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体验新版 GitCode,发现更多精彩内容 >>
提交
fe21578a
编写于
3月 20, 2019
作者:
S
Sylwester Fraczek
浏览文件
操作
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电子邮件补丁
差异文件
create test for quantized resnet50
test=develop
上级
2d8b7b3a
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
268 addition
and
13 deletion
+268
-13
paddle/fluid/inference/tests/api/CMakeLists.txt
paddle/fluid/inference/tests/api/CMakeLists.txt
+28
-0
paddle/fluid/inference/tests/api/analyzer_bert_tester.cc
paddle/fluid/inference/tests/api/analyzer_bert_tester.cc
+0
-13
paddle/fluid/inference/tests/api/analyzer_int8_image_classification_tester.cc
...ce/tests/api/analyzer_int8_image_classification_tester.cc
+189
-0
paddle/fluid/inference/tests/api/tester_helper.h
paddle/fluid/inference/tests/api/tester_helper.h
+51
-0
未找到文件。
paddle/fluid/inference/tests/api/CMakeLists.txt
浏览文件 @
fe21578a
...
...
@@ -23,6 +23,12 @@ function(inference_analysis_api_test target install_dir filename)
ARGS --infer_model=
${
install_dir
}
/model --infer_data=
${
install_dir
}
/data.txt
)
endfunction
()
function
(
inference_analysis_api_int8_test target model_dir data_dir filename
)
inference_analysis_test
(
${
target
}
SRCS
${
filename
}
EXTRA_DEPS
${
INFERENCE_EXTRA_DEPS
}
benchmark
ARGS --infer_model=
${
model_dir
}
/model --infer_data=
${
data_dir
}
/data.bin --batch_size=100
)
endfunction
()
function
(
inference_analysis_api_test_with_fake_data target install_dir filename model_name
)
download_model
(
${
install_dir
}
${
model_name
}
)
inference_analysis_test
(
${
target
}
SRCS
${
filename
}
...
...
@@ -138,6 +144,28 @@ inference_analysis_api_test_with_fake_data(test_analyzer_resnet50
inference_analysis_api_test_with_fake_data
(
test_analyzer_mobilenet_depthwise_conv
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/mobilenet_depthwise_conv"
analyzer_resnet50_tester.cc
"mobilenet_model.tar.gz"
SERIAL
)
# int8 image classification tests
if
(
WITH_MKLDNN
)
set
(
INT8_DATA_DIR
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/int8"
)
if
(
NOT EXISTS
${
INT8_DATA_DIR
}
)
inference_download_and_uncompress
(
${
INT8_DATA_DIR
}
"http://paddle-inference-dist.bj.bcebos.com/int8"
"imagenet_val_100.bin.tar.gz"
)
endif
()
#resnet50 int8
set
(
INT8_RESNET50_MODEL_DIR
"
${
INT8_DATA_DIR
}
/resnet50"
)
if
(
NOT EXISTS
${
INT8_RESNET50_MODEL_DIR
}
)
inference_download_and_uncompress
(
${
INT8_RESNET50_MODEL_DIR
}
"http://paddle-inference-dist.bj.bcebos.com/int8"
"resnet50_int8_model.tar.gz"
)
endif
()
inference_analysis_api_int8_test
(
test_analyzer_int8_resnet50
${
INT8_RESNET50_MODEL_DIR
}
${
INT8_DATA_DIR
}
analyzer_int8_image_classification_tester.cc SERIAL
)
#mobilenet int8
set
(
INT8_MOBILENET_MODEL_DIR
"
${
INT8_DATA_DIR
}
/mobilenet"
)
if
(
NOT EXISTS
${
INT8_MOBILENET_MODEL_DIR
}
)
inference_download_and_uncompress
(
${
INT8_MOBILENET_MODEL_DIR
}
"http://paddle-inference-dist.bj.bcebos.com/int8"
"mobilenetv1_int8_model.tar.gz"
)
endif
()
inference_analysis_api_int8_test
(
test_analyzer_int8_mobilenet
${
INT8_MOBILENET_MODEL_DIR
}
${
INT8_DATA_DIR
}
analyzer_int8_image_classification_tester.cc SERIAL
)
endif
()
# bert, max_len=20, embedding_dim=128
set
(
BERT_INSTALL_DIR
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/bert_emb128"
)
download_model_and_data
(
${
BERT_INSTALL_DIR
}
"bert_emb128_model.tar.gz"
"bert_data_len20.txt.tar.gz"
)
...
...
paddle/fluid/inference/tests/api/analyzer_bert_tester.cc
浏览文件 @
fe21578a
...
...
@@ -53,19 +53,6 @@ void Split(const std::string &line, char sep, std::vector<T> *v) {
}
}
template
<
typename
T
>
constexpr
paddle
::
PaddleDType
GetPaddleDType
();
template
<
>
constexpr
paddle
::
PaddleDType
GetPaddleDType
<
int64_t
>
()
{
return
paddle
::
PaddleDType
::
INT64
;
}
template
<
>
constexpr
paddle
::
PaddleDType
GetPaddleDType
<
float
>
()
{
return
paddle
::
PaddleDType
::
FLOAT32
;
}
// Parse tensor from string
template
<
typename
T
>
bool
ParseTensor
(
const
std
::
string
&
field
,
paddle
::
PaddleTensor
*
tensor
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_int8_image_classification_tester.cc
0 → 100644
浏览文件 @
fe21578a
/* Copyright (c) 2019 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 <fstream>
#include <iostream>
#include "paddle/fluid/inference/api/paddle_analysis_config.h"
#include "paddle/fluid/inference/tests/api/tester_helper.h"
DEFINE_int32
(
iterations
,
0
,
"Number of iterations"
);
namespace
paddle
{
namespace
inference
{
namespace
analysis
{
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
SetModel
(
FLAGS_infer_model
);
cfg
->
SetProgFile
(
"__model__"
);
cfg
->
DisableGpu
();
cfg
->
SwitchIrOptim
();
cfg
->
SwitchSpecifyInputNames
(
false
);
cfg
->
SetCpuMathLibraryNumThreads
(
FLAGS_paddle_num_threads
);
cfg
->
EnableMKLDNN
();
}
template
<
typename
T
>
class
TensorReader
{
public:
TensorReader
(
std
::
ifstream
&
file
,
size_t
beginning_offset
,
std
::
vector
<
int
>
shape
,
std
::
string
name
)
:
file_
(
file
),
position
(
beginning_offset
),
shape_
(
shape
),
name_
(
name
)
{
numel
=
std
::
accumulate
(
shape_
.
begin
(),
shape_
.
end
(),
1
,
std
::
multiplies
<
T
>
());
}
PaddleTensor
NextBatch
()
{
PaddleTensor
tensor
;
tensor
.
name
=
name_
;
tensor
.
shape
=
shape_
;
tensor
.
dtype
=
GetPaddleDType
<
T
>
();
tensor
.
data
.
Resize
(
numel
*
sizeof
(
T
));
file_
.
seekg
(
position
);
file_
.
read
(
static_cast
<
char
*>
(
tensor
.
data
.
data
()),
numel
*
sizeof
(
T
));
position
=
file_
.
tellg
();
if
(
file_
.
eof
())
LOG
(
ERROR
)
<<
name_
<<
": reached end of stream"
;
if
(
file_
.
fail
())
throw
std
::
runtime_error
(
name_
+
": failed reading file."
);
return
tensor
;
}
protected:
std
::
ifstream
&
file_
;
size_t
position
;
std
::
vector
<
int
>
shape_
;
std
::
string
name_
;
size_t
numel
;
};
std
::
shared_ptr
<
std
::
vector
<
PaddleTensor
>>
GetWarmupData
(
const
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
&
test_data
,
int
num_images
)
{
int
test_data_batch_size
=
test_data
[
0
][
0
].
shape
[
0
];
CHECK_LE
(
static_cast
<
size_t
>
(
num_images
),
test_data
.
size
()
*
test_data_batch_size
);
PaddleTensor
images
;
images
.
name
=
"input"
;
images
.
shape
=
{
num_images
,
3
,
224
,
224
};
images
.
dtype
=
PaddleDType
::
FLOAT32
;
images
.
data
.
Resize
(
sizeof
(
float
)
*
num_images
*
3
*
224
*
224
);
PaddleTensor
labels
;
labels
.
name
=
"labels"
;
labels
.
shape
=
{
num_images
,
1
};
labels
.
dtype
=
PaddleDType
::
INT64
;
labels
.
data
.
Resize
(
sizeof
(
int64_t
)
*
num_images
);
for
(
int
i
=
0
;
i
<
num_images
;
i
++
)
{
auto
batch
=
i
/
test_data_batch_size
;
auto
element_in_batch
=
i
%
test_data_batch_size
;
std
::
copy_n
(
static_cast
<
float
*>
(
test_data
[
batch
][
0
].
data
.
data
())
+
element_in_batch
*
3
*
224
*
224
,
3
*
224
*
224
,
static_cast
<
float
*>
(
images
.
data
.
data
())
+
i
*
3
*
224
*
224
);
std
::
copy_n
(
static_cast
<
int64_t
*>
(
test_data
[
batch
][
1
].
data
.
data
())
+
element_in_batch
,
1
,
static_cast
<
int64_t
*>
(
labels
.
data
.
data
())
+
i
);
}
auto
warmup_data
=
std
::
make_shared
<
std
::
vector
<
PaddleTensor
>>
(
2
);
(
*
warmup_data
)[
0
]
=
std
::
move
(
images
);
(
*
warmup_data
)[
1
]
=
std
::
move
(
labels
);
return
warmup_data
;
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
,
int32_t
batch_size
=
FLAGS_batch_size
)
{
std
::
ifstream
file
(
FLAGS_infer_data
,
std
::
ios
::
binary
);
if
(
!
file
)
{
FAIL
()
<<
"Couldn't open file: "
<<
FLAGS_infer_data
;
}
int64_t
total_images
{
0
};
file
.
read
(
reinterpret_cast
<
char
*>
(
&
total_images
),
sizeof
(
total_images
));
LOG
(
INFO
)
<<
"Total images in file: "
<<
total_images
;
std
::
vector
<
int
>
image_batch_shape
{
batch_size
,
3
,
224
,
224
};
std
::
vector
<
int
>
label_batch_shape
{
batch_size
,
1
};
auto
labels_offset_in_file
=
static_cast
<
size_t
>
(
file
.
tellg
())
+
sizeof
(
float
)
*
total_images
*
std
::
accumulate
(
image_batch_shape
.
begin
()
+
1
,
image_batch_shape
.
end
(),
1
,
std
::
multiplies
<
int
>
());
TensorReader
<
float
>
image_reader
(
file
,
0
,
image_batch_shape
,
"input"
);
TensorReader
<
int64_t
>
label_reader
(
file
,
labels_offset_in_file
,
label_batch_shape
,
"label"
);
auto
iterations
=
total_images
/
batch_size
;
if
(
FLAGS_iterations
>
0
&&
FLAGS_iterations
<
iterations
)
iterations
=
FLAGS_iterations
;
for
(
auto
i
=
0
;
i
<
iterations
;
i
++
)
{
auto
images
=
image_reader
.
NextBatch
();
auto
labels
=
label_reader
.
NextBatch
();
inputs
->
emplace_back
(
std
::
vector
<
PaddleTensor
>
{
std
::
move
(
images
),
std
::
move
(
labels
)});
}
}
TEST
(
Analyzer_int8_resnet50
,
quantization
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
AnalysisConfig
q_cfg
;
SetConfig
(
&
q_cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
,
100
);
std
::
shared_ptr
<
std
::
vector
<
PaddleTensor
>>
warmup_data
=
GetWarmupData
(
input_slots_all
,
100
);
q_cfg
.
EnableMkldnnQuantizer
();
q_cfg
.
mkldnn_quantizer_config
()
->
SetWarmupData
(
warmup_data
);
q_cfg
.
mkldnn_quantizer_config
()
->
SetWarmupBatchSize
(
100
);
CompareQuantizedAndAnalysis
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
q_cfg
),
input_slots_all
);
}
TEST
(
Analyzer_int8_resnet50
,
profile
)
{
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
SetInput
(
&
input_slots_all
);
std
::
shared_ptr
<
std
::
vector
<
PaddleTensor
>>
warmup_data
=
GetWarmupData
(
input_slots_all
,
100
);
cfg
.
EnableMkldnnQuantizer
();
cfg
.
mkldnn_quantizer_config
()
->
SetWarmupData
(
warmup_data
);
cfg
.
mkldnn_quantizer_config
()
->
SetWarmupBatchSize
(
100
);
std
::
vector
<
PaddleTensor
>
outputs
;
TestPrediction
(
reinterpret_cast
<
const
PaddlePredictor
::
Config
*>
(
&
cfg
),
input_slots_all
,
&
outputs
,
FLAGS_num_threads
);
}
}
// namespace analysis
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/tester_helper.h
浏览文件 @
fe21578a
...
...
@@ -50,6 +50,7 @@ DEFINE_bool(use_analysis, true,
DEFINE_bool
(
record_benchmark
,
false
,
"Record benchmark after profiling the model"
);
DEFINE_double
(
accuracy
,
1e-3
,
"Result Accuracy."
);
DEFINE_double
(
quantized_accuracy
,
1e-2
,
"Result Quantized Accuracy."
);
DEFINE_bool
(
zero_copy
,
false
,
"Use ZeroCopy to speedup Feed/Fetch."
);
DECLARE_bool
(
profile
);
...
...
@@ -58,6 +59,19 @@ DECLARE_int32(paddle_num_threads);
namespace
paddle
{
namespace
inference
{
template
<
typename
T
>
constexpr
paddle
::
PaddleDType
GetPaddleDType
();
template
<
>
constexpr
paddle
::
PaddleDType
GetPaddleDType
<
int64_t
>
()
{
return
paddle
::
PaddleDType
::
INT64
;
}
template
<
>
constexpr
paddle
::
PaddleDType
GetPaddleDType
<
float
>
()
{
return
paddle
::
PaddleDType
::
FLOAT32
;
}
void
PrintConfig
(
const
PaddlePredictor
::
Config
*
config
,
bool
use_analysis
)
{
const
auto
*
analysis_config
=
reinterpret_cast
<
const
AnalysisConfig
*>
(
config
);
...
...
@@ -392,6 +406,32 @@ void TestPrediction(const PaddlePredictor::Config *config,
}
}
void
CompareTopAccuracy
(
const
std
::
vector
<
PaddleTensor
>
&
output_slots1
,
const
std
::
vector
<
PaddleTensor
>
&
output_slots2
)
{
// first output: avg_cost
if
(
output_slots1
.
size
()
==
0
||
output_slots2
.
size
()
==
0
)
throw
std
::
invalid_argument
(
"CompareTopAccuracy: output_slots vector is empty."
);
PADDLE_ENFORCE
(
output_slots1
.
size
()
>=
2UL
);
PADDLE_ENFORCE
(
output_slots2
.
size
()
>=
2UL
);
// second output: acc_top1
if
(
output_slots1
[
1
].
lod
.
size
()
>
0
||
output_slots2
[
1
].
lod
.
size
()
>
0
)
throw
std
::
invalid_argument
(
"CompareTopAccuracy: top1 accuracy output has nonempty LoD."
);
if
(
output_slots1
[
1
].
dtype
!=
paddle
::
PaddleDType
::
FLOAT32
||
output_slots2
[
1
].
dtype
!=
paddle
::
PaddleDType
::
FLOAT32
)
throw
std
::
invalid_argument
(
"CompareTopAccuracy: top1 accuracy output is of a wrong type."
);
float
*
top1_quantized
=
static_cast
<
float
*>
(
output_slots1
[
1
].
data
.
data
());
float
*
top1_reference
=
static_cast
<
float
*>
(
output_slots2
[
1
].
data
.
data
());
LOG
(
INFO
)
<<
"top1 INT8 accuracy: "
<<
*
top1_quantized
;
LOG
(
INFO
)
<<
"top1 FP32 accuracy: "
<<
*
top1_reference
;
LOG
(
INFO
)
<<
"Accepted accuracy drop threshold: "
<<
FLAGS_quantized_accuracy
;
CHECK_LE
(
std
::
abs
(
*
top1_quantized
-
*
top1_reference
),
FLAGS_quantized_accuracy
);
}
void
CompareDeterministic
(
const
PaddlePredictor
::
Config
*
config
,
const
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
&
inputs
)
{
...
...
@@ -421,6 +461,17 @@ void CompareNativeAndAnalysis(
CompareResult
(
analysis_outputs
,
native_outputs
);
}
void
CompareQuantizedAndAnalysis
(
const
PaddlePredictor
::
Config
*
config
,
const
PaddlePredictor
::
Config
*
qconfig
,
const
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
&
inputs
)
{
PrintConfig
(
config
,
true
);
std
::
vector
<
PaddleTensor
>
analysis_outputs
,
quantized_outputs
;
TestOneThreadPrediction
(
config
,
inputs
,
&
analysis_outputs
,
true
);
TestOneThreadPrediction
(
qconfig
,
inputs
,
&
quantized_outputs
,
true
);
CompareTopAccuracy
(
quantized_outputs
,
analysis_outputs
);
}
void
CompareNativeAndAnalysis
(
PaddlePredictor
*
native_pred
,
PaddlePredictor
*
analysis_pred
,
const
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
&
inputs
)
{
...
...
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