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afb5496c
编写于
1月 01, 2018
作者:
S
sweetsky0901
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 detection_output
上级
d52fd00a
62166317
变更
31
显示空白变更内容
内联
并排
Showing
31 changed file
with
700 addition
and
78 deletion
+700
-78
benchmark/IntelOptimizedPaddle.md
benchmark/IntelOptimizedPaddle.md
+9
-0
benchmark/paddle/image/alexnet.py
benchmark/paddle/image/alexnet.py
+5
-1
benchmark/paddle/image/run_openblas_infer.sh
benchmark/paddle/image/run_openblas_infer.sh
+10
-6
benchmark/paddle/image/run_openblas_train.sh
benchmark/paddle/image/run_openblas_train.sh
+1
-1
doc/getstarted/build_and_install/docker_install_cn.rst
doc/getstarted/build_and_install/docker_install_cn.rst
+4
-4
doc/getstarted/build_and_install/docker_install_en.rst
doc/getstarted/build_and_install/docker_install_en.rst
+3
-3
doc/getstarted/build_and_install/pip_install_cn.rst
doc/getstarted/build_and_install/pip_install_cn.rst
+2
-2
doc/getstarted/build_and_install/pip_install_en.rst
doc/getstarted/build_and_install/pip_install_en.rst
+2
-2
doc/getstarted/index_cn.rst
doc/getstarted/index_cn.rst
+2
-2
doc/getstarted/index_en.rst
doc/getstarted/index_en.rst
+2
-2
paddle/framework/CMakeLists.txt
paddle/framework/CMakeLists.txt
+10
-2
paddle/framework/data_transform.h
paddle/framework/data_transform.h
+2
-3
paddle/framework/data_transform_test.cc
paddle/framework/data_transform_test.cc
+8
-7
paddle/framework/executor.cc
paddle/framework/executor.cc
+27
-6
paddle/framework/operator.cc
paddle/framework/operator.cc
+23
-9
paddle/framework/tensor_util.cc
paddle/framework/tensor_util.cc
+119
-0
paddle/framework/tensor_util.cu
paddle/framework/tensor_util.cu
+1
-0
paddle/framework/tensor_util.h
paddle/framework/tensor_util.h
+8
-0
paddle/framework/tensor_util_test.cc
paddle/framework/tensor_util_test.cc
+24
-0
paddle/framework/tensor_util_test.cu
paddle/framework/tensor_util_test.cu
+57
-0
paddle/framework/threadpool.h
paddle/framework/threadpool.h
+13
-6
paddle/framework/threadpool_test.cc
paddle/framework/threadpool_test.cc
+12
-7
paddle/function/GemmConvOp.cpp
paddle/function/GemmConvOp.cpp
+158
-3
paddle/function/Im2Col.h
paddle/function/Im2Col.h
+50
-0
paddle/function/Im2ColTest.cpp
paddle/function/Im2ColTest.cpp
+82
-0
paddle/platform/device_context.h
paddle/platform/device_context.h
+20
-0
paddle/platform/place.h
paddle/platform/place.h
+27
-1
paddle/pybind/CMakeLists.txt
paddle/pybind/CMakeLists.txt
+3
-0
paddle/scripts/submit_local.sh.in
paddle/scripts/submit_local.sh.in
+14
-9
python/paddle/v2/dataset/flowers.py
python/paddle/v2/dataset/flowers.py
+1
-1
python/paddle/v2/fluid/__init__.py
python/paddle/v2/fluid/__init__.py
+1
-1
未找到文件。
benchmark/IntelOptimizedPaddle.md
浏览文件 @
afb5496c
...
...
@@ -93,6 +93,15 @@ Test on batch size 1, 2, 4, 8, 16 on Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz
| MKLML | 22.74 | 41.56 | 81.22 | 133.47 | 210.53 |
| MKL-DNN | 175.10 | 272.92 | 450.70 | 512.00 | 600.94 |
-
Alexnet
| BatchSize | 1 | 2 | 4 | 8 | 16 |
|-----------|--------|--------|--------|--------|--------|
| OpenBLAS | | | | | |
| MKLML | 21.32 | 36.55 | 73.06 | 131.15 | 192.77 |
| MKL-DNN | 442.91 | 656.41 | 719.10 | 847.68 | 850.51 |
chart TBD
### Laptop
TBD
benchmark/paddle/image/alexnet.py
浏览文件 @
afb5496c
...
...
@@ -19,7 +19,11 @@ args = {
'num_samples'
:
num_samples
}
define_py_data_sources2
(
"train.list"
,
None
,
module
=
"provider"
,
obj
=
"process"
,
args
=
args
)
"train.list"
if
not
is_infer
else
None
,
"test.list"
if
is_infer
else
None
,
module
=
"provider"
,
obj
=
"process"
,
args
=
args
)
settings
(
batch_size
=
batch_size
,
...
...
benchmark/paddle/image/run_openblas_infer.sh
浏览文件 @
afb5496c
...
...
@@ -8,15 +8,19 @@ function clock_to_seconds() {
}
function
infer
()
{
unset
OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
topology
=
$1
layer_num
=
$2
bs
=
$3
t
hread
=
`
nproc
`
if
[
$t
hread
-gt
$bs
]
;
then
t
hread
=
$bs
t
rainers
=
`
nproc
`
if
[
$t
rainers
-gt
$bs
]
;
then
t
rainers
=
$bs
fi
log
=
"logs/infer-
${
topology
}
-
${
layer_num
}
-
${
thread
}
openblas-
${
bs
}
.log"
log
=
"logs/infer-
${
topology
}
-
${
layer_num
}
-
${
trainers
}
openblas-
${
bs
}
.log"
threads
=
$((
`
nproc
`
/
trainers
))
if
[
$threads
-eq
0
]
;
then
threads
=
1
fi
export
OPENBLAS_NUM_THREADS
=
$threads
models_in
=
"models/
${
topology
}
-
${
layer_num
}
/pass-00000/"
if
[
!
-d
$models_in
]
;
then
...
...
@@ -28,7 +32,7 @@ function infer() {
--config
=
"
${
topology
}
.py"
\
--use_mkldnn
=
False
\
--use_gpu
=
False
\
--trainer_count
=
$t
hread
\
--trainer_count
=
$t
rainers
\
--log_period
=
$log_period
\
--config_args
=
"batch_size=
${
bs
}
,layer_num=
${
layer_num
}
,is_infer=True,num_samples=256"
\
--init_model_path
=
$models_in
\
...
...
benchmark/paddle/image/run_openblas_train.sh
浏览文件 @
afb5496c
set
-e
function
train
()
{
unset
OMP_NUM_THREADS MKL_NUM_THREADS OMP_DYNAMIC KMP_AFFINITY
export
OPENBLAS_NUM_THREADS
=
1
topology
=
$1
layer_num
=
$2
bs
=
$3
...
...
doc/getstarted/build_and_install/docker_install_cn.rst
浏览文件 @
afb5496c
...
...
@@ -15,7 +15,7 @@
获取PaddlePaddle的Docker镜像
------------------------------
执行下面的命令获取最新的PaddlePaddle Docker镜像
执行下面的命令获取最新的PaddlePaddle Docker镜像
,版本为cpu_avx_mkl:
.. code-block:: bash
...
...
@@ -27,7 +27,7 @@
docker pull docker.paddlepaddle.org/paddle
下载GPU版本的Docker镜像:
下载GPU版本
(cuda8.0_cudnn5_avx_mkl)
的Docker镜像:
.. code-block:: bash
...
...
@@ -54,7 +54,7 @@
.. _docker_run:
在Docker中执行PaddlePaddle训练程序
------------------------------
------------------------------
----
假设您已经在当前目录(比如在/home/work)编写了一个PaddlePaddle的程序 :code:`train.py` (可以参考
`PaddlePaddleBook <http://www.paddlepaddle.org/docs/develop/book/01.fit_a_line/index.cn.html>`_
...
...
@@ -82,7 +82,7 @@
.. _docker_run_book:
使用Docker启动PaddlePaddle Book教程
------------------------------
------------------------------
-----
使用Docker可以快速在本地启动一个包含了PaddlePaddle官方Book教程的Jupyter Notebook,可以通过网页浏览。
PaddlePaddle Book是为用户和开发者制作的一个交互式的Jupyter Notebook。
...
...
doc/getstarted/build_and_install/docker_install_en.rst
浏览文件 @
afb5496c
...
...
@@ -16,7 +16,7 @@ After you've read above tutorials you may proceed the following steps.
Pull PaddlePaddle Docker Image
------------------------------
Run the following command to download the latest Docker images:
Run the following command to download the latest Docker images
, the version is cpu_avx_mkl
:
.. code-block:: bash
...
...
@@ -28,7 +28,7 @@ For users in China, we provide a faster mirror:
docker pull docker.paddlepaddle.org/paddle
Download GPU version images:
Download GPU version
(cuda8.0_cudnn5_avx_mkl)
images:
.. code-block:: bash
...
...
@@ -58,7 +58,7 @@ and run:
.. _docker_run:
Launch your training program in Docker
------------------------------
------------------------------
--------
Assume that you have already written a PaddlePaddle program
named :code:`train.py` under directory :code:`/home/work` (refer to
...
...
doc/getstarted/build_and_install/pip_install_cn.rst
浏览文件 @
afb5496c
...
...
@@ -11,14 +11,14 @@ PaddlePaddle可以使用常用的Python包管理工具
------------------------------
执行下面的命令即可在当前机器上安装PaddlePaddle的运行时环境,并自动下载安装依赖软件。
执行下面的命令即可在当前机器上安装PaddlePaddle的运行时环境,并自动下载安装依赖软件
,版本为cpu_avx_openblas
。
.. code-block:: bash
pip install paddlepaddle
如果需要安装支持GPU的版本,需要执行:
如果需要安装支持GPU的版本
(cuda7.5_cudnn5_avx_openblas)
,需要执行:
.. code-block:: bash
...
...
doc/getstarted/build_and_install/pip_install_en.rst
浏览文件 @
afb5496c
...
...
@@ -12,14 +12,14 @@ Install Using pip
------------------------------
Run the following command to install PaddlePaddle on the current
machine, it will also download requirements.
machine, it will also download requirements
, the version is cpu_avx_openblas
.
.. code-block:: bash
pip install paddlepaddle
If you wish to install GPU version, just run:
If you wish to install GPU version
(cuda7.5_cudnn5_avx_openblas)
, just run:
.. code-block:: bash
...
...
doc/getstarted/index_cn.rst
浏览文件 @
afb5496c
...
...
@@ -7,13 +7,13 @@
++++++++
PaddlePaddle支持使用pip快速安装,目前支持CentOS 6以上, Ubuntu 14.04以及MacOS 10.12,并安装有Python2.7。
执行下面的命令完成快速安装:
执行下面的命令完成快速安装
,版本为cpu_avx_openblas
:
.. code-block:: bash
pip install paddlepaddle
如果需要安装支持GPU的版本,需要执行:
如果需要安装支持GPU的版本
(cuda7.5_cudnn5_avx_openblas)
,需要执行:
.. code-block:: bash
...
...
doc/getstarted/index_en.rst
浏览文件 @
afb5496c
...
...
@@ -8,13 +8,13 @@ Quick Install
You can use pip to install PaddlePaddle with a single command, supports
CentOS 6 above, Ubuntu 14.04 above or MacOS 10.12, with Python 2.7 installed.
Simply run the following command to install:
Simply run the following command to install
, the version is cpu_avx_openblas
:
.. code-block:: bash
pip install paddlepaddle
If you need to install GPU version, run:
If you need to install GPU version
(cuda7.5_cudnn5_avx_openblas)
, run:
.. code-block:: bash
...
...
paddle/framework/CMakeLists.txt
浏览文件 @
afb5496c
...
...
@@ -5,10 +5,18 @@ cc_library(ddim SRCS ddim.cc DEPS eigen3)
cc_test
(
ddim_test SRCS ddim_test.cc DEPS ddim
)
nv_test
(
dim_test SRCS dim_test.cu DEPS ddim
)
cc_library
(
tensor SRCS tensor.cc DEPS ddim place paddle_memory device_context framework_proto
)
if
(
WITH_GPU
)
nv_library
(
tensor SRCS tensor.cc tensor_util.cu DEPS ddim place paddle_memory device_context framework_proto
)
else
()
cc_library
(
tensor SRCS tensor.cc tensor_util.cc DEPS ddim place paddle_memory device_context framework_proto
)
endif
()
cc_test
(
tensor_test SRCS tensor_test.cc DEPS tensor
)
cc_test
(
tensor_util_test SRCS tensor_util_test.cc DEPS tensor
)
if
(
WITH_GPU
)
nv_test
(
tensor_util_test SRCS tensor_util_test.cc tensor_util_test.cu DEPS tensor
)
else
()
cc_test
(
tensor_util_test SRCS tensor_util_test.cc DEPS tensor
)
endif
()
cc_test
(
eigen_test SRCS eigen_test.cc DEPS tensor
)
...
...
paddle/framework/data_transform.h
浏览文件 @
afb5496c
...
...
@@ -27,8 +27,7 @@ limitations under the License. */
namespace
paddle
{
namespace
framework
{
using
DataTransformFn
=
std
::
function
<
void
(
const
std
::
vector
<
platform
::
DeviceContext
*>
ctx
,
using
DataTransformFn
=
std
::
function
<
void
(
const
platform
::
DeviceContext
*
ctx
,
const
Variable
&
in
,
Variable
*
out
)
>
;
using
KernelTypePair
=
std
::
pair
<
OpKernelType
,
OpKernelType
>
;
...
...
paddle/framework/data_transform_test.cc
浏览文件 @
afb5496c
...
...
@@ -54,18 +54,18 @@ auto kernel1 = GenFromBit({0, 0, 0, 1});
auto
kernel2
=
GenFromBit
({
0
,
0
,
1
,
0
});
auto
kernel3
=
GenFromBit
({
0
,
0
,
1
,
1
});
void
TransDataType_t
(
std
::
vector
<
platform
::
DeviceContext
*>
ctx
,
const
Variable
&
in
,
Variable
*
out
)
{
void
TransDataType_t
(
const
platform
::
DeviceContext
*
ctx
,
const
Variable
&
in
,
Variable
*
out
)
{
test_value
++
;
}
void
TransDataLayout_t
(
std
::
vector
<
platform
::
DeviceContext
*>
ctx
,
const
Variable
&
in
,
Variable
*
out
)
{
void
TransDataLayout_t
(
const
platform
::
DeviceContext
*
ctx
,
const
Variable
&
in
,
Variable
*
out
)
{
test_value
--
;
}
void
TransLibraryType_t
(
std
::
vector
<
platform
::
DeviceContext
*>
ctx
,
const
Variable
&
in
,
Variable
*
out
)
{
void
TransLibraryType_t
(
const
platform
::
DeviceContext
*
ctx
,
const
Variable
&
in
,
Variable
*
out
)
{
test_value
+=
2
;
}
...
...
@@ -83,7 +83,8 @@ TEST(DataTransform, Register) {
using
namespace
paddle
::
platform
;
auto
&
instance
=
DataTransformFnMap
::
Instance
();
std
::
vector
<
DeviceContext
*>
ctx
;
ASSERT_EQ
(
instance
.
Map
().
size
(),
3UL
);
DeviceContext
*
ctx
=
nullptr
;
paddle
::
framework
::
Variable
in
;
paddle
::
framework
::
Variable
out
;
...
...
paddle/framework/executor.cc
浏览文件 @
afb5496c
...
...
@@ -14,18 +14,17 @@ limitations under the License. */
#include "paddle/framework/executor.h"
#include <algorithm>
#include <iostream>
#include <memory>
#include <set>
#include <vector>
#include "gflags/gflags.h"
#include "paddle/framework/feed_fetch_type.h"
#include "paddle/framework/lod_rank_table.h"
#include "paddle/framework/lod_tensor.h"
#include "paddle/framework/lod_tensor_array.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/scope.h"
DEFINE_bool
(
check_nan_inf
,
false
,
"Checking whether operator produce NAN/INF or not. It will be "
"extremely slow so please use this flag wisely."
);
namespace
paddle
{
namespace
framework
{
...
...
@@ -58,6 +57,19 @@ static void CreateTensor(Variable* var, proto::VarDesc::VarType var_type) {
}
}
static
void
CheckTensorNANOrInf
(
const
std
::
string
&
name
,
const
framework
::
Tensor
&
tensor
)
{
if
(
tensor
.
memory_size
()
==
0
)
{
return
;
}
if
(
tensor
.
type
().
hash_code
()
!=
typeid
(
float
).
hash_code
()
&&
tensor
.
type
().
hash_code
()
!=
typeid
(
double
).
hash_code
())
{
return
;
}
PADDLE_ENFORCE
(
!
framework
::
HasInf
(
tensor
),
"Tensor %s has Inf"
,
name
);
PADDLE_ENFORCE
(
!
framework
::
HasNAN
(
tensor
),
"Tensor %s has NAN"
,
name
);
}
void
Executor
::
Run
(
const
ProgramDesc
&
pdesc
,
Scope
*
scope
,
int
block_id
,
bool
create_local_scope
,
bool
create_vars
)
{
// TODO(tonyyang-svail):
...
...
@@ -101,6 +113,15 @@ void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id,
auto
op
=
paddle
::
framework
::
OpRegistry
::
CreateOp
(
*
op_desc
);
VLOG
(
3
)
<<
op
->
DebugString
();
op
->
Run
(
*
local_scope
,
place_
);
if
(
FLAGS_check_nan_inf
)
{
for
(
auto
&
vname
:
op
->
OutputVars
(
true
))
{
auto
*
var
=
local_scope
->
FindVar
(
vname
);
if
(
var
==
nullptr
)
continue
;
if
(
var
->
IsType
<
framework
::
LoDTensor
>
())
{
CheckTensorNANOrInf
(
vname
,
var
->
Get
<
framework
::
LoDTensor
>
());
}
}
}
}
if
(
create_vars
&&
create_local_scope
)
{
scope
->
DeleteScope
(
local_scope
);
...
...
paddle/framework/operator.cc
浏览文件 @
afb5496c
...
...
@@ -384,6 +384,24 @@ class RuntimeInferShapeContext : public InferShapeContext {
const
Scope
&
scope_
;
};
const
platform
::
DeviceContext
*
GetDeviceContext
(
framework
::
KernelTypePair
&
kernel_pair
)
{
auto
&
actual_kernel_key
=
kernel_pair
.
first
;
auto
&
expected_kernel_key
=
kernel_pair
.
second
;
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
if
(
platform
::
is_gpu_place
(
actual_kernel_key
.
place_
)
&&
platform
::
is_cpu_place
(
expected_kernel_key
.
place_
))
{
return
pool
.
Get
(
actual_kernel_key
.
place_
);
}
else
if
(
platform
::
is_cpu_place
(
actual_kernel_key
.
place_
)
&&
platform
::
is_gpu_place
(
expected_kernel_key
.
place_
))
{
return
pool
.
Get
(
expected_kernel_key
.
place_
);
}
else
{
PADDLE_THROW
(
"Currently, model parallelism is only supported between CPU and CUDA"
);
}
}
void
OperatorWithKernel
::
Run
(
const
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
{
RuntimeInferShapeContext
infer_shape_ctx
(
*
this
,
scope
);
...
...
@@ -418,9 +436,9 @@ void OperatorWithKernel::Run(const Scope& scope,
"CPU and other devices. For example, multi-GPU model "
"parallelism will failed."
);
}
else
{
auto
kernel_pair
=
std
::
make_pair
(
actual_kernel_key
,
expected_kernel_key
);
const
DataTransformFn
*
trans_fun
=
DataTransformFnMap
::
Instance
().
GetNullable
(
std
::
make_pair
(
actual_kernel_key
,
expected_kernel_key
));
DataTransformFnMap
::
Instance
().
GetNullable
(
kernel_pair
);
if
(
trans_fun
)
{
auto
input_vars
=
this
->
InputVars
();
// TODO(qijun) filter the input vars that do not need to be transformed
...
...
@@ -437,22 +455,18 @@ void OperatorWithKernel::Run(const Scope& scope,
}
if
(
!
need_trans
.
empty
())
{
// TODO(qijun) get appropriate DeviceContext from DeviceContext pool
platform
::
DeviceContext
*
trans_dev_ctx
=
nullptr
;
std
::
vector
<
platform
::
DeviceContext
*>
trans_dev_ctx_vec
{
trans_dev_ctx
};
auto
trans_dev_ctx
=
GetDeviceContext
(
kernel_pair
);
// Wait for transform starting
dev_ctx
->
Wait
();
for
(
auto
var_name
:
need_trans
)
{
(
*
trans_fun
)(
trans_dev_ctx
_vec
,
*
(
scope
.
FindVar
(
var_name
)),
(
*
trans_fun
)(
trans_dev_ctx
,
*
(
scope
.
FindVar
(
var_name
)),
scope
.
FindVar
(
var_name
+
framework
::
KernelTypeToString
(
expected_kernel_key
)));
}
// Wait for data transform finishing
for
(
auto
ctx
:
trans_dev_ctx_vec
)
{
ctx
->
Wait
();
}
trans_dev_ctx
->
Wait
();
}
}
}
...
...
paddle/framework/tensor_util.cc
0 → 100644
浏览文件 @
afb5496c
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/framework/tensor_util.h"
namespace
paddle
{
namespace
framework
{
template
<
typename
Predicate
,
typename
DevCtx
>
struct
AnyDTypeVisitor
{
Predicate
predicate_
;
const
Tensor
&
tensor_
;
const
DevCtx
&
ctx_
;
Tensor
*
out_
;
AnyDTypeVisitor
(
Predicate
predicate
,
const
Tensor
&
tensor
,
const
DevCtx
&
ctx
,
Tensor
*
out
)
:
predicate_
(
predicate
),
tensor_
(
tensor
),
ctx_
(
ctx
),
out_
(
out
)
{}
template
<
typename
T
>
void
operator
()()
const
{
auto
t
=
EigenVector
<
T
>::
Flatten
(
tensor_
);
auto
o
=
EigenScalar
<
bool
>::
From
(
*
out_
);
// return any of predicate_(t) is true.
o
.
device
(
*
ctx_
.
eigen_device
())
=
predicate_
(
t
).
any
();
}
};
template
<
typename
Predicate
,
typename
DevCtx
>
inline
void
AnyImpl
(
Predicate
predicate
,
const
framework
::
Tensor
&
tensor
,
const
DevCtx
&
ctx
,
framework
::
Tensor
*
out
)
{
VisitDataType
(
ToDataType
(
tensor
.
type
()),
AnyDTypeVisitor
<
Predicate
,
DevCtx
>
(
predicate
,
tensor
,
ctx
,
out
));
}
template
<
typename
Predicate
>
struct
AnyVisitor
:
public
boost
::
static_visitor
<
bool
>
{
const
framework
::
Tensor
&
tensor_
;
Predicate
predicate_
;
AnyVisitor
(
const
framework
::
Tensor
&
tensor
,
Predicate
predicate
)
:
tensor_
(
tensor
),
predicate_
(
std
::
move
(
predicate
))
{}
template
<
typename
Place
>
bool
operator
()(
const
Place
&
place
)
const
{
framework
::
Tensor
out
;
out
.
Resize
({
1
});
out
.
mutable_data
<
bool
>
(
place
);
auto
*
ctx
=
platform
::
DeviceContextPool
::
Instance
().
GetByPlace
(
place
);
AnyImpl
(
predicate_
,
tensor_
,
*
ctx
,
&
out
);
return
this
->
GetResult
(
out
,
place
);
}
bool
GetResult
(
const
framework
::
Tensor
&
out
,
const
platform
::
CUDAPlace
&
gpu
)
const
{
platform
::
CPUPlace
cpu
;
framework
::
Tensor
tmp
;
tmp
.
Resize
({
1
});
tmp
.
mutable_data
<
bool
>
(
cpu
);
auto
gpuctx
=
platform
::
DeviceContextPool
::
Instance
().
Get
(
gpu
);
gpuctx
->
Wait
();
CopyFrom
(
out
,
cpu
,
*
gpuctx
,
&
tmp
);
gpuctx
->
Wait
();
return
GetResult
(
tmp
,
cpu
);
}
bool
GetResult
(
const
framework
::
Tensor
&
out
,
const
platform
::
CPUPlace
&
cpu
)
const
{
return
*
out
.
data
<
bool
>
();
}
};
template
<
typename
Predicate
>
inline
bool
Any
(
const
framework
::
Tensor
&
tensor
,
Predicate
predicate
)
{
AnyVisitor
<
Predicate
>
visitor
(
tensor
,
predicate
);
auto
place
=
tensor
.
place
();
return
platform
::
VisitPlace
(
place
,
visitor
);
}
struct
HasNANPredicate
{
template
<
typename
T
>
auto
operator
()(
const
T
&
eigen_vec
)
const
->
decltype
(
std
::
declval
<
T
>
().
isnan
())
{
// Cast eigen_vector to vector of bool. true if is inf.
return
eigen_vec
.
isnan
();
}
};
bool
HasNAN
(
const
framework
::
Tensor
&
tensor
)
{
HasNANPredicate
predicate
;
return
Any
(
tensor
,
predicate
);
}
struct
HasInfPredicate
{
template
<
typename
T
>
auto
operator
()(
const
T
&
eigen_vec
)
const
->
decltype
(
std
::
declval
<
T
>
().
isinf
())
{
// Cast eigen_vector to vector of bool. true if is inf.
return
eigen_vec
.
isinf
();
}
};
bool
HasInf
(
const
framework
::
Tensor
&
tensor
)
{
HasInfPredicate
predicate
;
return
Any
(
tensor
,
predicate
);
}
}
// namespace framework
}
// namespace paddle
paddle/framework/tensor_util.cu
0 → 120000
浏览文件 @
afb5496c
.
/
tensor_util
.
cc
\ No newline at end of file
paddle/framework/tensor_util.h
浏览文件 @
afb5496c
...
...
@@ -14,8 +14,10 @@ limitations under the License. */
#pragma once
#include "paddle/framework/data_type.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/framework.pb.h"
#include "paddle/framework/tensor.h"
#include "paddle/platform/device_context.h"
namespace
paddle
{
namespace
framework
{
...
...
@@ -207,6 +209,12 @@ inline void CopyToVector(const Tensor& src, std::vector<T>* dst) {
src_ptr
,
size
);
}
// Returns true if a tensor contains NAN, i.e., Not A Number.
bool
HasNAN
(
const
framework
::
Tensor
&
tensor
);
// Returns true if a tensor contains Inf, i.e., Infinity.
bool
HasInf
(
const
framework
::
Tensor
&
tensor
);
inline
void
SerializeToStream
(
std
::
ostream
&
os
,
const
Tensor
&
tensor
,
const
platform
::
DeviceContext
&
dev_ctx
)
{
// TODO(typhoonzero): serialize to ostream
...
...
paddle/framework/tensor_util_test.cc
浏览文件 @
afb5496c
...
...
@@ -13,6 +13,7 @@
#include "paddle/framework/tensor_util.h"
#include <gtest/gtest.h>
#include <cmath>
#include <string>
namespace
paddle
{
...
...
@@ -230,6 +231,29 @@ TEST(CopyToVector, Tensor) {
#endif
}
TEST
(
HasNAN
,
CPU
)
{
using
namespace
paddle
::
framework
;
using
namespace
paddle
::
platform
;
Tensor
src
;
float
*
buf
=
src
.
mutable_data
<
float
>
({
3
},
CPUPlace
());
buf
[
0
]
=
0.0
;
buf
[
1
]
=
NAN
;
buf
[
2
]
=
0.0
;
ASSERT_TRUE
(
HasNAN
(
src
));
}
TEST
(
HasInf
,
CPU
)
{
using
namespace
paddle
::
framework
;
using
namespace
paddle
::
platform
;
Tensor
src
;
double
*
buf
=
src
.
mutable_data
<
double
>
({
3
},
CPUPlace
());
buf
[
0
]
=
1.0
;
buf
[
1
]
=
INFINITY
;
buf
[
2
]
=
0.0
;
ASSERT_TRUE
(
HasInf
(
src
));
}
TEST
(
Tensor
,
SerializeAndDeserialize
)
{
framework
::
Tensor
src_tensor
;
int
array
[
6
]
=
{
1
,
2
,
3
,
4
,
5
,
6
};
...
...
paddle/framework/tensor_util_test.cu
0 → 100644
浏览文件 @
afb5496c
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "gtest/gtest.h"
#include "paddle/framework/tensor_util.h"
#include "paddle/platform/device_context.h"
#include "paddle/platform/place.h"
namespace
paddle
{
namespace
framework
{
static
__global__
void
FillNAN
(
float
*
buf
)
{
buf
[
0
]
=
0.0
;
buf
[
1
]
=
0.1
;
buf
[
2
]
=
NAN
;
}
static
__global__
void
FillInf
(
float
*
buf
)
{
buf
[
0
]
=
0.0
;
buf
[
1
]
=
INFINITY
;
buf
[
2
]
=
0.5
;
}
TEST
(
HasNAN
,
GPU
)
{
Tensor
tensor
;
platform
::
CUDAPlace
gpu
(
0
);
auto
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
*
cuda_ctx
=
pool
.
GetByPlace
(
gpu
);
float
*
buf
=
tensor
.
mutable_data
<
float
>
({
3
},
gpu
);
FillNAN
<<<
1
,
1
,
0
,
cuda_ctx
->
stream
()
>>>
(
buf
);
cuda_ctx
->
Wait
();
ASSERT_TRUE
(
HasNAN
(
tensor
));
}
TEST
(
HasInf
,
GPU
)
{
Tensor
tensor
;
platform
::
CUDAPlace
gpu
(
0
);
auto
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
*
cuda_ctx
=
pool
.
GetByPlace
(
gpu
);
float
*
buf
=
tensor
.
mutable_data
<
float
>
({
3
},
gpu
);
FillInf
<<<
1
,
1
,
0
,
cuda_ctx
->
stream
()
>>>
(
buf
);
cuda_ctx
->
Wait
();
ASSERT_TRUE
(
HasInf
(
tensor
));
}
}
// namespace framework
}
// namespace paddle
paddle/framework/threadpool.h
浏览文件 @
afb5496c
...
...
@@ -16,6 +16,7 @@ limitations under the License. */
#include <condition_variable>
#include <functional>
#include <future>
#include <mutex>
#include <queue>
#include <thread>
...
...
@@ -25,10 +26,11 @@ limitations under the License. */
namespace
paddle
{
namespace
framework
{
typedef
std
::
function
<
void
()
>
Task
;
class
ThreadPool
{
public:
typedef
std
::
packaged_task
<
void
()
>
Task
;
typedef
std
::
function
<
void
()
>
Fun
;
/**
* @brief Get a instance of threadpool, the thread number will
* be specified as the number of hardware thread contexts
...
...
@@ -61,13 +63,18 @@ class ThreadPool {
/**
* @brief Push a function to the queue, and will be scheduled and
* executed if a thread is available.
* @param[in] Task will be pushed to the task queue.
* @param[in] Task, will be pushed to the task queue.
* @return std::future<void>, we could wait for the task finished by
* f.wait().
*/
void
Run
(
const
Task
&
fn
)
{
std
::
future
<
void
>
Run
(
const
Fun
&
fn
)
{
std
::
unique_lock
<
std
::
mutex
>
lock
(
mutex_
);
tasks_
.
push
(
fn
);
Task
task
(
std
::
bind
(
fn
));
std
::
future
<
void
>
f
=
task
.
get_future
();
tasks_
.
push
(
std
::
move
(
task
));
lock
.
unlock
();
scheduled_
.
notify_one
();
return
f
;
}
/**
...
...
@@ -110,7 +117,7 @@ class ThreadPool {
break
;
}
// pop a task from the task queue
auto
task
=
tasks_
.
front
(
);
auto
task
=
std
::
move
(
tasks_
.
front
()
);
tasks_
.
pop
();
--
available_
;
...
...
paddle/framework/threadpool_test.cc
浏览文件 @
afb5496c
...
...
@@ -20,16 +20,21 @@ limitations under the License. */
namespace
framework
=
paddle
::
framework
;
void
do_sum
(
framework
::
ThreadPool
*
pool
,
std
::
atomic
<
int
>&
sum
,
int
cnt
)
{
std
::
vector
<
std
::
future
<
void
>>
fs
;
for
(
int
i
=
0
;
i
<
cnt
;
++
i
)
{
pool
->
Run
([
&
sum
]()
{
sum
.
fetch_add
(
1
);
});
auto
f
=
pool
->
Run
([
&
sum
]()
{
sum
.
fetch_add
(
1
);
});
fs
.
push_back
(
std
::
move
(
f
));
}
for
(
auto
&
f
:
fs
)
{
f
.
wait
();
}
}
TEST
(
ThreadPool
,
ConcurrentInit
)
{
framework
::
ThreadPool
*
pool
;
int
concurrent_cnt
=
50
;
int
n
=
50
;
std
::
vector
<
std
::
thread
>
threads
;
for
(
int
i
=
0
;
i
<
concurrent_cnt
;
++
i
)
{
for
(
int
i
=
0
;
i
<
n
;
++
i
)
{
std
::
thread
t
([
&
pool
]()
{
pool
=
framework
::
ThreadPool
::
GetInstance
();
});
threads
.
push_back
(
std
::
move
(
t
));
}
...
...
@@ -38,13 +43,13 @@ TEST(ThreadPool, ConcurrentInit) {
}
}
TEST
(
ThreadPool
,
Concurrent
Start
)
{
TEST
(
ThreadPool
,
Concurrent
Run
)
{
framework
::
ThreadPool
*
pool
=
framework
::
ThreadPool
::
GetInstance
();
std
::
atomic
<
int
>
sum
(
0
);
std
::
vector
<
std
::
thread
>
threads
;
int
concurrent_cnt
=
50
;
int
n
=
50
;
// sum = (n * (n + 1)) / 2
for
(
int
i
=
1
;
i
<=
concurrent_cnt
;
++
i
)
{
for
(
int
i
=
1
;
i
<=
n
;
++
i
)
{
std
::
thread
t
(
do_sum
,
pool
,
std
::
ref
(
sum
),
i
);
threads
.
push_back
(
std
::
move
(
t
));
}
...
...
@@ -52,5 +57,5 @@ TEST(ThreadPool, ConcurrentStart) {
t
.
join
();
}
pool
->
Wait
();
EXPECT_EQ
(
sum
,
((
concurrent_cnt
+
1
)
*
concurrent_cnt
)
/
2
);
EXPECT_EQ
(
sum
,
((
n
+
1
)
*
n
)
/
2
);
}
paddle/function/GemmConvOp.cpp
浏览文件 @
afb5496c
...
...
@@ -126,14 +126,165 @@ public:
inputData
+=
inputChannels
*
inputHeight
*
inputWidth
;
outputData
+=
outputChannels
*
outputHeight
*
outputWidth
;
}
}
};
#ifdef PADDLE_MOBILE_INFERENCE
if
(
Device
==
DEVICE_TYPE_CPU
)
{
memory_
.
reset
();
/*
* \brief Forward calculation of convolution, optimized for mobile.
*/
template
<
DeviceType
Device
>
class
GemmConvMobileFunction
:
public
ConvFunctionBase
{
public:
void
init
(
const
FuncConfig
&
config
)
override
{
ConvFunctionBase
::
init
(
config
);
}
#endif
void
check
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
const
TensorShape
&
input
=
inputs
[
0
].
shape
();
const
TensorShape
&
filter
=
inputs
[
1
].
shape
();
const
TensorShape
&
output
=
outputs
[
0
].
shape
();
checkShape
(
input
,
filter
,
output
);
}
void
calc
(
const
BufferArgs
&
inputs
,
const
BufferArgs
&
outputs
)
override
{
CHECK_EQ
(
numInputs_
,
inputs
.
size
());
CHECK_EQ
(
numOutputs_
,
outputs
.
size
());
check
(
inputs
,
outputs
);
// TODO(hedaoyuan): Need to define some index macros,
// to avoid useing 0 and 1.
const
TensorShape
&
input
=
inputs
[
0
].
shape
();
const
TensorShape
&
filter
=
inputs
[
1
].
shape
();
const
TensorShape
&
output
=
outputs
[
0
].
shape
();
real
beta
;
if
(
outputs
[
0
].
getArgType
()
==
ADD_TO
)
{
beta
=
1.0
;
}
else
{
beta
=
0.0
;
}
size_t
batchSize
=
input
[
0
];
size_t
inputChannels
=
input
[
1
];
size_t
inputHeight
=
input
[
2
];
size_t
inputWidth
=
input
[
3
];
size_t
filterHeight
=
getFilterHeight
(
filter
);
size_t
filterWidth
=
getFilterWidth
(
filter
);
size_t
outputChannels
=
output
[
1
];
size_t
outputHeight
=
output
[
2
];
size_t
outputWidth
=
output
[
3
];
real
*
inputData
=
inputs
[
0
].
data
<
real
>
();
real
*
filterData
=
inputs
[
1
].
data
<
real
>
();
real
*
outputData
=
outputs
[
0
].
data
<
real
>
();
bool
needIm2col
=
isNeedIm2col
(
filter
);
TensorShape
imShape
=
TensorShape
({
inputChannels
/
groups_
,
inputHeight
,
inputWidth
});
TensorShape
colShape
;
real
*
colData
=
NULL
;
size_t
colHeight
=
inputChannels
/
groups_
*
filterHeight
*
filterWidth
;
size_t
colWidth
=
outputHeight
*
outputWidth
;
// Max col matrix height 256, Max col matrix width 1024
size_t
stepColHeight
=
std
::
min
(
colHeight
,
static_cast
<
size_t
>
(
256
));
size_t
stepColWidth
=
std
::
min
(
colWidth
,
static_cast
<
size_t
>
(
2048
));
if
(
needIm2col
)
{
colShape
=
TensorShape
({
inputChannels
/
groups_
,
filterHeight
,
filterWidth
,
outputHeight
,
outputWidth
});
resizeBuffer
<
Device
>
(
stepColHeight
*
stepColWidth
*
sizeof
(
real
));
colData
=
reinterpret_cast
<
real
*>
(
memory_
->
getBuf
());
}
Im2ColMobileFunctor
<
real
>
im2col
;
size_t
inputOffset
=
imShape
.
getElements
();
size_t
outputOffset
=
(
outputChannels
/
groups_
)
*
outputHeight
*
outputWidth
;
size_t
filterOffset
=
filter
.
getElements
()
/
groups_
;
int
nStride
=
colWidth
;
int
kStride
=
colHeight
;
for
(
size_t
i
=
0
;
i
<
batchSize
;
i
++
)
{
for
(
size_t
g
=
0
;
g
<
groups_
;
g
++
)
{
if
(
needIm2col
)
{
real
beta_
=
beta
;
for
(
size_t
colHeightStart
=
0
;
colHeightStart
<
colHeight
;
colHeightStart
+=
stepColHeight
)
{
for
(
size_t
colWidthStart
=
0
;
colWidthStart
<
colWidth
;
colWidthStart
+=
stepColWidth
)
{
int
N
=
std
::
min
(
colWidth
-
colWidthStart
,
stepColWidth
);
int
K
=
std
::
min
(
colHeight
-
colHeightStart
,
stepColHeight
);
// im2col
im2col
(
inputData
+
g
*
inputOffset
,
imShape
,
colData
,
colShape
,
strideH
(),
strideW
(),
paddingH
(),
paddingW
(),
dilationH
(),
dilationW
(),
colHeightStart
,
K
,
colWidthStart
,
N
);
// gemm
int
M
=
outputChannels
/
groups_
;
BlasGemm
<
Device
,
real
>::
compute
(
false
,
false
,
M
,
N
,
K
,
1.0
f
,
filterData
+
g
*
filterOffset
+
colHeightStart
,
kStride
,
colData
,
N
,
beta_
,
outputData
+
g
*
outputOffset
+
colWidthStart
,
nStride
);
}
beta_
=
1.0
;
}
}
else
{
int
M
=
outputChannels
/
groups_
;
int
N
=
outputHeight
*
outputWidth
;
int
K
=
inputChannels
/
groups_
*
filterHeight
*
filterWidth
;
BlasGemm
<
Device
,
real
>::
compute
(
false
,
false
,
M
,
N
,
K
,
1.0
f
,
filterData
+
g
*
filterOffset
,
K
,
inputData
+
g
*
inputOffset
,
N
,
beta
,
outputData
+
g
*
outputOffset
,
N
);
}
}
inputData
+=
inputChannels
*
inputHeight
*
inputWidth
;
outputData
+=
outputChannels
*
outputHeight
*
outputWidth
;
}
memory_
.
reset
();
}
};
#endif
/*
* \brief Backward input calculation of convolution.
*/
...
...
@@ -348,7 +499,11 @@ public:
}
};
#ifdef PADDLE_MOBILE_INFERENCE
REGISTER_TYPED_FUNC
(
GemmConv
,
CPU
,
GemmConvMobileFunction
);
#else
REGISTER_TYPED_FUNC
(
GemmConv
,
CPU
,
GemmConvFunction
);
#endif
REGISTER_TYPED_FUNC
(
GemmConvGradInput
,
CPU
,
GemmConvGradInputFunction
);
REGISTER_TYPED_FUNC
(
GemmConvGradFilter
,
CPU
,
GemmConvGradFilterFunction
);
#ifdef PADDLE_WITH_CUDA
...
...
paddle/function/Im2Col.h
浏览文件 @
afb5496c
...
...
@@ -98,4 +98,54 @@ public:
int
dilationWidth
=
1
);
};
template
<
class
T
>
class
Im2ColMobileFunctor
{
public:
void
operator
()(
const
T
*
imData
,
const
TensorShape
&
imShape
,
T
*
colData
,
const
TensorShape
&
colShape
,
int
strideHeight
,
int
strideWidth
,
int
paddingHeight
,
int
paddingWidth
,
int
dilationHeight
,
int
dilationWidth
,
int
colHeightStart
,
int
colHeightSize
,
int
colWidthStart
,
int
colWidthSize
)
{
int
inputHeight
=
imShape
[
1
];
int
inputWidth
=
imShape
[
2
];
int
filterHeight
=
colShape
[
1
];
int
filterWidth
=
colShape
[
2
];
int
outputWidth
=
colShape
[
4
];
for
(
int
colh
=
0
;
colh
<
colHeightSize
;
colh
++
)
{
int
wOffset
=
(
colHeightStart
+
colh
)
%
filterWidth
;
int
hOffset
=
((
colHeightStart
+
colh
)
/
filterWidth
)
%
filterHeight
;
int
c_im
=
(
colHeightStart
+
colh
)
/
filterWidth
/
filterHeight
;
for
(
int
colw
=
0
;
colw
<
colWidthSize
;
colw
++
)
{
int
h
=
(
colWidthStart
+
colw
)
/
outputWidth
;
int
w
=
(
colWidthStart
+
colw
)
%
outputWidth
;
int
imRowIdx
=
h
*
strideHeight
+
hOffset
*
dilationHeight
;
int
imColIdx
=
w
*
strideWidth
+
wOffset
*
dilationWidth
;
if
((
imRowIdx
-
paddingHeight
)
<
0
||
(
imRowIdx
-
paddingHeight
)
>=
inputHeight
||
(
imColIdx
-
paddingWidth
)
<
0
||
(
imColIdx
-
paddingWidth
)
>=
inputWidth
)
{
colData
[
colh
*
colWidthSize
+
colw
]
=
static_cast
<
T
>
(
0
);
}
else
{
imRowIdx
+=
c_im
*
inputHeight
-
paddingHeight
;
imColIdx
-=
paddingWidth
;
colData
[
colh
*
colWidthSize
+
colw
]
=
imData
[
imRowIdx
*
inputWidth
+
imColIdx
];
}
}
}
}
};
}
// namespace paddle
paddle/function/Im2ColTest.cpp
浏览文件 @
afb5496c
...
...
@@ -138,4 +138,86 @@ TEST(Im2ColFunctor, GPU) { TestIm2ColFunctor<DEVICE_TYPE_GPU, float>(); }
#endif
template
<
class
T
>
void
TestIm2ColMobileFunctor
()
{
for
(
size_t
channels
:
{
32
})
{
for
(
size_t
inputHeight
:
{
33
,
100
})
{
for
(
size_t
inputWidth
:
{
32
,
96
})
{
for
(
size_t
filterHeight
:
{
5
})
{
for
(
size_t
filterWidth
:
{
7
})
{
for
(
size_t
stride
:
{
2
})
{
for
(
size_t
padding
:
{
1
})
{
for
(
size_t
dilation
:
{
1
,
3
})
{
size_t
filterSizeH
=
(
filterHeight
-
1
)
*
dilation
+
1
;
size_t
filterSizeW
=
(
filterWidth
-
1
)
*
dilation
+
1
;
if
(
inputHeight
+
2
*
padding
<
filterSizeH
||
inputWidth
+
2
*
padding
<
filterSizeW
)
break
;
if
(
padding
>=
filterSizeH
||
padding
>=
filterSizeW
)
break
;
size_t
outputHeight
=
(
inputHeight
-
filterSizeH
+
2
*
padding
)
/
stride
+
1
;
size_t
outputWidth
=
(
inputWidth
-
filterSizeW
+
2
*
padding
)
/
stride
+
1
;
TensorShape
imShape
=
TensorShape
({
channels
,
inputHeight
,
inputWidth
});
TensorShape
colShape1
=
TensorShape
({
channels
,
filterHeight
,
filterWidth
,
outputHeight
,
outputWidth
});
size_t
height
=
channels
*
filterHeight
*
filterWidth
;
size_t
width
=
outputHeight
*
outputWidth
;
VectorPtr
input1
=
Vector
::
create
(
imShape
.
getElements
(),
false
);
VectorPtr
input2
=
Vector
::
create
(
imShape
.
getElements
(),
false
);
MatrixPtr
output1
=
Matrix
::
create
(
height
,
width
,
false
,
false
);
MatrixPtr
output2
=
Matrix
::
create
(
height
,
width
,
false
,
false
);
input1
->
uniform
(
0.001
,
1
);
input2
->
copyFrom
(
*
input1
);
Im2ColFunctor
<
kCFO
,
DEVICE_TYPE_CPU
,
T
>
im2Col1
;
Im2ColMobileFunctor
<
T
>
im2Col2
;
im2Col1
(
input1
->
getData
(),
imShape
,
output1
->
getData
(),
colShape1
,
stride
,
stride
,
padding
,
padding
,
dilation
,
dilation
);
im2Col2
(
input2
->
getData
(),
imShape
,
output2
->
getData
(),
colShape1
,
stride
,
stride
,
padding
,
padding
,
dilation
,
dilation
,
0
,
height
,
0
,
width
);
autotest
::
TensorCheckEqual
(
*
output1
,
*
output2
);
}
}
}
}
}
}
}
}
}
TEST
(
Im2ColFunctor
,
Mobile
)
{
TestIm2ColMobileFunctor
<
float
>
();
}
}
// namespace paddle
paddle/platform/device_context.h
浏览文件 @
afb5496c
...
...
@@ -52,6 +52,14 @@ class CPUDeviceContext : public DeviceContext {
std
::
unique_ptr
<
Eigen
::
DefaultDevice
>
eigen_device_
;
};
template
<
typename
Place
>
struct
DefaultDeviceContextType
;
template
<
>
struct
DefaultDeviceContextType
<
platform
::
CPUPlace
>
{
using
TYPE
=
CPUDeviceContext
;
};
#ifdef PADDLE_WITH_CUDA
class
EigenCudaStreamDevice
;
...
...
@@ -90,6 +98,11 @@ class CUDADeviceContext : public DeviceContext {
cublasHandle_t
cublas_handle_
;
};
template
<
>
struct
DefaultDeviceContextType
<
platform
::
CUDAPlace
>
{
using
TYPE
=
CUDADeviceContext
;
};
class
CUDNNDeviceContext
:
public
CUDADeviceContext
{
public:
explicit
CUDNNDeviceContext
(
CUDAPlace
place
);
...
...
@@ -125,6 +138,13 @@ class DeviceContextPool {
/*! \brief Return handle of single device context. */
const
platform
::
DeviceContext
*
Get
(
const
platform
::
Place
&
place
);
template
<
typename
Place
>
const
typename
DefaultDeviceContextType
<
Place
>::
TYPE
*
GetByPlace
(
const
Place
&
place
)
{
return
reinterpret_cast
<
const
typename
DefaultDeviceContextType
<
Place
>::
TYPE
*>
(
Get
(
place
));
}
private:
static
DeviceContextPool
*
pool
;
constexpr
static
int
LEFT_SHIFT
=
8
;
...
...
paddle/platform/place.h
浏览文件 @
afb5496c
...
...
@@ -15,7 +15,7 @@ limitations under the License. */
#pragma once
#include <iostream>
#include "paddle/platform/enforce.h"
#include "paddle/platform/variant.h"
namespace
paddle
{
...
...
@@ -64,5 +64,31 @@ bool places_are_same_class(const Place &, const Place &);
std
::
ostream
&
operator
<<
(
std
::
ostream
&
,
const
Place
&
);
template
<
typename
Visitor
>
struct
PlaceVisitorWrapper
:
public
boost
::
static_visitor
<
typename
Visitor
::
result_type
>
{
const
Visitor
&
visitor_
;
explicit
PlaceVisitorWrapper
(
const
Visitor
&
visitor
)
:
visitor_
(
visitor
)
{}
typename
Visitor
::
result_type
operator
()(
const
CPUPlace
&
cpu
)
const
{
return
visitor_
(
cpu
);
}
typename
Visitor
::
result_type
operator
()(
const
CUDAPlace
&
cuda
)
const
{
#ifdef PADDLE_WITH_CUDA
return
visitor_
(
cuda
);
#else
PADDLE_THROW
(
"Paddle is not compiled with CUDA. Cannot visit cuda device"
);
return
typename
Visitor
::
result_type
();
#endif
}
};
template
<
typename
Visitor
>
typename
Visitor
::
result_type
VisitPlace
(
const
Place
&
place
,
const
Visitor
&
visitor
)
{
return
boost
::
apply_visitor
(
PlaceVisitorWrapper
<
Visitor
>
(
visitor
),
place
);
}
}
// namespace platform
}
// namespace paddle
paddle/pybind/CMakeLists.txt
浏览文件 @
afb5496c
...
...
@@ -3,6 +3,9 @@ if(WITH_PYTHON)
SRCS pybind.cc exception.cc protobuf.cc const_value.cc
DEPS pybind python backward proto_desc paddle_memory executor prune init
${
GLOB_OP_LIB
}
)
if
(
NOT APPLE AND NOT ANDROID
)
target_link_libraries
(
paddle_pybind rt
)
endif
(
NOT APPLE AND NOT ANDROID
)
endif
(
WITH_PYTHON
)
if
(
WITH_DOC
)
...
...
paddle/scripts/submit_local.sh.in
浏览文件 @
afb5496c
...
...
@@ -71,9 +71,7 @@ function threads_config() {
# auto set OMP_NUM_THREADS and MKL_NUM_THREADS
# according to trainer_count and total processors
# only when MKL enabled
if
[
"@WITH_MKL@"
==
"OFF"
]
;
then
return
0
fi
# auto set OPENBLAS_NUM_THREADS when do not use MKL
processors
=
`
grep
"processor"
/proc/cpuinfo|sort
-u
|wc
-l
`
trainers
=
`
grep
-Eo
'trainer_count.[0-9]+'
<<<
"
$@
"
|grep
-Eo
'[0-9]+'
|xargs
`
if
[
-z
$trainers
]
;
then
...
...
@@ -83,12 +81,19 @@ function threads_config() {
if
[
$threads
-eq
0
]
;
then
threads
=
1
fi
if
[
"@WITH_MKL@"
==
"ON"
]
;
then
if
[
-z
"
$OMP_NUM_THREADS
"
]
;
then
export
OMP_NUM_THREADS
=
$threads
fi
if
[
-z
"
$MKL_NUM_THREADS
"
]
;
then
export
MKL_NUM_THREADS
=
$threads
fi
else
if
[
-z
"
$OPENBLAS_NUM_THREADS
"
]
;
then
export
OPENBLAS_NUM_THREADS
=
$threads
fi
fi
}
PADDLE_CONF_HOME
=
"
$HOME
/.config/paddle"
...
...
@@ -150,7 +155,7 @@ fi
case
"
$1
"
in
"train"
)
threads_config
$@
# echo $OMP_NUM_THREADS $MKL_NUM_THREADS
# echo $OMP_NUM_THREADS $MKL_NUM_THREADS
$OPENBLAS_NUM_THREADS
${
DEBUGGER
}
$PADDLE_BIN_PATH
/paddle_trainer
${
@
:2
}
;;
"merge_model"
)
...
...
python/paddle/v2/dataset/flowers.py
浏览文件 @
afb5496c
...
...
@@ -44,7 +44,7 @@ __all__ = ['train', 'test', 'valid']
DATA_URL
=
'http://www.robots.ox.ac.uk/~vgg/data/flowers/102/102flowers.tgz'
LABEL_URL
=
'http://www.robots.ox.ac.uk/~vgg/data/flowers/102/imagelabels.mat'
SETID_URL
=
'http://www.robots.ox.ac.uk/~vgg/data/flowers/102/setid.mat'
DATA_MD5
=
'
52808999861908f626f3c1f4e79d11fa
'
DATA_MD5
=
'
33bfc11892f1e405ca193ae9a9f2a118
'
LABEL_MD5
=
'e0620be6f572b9609742df49c70aed4d'
SETID_MD5
=
'a5357ecc9cb78c4bef273ce3793fc85c'
# In official 'readme', tstid is the flag of test data
...
...
python/paddle/v2/fluid/__init__.py
浏览文件 @
afb5496c
...
...
@@ -36,7 +36,7 @@ def __read_gflags_from_env__():
"""
import
sys
import
core
read_env_flags
=
[
'use_pinned_memory'
]
read_env_flags
=
[
'use_pinned_memory'
,
'check_nan_inf'
]
if
core
.
is_compile_gpu
():
read_env_flags
.
append
(
'fraction_of_gpu_memory_to_use'
)
core
.
init_gflags
([
sys
.
argv
[
0
]]
+
...
...
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