Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
PaddleDetection
提交
0fbe0a7a
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
大约 1 年 前同步成功
通知
692
Star
11112
Fork
2696
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
184
列表
看板
标记
里程碑
合并请求
40
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
PaddleDetection
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
184
Issue
184
列表
看板
标记
里程碑
合并请求
40
合并请求
40
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
提交
0fbe0a7a
编写于
8月 31, 2018
作者:
L
luotao1
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add multi-thread ut for ditu-rnn
上级
d0c65bff
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
119 addition
and
86 deletion
+119
-86
paddle/fluid/framework/ir/attention_lstm_fuse_pass.cc
paddle/fluid/framework/ir/attention_lstm_fuse_pass.cc
+1
-1
paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc
paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc
+4
-4
paddle/fluid/framework/ir/graph_pattern_detector.cc
paddle/fluid/framework/ir/graph_pattern_detector.cc
+1
-1
paddle/fluid/inference/analysis/analyzer_tester.cc
paddle/fluid/inference/analysis/analyzer_tester.cc
+69
-76
paddle/fluid/inference/api/analysis_predictor.cc
paddle/fluid/inference/api/analysis_predictor.cc
+3
-4
paddle/fluid/inference/api/helper.h
paddle/fluid/inference/api/helper.h
+41
-0
未找到文件。
paddle/fluid/framework/ir/attention_lstm_fuse_pass.cc
浏览文件 @
0fbe0a7a
...
...
@@ -13,10 +13,10 @@
// limitations under the License.
#include "paddle/fluid/framework/ir/attention_lstm_fuse_pass.h"
#include <string>
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
#include "paddle/fluid/framework/ir/graph_viz_pass.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/inference/api/helper.h"
namespace
paddle
{
namespace
framework
{
...
...
paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc
浏览文件 @
0fbe0a7a
...
...
@@ -35,7 +35,6 @@ std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
auto
handler
=
[
&
](
const
GraphPatternDetector
::
subgraph_t
&
subgraph
,
Graph
*
g
)
{
auto
*
id
=
subgraph
.
at
(
gpd
.
pattern
().
RetrieveNode
(
"any_node"
));
marked_nodes
.
insert
(
id
);
};
...
...
@@ -89,7 +88,6 @@ std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
LINK_TO
(
op
,
hidden_n
);
#undef LINK_TO
return
op
;
};
lstm_creator
(
16
,
12
,
14
,
18
,
17
,
22
,
21
,
19
);
...
...
@@ -105,14 +103,16 @@ std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
for
(
auto
it
=
node
->
inputs
.
begin
();
it
!=
node
->
inputs
.
end
();)
{
if
(
marked_nodes
.
count
(
*
it
))
{
it
=
const_cast
<
Node
*>
(
node
)
->
inputs
.
erase
(
it
);
}
else
}
else
{
it
++
;
}
}
for
(
auto
it
=
node
->
outputs
.
begin
();
it
!=
node
->
outputs
.
end
();)
{
if
(
marked_nodes
.
count
(
*
it
))
{
it
=
const_cast
<
Node
*>
(
node
)
->
outputs
.
erase
(
it
);
}
else
}
else
{
it
++
;
}
}
}
...
...
paddle/fluid/framework/ir/graph_pattern_detector.cc
浏览文件 @
0fbe0a7a
...
...
@@ -81,7 +81,7 @@ void GraphPatternDetector::operator()(Graph* graph,
LOG
(
INFO
)
<<
"detect "
<<
subgraphs
.
size
()
<<
" subgraph matches the pattern"
;
int
id
=
0
;
for
(
auto
&
g
:
subgraphs
)
{
LOG
(
INFO
)
<<
"optimizing #"
<<
id
++
<<
" subgraph"
;
VLOG
(
3
)
<<
"optimizing #"
<<
id
++
<<
" subgraph"
;
handler
(
g
,
graph
);
}
}
...
...
paddle/fluid/inference/analysis/analyzer_tester.cc
浏览文件 @
0fbe0a7a
...
...
@@ -16,6 +16,7 @@
#include <google/protobuf/text_format.h>
#include <gtest/gtest.h>
#include <thread> // NOLINT
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/pass.h"
#include "paddle/fluid/inference/analysis/ut_helper.h"
...
...
@@ -23,19 +24,17 @@
#include "paddle/fluid/inference/api/helper.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/inference/utils/singleton.h"
#include "paddle/fluid/platform/profiler.h"
DEFINE_string
(
infer_ditu_rnn_model
,
""
,
"model path for ditu RNN"
);
DEFINE_string
(
infer_ditu_rnn_data
,
""
,
"data path for ditu RNN"
);
DEFINE_int32
(
batch_size
,
10
,
"batch size."
);
DEFINE_int32
(
repeat
,
1
,
"Running the inference program repeat times."
);
DEFINE_int32
(
num_threads
,
1
,
"Running the inference program in multi-threads."
);
namespace
paddle
{
namespace
inference
{
namespace
analysis
{
using
namespace
framework
;
TEST
(
Analyzer
,
analysis_without_tensorrt
)
{
FLAGS_IA_enable_tensorrt_subgraph_engine
=
false
;
Argument
argument
;
...
...
@@ -219,39 +218,6 @@ void PrepareInputs(std::vector<PaddleTensor> *input_slots, DataRecord *data,
}
}
std
::
string
DescribeTensor
(
const
PaddleTensor
&
tensor
)
{
std
::
stringstream
os
;
os
<<
"Tensor ["
<<
tensor
.
name
<<
"]
\n
"
;
os
<<
" - type: "
;
switch
(
tensor
.
dtype
)
{
case
PaddleDType
::
FLOAT32
:
os
<<
"float32"
;
break
;
case
PaddleDType
::
INT64
:
os
<<
"int64"
;
break
;
default:
os
<<
"unset"
;
}
os
<<
'\n'
;
os
<<
" - shape: "
<<
to_string
(
tensor
.
shape
)
<<
'\n'
;
os
<<
" - lod: "
;
for
(
auto
&
l
:
tensor
.
lod
)
{
os
<<
to_string
(
l
)
<<
"; "
;
}
os
<<
"
\n
"
;
os
<<
" - data: "
;
int
dim
=
std
::
accumulate
(
tensor
.
shape
.
begin
(),
tensor
.
shape
.
end
(),
1
,
[](
int
a
,
int
b
)
{
return
a
*
b
;
});
for
(
int
i
=
0
;
i
<
dim
;
i
++
)
{
os
<<
static_cast
<
float
*>
(
tensor
.
data
.
data
())[
i
]
<<
" "
;
}
os
<<
'\n'
;
return
os
.
str
();
}
}
// namespace
const
float
ditu_rnn_target_data
[]
=
{
...
...
@@ -266,58 +232,92 @@ const float ditu_rnn_target_data[] = {
93.5771
,
3.84641
,
0
,
0
,
0
,
0
,
0
,
0
,
169.426
,
0
,
0
,
0
,
0
,
0
,
0
,
0
};
// Test with a really complicate model.
void
TestDituRNNPrediction
(
const
std
::
string
&
model_path
,
const
std
::
string
&
data_path
,
int
batch_size
,
bool
use_analysis
,
bool
activate_ir
,
int
num_times
=
1
)
{
void
TestDituRNNPrediction
(
bool
use_analysis_and_activate_ir
=
false
,
int
num_threads
=
FLAGS_num_threads
)
{
NativeConfig
config
;
config
.
prog_file
=
FLAGS_infer_ditu_rnn_model
+
"/__model__"
;
config
.
param_file
=
FLAGS_infer_ditu_rnn_model
+
"/param"
;
config
.
use_gpu
=
false
;
config
.
device
=
0
;
config
.
specify_input_name
=
true
;
int
batch_size
=
FLAGS_batch_size
;
int
num_times
=
FLAGS_repeat
;
auto
base_predictor
=
CreatePaddlePredictor
<
NativeConfig
,
PaddleEngineKind
::
kNative
>
(
config
);
auto
predictor
=
CreatePaddlePredictor
<
NativeConfig
,
PaddleEngineKind
::
kAnalysis
>
(
config
);
std
::
vector
<
PaddleTensor
>
input_slots
;
DataRecord
data
(
data_path
,
batch_size
);
DataRecord
data
(
FLAGS_infer_ditu_rnn_data
,
batch_size
);
// Prepare inputs.
PrepareInputs
(
&
input_slots
,
&
data
,
batch_size
);
std
::
vector
<
PaddleTensor
>
outputs
,
base_outputs
;
base_predictor
->
Run
(
input_slots
,
&
base_outputs
);
Timer
timer
;
timer
.
tic
();
for
(
int
i
=
0
;
i
<
num_times
;
i
++
)
{
predictor
->
Run
(
input_slots
,
&
outputs
);
}
LOG
(
INFO
)
<<
"===========profile result==========="
;
LOG
(
INFO
)
<<
"batch_size: "
<<
batch_size
<<
", repeat: "
<<
num_times
<<
", latency: "
<<
timer
.
toc
()
/
num_times
<<
"ms"
;
if
(
num_threads
==
1
)
{
std
::
vector
<
PaddleTensor
>
input_slots
;
// Prepare inputs.
DataRecord
data
(
FLAGS_infer_ditu_rnn_data
,
batch_size
);
PrepareInputs
(
&
input_slots
,
&
data
,
batch_size
);
Timer
timer
;
timer
.
tic
();
for
(
int
i
=
0
;
i
<
num_times
;
i
++
)
{
predictor
->
Run
(
input_slots
,
&
outputs
);
}
print_time
(
batch_size
,
num_times
,
1
,
0
,
timer
.
toc
()
/
num_times
);
}
else
{
std
::
vector
<
std
::
thread
>
threads
;
std
::
vector
<
PaddleTensor
>
input_slots
;
// Prepare inputs.
PrepareInputs
(
&
input_slots
,
&
data
,
batch_size
);
std
::
vector
<
PaddleTensor
>
outputs
;
for
(
int
tid
=
0
;
tid
<
num_threads
;
++
tid
)
{
threads
.
emplace_back
([
&
,
tid
]()
{
auto
predictor_tid
=
CreatePaddlePredictor
<
NativeConfig
,
PaddleEngineKind
::
kAnalysis
>
(
config
);
DataRecord
data
(
FLAGS_infer_ditu_rnn_data
,
batch_size
);
Timer
timer
;
timer
.
tic
();
for
(
int
i
=
0
;
i
<
num_times
;
i
++
)
{
predictor_tid
->
Run
(
input_slots
,
&
outputs
);
}
print_time
(
batch_size
,
num_times
,
num_threads
,
tid
,
timer
.
toc
()
/
num_times
);
});
}
for
(
int
i
=
0
;
i
<
num_threads
;
++
i
)
{
threads
[
i
].
join
();
}
}
LOG
(
INFO
)
<<
"====================================="
;
PADDLE_ENFORCE_GT
(
outputs
.
size
(),
0
);
PADDLE_ENFORCE_EQ
(
outputs
.
size
(),
base_outputs
.
size
());
for
(
size_t
i
=
0
;
i
<
outputs
.
size
();
i
++
)
{
auto
&
out
=
outputs
[
i
];
auto
&
base_out
=
base_outputs
[
i
];
size_t
size
=
std
::
accumulate
(
out
.
shape
.
begin
(),
out
.
shape
.
end
(),
1
,
[](
int
a
,
int
b
)
{
return
a
*
b
;
});
size_t
size1
=
std
::
accumulate
(
base_out
.
shape
.
begin
(),
base_out
.
shape
.
end
(),
1
,
[](
int
a
,
int
b
)
{
return
a
*
b
;
});
PADDLE_ENFORCE_EQ
(
size
,
size1
);
PADDLE_ENFORCE_GT
(
size
,
0
);
float
*
data
=
static_cast
<
float
*>
(
out
.
data
.
data
());
float
*
base_data
=
static_cast
<
float
*>
(
base_out
.
data
.
data
());
for
(
size_t
i
=
0
;
i
<
size
;
i
++
)
{
EXPECT_NEAR
(
data
[
i
],
base_data
[
i
],
1e-3
);
if
(
num_threads
==
1
)
{
PADDLE_ENFORCE_GT
(
outputs
.
size
(),
0
);
PADDLE_ENFORCE_EQ
(
outputs
.
size
(),
base_outputs
.
size
());
for
(
size_t
i
=
0
;
i
<
outputs
.
size
();
i
++
)
{
auto
&
out
=
outputs
[
i
];
auto
&
base_out
=
base_outputs
[
i
];
size_t
size
=
std
::
accumulate
(
out
.
shape
.
begin
(),
out
.
shape
.
end
(),
1
,
[](
int
a
,
int
b
)
{
return
a
*
b
;
});
size_t
size1
=
std
::
accumulate
(
base_out
.
shape
.
begin
(),
base_out
.
shape
.
end
(),
1
,
[](
int
a
,
int
b
)
{
return
a
*
b
;
});
PADDLE_ENFORCE_EQ
(
size
,
size1
);
PADDLE_ENFORCE_GT
(
size
,
0
);
float
*
data
=
static_cast
<
float
*>
(
out
.
data
.
data
());
float
*
base_data
=
static_cast
<
float
*>
(
base_out
.
data
.
data
());
for
(
size_t
i
=
0
;
i
<
size
;
i
++
)
{
EXPECT_NEAR
(
data
[
i
],
base_data
[
i
],
1e-3
);
}
}
}
if
(
use_analysis
&&
activate_ir
)
{
if
(
use_analysis
_and_
activate_ir
)
{
AnalysisPredictor
*
analysis_predictor
=
dynamic_cast
<
AnalysisPredictor
*>
(
predictor
.
get
());
auto
&
fuse_statis
=
analysis_predictor
->
analysis_argument
()
...
...
@@ -334,23 +334,16 @@ void TestDituRNNPrediction(const std::string &model_path,
// Directly infer with the original model.
TEST
(
Analyzer
,
DituRNN_without_analysis
)
{
TestDituRNNPrediction
(
FLAGS_infer_ditu_rnn_model
,
FLAGS_infer_ditu_rnn_data
,
FLAGS_batch_size
,
false
,
false
,
FLAGS_repeat
);
}
// Inference with the original model with the analysis turned on, the analysis
// module will transform the program to a data flow graph.
TEST
(
Analyzer
,
DituRNN_with_analysis
)
{
LOG
(
INFO
)
<<
"ditu rnn with analysis"
;
TestDituRNNPrediction
(
FLAGS_infer_ditu_rnn_model
,
FLAGS_infer_ditu_rnn_data
,
FLAGS_batch_size
,
true
,
false
,
FLAGS_repeat
);
LOG
(
INFO
)
<<
"ditu rnn without analysis"
;
TestDituRNNPrediction
(
false
,
1
);
TestDituRNNPrediction
(
false
,
4
);
// multi-threads
}
// Inference with analysis and IR. The IR module will fuse some large kernels.
TEST
(
Analyzer
,
DituRNN_with_analysis_with_IR
)
{
LOG
(
INFO
)
<<
"ditu rnn with analysis and IR fuse"
;
TestDituRNNPrediction
(
FLAGS_infer_ditu_rnn_model
,
FLAGS_infer_ditu_rnn_data
,
FLAGS_batch_size
,
true
,
true
,
FLAGS_repeat
);
TestDituRNNPrediction
(
true
,
1
);
TestDituRNNPrediction
(
true
,
4
);
// multi-threads
}
}
// namespace analysis
...
...
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @
0fbe0a7a
...
...
@@ -14,6 +14,8 @@
#include "paddle/fluid/inference/api/analysis_predictor.h"
#include <memory>
#include <string>
#include <vector>
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/pass.h"
#include "paddle/fluid/framework/scope.h"
...
...
@@ -30,7 +32,6 @@ bool AnalysisPredictor::Init(
}
else
{
place_
=
paddle
::
platform
::
CPUPlace
();
}
PADDLE_ENFORCE
(
!
parent_scope
);
if
(
parent_scope
)
{
scope_
=
parent_scope
;
sub_scope_
=
&
(
parent_scope
->
NewScope
());
...
...
@@ -92,8 +93,6 @@ void AnalysisPredictor::OptimizeInferenceProgram() {
Analyzer
().
Run
(
&
argument_
);
CHECK
(
argument_
.
transformed_program_desc
);
VLOG
(
5
)
<<
"to prepare executor"
;
// LOG(INFO) << "transformed_parogram_desc " <<
// argument.transformed_program_desc->DebugString();
inference_program_
.
reset
(
new
framework
::
ProgramDesc
(
*
argument_
.
transformed_program_desc
));
PADDLE_ENFORCE
(
argument_
.
Has
(
framework
::
ir
::
kParamScopeAttr
));
...
...
@@ -106,7 +105,7 @@ void AnalysisPredictor::OptimizeInferenceProgram() {
template
<
>
std
::
unique_ptr
<
PaddlePredictor
>
CreatePaddlePredictor
<
NativeConfig
,
PaddleEngineKind
::
kAnalysis
>
(
const
NativeConfig
&
config
)
{
VLOG
(
3
)
<<
"create
Native
Predictor"
;
VLOG
(
3
)
<<
"create
Analysis
Predictor"
;
if
(
config
.
use_gpu
)
{
// 1. GPU memeroy
PADDLE_ENFORCE_GT
(
...
...
paddle/fluid/inference/api/helper.h
浏览文件 @
0fbe0a7a
...
...
@@ -14,6 +14,7 @@
#pragma once
#include <glog/logging.h>
#include <sys/time.h>
#include <algorithm>
#include <sstream>
...
...
@@ -106,5 +107,45 @@ static void TensorAssignData(PaddleTensor *tensor,
}
}
std
::
string
DescribeTensor
(
const
PaddleTensor
&
tensor
)
{
std
::
stringstream
os
;
os
<<
"Tensor ["
<<
tensor
.
name
<<
"]
\n
"
;
os
<<
" - type: "
;
switch
(
tensor
.
dtype
)
{
case
PaddleDType
::
FLOAT32
:
os
<<
"float32"
;
break
;
case
PaddleDType
::
INT64
:
os
<<
"int64"
;
break
;
default:
os
<<
"unset"
;
}
os
<<
'\n'
;
os
<<
" - shape: "
<<
to_string
(
tensor
.
shape
)
<<
'\n'
;
os
<<
" - lod: "
;
for
(
auto
&
l
:
tensor
.
lod
)
{
os
<<
to_string
(
l
)
<<
"; "
;
}
os
<<
"
\n
"
;
os
<<
" - data: "
;
int
dim
=
std
::
accumulate
(
tensor
.
shape
.
begin
(),
tensor
.
shape
.
end
(),
1
,
[](
int
a
,
int
b
)
{
return
a
*
b
;
});
for
(
int
i
=
0
;
i
<
dim
;
i
++
)
{
os
<<
static_cast
<
float
*>
(
tensor
.
data
.
data
())[
i
]
<<
" "
;
}
os
<<
'\n'
;
return
os
.
str
();
}
void
print_time
(
int
batch_size
,
int
repeat
,
int
num_threads
,
int
tid
,
double
latency
)
{
LOG
(
INFO
)
<<
"batch_size: "
<<
batch_size
<<
", repeat: "
<<
repeat
<<
", threads: "
<<
num_threads
<<
", thread id: "
<<
tid
<<
", latency: "
<<
latency
<<
"ms"
;
}
}
// namespace inference
}
// namespace paddle
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录