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体验新版 GitCode,发现更多精彩内容 >>
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140fc1e9
编写于
1月 18, 2019
作者:
T
Tao Luo
提交者:
GitHub
1月 18, 2019
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Merge pull request #15392 from luotao1/pyramid_dnn
add pyramid_dnn c++ inference test
上级
c9e5aa19
66856308
变更
2
隐藏空白更改
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并排
Showing
2 changed file
with
187 addition
and
0 deletion
+187
-0
paddle/fluid/inference/tests/api/CMakeLists.txt
paddle/fluid/inference/tests/api/CMakeLists.txt
+5
-0
paddle/fluid/inference/tests/api/analyzer_pyramid_dnn_tester.cc
.../fluid/inference/tests/api/analyzer_pyramid_dnn_tester.cc
+182
-0
未找到文件。
paddle/fluid/inference/tests/api/CMakeLists.txt
浏览文件 @
140fc1e9
...
...
@@ -86,6 +86,11 @@ set(MM_DNN_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/mm_dnn")
download_model_and_data
(
${
MM_DNN_INSTALL_DIR
}
"MM_DNN_model.tar.gz"
"MM_DNN_data.txt.tar.gz"
)
inference_analysis_api_test
(
test_analyzer_mm_dnn
${
MM_DNN_INSTALL_DIR
}
analyzer_mm_dnn_tester.cc
)
# Pyramid DNN
set
(
PYRAMID_DNN_INSTALL_DIR
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/pyramid_dnn"
)
download_model_and_data
(
${
PYRAMID_DNN_INSTALL_DIR
}
"PyramidDNN_model.tar.gz"
"PyramidDNN_data.txt.tar.gz"
)
inference_analysis_api_test
(
test_analyzer_pyramid_dnn
${
PYRAMID_DNN_INSTALL_DIR
}
analyzer_pyramid_dnn_tester.cc
)
# text_classification
set
(
TEXT_CLASSIFICATION_INSTALL_DIR
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/text_classification"
)
download_model_and_data
(
${
TEXT_CLASSIFICATION_INSTALL_DIR
}
"text-classification-Senta.tar.gz"
"text_classification_data.txt.tar.gz"
)
...
...
paddle/fluid/inference/tests/api/analyzer_pyramid_dnn_tester.cc
0 → 100644
浏览文件 @
140fc1e9
// Copyright (c) 2018 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/fluid/inference/tests/api/tester_helper.h"
namespace
paddle
{
namespace
inference
{
using
contrib
::
AnalysisConfig
;
struct
DataRecord
{
std
::
vector
<
std
::
vector
<
int64_t
>>
query_basic
,
query_phrase
,
title_basic
,
title_phrase
;
std
::
vector
<
size_t
>
lod1
,
lod2
,
lod3
,
lod4
;
size_t
batch_iter
{
0
},
batch_size
{
1
},
num_samples
;
// total number of samples
DataRecord
()
=
default
;
explicit
DataRecord
(
const
std
::
string
&
path
,
int
batch_size
=
1
)
:
batch_size
(
batch_size
)
{
Load
(
path
);
}
DataRecord
NextBatch
()
{
DataRecord
data
;
size_t
batch_end
=
batch_iter
+
batch_size
;
// NOTE skip the final batch, if no enough data is provided.
if
(
batch_end
<=
query_basic
.
size
())
{
GetInputPerBatch
(
query_basic
,
&
data
.
query_basic
,
&
data
.
lod1
,
batch_iter
,
batch_end
);
GetInputPerBatch
(
query_phrase
,
&
data
.
query_phrase
,
&
data
.
lod2
,
batch_iter
,
batch_end
);
GetInputPerBatch
(
title_basic
,
&
data
.
title_basic
,
&
data
.
lod3
,
batch_iter
,
batch_end
);
GetInputPerBatch
(
title_phrase
,
&
data
.
title_phrase
,
&
data
.
lod4
,
batch_iter
,
batch_end
);
}
batch_iter
+=
batch_size
;
return
data
;
}
void
Load
(
const
std
::
string
&
path
)
{
std
::
ifstream
file
(
path
);
std
::
string
line
;
int
num_lines
=
0
;
while
(
std
::
getline
(
file
,
line
))
{
std
::
vector
<
std
::
string
>
data
;
split
(
line
,
';'
,
&
data
);
// load query data
std
::
vector
<
int64_t
>
query_basic_data
;
split_to_int64
(
data
[
1
],
' '
,
&
query_basic_data
);
std
::
vector
<
int64_t
>
query_phrase_data
;
split_to_int64
(
data
[
2
],
' '
,
&
query_phrase_data
);
// load title data
std
::
vector
<
int64_t
>
title_basic_data
;
split_to_int64
(
data
[
3
],
' '
,
&
title_basic_data
);
std
::
vector
<
int64_t
>
title_phrase_data
;
split_to_int64
(
data
[
4
],
' '
,
&
title_phrase_data
);
// filter the empty data
bool
flag
=
data
[
1
].
size
()
&&
data
[
2
].
size
()
&&
data
[
3
].
size
()
&&
data
[
4
].
size
();
if
(
flag
)
{
query_basic
.
push_back
(
std
::
move
(
query_basic_data
));
query_phrase
.
push_back
(
std
::
move
(
query_phrase_data
));
title_basic
.
push_back
(
std
::
move
(
title_basic_data
));
title_phrase
.
push_back
(
std
::
move
(
title_phrase_data
));
num_lines
++
;
}
}
num_samples
=
num_lines
;
}
};
void
PrepareInputs
(
std
::
vector
<
PaddleTensor
>
*
input_slots
,
DataRecord
*
data
,
int
batch_size
)
{
PaddleTensor
query_basic_tensor
,
query_phrase_tensor
,
title_basic_tensor
,
title_phrase_tensor
;
query_basic_tensor
.
name
=
"query_basic"
;
query_phrase_tensor
.
name
=
"query_phrase"
;
title_basic_tensor
.
name
=
"pos_title_basic"
;
title_phrase_tensor
.
name
=
"pos_title_phrase"
;
auto
one_batch
=
data
->
NextBatch
();
// assign data
TensorAssignData
<
int64_t
>
(
&
query_basic_tensor
,
one_batch
.
query_basic
,
one_batch
.
lod1
);
TensorAssignData
<
int64_t
>
(
&
query_phrase_tensor
,
one_batch
.
query_phrase
,
one_batch
.
lod2
);
TensorAssignData
<
int64_t
>
(
&
title_basic_tensor
,
one_batch
.
title_basic
,
one_batch
.
lod3
);
TensorAssignData
<
int64_t
>
(
&
title_phrase_tensor
,
one_batch
.
title_phrase
,
one_batch
.
lod4
);
// Set inputs.
input_slots
->
assign
({
query_basic_tensor
,
query_phrase_tensor
,
title_basic_tensor
,
title_phrase_tensor
});
for
(
auto
&
tensor
:
*
input_slots
)
{
tensor
.
dtype
=
PaddleDType
::
INT64
;
}
}
void
SetConfig
(
contrib
::
AnalysisConfig
*
cfg
)
{
cfg
->
SetModel
(
FLAGS_infer_model
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
DataRecord
data
(
FLAGS_infer_data
,
FLAGS_batch_size
);
std
::
vector
<
PaddleTensor
>
input_slots
;
int
epoch
=
FLAGS_test_all_data
?
data
.
num_samples
/
FLAGS_batch_size
:
1
;
LOG
(
INFO
)
<<
"number of samples: "
<<
epoch
*
FLAGS_batch_size
;
for
(
int
bid
=
0
;
bid
<
epoch
;
++
bid
)
{
PrepareInputs
(
&
input_slots
,
&
data
,
FLAGS_batch_size
);
(
*
inputs
).
emplace_back
(
input_slots
);
}
}
// Easy for profiling independently.
TEST
(
Analyzer_Pyramid_DNN
,
profile
)
{
contrib
::
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
PaddleTensor
>
outputs
;
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
TestPrediction
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
,
&
outputs
,
FLAGS_num_threads
);
if
(
FLAGS_num_threads
==
1
&&
!
FLAGS_test_all_data
)
{
PADDLE_ENFORCE_EQ
(
outputs
.
size
(),
1UL
);
size_t
size
=
GetSize
(
outputs
[
0
]);
PADDLE_ENFORCE_GT
(
size
,
0
);
float
*
result
=
static_cast
<
float
*>
(
outputs
[
0
].
data
.
data
());
// output is probability, which is in (0, 1).
for
(
size_t
i
=
0
;
i
<
size
;
i
++
)
{
EXPECT_GT
(
result
[
i
],
0
);
EXPECT_LT
(
result
[
i
],
1
);
}
}
}
// Check the fuse status
TEST
(
Analyzer_Pyramid_DNN
,
fuse_statis
)
{
contrib
::
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
int
num_ops
;
auto
predictor
=
CreatePaddlePredictor
<
AnalysisConfig
>
(
cfg
);
auto
fuse_statis
=
GetFuseStatis
(
static_cast
<
AnalysisPredictor
*>
(
predictor
.
get
()),
&
num_ops
);
}
// Compare result of NativeConfig and AnalysisConfig
TEST
(
Analyzer_Pyramid_DNN
,
compare
)
{
contrib
::
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareNativeAndAnalysis
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
// Compare Deterministic result
TEST
(
Analyzer_Pyramid_DNN
,
compare_determine
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
CompareDeterministic
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
);
}
}
// namespace inference
}
// namespace paddle
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