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92cf4a4c
编写于
1月 25, 2019
作者:
N
nhzlx
浏览文件
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电子邮件补丁
差异文件
fix comments
test=develop
上级
36abc964
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
82 addition
and
37 deletion
+82
-37
paddle/fluid/inference/analysis/argument.h
paddle/fluid/inference/analysis/argument.h
+0
-1
paddle/fluid/inference/analysis/helper.h
paddle/fluid/inference/analysis/helper.h
+36
-1
paddle/fluid/inference/analysis/ir_pass_manager.cc
paddle/fluid/inference/analysis/ir_pass_manager.cc
+9
-6
paddle/fluid/inference/analysis/ir_pass_manager.h
paddle/fluid/inference/analysis/ir_pass_manager.h
+1
-0
paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
...id/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
+22
-23
paddle/fluid/inference/api/analysis_predictor.cc
paddle/fluid/inference/api/analysis_predictor.cc
+12
-5
paddle/fluid/operators/tensorrt/tensorrt_engine_op.h
paddle/fluid/operators/tensorrt/tensorrt_engine_op.h
+2
-1
未找到文件。
paddle/fluid/inference/analysis/argument.h
浏览文件 @
92cf4a4c
...
...
@@ -105,7 +105,6 @@ struct Argument {
DECL_ARGUMENT_FIELD
(
model_program_path
,
ModelProgramPath
,
std
::
string
);
DECL_ARGUMENT_FIELD
(
model_params_path
,
ModelParamsPath
,
std
::
string
);
DECL_ARGUMENT_FIELD
(
model_from_memory
,
ModelFromMemory
,
bool
);
DECL_ARGUMENT_FIELD
(
model_path
,
ModelPath
,
std
::
string
);
// The overall graph to work on.
DECL_ARGUMENT_UNIQUE_FIELD
(
main_graph
,
MainGraph
,
framework
::
ir
::
Graph
);
...
...
paddle/fluid/inference/analysis/helper.h
浏览文件 @
92cf4a4c
...
...
@@ -17,6 +17,7 @@ limitations under the License. */
#include <sys/stat.h>
#include <cstdio>
#include <fstream>
#include <set>
#include <string>
#include <typeindex>
#include <unordered_map>
...
...
@@ -29,9 +30,14 @@ limitations under the License. */
#include "paddle/fluid/platform/port.h"
#ifdef _WIN32
#include <direct.h>
#include <io.h>
#define GCC_ATTRIBUTE(attr__) ;
#define MKDIR(path) _mkdir(path)
#else
#include <unistd.h>
#define GCC_ATTRIBUTE(attr__) __attribute__((attr__));
#define MKDIR(path) mkdir(path, S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH)
#endif
#define __SHOULD_USE_RESULT__ GCC_ATTRIBUTE(warn_unused_result)
...
...
@@ -163,7 +169,7 @@ static bool PathExists(const std::string &path) {
return
false
;
}
static
std
::
string
GetDirRoot
(
const
std
::
string
path
)
{
static
std
::
string
GetDirRoot
(
const
std
::
string
&
path
)
{
char
sep
=
'/'
;
#ifdef _WIN32
...
...
@@ -177,11 +183,40 @@ static std::string GetDirRoot(const std::string path) {
return
path
;
}
static
std
::
string
GetOrCreateModelOptCacheDir
(
const
std
::
string
&
model_root
)
{
std
::
string
opt_cache_dir
=
model_root
+
"/_opt_cache/"
;
if
(
!
PathExists
(
opt_cache_dir
))
{
PADDLE_ENFORCE
(
MKDIR
(
opt_cache_dir
.
c_str
())
!=
-
1
,
"Can not create optimize cache directory: %s, Make sure you "
"have permission to write"
,
opt_cache_dir
);
}
return
opt_cache_dir
;
}
static
std
::
string
GetTrtCalibPath
(
const
std
::
string
&
model_root
,
const
std
::
string
&
engine_key
)
{
return
model_root
+
"/trt_calib_"
+
engine_key
;
}
// If there is no calib table data file in model_opt_cache_dir, return "".
static
std
::
string
GetTrtCalibTableData
(
const
std
::
string
&
model_opt_cache_dir
,
const
std
::
string
&
engine_key
,
bool
enable_int8
)
{
std
::
string
trt_calib_table_path
=
GetTrtCalibPath
(
model_opt_cache_dir
,
engine_key
);
if
(
enable_int8
&&
FileExists
(
trt_calib_table_path
))
{
VLOG
(
3
)
<<
"Calibration table file: "
<<
trt_calib_table_path
<<
"is found here"
;
std
::
ifstream
infile
(
trt_calib_table_path
,
std
::
ios
::
in
);
std
::
stringstream
buffer
;
buffer
<<
infile
.
rdbuf
();
std
::
string
calibration_data
(
buffer
.
str
());
return
calibration_data
;
}
return
""
;
}
}
// namespace analysis
}
// namespace inference
}
// namespace paddle
...
...
paddle/fluid/inference/analysis/ir_pass_manager.cc
浏览文件 @
92cf4a4c
...
...
@@ -72,14 +72,17 @@ void IRPassManager::CreatePasses(Argument *argument,
new
framework
::
ProgramDesc
*
(
const_cast
<
framework
::
ProgramDesc
*>
(
&
argument
->
main_program
())));
bool
enable_int8
=
false
;
if
(
argument
->
tensorrt_precision_mode
()
==
contrib
::
AnalysisConfig
::
Precision
::
kInt8
)
{
enable_int8
=
true
;
}
bool
enable_int8
=
argument
->
tensorrt_precision_mode
()
==
contrib
::
AnalysisConfig
::
Precision
::
kInt8
;
pass
->
Set
(
"enable_int8"
,
new
bool
(
enable_int8
));
pass
->
Set
(
"model_dir"
,
new
std
::
string
(
argument
->
model_path
()));
std
::
string
model_opt_cache_dir
=
argument
->
Has
(
"model_dir"
)
?
argument
->
model_dir
()
:
GetDirRoot
(
argument
->
model_program_path
());
pass
->
Set
(
"model_opt_cache_dir"
,
new
std
::
string
(
GetOrCreateModelOptCacheDir
(
model_opt_cache_dir
)));
}
// graph_ = pass->Apply(std::move(graph_));
...
...
paddle/fluid/inference/analysis/ir_pass_manager.h
浏览文件 @
92cf4a4c
...
...
@@ -29,6 +29,7 @@
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/inference/analysis/argument.h"
#include "paddle/fluid/inference/analysis/helper.h"
namespace
paddle
{
namespace
inference
{
...
...
paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
浏览文件 @
92cf4a4c
...
...
@@ -68,6 +68,19 @@ std::unique_ptr<framework::ir::Graph> analysis::TensorRtSubgraphPass::ApplyImpl(
return
graph
;
}
std
::
string
GenerateEngineKey
(
const
std
::
set
<
std
::
string
>
&
engine_inputs
,
const
std
::
set
<
std
::
string
>
&
engine_outputs
)
{
std
::
string
engine_hash_key
=
""
;
for
(
auto
name
:
engine_inputs
)
{
engine_hash_key
+=
name
;
}
for
(
auto
name
:
engine_outputs
)
{
engine_hash_key
+=
name
;
}
auto
engine_key
=
std
::
to_string
(
std
::
hash
<
std
::
string
>
()(
engine_hash_key
));
return
engine_key
;
}
void
TensorRtSubgraphPass
::
CreateTensorRTOp
(
framework
::
ir
::
Node
*
node
,
Graph
*
graph
)
const
{
auto
*
op_desc
=
node
->
Op
();
...
...
@@ -97,7 +110,10 @@ void TensorRtSubgraphPass::CreateTensorRTOp(framework::ir::Node *node,
*
op
->
Proto
()
=
*
node
->
Op
()
->
Proto
();
}
// collect inputs
// Then, we will use the input_names_with_id and output_names_with_id to
// generate the eigine key.
// So, We use set instead of unordered_set here to ensure that the engine key
// is unique.
std
::
set
<
std
::
string
>
input_names
;
std
::
set
<
std
::
string
>
input_names_with_id
;
for
(
auto
*
x
:
node
->
inputs
)
{
...
...
@@ -217,30 +233,13 @@ void TensorRtSubgraphPass::CreateTensorRTOp(framework::ir::Node *node,
SetAttr
(
op_desc
->
Proto
(),
"output_name_mapping"
,
output_mapping
);
auto
enable_int8
=
Get
<
bool
>
(
"enable_int8"
);
SetAttr
(
op_desc
->
Proto
(),
"calibration_data"
,
std
::
string
(
""
));
auto
engine_key
=
GenerateEngineKey
(
input_names_with_id
,
output_names_with_id
);
// we use the subgraph's inputs and outputs to generate the engine key.
std
::
string
engine_hash_key
=
""
;
for
(
auto
name
:
input_names_with_id
)
{
engine_hash_key
+=
name
;
}
for
(
auto
name
:
output_names_with_id
)
{
engine_hash_key
+=
name
;
}
auto
engine_key
=
std
::
to_string
(
std
::
hash
<
std
::
string
>
()(
engine_hash_key
));
std
::
string
calibration_data
=
GetTrtCalibTableData
(
Get
<
std
::
string
>
(
"model_opt_cache_dir"
),
engine_key
,
enable_int8
);
SetAttr
(
op_desc
->
Proto
(),
"calibration_data"
,
calibration_data
);
auto
trt_calib_file
=
GetTrtCalibPath
(
Get
<
std
::
string
>
(
"model_dir"
),
engine_key
);
VLOG
(
3
)
<<
"engine key: "
<<
engine_key
;
if
(
enable_int8
&&
FileExists
(
trt_calib_file
))
{
VLOG
(
3
)
<<
"Calibration table file: "
<<
trt_calib_file
<<
"is found here"
;
std
::
ifstream
infile
(
trt_calib_file
,
std
::
ios
::
in
);
std
::
stringstream
buffer
;
buffer
<<
infile
.
rdbuf
();
std
::
string
calibration_data
(
buffer
.
str
());
SetAttr
(
op_desc
->
Proto
(),
"calibration_data"
,
calibration_data
);
}
SetAttr
(
op_desc
->
Proto
(),
"enable_int8"
,
enable_int8
);
SetAttr
(
op_desc
->
Proto
(),
"engine_key"
,
engine_key
);
}
...
...
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @
92cf4a4c
...
...
@@ -40,6 +40,7 @@
#if PADDLE_WITH_TENSORRT
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/inference/tensorrt/trt_int8_calibrator.h"
#endif
DECLARE_bool
(
profile
);
...
...
@@ -341,7 +342,6 @@ void AnalysisPredictor::OptimizeInferenceProgram() {
// Analyze inference_program
if
(
!
config_
.
model_dir
().
empty
())
{
argument_
.
SetModelDir
(
config_
.
model_dir
());
argument_
.
SetModelPath
(
config_
.
model_dir
());
}
else
{
PADDLE_ENFORCE
(
!
config_
.
params_file
().
empty
(),
...
...
@@ -349,7 +349,6 @@ void AnalysisPredictor::OptimizeInferenceProgram() {
PADDLE_ENFORCE
(
!
config_
.
prog_file
().
empty
());
std
::
string
dir
=
inference
::
analysis
::
GetDirRoot
(
config_
.
prog_file
());
argument_
.
SetModelPath
(
dir
);
argument_
.
SetModelProgramPath
(
config_
.
prog_file
());
argument_
.
SetModelParamsPath
(
config_
.
params_file
());
}
...
...
@@ -599,7 +598,8 @@ bool AnalysisPredictor::SaveTrtCalibToDisk() {
Singleton
<
TRTCalibratorEngineManager
>::
Global
().
Get
(
engine_name
);
LOG
(
INFO
)
<<
"Wait for calib threads done."
;
calib_engine
->
calib_
->
waitAndSetDone
();
LOG
(
INFO
)
<<
"Finish wait."
;
LOG
(
INFO
)
<<
"Generating TRT Calibration table data, this may cost a lot "
"of time..."
;
calib_engine
->
thr_
->
join
();
std
::
string
calibration_table_data
=
calib_engine
->
calib_
->
getCalibrationTableAsString
();
...
...
@@ -609,9 +609,16 @@ bool AnalysisPredictor::SaveTrtCalibToDisk() {
return
false
;
}
std
::
string
model_opt_cache_dir
=
argument_
.
Has
(
"model_dir"
)
?
argument_
.
model_dir
()
:
inference
::
analysis
::
GetDirRoot
(
argument_
.
model_program_path
());
std
::
string
calibration_table_data_path
=
inference
::
analysis
::
GetTrtCalibPath
(
argument_
.
model_path
(),
engine_name
);
inference
::
analysis
::
GetTrtCalibPath
(
inference
::
analysis
::
GetOrCreateModelOptCacheDir
(
model_opt_cache_dir
),
engine_name
);
std
::
ofstream
ofile
(
calibration_table_data_path
,
std
::
ios
::
out
);
LOG
(
INFO
)
<<
"Write Paddle-TRT INT8 calibration table data to file "
...
...
paddle/fluid/operators/tensorrt/tensorrt_engine_op.h
浏览文件 @
92cf4a4c
...
...
@@ -133,7 +133,8 @@ class TensorRTEngineOp : public framework::OperatorBase {
// This process will builds a 32-bit trt engine, runs it on the calibration
// set, and records a histogram for each
// tensor of the distribution of activation values.
LOG
(
INFO
)
<<
"Running calibration trt int8 ..."
;
LOG_FIRST_N
(
INFO
,
1
)
<<
"The TRT engine: "
<<
engine_key_
<<
" is running calibration trt int8... "
;
int
runtime_batch
=
1
;
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
&
dev_ctx
=
*
pool
.
Get
(
dev_place
);
...
...
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