(
cblas STATIC IMPORTED
)
SET_PROPERTY
(
TARGET cblas PROPERTY IMPORTED_LOCATION
${
CBLAS_LIBRARIES
}
)
# FIXME(gangliao): generate cblas target to track all high performance
# linear algebra libraries for cc_library(xxx SRCS xxx.c DEPS cblas)
SET
(
dummyfile
${
CMAKE_CURRENT_BINARY_DIR
}
/cblas_dummy.c
)
FILE
(
WRITE
${
dummyfile
}
"const char * dummy =
\"
${
dummyfile
}
\"
;"
)
ADD_LIBRARY
(
cblas STATIC
${
dummyfile
}
)
TARGET_LINK_LIBRARIES
(
cblas
${
CBLAS_LIBRARIES
}
)
IF
(
NOT
${
CBLAS_FOUND
}
)
ADD_DEPENDENCIES
(
cblas extern_openblas
)
LIST
(
APPEND external_project_dependencies cblas
)
...
...
cmake/flags.cmake
浏览文件 @
3e4c671c
...
...
@@ -115,7 +115,7 @@ set(COMMON_FLAGS
-Wno-error=literal-suffix
-Wno-error=sign-compare
-Wno-error=unused-local-typedefs
-Wno-error=parentheses-equality
# Warnings in
P
ybind11
-Wno-error=parentheses-equality
# Warnings in
p
ybind11
)
set
(
GPU_COMMON_FLAGS
...
...
@@ -195,6 +195,7 @@ endif()
# Modern gpu architectures: Pascal
if
(
CUDA_VERSION VERSION_GREATER
"8.0"
OR CUDA_VERSION VERSION_EQUAL
"8.0"
)
list
(
APPEND __arch_flags
" -gencode arch=compute_60,code=sm_60"
)
list
(
APPEND CUDA_NVCC_FLAGS --expt-relaxed-constexpr
)
endif
()
# Custom gpu architecture
...
...
cmake/generic.cmake
浏览文件 @
3e4c671c
...
...
@@ -403,3 +403,16 @@ function(py_proto_compile TARGET_NAME)
protobuf_generate_python
(
py_srcs
${
py_proto_compile_SRCS
}
)
add_custom_target
(
${
TARGET_NAME
}
ALL DEPENDS
${
py_srcs
}
)
endfunction
()
function
(
py_test TARGET_NAME
)
if
(
WITH_TESTING
)
set
(
options STATIC static SHARED shared
)
set
(
oneValueArgs
""
)
set
(
multiValueArgs SRCS DEPS
)
cmake_parse_arguments
(
py_test
"
${
options
}
"
"
${
oneValueArgs
}
"
"
${
multiValueArgs
}
"
${
ARGN
}
)
add_test
(
NAME
${
TARGET_NAME
}
COMMAND env PYTHONPATH=
${
PADDLE_PYTHON_PACKAGE_DIR
}
python2
${
py_test_SRCS
}
WORKING_DIRECTORY
${
CMAKE_CURRENT_SOURCE_DIR
}
)
endif
()
endfunction
()
doc/design/mkldnn/README.MD
0 → 100644
浏览文件 @
3e4c671c
# Intel® MKL-DNN on PaddlePaddle: Design Doc
我们计划将Intel深度神经网络数学库(
**MKL-DNN**
\[
[
1
](
#references
)
\]
)集成到PaddlePaddle,充分展现英特尔平台的优势,有效提升PaddlePaddle在英特尔架构上的性能。
我们短期内的基本目标是:
-
完成常用layer的MKL-DNN实现。
-
完成常见深度神经网络VGG,GoogLeNet 和 ResNet的MKL-DNN实现。
## Contents
-
[
Overview
](
#overview
)
-
[
Actions
](
#actions
)
-
[
CMake
](
#cmake
)
-
[
Layers
](
#layers
)
-
[
Activations
](
#activations
)
-
[
Unit Tests
](
#unit-tests
)
-
[
Protobuf Messages
](
#protobuf-messages
)
-
[
Python API
](
#python-api
)
-
[
Demos
](
#demos
)
-
[
Benchmarking
](
#benchmarking
)
-
[
Others
](
#others
)
-
[
Design Concerns
](
#design-concerns
)
## Overview
我们会把MKL-DNN作为第三方库集成进PaddlePaddle,整体框架图
<div
align=
"center"
>
<img
src=
"image/overview.png"
width=
350
><br/>
Figure 1. PaddlePaddle on IA.
</div>
## Actions
我们把集成方案大致分为了如下几个方面。
### CMake
我们会在
`CMakeLists.txt`
中会添加
`WITH_MKLDNN`
的选项,当设置这个值为
`ON`
的时候会启用编译MKL-DNN功能。同时会自动开启OpenMP用于提高MKL-DNN的性能。
同时,我们会引入
`WITH_MKLML`
选项,用于选择是否使用MKL-DNN自带的MKLML安装包。这个安装包可以独立于MKL-DNN使用,但是建议在开启MKL-DNN的同时也打开MKLML的开关,这样才能发挥最好的性能。
所以,我们会在
`cmake/external`
目录新建
`mkldnn.cmake`
和
`mklml.cmake`
文件,它们会在编译PaddlePaddle的时候下载对应的软件包,并放到PaddlePaddle的third party目录中。
**备注**
:当
`WITH_MKLML=ON`
的时候,会优先使用这个包作为PaddlePaddle的CBLAS和LAPACK库,所以会稍微改动
`cmake/cblas.cmake`
中的逻辑。
### Layers
所有MKL-DNN相关的C++ layers,都会按照PaddlePaddle的目录结构存放在
`paddle/gserver/layers`
中,并且文件名都会一以
*Mkldnn*
开头。
所有MKL-DNN的layers都会继承于一个叫做
`MkldnnLayer`
的父类,该父类继承于PaddlePaddle的基类
`Layer`
。
### Activations
由于在PaddlePaddle中,激活函数是独立于layer概念的,所以会在
`paddle/gserver/activations`
目录下添加一个
`MkldnnActivation.h`
文件定义一些用于MKL-DNN的接口,实现方法还是会在
`ActivationFunction.cpp`
文件。
### Unit Tests
会在
`paddle/gserver/test`
目录下添加
`test_Mkldnn.cpp`
和
`MkldnnTester.*`
用于MKL-DNN的测试。
Activation的测试,计划在PaddlePaddle原有的测试文件上直接添加新的测试type。
### Protobuf Messages
根据具体layer的需求可能会在
`proto/ModelConfig.proto`
里面添加必要的选项。
### Python API
目前只考虑
**v1 API**
。
计划在
`python/paddle/trainer/config_parser.py`
里面添加
`use_mkldnn`
这个选择,方便用户选择使用MKL-DNN的layers。
具体实现方式比如:
```
python
use_mkldnn
=
bool
(
int
(
g_command_config_args
.
get
(
"use_mkldnn"
,
0
)))
if
use_mkldnn
self
.
layer_type
=
mkldnn_
*
```
所有MKL-DNN的layer type会以
*mkldnn_*
开头,以示区分。
并且可能在
`python/paddle/trainer_config_helper`
目录下的
`activations.py `
和
`layers.py`
里面添加必要的MKL-DNN的接口。
### Demos
会在
`v1_api_demo`
目录下添加一个
`mkldnn`
的文件夹,里面放入一些用于MKL-DNN测试的demo脚本。
### Benchmarking
会考虑添加部分逻辑在
`benchmark/paddle/image/run.sh`
,添加使用MKL-DNN的测试。
### Others
1.
如果在使用MKL-DNN的情况下,会把CPU的Buffer对齐为64。
2.
深入PaddlePaddle,寻找有没有其他可以优化的可能,进一步优化。比如可能会用OpenMP改进SGD的更新性能。
## Design Concerns
为了更好的符合PaddlePaddle的代码风格
\[
[
2
](
#references
)
\]
,同时又尽可能少的牺牲MKL-DNN的性能
\[
[
3
](
#references
)
\]
。
我们总结出一些特别需要注意的点:
1.
使用
**deviceId_**
。为了尽可能少的在父类Layer中添加变量或者函数,我们决定使用已有的
`deviceId_`
变量来区分layer的属性,定义
`-2`
为
`MkldnnLayer`
特有的设备ID。
2.
重写父类Layer的
**init**
函数,修改
`deviceId_`
为
`-2`
,代表这个layer是用于跑在MKL-DNN的环境下。
3.
创建
`MkldnnMatrix`
,用于管理MKL-DNN会用到的相关memory函数、接口以及会用的到格式信息。
4.
创建
`MkldnnBase`
,定义一些除了layer和memory相关的类和函数。包括MKL-DNN会用到
`MkldnnStream`
和
`CpuEngine`
,和未来可能还会用到
`FPGAEngine`
等。
5.
在
**Argument**
里添加两个
`MkldnnMatrixPtr`
,取名为
`mkldnnValue`
和
`mkldnnGrad`
,用于存放
`MkldnnLayer`
会用到的memory buffer。 并且添加函数cvt(会修改为一个更加合适的函数名),用于处理"CPU device"和"MKL-DNN device"之间memory的相互转化。
6.
在父类
`Layer`
中的
`getOutput`
函数中添加一段逻辑,用于判断
`deviceId`
,并针对device在MKL-DNN和CPU之间不统一的情况,做一个前期转换。 也就是调用
`Argument`
的cvt函数把output统一到需要的device上。
7.
在原来的
`FLAGS`
中添加一个
`use_mkldnn`
的flag,用于选择是否使用MKL-DNN的相关功能。
## References
1.
[
Intel Math Kernel Library for Deep Neural Networks (Intel MKL-DNN)
](
https://github.com/01org/mkl-dnn
"Intel MKL-DNN"
)
2.
[
原来的方案
](
https://github.com/PaddlePaddle/Paddle/pull/3096
)
会引入
**nextLayer**
的信息。但是在PaddlePaddle中,无论是重构前的layer还是重构后的op,都不会想要知道next layer/op的信息。
3.
MKL-DNN的高性能格式与PaddlePaddle原有的
`NCHW`
不同(PaddlePaddle中的CUDNN部分使用的也是
`NCHW`
,所以不存在这个问题),所以需要引入一个转换方法,并且只需要在必要的时候转换这种格式,才能更好的发挥MKL-DNN的性能。
doc/design/mkldnn/image/overview.png
0 → 100644
浏览文件 @
3e4c671c
9.7 KB
paddle/api/test/CMakeLists.txt
浏览文件 @
3e4c671c
add_python_test
(
test_swig_api
testArguments.py testGradientMachine.py testMatrix.py testVector.py testTrain.py testTrainer.py
)
py_test
(
testTrain SRCS testTrain.py
)
py_test
(
testMatrix SRCS testMatrix.py
)
py_test
(
testVector SRCS testVector.py
)
py_test
(
testTrainer SRCS testTrainer.py
)
py_test
(
testArguments SRCS testArguments.py
)
py_test
(
testGradientMachine SRCS testGradientMachine.py
)
paddle/framework/operator.h
浏览文件 @
3e4c671c
...
...
@@ -174,7 +174,11 @@ class OperatorContext {
template
<
typename
T
>
T
*
Output
(
const
size_t
index
)
const
{
auto
var
=
OutputVar
(
index
);
PADDLE_ENFORCE
(
var
!=
nullptr
,
"Output(%d) should not be nullptr"
,
index
);
PADDLE_ENFORCE
(
var
!=
nullptr
,
"Output(%d) not be nullptr, which means variable [%s] does not "
"exist in scope"
,
index
,
op_
.
outputs_
[
index
]);
return
var
->
GetMutable
<
T
>
();
}
...
...
paddle/gserver/tests/CMakeLists.txt
浏览文件 @
3e4c671c
# gserver pacakge unittests
file
(
GLOB_RECURSE GSERVER_HEADER RELATIVE
"
${
CMAKE_CURRENT_SOURCE_DIR
}
"
"*.h"
)
file
(
GLOB_RECURSE GSERVER_SOURCES RELATIVE
"
${
CMAKE_CURRENT_SOURCE_DIR
}
"
"*.cpp"
)
add_style_check_target
(
paddle_gserver
${
GSERVER_SOURCES
}
)
add_style_check_target
(
paddle_gserver
${
GSERVER_HEADER
}
)
################### test_ProtoDataProvider ############
add_unittest_without_exec
(
test_ProtoDataProvider
test_ProtoDataProvider.cpp
)
...
...
paddle/operators/add_op.cc
浏览文件 @
3e4c671c
...
...
@@ -20,8 +20,8 @@ namespace operators {
class
AddOp
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
InferShapeContext
&
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
.
InputSize
()
==
2
,
"Input size of AddOp must be two"
);
PADDLE_ENFORCE
(
ctx
.
OutputSize
()
==
1
,
"Output size of AddOp must be one"
);
PADDLE_ENFORCE
_EQ
(
ctx
.
InputSize
(),
2
);
PADDLE_ENFORCE
_EQ
(
ctx
.
OutputSize
(),
1
);
PADDLE_ENFORCE
(
ctx
.
InputVar
(
0
)
!=
nullptr
&&
ctx
.
InputVar
(
1
)
!=
nullptr
,
"Inputs of AddOp must all be set"
);
PADDLE_ENFORCE
(
ctx
.
OutputVar
(
0
)
!=
nullptr
,
...
...
paddle/operators/mul_op.cc
浏览文件 @
3e4c671c
...
...
@@ -23,12 +23,16 @@ class MulOp : public OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
.
InputSize
()
==
2
,
"The mul op must take two inputs"
);
auto
dim0
=
ctx
.
Input
<
Tensor
>
(
0
)
->
dims
();
auto
dim1
=
ctx
.
Input
<
Tensor
>
(
1
)
->
dims
();
PADDLE_ENFORCE
(
dim0
.
size
()
==
2
&&
dim1
.
size
()
==
2
,
"The input of mul op must be matrix"
);
PADDLE_ENFORCE
(
dim0
[
1
]
==
dim1
[
0
],
PADDLE_ENFORCE_EQ
(
dim0
.
size
(),
2
,
"input X(%s) should be a tensor with 2 dims, a matrix"
,
ctx
.
op_
.
Input
(
"X"
));
PADDLE_ENFORCE_EQ
(
dim1
.
size
(),
2
,
"input Y(%s) should be a tensor with 2 dims, a matrix"
,
ctx
.
op_
.
Input
(
"Y"
));
PADDLE_ENFORCE_EQ
(
dim0
[
1
],
dim1
[
0
],
"First matrix's width must be equal with second matrix's height."
);
PADDLE_ENFORCE
(
ctx
.
OutputSize
()
==
1
,
"The mul op must take
one output"
);
PADDLE_ENFORCE
_EQ
(
ctx
.
OutputSize
(),
1
,
"The mul op takes only
one output"
);
ctx
.
Output
<
Tensor
>
(
0
)
->
Resize
({
dim0
[
0
],
dim1
[
1
]});
}
};
...
...
paddle/operators/recurrent_op.cc
浏览文件 @
3e4c671c
...
...
@@ -36,6 +36,7 @@ void RecurrentAlgorithm::InferShape(const Scope& scope) const {
InitMemories
(
step_scopes
[
0
],
true
/*infer_shape_mode*/
);
Variable
*
net
=
scope
.
FindVar
(
arg_
->
step_net
);
PADDLE_ENFORCE
(
net
!=
nullptr
,
"failed to get step net"
);
for
(
size_t
i
=
0
;
i
<
seq_len_
;
i
++
)
{
if
(
i
>
0
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
i
,
-
1
,
...
...
@@ -56,6 +57,7 @@ void RecurrentAlgorithm::Run(const Scope& scope,
Variable
*
net
=
scope
.
FindVar
(
arg_
->
step_net
);
for
(
size_t
step_id
=
0
;
step_id
<
seq_len_
;
step_id
++
)
{
// create output alias variables
if
(
step_id
>
0
)
{
rnn
::
LinkMemories
(
step_scopes
,
arg_
->
memories
,
step_id
,
-
1
,
false
/*infer_shape_mode*/
);
...
...
@@ -67,22 +69,31 @@ void RecurrentAlgorithm::Run(const Scope& scope,
}
void
RecurrentAlgorithm
::
CreateScopes
(
const
Scope
&
scope
)
const
{
// TODO(
xxx
) Only two scopes are needed for inference, this case will be
// TODO(
superjom
) Only two scopes are needed for inference, this case will be
// supported later.
auto
step_scopes
=
scope
.
FindVar
(
arg_
->
step_scopes
)
->
GetMutable
<
std
::
vector
<
Scope
*>>
();
auto
step_scopes_var
=
scope
.
FindVar
(
arg_
->
step_scopes
);
PADDLE_ENFORCE
(
step_scopes_var
!=
nullptr
,
""
);
auto
step_scopes
=
step_scopes_var
->
GetMutable
<
std
::
vector
<
Scope
*>>
();
// Now all variables in scope must be created outside of op.
auto
net_var
=
scope
.
FindVar
(
arg_
->
step_net
);
PADDLE_ENFORCE
(
net_var
!=
nullptr
,
"no stepnet called %s in scope"
,
arg_
->
step_net
);
auto
net_op
=
net_var
->
GetMutable
<
NetOp
>
();
PADDLE_ENFORCE
(
!
net_op
->
outputs_
.
empty
(),
"net_op has no outputs"
);
if
(
seq_len_
>
step_scopes
->
size
())
{
for
(
size_t
i
=
step_scopes
->
size
();
i
<
seq_len_
;
++
i
)
{
auto
&
step_scope
=
scope
.
NewScope
();
// Now all variables in scope must be created outside of op.
auto
net_op
=
scope
.
FindVar
(
arg_
->
step_net
)
->
GetMutable
<
NetOp
>
();
// create step net's temp inputs
for
(
auto
&
input
:
net_op
->
inputs_
)
{
// the weight are located in parent scope
if
(
!
step_scope
.
FindVar
(
input
))
step_scope
.
NewVar
(
input
);
if
(
!
step_scope
.
FindVar
(
input
))
step_scope
.
NewVar
(
input
)
->
GetMutable
<
Tensor
>
();
}
for
(
auto
&
output
:
net_op
->
outputs_
)
{
// create stepnet's outputs
for
(
const
auto
&
output
:
net_op
->
outputs_
)
{
step_scope
.
NewVar
(
output
);
}
step_scopes
->
emplace_back
(
&
step_scope
);
...
...
@@ -100,6 +111,7 @@ void RecurrentAlgorithm::InitMemories(Scope* step_scope,
Tensor
*
boot_mem
=
step_scope
->
FindVar
(
attr
.
boot_var
)
->
GetMutable
<
Tensor
>
();
if
(
infer_shape_mode
)
{
pre_mem
->
Resize
(
boot_mem
->
dims
());
PADDLE_ENFORCE_EQ
(
pre_mem
->
dims
().
size
(),
2
);
}
else
{
pre_mem
->
ShareDataWith
<
float
>
(
*
boot_mem
);
}
...
...
paddle/operators/rnn/recurrent_op_utils.cc
浏览文件 @
3e4c671c
...
...
@@ -53,11 +53,13 @@ void ConcatOutputs(const std::vector<Scope*>& step_scopes,
PADDLE_ENFORCE
(
output_var
!=
nullptr
,
"output link [%s] is not in scope."
,
outlinks
[
i
].
external
);
Tensor
*
output
=
output_var
->
GetMutable
<
Tensor
>
();
if
(
infer_shape_mode
)
{
fmw
::
DDim
step_dims
=
step_scopes
[
0
]
->
FindVar
(
outlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
()
->
dims
();
auto
step_scope_var
=
step_scopes
[
0
]
->
FindVar
(
outlinks
[
i
].
internal
);
PADDLE_ENFORCE
(
step_scope_var
!=
nullptr
,
"%s not in scope"
,
outlinks
[
i
].
internal
);
fmw
::
DDim
step_dims
=
step_scope_var
->
template
GetMutable
<
Tensor
>()
->
dims
();
std
::
vector
<
int
>
dims_vec
=
vectorize
(
step_dims
);
dims_vec
.
insert
(
dims_vec
.
begin
(),
seq_len
);
output
->
Resize
(
fmw
::
make_ddim
(
dims_vec
));
...
...
@@ -79,14 +81,15 @@ void LinkMemories(const std::vector<Scope*>& scopes,
const
std
::
vector
<
rnn
::
MemoryAttr
>&
memories
,
const
size_t
step_id
,
const
int
offset
,
bool
infer_shape_mode
)
{
PADDLE_ENFORCE
(
step_id
<
scopes
.
size
(),
"step [%d] is out of range of step scopes' size [%d]"
,
step_id
,
scopes
.
size
());
PADDLE_ENFORCE
(
static_cast
<
int
>
(
step_id
)
+
offset
>=
0
,
"offset [%d] must be large than -[%d]"
,
offset
,
step_id
);
PADDLE_ENFORCE
(
step_id
+
offset
<
scopes
.
size
(),
"offset [%d] is out of range, it must be less than (%d - %d)"
,
offset
,
scopes
.
size
(),
step_id
);
PADDLE_ENFORCE_LT
(
step_id
,
scopes
.
size
(),
"step [%d] is out of range of step scopes' size [%d]"
,
step_id
,
scopes
.
size
());
PADDLE_ENFORCE_GE
(
static_cast
<
int
>
(
step_id
)
+
offset
,
0
,
"offset [%d] must be large than -[%d]"
,
offset
,
step_id
);
PADDLE_ENFORCE_LT
(
step_id
+
offset
,
scopes
.
size
(),
"offset [%d] is out of range, it must be less than (%d - %d)"
,
offset
,
scopes
.
size
(),
step_id
);
auto
scope
=
scopes
[
step_id
];
auto
linked_scope
=
scopes
[
step_id
+
offset
];
for
(
auto
&
attr
:
memories
)
{
...
...
paddle/operators/sigmoid_op.cc
浏览文件 @
3e4c671c
...
...
@@ -37,10 +37,8 @@ class SigmoidOpMaker : public OpProtoAndCheckerMaker {
class
SigmoidOpGrad
:
public
OperatorWithKernel
{
protected:
void
InferShape
(
const
InferShapeContext
&
ctx
)
const
override
{}
std
::
string
DebugString
()
const
override
{
LOG
(
INFO
)
<<
"SigmoidGrad"
;
return
""
;
void
InferShape
(
const
InferShapeContext
&
ctx
)
const
override
{
ctx
.
Output
<
Tensor
>
(
0
)
->
Resize
(
ctx
.
Input
<
Tensor
>
(
0
)
->
dims
());
}
};
...
...
@@ -51,3 +49,5 @@ REGISTER_OP(sigmoid, ops::SigmoidOp, ops::SigmoidOpMaker);
REGISTER_GRADIENT_OP
(
sigmoid
,
sigmoid_grad
,
ops
::
SigmoidOpGrad
);
REGISTER_OP_CPU_KERNEL
(
sigmoid
,
ops
::
SigmoidKernel
<
ops
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
sigmoid_grad
,
ops
::
SigmoidGradKernel
<
ops
::
CPUPlace
,
float
>
);
paddle/operators/sigmoid_op.cu
浏览文件 @
3e4c671c
...
...
@@ -16,3 +16,5 @@
#include "paddle/operators/sigmoid_op.h"
REGISTER_OP_GPU_KERNEL
(
sigmoid
,
ops
::
SigmoidKernel
<
ops
::
GPUPlace
,
float
>
);
REGISTER_OP_GPU_KERNEL
(
sigmoid_grad
,
ops
::
SigmoidGradKernel
<
ops
::
GPUPlace
,
float
>
);
paddle/operators/sigmoid_op.h
浏览文件 @
3e4c671c
...
...
@@ -27,6 +27,7 @@ class SigmoidKernel : public OpKernel {
auto
output
=
context
.
Output
<
Tensor
>
(
0
);
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
// The clipping is used in Paddle's raw implenmention
auto
X
=
EigenVector
<
T
>::
Flatten
(
*
input
);
auto
Y
=
EigenVector
<
T
>::
Flatten
(
*
output
);
auto
place
=
context
.
GetEigenDevice
<
Place
>
();
...
...
@@ -34,5 +35,23 @@ class SigmoidKernel : public OpKernel {
Y
.
device
(
place
)
=
1.0
/
(
1.0
+
(
-
1.0
*
X
).
exp
());
}
};
template
<
typename
Place
,
typename
T
>
class
SigmoidGradKernel
:
public
OpKernel
{
public:
void
Compute
(
const
ExecutionContext
&
context
)
const
override
{
auto
Y_t
=
context
.
Input
<
Tensor
>
(
"Y"
);
auto
dY_t
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
dX_t
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
dX_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
dX
=
EigenVector
<
T
>::
Flatten
(
*
dX_t
);
auto
Y
=
EigenVector
<
T
>::
Flatten
(
*
Y_t
);
auto
dY
=
EigenVector
<
T
>::
Flatten
(
*
dY_t
);
dX
.
device
(
context
.
GetEigenDevice
<
Place
>
())
=
dY
*
Y
*
(
1.
-
Y
);
}
};
}
// namespace operators
}
// namespace paddle
paddle/trainer/tests/simple_sparse_neural_network.py
浏览文件 @
3e4c671c
from
paddle.trainer_config_helpers
import
*
settings
(
batch_size
=
1
28
,
learning_method
=
AdaGradOptimizer
(),
learning_rate
=
1e-4
)
settings
(
batch_size
=
1
7
,
learning_method
=
AdaGradOptimizer
(),
learning_rate
=
1e-4
)
file_list
=
'trainer/tests/fake_file_list.list'
...
...
@@ -12,7 +12,7 @@ define_py_data_sources2(
embedding
=
embedding_layer
(
input
=
data_layer
(
name
=
"word_ids"
,
size
=
65536
),
name
=
"word_ids"
,
size
=
8191
),
size
=
128
,
param_attr
=
ParamAttr
(
sparse_update
=
True
))
prediction
=
fc_layer
(
input
=
embedding
,
size
=
10
,
act
=
SoftmaxActivation
())
...
...
paddle/trainer/tests/simple_sparse_neural_network_dp.py
浏览文件 @
3e4c671c
...
...
@@ -7,15 +7,15 @@ def init_hook(settings, is_train, **kwargs):
@
provider
(
input_types
=
{
'word_ids'
:
integer_value
(
65536
),
input_types
=
{
'word_ids'
:
integer_value
(
8191
),
'label'
:
integer_value
(
10
)},
min_pool_size
=
0
,
init_hook
=
init_hook
)
def
process
(
settings
,
filename
):
if
settings
.
is_train
:
data_size
=
2
**
20
else
:
data_size
=
2
**
10
else
:
data_size
=
2
**
5
for
_
in
xrange
(
data_size
):
yield
random
.
randint
(
0
,
65535
),
random
.
randint
(
0
,
9
)
yield
random
.
randint
(
0
,
8190
),
random
.
randint
(
0
,
9
)
paddle/trainer/tests/test_TrainerOnePass.cpp
浏览文件 @
3e4c671c
...
...
@@ -100,25 +100,25 @@ TEST(average_window, gpu) {
}
TEST
(
average_window
,
gpu2
)
{
FLAGS_num_passes
=
10
0
;
FLAGS_num_passes
=
2
0
;
trainerOnePassTest
(
configFile1
,
true
,
false
,
2
,
0.01
);
FLAGS_num_passes
=
1
;
}
TEST
(
average_window
,
gpu4
)
{
FLAGS_num_passes
=
10
0
;
FLAGS_num_passes
=
2
0
;
trainerOnePassTest
(
configFile1
,
true
,
false
,
4
,
0.01
);
FLAGS_num_passes
=
1
;
}
TEST
(
average_window_cpu
,
gpu2
)
{
FLAGS_num_passes
=
10
0
;
FLAGS_num_passes
=
2
0
;
trainerOnePassTest
(
configFile1
,
true
,
false
,
2
,
0.01
,
true
);
FLAGS_num_passes
=
1
;
}
TEST
(
average_window_cpu
,
gpu4
)
{
FLAGS_num_passes
=
10
0
;
FLAGS_num_passes
=
2
0
;
trainerOnePassTest
(
configFile1
,
true
,
false
,
4
,
0.01
,
true
);
FLAGS_num_passes
=
1
;
}
...
...
python/paddle/v2/framework/tests/CMakeLists.txt
浏览文件 @
3e4c671c
add_python_test
(
test_framework
test_protobuf.py
test_scope.py
test_default_scope_funcs.py
test_op_creation_methods.py
test_net.py
test_tensor.py
test_fc_op.py
test_add_two_op.py
test_sgd_op.py
test_mul_op.py
test_mean_op.py
test_sigmoid_op.py
test_softmax_op.py
test_rowwise_add_op.py
test_network.py
gradient_checker.py
)
py_test
(
test_net SRCS test_net.py
)
py_test
(
test_fc_op SRCS test_fc_op.py
)
py_test
(
test_scope SRCS test_scope.py
)
py_test
(
test_tensor SRCS test_tensor.py
)
py_test
(
test_mul_op SRCS test_mul_op.py
)
py_test
(
test_network SRCS test_network.py
)
py_test
(
test_mean_op SRCS test_mean_op.py
)
py_test
(
test_protobuf SRCS test_protobuf.py
)
py_test
(
test_add_two_op SRCS test_add_two_op.py
)
py_test
(
test_sigmoid_op SRCS test_sigmoid_op.py
)
py_test
(
test_softmax_op SRCS test_softmax_op.py
)
py_test
(
gradient_checker SRCS gradient_checker.py
)
py_test
(
test_rowwise_add_op SRCS test_rowwise_add_op.py
)
py_test
(
test_default_scope_funcs SRCS test_default_scope_funcs.py
)
py_test
(
test_op_creation_methods SRCS test_op_creation_methods.py
)
python/paddle/v2/framework/tests/test_recurrent_op.py
浏览文件 @
3e4c671c
import
logging
import
paddle.v2.framework.core
as
core
import
unittest
import
numpy
as
np
...
...
@@ -7,10 +8,9 @@ ops = creation.op_creations
def
create_tensor
(
scope
,
name
,
shape
):
tensor
=
scope
.
create
_var
(
name
).
get_tensor
()
tensor
=
scope
.
new
_var
(
name
).
get_tensor
()
tensor
.
set_dims
(
shape
)
tensor
.
alloc_float
()
tensor
.
set
(
np
.
random
.
random
(
shape
))
tensor
.
set
(
np
.
random
.
random
(
shape
),
core
.
CPUPlace
())
return
tensor
...
...
@@ -31,40 +31,36 @@ class TestRNN(unittest.TestCase):
- h
'''
input_dim
=
30
batch_size
=
50
weight_dim
=
15
sent_len
=
11
def
init
(
self
):
input_dim
=
30
batch_size
=
50
weight_dim
=
15
self
.
scope
=
core
.
Scope
(
None
)
# create vars
create_tensor
(
self
.
scope
,
"x"
,
[
batch_size
,
input_dim
])
create_tensor
(
self
.
scope
,
"W"
,
[
input_dim
,
weight_dim
])
create_tensor
(
self
.
scope
,
"U"
,
[
weight_dim
,
weight_dim
])
create_tensor
(
self
.
scope
,
"h_boot"
,
[
batch_size
,
weight_dim
])
x_alias
=
"x@alias"
y_alias
=
"y@alias"
memory
=
"h@alias"
prememory
=
"h@pre"
output
=
"rnn_out"
output_alias
=
"rnn_out@alias"
# create step net
stepnet_var
=
self
.
scope
.
create_var
(
"stepnet"
)
stepnet
=
stepnet_var
.
get_net
()
# stepnet = core.Net.create()
x_fc_op
=
ops
.
fc
(
X
=
x_alias
,
W
=
"W"
,
Y
=
"Wx"
)
h_fc_op
=
ops
.
fc
(
X
=
prememory
,
W
=
"U"
,
Y
=
"Uh"
)
sum_op
=
ops
.
add_two
(
X
=
"Wx"
,
Y
=
"Uh"
,
Out
=
"sum"
)
sig_op
=
ops
.
sigmoid
(
X
=
"sum"
,
Y
=
memory
)
stepnet
.
add_op
(
x_fc_op
)
stepnet
.
add_op
(
h_fc_op
)
stepnet
.
add_op
(
sum_op
)
stepnet
.
add_op
(
sig_op
)
stepnet
.
complete_add_op
(
True
)
self
.
scope
=
core
.
Scope
()
self
.
create_global_variables
()
self
.
create_step_net
()
rnn_op
=
self
.
create_rnn_op
()
ctx
=
core
.
DeviceContext
.
create
(
core
.
CPUPlace
())
print
'infer_shape'
rnn_op
.
infer_shape
(
self
.
scope
)
rnn_op
.
run
(
self
.
scope
,
ctx
)
def
create_global_variables
(
self
):
# create inlink
create_tensor
(
self
.
scope
,
"x"
,
[
self
.
sent_len
,
self
.
batch_size
,
self
.
input_dim
])
create_tensor
(
self
.
scope
,
"W"
,
[
self
.
input_dim
,
self
.
input_dim
])
create_tensor
(
self
.
scope
,
"U"
,
[
self
.
input_dim
,
self
.
input_dim
])
create_tensor
(
self
.
scope
,
"h_boot"
,
[
self
.
batch_size
,
self
.
input_dim
])
self
.
scope
.
new_var
(
"step_scopes"
)
self
.
scope
.
new_var
(
"h@alias"
)
self
.
scope
.
new_var
(
"h"
)
def
create_rnn_op
(
self
):
# create RNNOp
rnnop
=
ops
.
recurrent_op
(
# inputs
...
...
@@ -72,17 +68,27 @@ class TestRNN(unittest.TestCase):
boot_memories
=
[
"h_boot"
],
step_net
=
"stepnet"
,
# outputs
outlinks
=
[
output
],
outlinks
=
[
"h"
],
step_scopes
=
"step_scopes"
,
# attributes
inlink_alias
=
[
"x@alias"
],
outlink_alias
=
[
output_alias
],
pre_memories
=
[
prememory
],
memories
=
[
memory
])
outlink_alias
=
[
"h@alias"
],
pre_memories
=
[
"h@pre"
],
memories
=
[
"h@alias"
])
return
rnnop
def
create_step_net
(
self
):
var
=
self
.
scope
.
new_var
(
"stepnet"
)
stepnet
=
var
.
get_net
()
ctx
=
core
.
DeviceContext
.
cpu_context
()
rnnop
.
infer_shape
(
self
.
scope
)
rnnop
.
run
(
self
.
scope
,
ctx
)
x_fc_op
=
ops
.
fc
(
X
=
"x@alias"
,
W
=
"W"
,
Y
=
"Wx"
)
h_fc_op
=
ops
.
fc
(
X
=
"h@pre"
,
W
=
"U"
,
Y
=
"Uh"
)
sum_op
=
ops
.
add_two
(
X
=
"Wx"
,
Y
=
"Uh"
,
Out
=
"sum"
)
sig_op
=
ops
.
sigmoid
(
X
=
"sum"
,
Y
=
"h@alias"
)
for
op
in
[
x_fc_op
,
h_fc_op
,
sum_op
,
sig_op
]:
stepnet
.
add_op
(
op
)
stepnet
.
complete_add_op
(
True
)
def
test_recurrent
(
self
):
self
.
init
()
...
...
python/paddle/v2/framework/tests/test_sigmoid_op.py
浏览文件 @
3e4c671c
...
...
@@ -12,5 +12,8 @@ class TestSigmoidOp(unittest.TestCase):
self
.
outputs
=
{
'Y'
:
1
/
(
1
+
np
.
exp
(
-
self
.
inputs
[
'X'
]))}
#class TestSigmoidGradOp(unittest.TestCase):
#TODO(qingqing) add unit test
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/v2/plot/tests/CMakeLists.txt
浏览文件 @
3e4c671c
if
(
NOT APPLE
)
# The Mac OS X backend will not be able to function correctly if Python is
# not installed as a framework.
add_python_test
(
test_ploter
test_ploter.py
)
py_test
(
test_ploter SRCS
test_ploter.py
)
endif
()
python/paddle/v2/reader/tests/CMakeLists.txt
浏览文件 @
3e4c671c
add_python_test
(
reader_tests creator_test.py decorator_test.py
)
py_test
(
creator_test SRCS creator_test.py
)
py_test
(
decorator_test SRCS decorator_test.py
)
python/paddle/v2/tests/CMakeLists.txt
浏览文件 @
3e4c671c
add_python_test
(
test_v2_api test_data_feeder.py test_op.py test_parameters.py
test_layer.py test_rnn_layer.py test_topology.py test_image.py
)
py_test
(
test_op SRCS test_op.py
)
py_test
(
test_image SRCS test_image.py
)
py_test
(
test_layer SRCS test_layer.py
)
py_test
(
test_topology SRCS test_topology.py
)
py_test
(
test_rnn_layer SRCS test_rnn_layer.py
)
py_test
(
test_parameters SRCS test_parameters.py
)
py_test
(
test_data_feeder SRCS test_data_feeder.py
)
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