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77340348
编写于
6月 01, 2018
作者:
T
tangwei12
浏览文件
操作
浏览文件
下载
差异文件
Merge branch 'develop' of github.com:PaddlePaddle/Paddle into new_api_about_cpkt
上级
55d908c9
d6997e5b
变更
22
隐藏空白更改
内联
并排
Showing
22 changed file
with
290 addition
and
125 deletion
+290
-125
AUTHORS.md
AUTHORS.md
+1
-0
doc/fluid/howto/index_cn.rst
doc/fluid/howto/index_cn.rst
+1
-1
doc/fluid/howto/index_en.rst
doc/fluid/howto/index_en.rst
+0
-1
doc/fluid/howto/inference/build_and_install_lib_cn.rst
doc/fluid/howto/inference/build_and_install_lib_cn.rst
+96
-0
doc/fluid/howto/inference/index_cn.rst
doc/fluid/howto/inference/index_cn.rst
+8
-0
doc/fluid/howto/inference/inference_support_in_fluid_cn.md
doc/fluid/howto/inference/inference_support_in_fluid_cn.md
+1
-58
paddle/contrib/inference/CMakeLists.txt
paddle/contrib/inference/CMakeLists.txt
+14
-23
paddle/fluid/framework/block_desc.cc
paddle/fluid/framework/block_desc.cc
+2
-2
paddle/fluid/framework/block_desc.h
paddle/fluid/framework/block_desc.h
+1
-1
paddle/fluid/framework/details/multi_devices_graph_builder.cc
...le/fluid/framework/details/multi_devices_graph_builder.cc
+29
-12
paddle/fluid/framework/details/multi_devices_graph_builder.h
paddle/fluid/framework/details/multi_devices_graph_builder.h
+1
-1
paddle/fluid/framework/op_desc.cc
paddle/fluid/framework/op_desc.cc
+1
-1
paddle/fluid/framework/op_desc.h
paddle/fluid/framework/op_desc.h
+2
-1
paddle/fluid/framework/program_desc.cc
paddle/fluid/framework/program_desc.cc
+19
-6
paddle/fluid/inference/tensorrt/convert/activation_op.cc
paddle/fluid/inference/tensorrt/convert/activation_op.cc
+1
-1
paddle/fluid/inference/tensorrt/convert/mul_op.cc
paddle/fluid/inference/tensorrt/convert/mul_op.cc
+1
-1
paddle/fluid/inference/tensorrt/convert/ut_helper.h
paddle/fluid/inference/tensorrt/convert/ut_helper.h
+1
-1
paddle/fluid/operators/bilinear_interp_op.cc
paddle/fluid/operators/bilinear_interp_op.cc
+23
-0
paddle/fluid/operators/bilinear_interp_op.cu
paddle/fluid/operators/bilinear_interp_op.cu
+23
-2
paddle/fluid/operators/bilinear_interp_op.h
paddle/fluid/operators/bilinear_interp_op.h
+18
-4
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+13
-6
python/paddle/fluid/tests/unittests/test_bilinear_interp_op.py
...n/paddle/fluid/tests/unittests/test_bilinear_interp_op.py
+34
-3
未找到文件。
AUTHORS.md
浏览文件 @
77340348
...
...
@@ -4,6 +4,7 @@
| backyes | Yan-Fei Wang |
| baiyfbupt | Yi-Fan Bai |
| beckett1124 | Bin Qi |
| ChengduoZH | Cheng-Duo Zhao|
| chengxiaohua1105 | Xiao-Hua Cheng |
| cxwangyi, yiwangbaidu, wangkuiyi | Yi Wang |
| cxysteven | Xing-Yi Cheng |
...
...
doc/fluid/howto/index_cn.rst
浏览文件 @
77340348
...
...
@@ -4,5 +4,5 @@
.. toctree::
:maxdepth: 1
inference/index_cn.rst
optimization/index_cn.rst
inference/inference_support_in_fluid.md
doc/fluid/howto/index_en.rst
浏览文件 @
77340348
...
...
@@ -5,4 +5,3 @@ HOW TO
:maxdepth: 1
optimization/index_en.rst
inference/inference_support_in_fluid.md
doc/fluid/howto/inference/build_and_install_lib_cn.rst
0 → 100644
浏览文件 @
77340348
安装与编译C++预测库
===========================
直接下载安装
-------------
====================== ========================================
版本说明 C++预测库
====================== ========================================
cpu_avx_mkl `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/fluid.tgz>`_
cpu_avx_openblas `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/fluid.tgz>`_
cpu_noavx_openblas `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/fluid.tgz>`_
cuda7.5_cudnn5_avx_mkl `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda75cudnn5cp27cp27mu/.lastSuccessful/fluid.tgz>`_
cuda8.0_cudnn5_avx_mkl `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/fluid.tgz>`_
cuda8.0_cudnn7_avx_mkl `fluid.tgz <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/fluid.tgz>`_
====================== ========================================
从源码编译
----------
用户也可以从 PaddlePaddle 核心代码编译C++预测库,只需在编译时配制下面这些编译选项:
================= =========
选项 值
================= =========
CMAKE_BUILD_TYPE Release
FLUID_INSTALL_DIR 安装路径
WITH_FLUID_ONLY ON(推荐)
WITH_SWIG_PY OFF(推荐
WITH_PYTHON OFF(推荐)
WITH_GPU ON/OFF
WITH_MKL ON/OFF
================= =========
建议按照推荐值设置,以避免链接不必要的库。其它可选编译选项按需进行设定。
下面的代码片段从github拉取最新代码,配制编译选项(需要将PADDLE_ROOT替换为PaddlePaddle预测库的安装路径):
.. code-block:: bash
pip install paddlepaddle-gpu
PADDLE_ROOT=/path/of/capi
git clone https://github.com/PaddlePaddle/Paddle.git
cd Paddle
mkdir build
cd build
cmake -DFLUID_INSTALL_DIR=$PADDLE_ROOT \
-DCMAKE_BUILD_TYPE=Release \
-DWITH_FLUID_ONLY=ON \
-DWITH_SWIG_PY=OFF \
-DWITH_PYTHON=OFF \
-DWITH_MKL=OFF \
-DWITH_GPU=OFF \
..
make
make inference_lib_dist
成功编译后,使用C++预测库所需的依赖(包括:(1)编译出的PaddlePaddle预测库和头文件;(2)第三方链接库和头文件;(3)版本信息与编译选项信息)
均会存放于PADDLE_ROOT目录中。目录结构如下:
.. code-block:: text
PaddleRoot/
├── CMakeCache.txt
├── paddle
│ └── fluid
│ ├── framework
│ ├── inference
│ ├── memory
│ ├── platform
│ ├── pybind
│ └── string
├── third_party
│ ├── boost
│ │ └── boost
│ ├── eigen3
│ │ ├── Eigen
│ │ └── unsupported
│ └── install
│ ├── gflags
│ ├── glog
│ ├── mklml
│ ├── protobuf
│ ├── snappy
│ ├── snappystream
│ └── zlib
└── version.txt
version.txt 中记录了该预测库的版本信息,包括Git Commit ID、使用OpenBlas或MKL数学库、CUDA/CUDNN版本号,如:
.. code-block:: text
GIT COMMIT ID: c95cd4742f02bb009e651a00b07b21c979637dc8
WITH_MKL: ON
WITH_GPU: ON
CUDA version: 8.0
CUDNN version: v5
doc/fluid/howto/inference/index_cn.rst
0 → 100644
浏览文件 @
77340348
预测库
------------
.. toctree::
:maxdepth: 1
build_and_install_lib_cn.rst
inference_support_in_fluid_cn.md
doc/fluid/howto/inference/inference_support_in_fluid.md
→
doc/fluid/howto/inference/inference_support_in_fluid
_cn
.md
浏览文件 @
77340348
#
Fluid Inference
使用指南
# 使用指南
## 目录:
-
Python Inference API
-
编译Fluid Inference库
-
Inference C++ API
-
Inference实例
-
Inference计算优化
...
...
@@ -55,62 +54,6 @@
return
[
program
,
feed_target_names
,
fetch_targets
]
```
## 编译Fluid Inference库
-
**不需要额外的CMake选项**
-
1、 配置CMake命令,更多配置请参考
[
源码编译PaddlePaddle
](
http://www.paddlepaddle.org/docs/develop/documentation/zh/build_and_install/build_from_source_cn.html
)
```
bash
$
git clone https://github.com/PaddlePaddle/Paddle.git
$
cd
Paddle
$
mkdir
build
$
cd
build
$
cmake
-DCMAKE_INSTALL_PREFIX
=
your/path/to/paddle_inference_lib
\
-DCMAKE_BUILD_TYPE
=
Release
\
-DWITH_PYTHON
=
ON
\
-DWITH_MKL
=
OFF
\
-DWITH_GPU
=
OFF
\
..
```
- 2、 编译PaddlePaddle
```bash
$ make
```
- 3、 部署。执行如下命令将PaddlePaddle Fluid Inference库部署到`your/path/to/paddle_inference_lib`目录。
```bash
$ make inference_lib_dist
```
-
目录结构
```
bash
$
cd
your/path/to/paddle_inference_lib
$
tree
.
|-- paddle
|
`
--
fluid
| |-- framework
| |-- inference
| | |-- io.h
| |
`
--
libpaddle_fluid.so
| |-- memory
| |-- platform
|
`
--
string
|-- third_party
| |-- eigen3
|
`
--
install
| |-- gflags
| |-- glog
|
`
--
protobuf
`
--
...
```
假设
`PADDLE_ROOT=your/path/to/paddle_inference_lib`
。
## 链接Fluid Inference库
-
示例项目(
[
链接
](
https://github.com/luotao1/fluid_inference_example.git
)
)
...
...
paddle/contrib/inference/CMakeLists.txt
浏览文件 @
77340348
...
...
@@ -17,32 +17,21 @@ if(APPLE)
set
(
CMAKE_CXX_FLAGS
"
${
CMAKE_CXX_FLAGS
}
-Wno-error=pessimizing-move"
)
endif
(
APPLE
)
function
(
inference_api_test TARGET_NAME
TEST_SRC
)
function
(
inference_api_test TARGET_NAME
)
set
(
options
""
)
set
(
oneValueArgs
""
)
set
(
multiValueArgs ARGS
)
cmake_parse_arguments
(
inference_test
"
${
options
}
"
"
${
oneValueArgs
}
"
"
${
multiValueArgs
}
"
${
ARGN
}
)
set
(
PYTHON_TESTS_DIR
${
PADDLE_BINARY_DIR
}
/python/paddle/fluid/tests
)
set
(
arg_list
""
)
cc_test
(
test_paddle_inference_
${
TARGET_NAME
}
SRCS test_paddle_inference_
${
TARGET_NAME
}
.cc
DEPS paddle_fluid_api paddle_inference_api
ARGS --dirname=
${
PYTHON_TESTS_DIR
}
/book/
)
if
(
inference_test_ARGS
)
foreach
(
arg
${
inference_test_ARGS
}
)
list
(
APPEND arg_list
"_
${
arg
}
"
)
endforeach
()
else
()
list
(
APPEND arg_list
"_"
)
set_tests_properties
(
test_paddle_inference_
${
TARGET_NAME
}
PROPERTIES DEPENDS
"
${
inference_test_ARGS
}
"
)
endif
()
foreach
(
arg
${
arg_list
}
)
string
(
REGEX REPLACE
"^_$"
""
arg
"
${
arg
}
"
)
cc_test
(
${
TARGET_NAME
}
SRCS
${
TEST_SRC
}
DEPS paddle_fluid_api paddle_inference_api
ARGS --dirname=
${
PYTHON_TESTS_DIR
}
/book/
)
# TODO(panyx0178): Figure out how to add word2vec and image_classification
# as deps.
# set_tests_properties(${TARGET_NAME}
# PROPERTIES DEPENDS ${DEP_TEST})
endforeach
()
endfunction
(
inference_api_test
)
...
...
@@ -50,9 +39,11 @@ cc_library(paddle_inference_api
SRCS paddle_inference_api.cc paddle_inference_api_impl.cc
DEPS
${
FLUID_CORE_MODULES
}
${
GLOB_OP_LIB
}
)
cc_test
(
test_paddle_inference_api
SRCS test_paddle_inference_api.cc
DEPS paddle_inference_api
)
if
(
WITH_TESTING
)
cc_test
(
test_paddle_inference_api
SRCS test_paddle_inference_api.cc
DEPS paddle_inference_api
)
inference_api_test
(
test_paddle_inference_api_impl
test_paddle_inference_api_impl.cc
)
inference_api_test
(
api_impl
ARGS test_word2vec test_image_classification
)
endif
()
paddle/fluid/framework/block_desc.cc
浏览文件 @
77340348
...
...
@@ -200,7 +200,7 @@ BlockDesc::BlockDesc(ProgramDesc *prog, proto::BlockDesc *desc)
vars_
[
var_desc
.
name
()].
reset
(
new
VarDesc
(
var_desc
));
}
for
(
const
proto
::
OpDesc
&
op_desc
:
desc_
->
ops
())
{
ops_
.
emplace_back
(
new
OpDesc
(
op_desc
,
prog
,
this
));
ops_
.
emplace_back
(
new
OpDesc
(
op_desc
,
this
));
}
}
...
...
@@ -209,7 +209,7 @@ BlockDesc::BlockDesc(const BlockDesc &other, proto::BlockDesc *desc,
:
prog_
(
prog
),
desc_
(
desc
)
{
need_update_
=
true
;
for
(
auto
&
op
:
other
.
ops_
)
{
ops_
.
emplace_back
(
new
OpDesc
(
*
op
->
Proto
(),
prog
,
this
));
ops_
.
emplace_back
(
new
OpDesc
(
*
op
,
this
));
}
for
(
auto
&
it
:
other
.
vars_
)
{
auto
*
var
=
new
VarDesc
(
*
it
.
second
);
...
...
paddle/fluid/framework/block_desc.h
浏览文件 @
77340348
...
...
@@ -105,7 +105,7 @@ class BlockDesc {
size_t
OpSize
()
const
{
return
ops_
.
size
();
}
OpDesc
*
Op
(
int
idx
)
{
return
ops_
.
at
(
idx
).
get
();
}
OpDesc
*
Op
(
int
idx
)
const
{
return
ops_
.
at
(
idx
).
get
();
}
void
Flush
();
...
...
paddle/fluid/framework/details/multi_devices_graph_builder.cc
浏览文件 @
77340348
...
...
@@ -11,11 +11,15 @@
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include
"paddle/fluid/framework/details/multi_devices_graph_builder.h"
#include
<algorithm>
#include <fstream>
#include <string>
#include <utility>
#include <vector>
#include "paddle/fluid/framework/details/broadcast_op_handle.h"
#include "paddle/fluid/framework/details/computation_op_handle.h"
#include "paddle/fluid/framework/details/multi_devices_graph_builder.h"
#include "paddle/fluid/framework/details/reduce_op_handle.h"
#include "paddle/fluid/framework/details/rpc_op_handle.h"
#include "paddle/fluid/framework/details/scale_loss_grad_op_handle.h"
...
...
@@ -26,9 +30,6 @@
#include "paddle/fluid/framework/details/nccl_all_reduce_op_handle.h"
#endif
#include <string>
#include <vector>
DEFINE_string
(
ssa_graph_path
,
"/tmp/ssa_graph.dot"
,
"the ssa graph path only print with GLOG_v=10,"
"default /tmp/graph.dot"
);
...
...
@@ -148,9 +149,9 @@ bool MultiDevSSAGraphBuilder::IsDistTrainOp(
std
::
unique_ptr
<
SSAGraph
>
MultiDevSSAGraphBuilder
::
Build
(
const
ProgramDesc
&
program
)
const
{
std
::
unordered_map
<
std
::
string
,
proto
::
VarType
::
Type
>
var_type
s
;
std
::
unordered_map
<
std
::
string
,
VarDesc
*>
all_var
s
;
for
(
auto
*
var
:
program
.
Block
(
0
).
AllVars
())
{
var_types
[
var
->
Name
()]
=
var
->
GetType
()
;
all_vars
[
var
->
Name
()]
=
var
;
}
auto
graph
=
new
SSAGraph
();
...
...
@@ -167,12 +168,28 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
auto
send_vars
=
FindDistTrainSendVars
(
program
);
auto
recv_vars
=
FindDistTrainRecvVars
(
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
());
size_t
cur_device_id
=
0
;
std
::
vector
<
int64_t
>
balance_grads
(
places_
.
size
(),
0
);
auto
get_appropriate_dev
=
[
&
](
std
::
string
&
g_name
)
->
size_t
{
auto
var_desc
=
all_vars
.
at
(
g_name
);
PADDLE_ENFORCE_NOT_NULL
(
var_desc
);
auto
dim
=
framework
::
make_ddim
(
var_desc
->
GetShape
());
int64_t
numel
=
framework
::
product
(
dim
);
PADDLE_ENFORCE_GE
(
numel
,
0
);
auto
smallest
=
std
::
min_element
(
std
::
begin
(
balance_grads
),
std
::
end
(
balance_grads
));
size_t
dev_id
=
static_cast
<
size_t
>
(
std
::
distance
(
std
::
begin
(
balance_grads
),
smallest
));
balance_grads
[
dev_id
]
+=
numel
;
return
dev_id
;
};
bool
is_forwarding
=
true
;
for
(
auto
*
op
:
program
.
Block
(
0
).
AllOps
())
{
if
(
boost
::
get
<
int
>
(
...
...
@@ -220,13 +237,13 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
switch
(
strategy_
.
reduce_
)
{
case
BuildStrategy
::
ReduceStrategy
::
kReduce
:
cur_device_id
=
get_appropriate_dev
(
g_name
);
CreateReduceOp
(
&
result
,
g_name
,
cur_device_id
);
var_name_on_devices
[
cur_device_id
].
emplace
(
g_name
);
bcast_var_name_set
[
cur_device_id
].
emplace
(
p_name
);
cur_device_id
=
(
cur_device_id
+
1
)
%
places_
.
size
();
break
;
case
BuildStrategy
::
ReduceStrategy
::
kAllReduce
:
if
(
IsSparseGradient
(
var_type
s
,
g_name
))
{
if
(
IsSparseGradient
(
all_var
s
,
g_name
))
{
CreateReduceOp
(
&
result
,
g_name
,
0
);
CreateBroadcastOp
(
&
result
,
g_name
,
0
);
}
else
{
...
...
@@ -269,10 +286,10 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
}
bool
MultiDevSSAGraphBuilder
::
IsSparseGradient
(
const
std
::
unordered_map
<
std
::
string
,
proto
::
VarType
::
Type
>
&
var_type
s
,
const
std
::
unordered_map
<
std
::
string
,
VarDesc
*>
&
all_var
s
,
const
std
::
string
&
og
)
const
{
PADDLE_ENFORCE
(
var_type
s
.
count
(
og
)
!=
0
);
if
(
var_types
.
at
(
og
)
==
proto
::
VarType
::
SELECTED_ROWS
)
{
PADDLE_ENFORCE
(
all_var
s
.
count
(
og
)
!=
0
);
if
(
all_vars
.
at
(
og
)
->
GetType
(
)
==
proto
::
VarType
::
SELECTED_ROWS
)
{
return
true
;
}
return
false
;
...
...
paddle/fluid/framework/details/multi_devices_graph_builder.h
浏览文件 @
77340348
...
...
@@ -106,7 +106,7 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
size_t
src_dev_id
)
const
;
bool
IsSparseGradient
(
const
std
::
unordered_map
<
std
::
string
,
proto
::
VarType
::
Type
>
&
var_type
s
,
const
std
::
unordered_map
<
std
::
string
,
VarDesc
*>
&
all_var
s
,
const
std
::
string
&
og
)
const
;
private:
...
...
paddle/fluid/framework/op_desc.cc
浏览文件 @
77340348
...
...
@@ -103,7 +103,7 @@ void OpDesc::CopyFrom(const OpDesc &op_desc) {
need_update_
=
true
;
}
OpDesc
::
OpDesc
(
const
proto
::
OpDesc
&
desc
,
ProgramDesc
*
prog
,
BlockDesc
*
block
)
OpDesc
::
OpDesc
(
const
proto
::
OpDesc
&
desc
,
BlockDesc
*
block
)
:
desc_
(
desc
),
need_update_
(
false
)
{
// restore inputs_
int
input_size
=
desc_
.
inputs_size
();
...
...
paddle/fluid/framework/op_desc.h
浏览文件 @
77340348
...
...
@@ -33,13 +33,14 @@ class OpDesc {
OpDesc
(
const
std
::
string
&
type
,
const
VariableNameMap
&
inputs
,
const
VariableNameMap
&
outputs
,
const
AttributeMap
&
attrs
);
OpDesc
(
const
proto
::
OpDesc
&
desc
,
ProgramDesc
*
prog
,
BlockDesc
*
block
);
OpDesc
(
const
proto
::
OpDesc
&
desc
,
BlockDesc
*
block
);
explicit
OpDesc
(
BlockDesc
*
block
)
:
block_
(
block
)
{}
OpDesc
(
const
OpDesc
&
other
,
BlockDesc
*
block
)
{
*
this
=
other
;
block_
=
block
;
need_update_
=
true
;
}
void
CopyFrom
(
const
OpDesc
&
op_desc
);
...
...
paddle/fluid/framework/program_desc.cc
浏览文件 @
77340348
...
...
@@ -51,12 +51,15 @@ ProgramDesc::ProgramDesc(const ProgramDesc &o) {
auto
*
block
=
desc_
.
mutable_blocks
(
i
);
blocks_
.
emplace_back
(
new
BlockDesc
(
*
o
.
blocks_
[
i
],
block
,
this
));
}
for
(
auto
&
block
:
blocks_
)
{
for
(
auto
*
op
:
block
->
AllOps
())
{
for
(
const
auto
&
attr
:
op
->
Proto
()
->
attrs
())
{
if
(
attr
.
type
()
==
proto
::
AttrType
::
BLOCK
)
{
size_t
blk_idx
=
attr
.
block_idx
();
op
->
SetBlockAttr
(
attr
.
name
(),
this
->
MutableBlock
(
blk_idx
));
for
(
size_t
block_id
=
0
;
block_id
<
blocks_
.
size
();
++
block_id
)
{
auto
all_ops
=
blocks_
[
block_id
]
->
AllOps
();
for
(
size_t
op_id
=
0
;
op_id
<
all_ops
.
size
();
++
op_id
)
{
auto
&
op
=
all_ops
[
op_id
];
for
(
const
std
::
string
&
attr_name
:
op
->
AttrNames
())
{
if
(
op
->
GetAttrType
(
attr_name
)
==
proto
::
AttrType
::
BLOCK
)
{
int
sub_block_id
=
o
.
Block
(
block_id
).
Op
(
op_id
)
->
GetBlockAttr
(
attr_name
);
op
->
SetBlockAttr
(
attr_name
,
MutableBlock
(
sub_block_id
));
}
}
}
...
...
@@ -86,6 +89,16 @@ ProgramDesc::ProgramDesc(const std::string &binary_str) {
for
(
auto
&
block_desc
:
*
desc_
.
mutable_blocks
())
{
blocks_
.
emplace_back
(
new
BlockDesc
(
this
,
&
block_desc
));
}
for
(
auto
&
block
:
blocks_
)
{
for
(
auto
*
op
:
block
->
AllOps
())
{
for
(
const
auto
&
attr
:
op
->
Proto
()
->
attrs
())
{
if
(
attr
.
type
()
==
proto
::
AttrType
::
BLOCK
)
{
size_t
blk_idx
=
attr
.
block_idx
();
op
->
SetBlockAttr
(
attr
.
name
(),
this
->
MutableBlock
(
blk_idx
));
}
}
}
}
}
const
std
::
vector
<
std
::
string
>
ProgramDesc
::
GetFeedTargetNames
()
{
...
...
paddle/fluid/inference/tensorrt/convert/activation_op.cc
浏览文件 @
77340348
...
...
@@ -24,7 +24,7 @@ class ReluOpConverter : public OpConverter {
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
)
override
{
// Here the two nullptr looks strange, that's because the
// framework::OpDesc's constructor is strange.
framework
::
OpDesc
op_desc
(
op
,
nullptr
,
nullptr
);
framework
::
OpDesc
op_desc
(
op
,
nullptr
);
LOG
(
INFO
)
<<
"convert a fluid relu op to tensorrt activation layer whose "
"type is Relu"
;
const
nvinfer1
::
ITensor
*
input_tensor
=
...
...
paddle/fluid/inference/tensorrt/convert/mul_op.cc
浏览文件 @
77340348
...
...
@@ -27,7 +27,7 @@ class MulOpConverter : public OpConverter {
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
)
override
{
VLOG
(
4
)
<<
"convert a fluid mul op to tensorrt fc layer without bias"
;
framework
::
OpDesc
op_desc
(
op
,
nullptr
,
nullptr
);
framework
::
OpDesc
op_desc
(
op
,
nullptr
);
// Declare inputs
auto
*
input1
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"X"
)[
0
]);
auto
*
input2
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"Y"
)[
0
]);
...
...
paddle/fluid/inference/tensorrt/convert/ut_helper.h
浏览文件 @
77340348
...
...
@@ -104,7 +104,7 @@ class TRTConvertValidation {
engine_
->
FreezeNetwork
();
// Declare outputs.
op_desc_
.
reset
(
new
framework
::
OpDesc
(
desc
,
nullptr
,
nullptr
));
op_desc_
.
reset
(
new
framework
::
OpDesc
(
desc
,
nullptr
));
// Set Inputs.
for
(
const
auto
&
input
:
op_desc_
->
InputArgumentNames
())
{
...
...
paddle/fluid/operators/bilinear_interp_op.cc
浏览文件 @
77340348
...
...
@@ -34,9 +34,22 @@ class BilinearInterpOp : public framework::OperatorWithKernel {
int
out_w
=
ctx
->
Attrs
().
Get
<
int
>
(
"out_w"
);
PADDLE_ENFORCE_EQ
(
dim_x
.
size
(),
4
,
"X's dimension must be 4"
);
if
(
ctx
->
HasInput
(
"OutSize"
))
{
auto
out_size_dim
=
ctx
->
GetInputDim
(
"OutSize"
);
PADDLE_ENFORCE_EQ
(
out_size_dim
.
size
(),
1
,
"OutSize's dimension size must be 1"
);
PADDLE_ENFORCE_EQ
(
out_size_dim
[
0
],
2
,
"OutSize's dim[0] must be 2"
);
}
std
::
vector
<
int64_t
>
dim_out
({
dim_x
[
0
],
dim_x
[
1
],
out_h
,
out_w
});
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
dim_out
));
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
()),
ctx
.
GetPlace
());
}
};
class
BilinearInterpOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -45,6 +58,10 @@ class BilinearInterpOpMaker : public framework::OpProtoAndCheckerMaker {
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)"
);
AddInput
(
"OutSize"
,
"(Tensor) This is a 1-D tensor with two number. "
"The first number is height and the second number is width."
)
.
AsDispensable
();
AddOutput
(
"Out"
,
"(Tensor) The dimension of output is (N x C x out_h x out_w]"
);
...
...
@@ -78,6 +95,12 @@ class BilinearInterpOpGrad : public framework::OperatorWithKernel {
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
dim_x
);
}
}
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
()),
ctx
.
GetPlace
());
}
};
}
// namespace operators
...
...
paddle/fluid/operators/bilinear_interp_op.cu
浏览文件 @
77340348
...
...
@@ -102,10 +102,21 @@ class BilinearInterpOpCUDAKernel : public framework::OpKernel<T> {
auto
*
input_t
=
ctx
.
Input
<
Tensor
>
(
"X"
);
// float tensor
auto
*
output_t
=
ctx
.
Output
<
Tensor
>
(
"Out"
);
// float tensor
auto
*
input
=
input_t
->
data
<
T
>
();
auto
*
output
=
output_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
int
out_h
=
ctx
.
Attr
<
int
>
(
"out_h"
);
int
out_w
=
ctx
.
Attr
<
int
>
(
"out_w"
);
auto
out_dims
=
output_t
->
dims
();
auto
out_size_t
=
ctx
.
Input
<
Tensor
>
(
"OutSize"
);
if
(
out_size_t
!=
nullptr
)
{
Tensor
sizes
;
framework
::
TensorCopy
(
*
out_size_t
,
platform
::
CPUPlace
(),
&
sizes
);
auto
size_data
=
sizes
.
data
<
int
>
();
out_h
=
size_data
[
0
];
out_w
=
size_data
[
1
];
}
auto
*
output
=
output_t
->
mutable_data
<
T
>
(
{
out_dims
[
0
],
out_dims
[
1
],
out_h
,
out_w
},
ctx
.
GetPlace
());
int
batch_size
=
input_t
->
dims
()[
0
];
int
channels
=
input_t
->
dims
()[
1
];
int
in_h
=
input_t
->
dims
()[
2
];
...
...
@@ -139,8 +150,8 @@ class BilinearInterpGradOpCUDAKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
d_input_t
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
d_output_t
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_input
=
d_input_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
*
d_output
=
d_output_t
->
data
<
T
>
();
auto
*
d_input
=
d_input_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
&
device_ctx
=
ctx
.
template
device_context
<
platform
::
CUDADeviceContext
>();
...
...
@@ -149,6 +160,16 @@ class BilinearInterpGradOpCUDAKernel : public framework::OpKernel<T> {
int
out_h
=
ctx
.
Attr
<
int
>
(
"out_h"
);
int
out_w
=
ctx
.
Attr
<
int
>
(
"out_w"
);
auto
out_size_t
=
ctx
.
Input
<
Tensor
>
(
"OutSize"
);
if
(
out_size_t
!=
nullptr
)
{
Tensor
sizes
;
framework
::
TensorCopy
(
*
out_size_t
,
platform
::
CPUPlace
(),
&
sizes
);
auto
size_data
=
sizes
.
data
<
int
>
();
out_h
=
size_data
[
0
];
out_w
=
size_data
[
1
];
}
int
batch_size
=
d_input_t
->
dims
()[
0
];
int
channels
=
d_input_t
->
dims
()[
1
];
int
in_h
=
d_input_t
->
dims
()[
2
];
...
...
paddle/fluid/operators/bilinear_interp_op.h
浏览文件 @
77340348
...
...
@@ -24,11 +24,18 @@ class BilinearInterpKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
input_t
=
ctx
.
Input
<
Tensor
>
(
"X"
);
// float tensor
auto
*
output_t
=
ctx
.
Output
<
Tensor
>
(
"Out"
);
// float tensor
auto
out_dims
=
output_t
->
dims
();
auto
*
input
=
input_t
->
data
<
T
>
();
auto
*
output
=
output_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
int
out_h
=
ctx
.
Attr
<
int
>
(
"out_h"
);
int
out_w
=
ctx
.
Attr
<
int
>
(
"out_w"
);
auto
out_size_t
=
ctx
.
Input
<
Tensor
>
(
"OutSize"
);
if
(
out_size_t
!=
nullptr
)
{
auto
out_size_data
=
out_size_t
->
data
<
int
>
();
out_h
=
out_size_data
[
0
];
out_w
=
out_size_data
[
1
];
}
auto
*
output
=
output_t
->
mutable_data
<
T
>
(
{
out_dims
[
0
],
out_dims
[
1
],
out_h
,
out_w
},
ctx
.
GetPlace
());
int
batch_size
=
input_t
->
dims
()[
0
];
int
channels
=
input_t
->
dims
()[
1
];
int
in_h
=
input_t
->
dims
()[
2
];
...
...
@@ -83,9 +90,8 @@ class BilinearInterpGradKernel : public framework::OpKernel<T> {
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
d_input_t
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
d_output_t
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_input
=
d_input_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
*
d_output
=
d_output_t
->
data
<
T
>
();
auto
*
d_input
=
d_input_t
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
&
device_ctx
=
ctx
.
template
device_context
<
platform
::
CPUDeviceContext
>();
math
::
SetConstant
<
platform
::
CPUDeviceContext
,
T
>
zero
;
...
...
@@ -93,6 +99,14 @@ class BilinearInterpGradKernel : public framework::OpKernel<T> {
int
out_h
=
ctx
.
Attr
<
int
>
(
"out_h"
);
int
out_w
=
ctx
.
Attr
<
int
>
(
"out_w"
);
auto
out_size_t
=
ctx
.
Input
<
Tensor
>
(
"OutSize"
);
if
(
out_size_t
!=
nullptr
)
{
auto
out_size_data
=
out_size_t
->
data
<
int
>
();
out_h
=
out_size_data
[
0
];
out_w
=
out_size_data
[
1
];
}
int
batch_size
=
d_input_t
->
dims
()[
0
];
int
channels
=
d_input_t
->
dims
()[
1
];
int
in_h
=
d_input_t
->
dims
()[
2
];
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
77340348
...
...
@@ -3944,7 +3944,7 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None):
input (Variable): The input tensor of bilinear interpolation,
This is a 4-D tensor of the shape
(num_batches, channels, in_h, in_w).
out_shape(list|tuple|None): Output shape of bilinear interpolation
out_shape(list|tuple|
Variable|
None): Output shape of bilinear interpolation
layer, the shape is (out_h, out_w).
Default: None
scale(int|None): The multiplier for the input height or width.
...
...
@@ -3971,13 +3971,20 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None):
def
_is_list_or_turple_
(
data
):
return
(
isinstance
(
data
,
list
)
or
isinstance
(
data
,
tuple
))
out_h
=
0
out_w
=
0
inputs
=
{
"X"
:
input
}
if
out_shape
is
not
None
:
if
not
(
_is_list_or_turple_
(
out_shape
)
and
len
(
out_shape
)
==
2
):
if
not
(
_is_list_or_turple_
(
out_shape
)
and
len
(
out_shape
)
==
2
)
and
(
out_shape
is
not
Variable
):
raise
ValueError
(
'out_shape should be a list or tuple '
,
'with length 2, (out_h, out_w).'
)
out_shape
=
list
(
map
(
int
,
out_shape
))
out_h
=
out_shape
[
0
]
out_w
=
out_shape
[
1
]
if
_is_list_or_turple_
(
out_shape
):
out_shape
=
list
(
map
(
int
,
out_shape
))
out_h
=
out_shape
[
0
]
out_w
=
out_shape
[
1
]
else
:
inputs
[
'OutSize'
]
=
out_shape
else
:
out_h
=
int
(
input
.
shape
[
2
]
*
scale
)
out_w
=
int
(
input
.
shape
[
3
]
*
scale
)
...
...
@@ -3985,7 +3992,7 @@ def upsampling_bilinear2d(input, out_shape=None, scale=None, name=None):
out
=
helper
.
create_tmp_variable
(
dtype
)
helper
.
append_op
(
type
=
"bilinear_interp"
,
inputs
=
{
"X"
:
input
}
,
inputs
=
inputs
,
outputs
=
{
"Out"
:
out
},
attrs
=
{
"out_h"
:
out_h
,
"out_w"
:
out_w
})
...
...
python/paddle/fluid/tests/unittests/test_bilinear_interp_op.py
浏览文件 @
77340348
...
...
@@ -17,7 +17,10 @@ import numpy as np
from
op_test
import
OpTest
def
bilinear_interp_np
(
input
,
out_h
,
out_w
):
def
bilinear_interp_np
(
input
,
out_h
,
out_w
,
out_size
):
if
out_size
is
not
None
:
out_h
=
out_size
[
0
]
out_w
=
out_size
[
1
]
batch_size
,
channel
,
in_h
,
in_w
=
input
.
shape
if
out_h
>
1
:
ratio_h
=
(
in_h
-
1.0
)
/
(
out_h
-
1.0
)
...
...
@@ -49,12 +52,15 @@ def bilinear_interp_np(input, out_h, out_w):
class
TestBilinearInterpOp
(
OpTest
):
def
setUp
(
self
):
self
.
out_size
=
None
self
.
init_test_case
()
self
.
op_type
=
"bilinear_interp"
input_np
=
np
.
random
.
random
(
self
.
input_shape
).
astype
(
"float32"
)
output_np
=
bilinear_interp_np
(
input_np
,
self
.
out_h
,
self
.
out_w
)
output_np
=
bilinear_interp_np
(
input_np
,
self
.
out_h
,
self
.
out_w
,
self
.
out_size
)
self
.
inputs
=
{
'X'
:
input_np
}
if
self
.
out_size
is
not
None
:
self
.
inputs
[
'OutSize'
]
=
self
.
out_size
self
.
attrs
=
{
'out_h'
:
self
.
out_h
,
'out_w'
:
self
.
out_w
}
self
.
outputs
=
{
'Out'
:
output_np
}
...
...
@@ -68,6 +74,7 @@ class TestBilinearInterpOp(OpTest):
self
.
input_shape
=
[
2
,
3
,
4
,
4
]
self
.
out_h
=
2
self
.
out_w
=
2
self
.
out_size
=
np
.
array
([
3
,
3
]).
astype
(
"int32"
)
class
TestCase1
(
TestBilinearInterpOp
):
...
...
@@ -91,5 +98,29 @@ class TestCase3(TestBilinearInterpOp):
self
.
out_w
=
128
class
TestCase4
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
input_shape
=
[
4
,
1
,
7
,
8
]
self
.
out_h
=
1
self
.
out_w
=
1
self
.
out_size
=
np
.
array
([
2
,
2
]).
astype
(
"int32"
)
class
TestCase5
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
input_shape
=
[
3
,
3
,
9
,
6
]
self
.
out_h
=
12
self
.
out_w
=
12
self
.
out_size
=
np
.
array
([
11
,
11
]).
astype
(
"int32"
)
class
TestCase6
(
TestBilinearInterpOp
):
def
init_test_case
(
self
):
self
.
input_shape
=
[
1
,
1
,
128
,
64
]
self
.
out_h
=
64
self
.
out_w
=
128
self
.
out_size
=
np
.
array
([
65
,
129
]).
astype
(
"int32"
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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