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体验新版 GitCode,发现更多精彩内容 >>
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2bbc0d7d
编写于
12月 25, 2019
作者:
F
flame
提交者:
GitHub
12月 25, 2019
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电子邮件补丁
差异文件
python zero copy inference, delete pass (#21897)
* python zero copy inference * support delete inference pass
上级
51a86d2b
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
165 addition
and
16 deletion
+165
-16
paddle/fluid/pybind/inference_api.cc
paddle/fluid/pybind/inference_api.cc
+165
-16
未找到文件。
paddle/fluid/pybind/inference_api.cc
浏览文件 @
2bbc0d7d
...
...
@@ -16,28 +16,35 @@
#include <pybind11/numpy.h>
#include <pybind11/stl.h>
#include <cstring>
#include <functional>
#include <iostream>
#include <iterator>
#include <map>
#include <memory>
#include <string>
#include <type_traits>
#include <unordered_set>
#include <utility>
#include <vector>
#include "paddle/fluid/inference/api/analysis_predictor.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_pass_builder.h"
namespace
py
=
pybind11
;
namespace
paddle
{
namespace
pybind
{
using
paddle
::
PaddleDType
;
using
paddle
::
AnalysisPredictor
;
using
paddle
::
NativeConfig
;
using
paddle
::
NativePaddlePredictor
;
using
paddle
::
PaddleBuf
;
using
paddle
::
PaddleTensor
;
using
paddle
::
PaddleDType
;
using
paddle
::
PaddlePassBuilder
;
using
paddle
::
PaddlePlace
;
using
paddle
::
PaddlePredictor
;
using
paddle
::
NativeConfig
;
using
paddle
::
NativePaddlePredictor
;
using
paddle
::
AnalysisPredict
or
;
using
paddle
::
PaddleTensor
;
using
paddle
::
PassStrategy
;
using
paddle
::
ZeroCopyTens
or
;
namespace
{
void
BindPaddleDType
(
py
::
module
*
m
);
...
...
@@ -49,6 +56,8 @@ void BindNativeConfig(py::module *m);
void
BindNativePredictor
(
py
::
module
*
m
);
void
BindAnalysisConfig
(
py
::
module
*
m
);
void
BindAnalysisPredictor
(
py
::
module
*
m
);
void
BindZeroCopyTensor
(
py
::
module
*
m
);
void
BindPaddlePassBuilder
(
py
::
module
*
m
);
#ifdef PADDLE_WITH_MKLDNN
void
BindMkldnnQuantizerConfig
(
py
::
module
*
m
);
...
...
@@ -57,7 +66,7 @@ void BindMkldnnQuantizerConfig(py::module *m);
template
<
typename
T
>
PaddleBuf
PaddleBufCreate
(
py
::
array_t
<
T
>
data
)
{
PaddleBuf
buf
(
data
.
size
()
*
sizeof
(
T
));
std
::
copy_n
(
static_cast
<
T
*>
(
data
.
mutable_
data
()),
data
.
size
(),
std
::
copy_n
(
static_cast
<
const
T
*>
(
data
.
data
()),
data
.
size
(),
static_cast
<
T
*>
(
buf
.
data
()));
return
buf
;
}
...
...
@@ -65,25 +74,25 @@ PaddleBuf PaddleBufCreate(py::array_t<T> data) {
template
<
typename
T
>
void
PaddleBufReset
(
PaddleBuf
&
buf
,
py
::
array_t
<
T
>
data
)
{
// NOLINT
buf
.
Resize
(
data
.
size
()
*
sizeof
(
T
));
std
::
copy_n
(
static_cast
<
T
*>
(
data
.
mutable_
data
()),
data
.
size
(),
std
::
copy_n
(
static_cast
<
const
T
*>
(
data
.
data
()),
data
.
size
(),
static_cast
<
T
*>
(
buf
.
data
()));
}
template
<
typename
T
>
PaddleDType
PaddleTensorGetDType
();
constexpr
PaddleDType
PaddleTensorGetDType
();
template
<
>
PaddleDType
PaddleTensorGetDType
<
int32_t
>
()
{
constexpr
PaddleDType
PaddleTensorGetDType
<
int32_t
>
()
{
return
PaddleDType
::
INT32
;
}
template
<
>
PaddleDType
PaddleTensorGetDType
<
int64_t
>
()
{
constexpr
PaddleDType
PaddleTensorGetDType
<
int64_t
>
()
{
return
PaddleDType
::
INT64
;
}
template
<
>
PaddleDType
PaddleTensorGetDType
<
float
>
()
{
constexpr
PaddleDType
PaddleTensorGetDType
<
float
>
()
{
return
PaddleDType
::
FLOAT32
;
}
...
...
@@ -95,7 +104,7 @@ PaddleTensor PaddleTensorCreate(
if
(
copy
)
{
PaddleBuf
buf
(
data
.
size
()
*
sizeof
(
T
));
std
::
copy_n
(
static_cast
<
T
*>
(
data
.
mutable_
data
()),
data
.
size
(),
std
::
copy_n
(
static_cast
<
const
T
*>
(
data
.
data
()),
data
.
size
(),
static_cast
<
T
*>
(
buf
.
data
()));
tensor
.
data
=
std
::
move
(
buf
);
}
else
{
...
...
@@ -111,9 +120,9 @@ PaddleTensor PaddleTensorCreate(
return
tensor
;
}
py
::
array
PaddleTensorGetData
(
PaddleTensor
&
tensor
)
{
// NOLINT
py
::
dtype
PaddleDTypeToNumpyDType
(
PaddleDType
dtype
)
{
py
::
dtype
dt
;
switch
(
tensor
.
dtype
)
{
switch
(
dtype
)
{
case
PaddleDType
::
INT32
:
dt
=
py
::
dtype
::
of
<
int32_t
>
();
break
;
...
...
@@ -126,7 +135,62 @@ py::array PaddleTensorGetData(PaddleTensor &tensor) { // NOLINT
default:
LOG
(
FATAL
)
<<
"unsupported dtype"
;
}
return
py
::
array
(
dt
,
{
tensor
.
shape
},
tensor
.
data
.
data
());
return
dt
;
}
py
::
array
PaddleTensorGetData
(
PaddleTensor
&
tensor
)
{
// NOLINT
py
::
dtype
dt
=
PaddleDTypeToNumpyDType
(
tensor
.
dtype
);
return
py
::
array
(
std
::
move
(
dt
),
{
tensor
.
shape
},
tensor
.
data
.
data
());
}
template
<
typename
T
>
void
ZeroCopyTensorCreate
(
ZeroCopyTensor
&
tensor
,
// NOLINT
py
::
array_t
<
T
>
data
)
{
std
::
vector
<
int
>
shape
;
std
::
copy_n
(
data
.
shape
(),
data
.
ndim
(),
std
::
back_inserter
(
shape
));
tensor
.
Reshape
(
std
::
move
(
shape
));
tensor
.
copy_from_cpu
(
static_cast
<
const
T
*>
(
data
.
data
()));
}
size_t
PaddleGetDTypeSize
(
PaddleDType
dt
)
{
size_t
size
{
0
};
switch
(
dt
)
{
case
PaddleDType
::
INT32
:
size
=
sizeof
(
int32_t
);
break
;
case
PaddleDType
::
INT64
:
size
=
sizeof
(
int64_t
);
break
;
case
PaddleDType
::
FLOAT32
:
size
=
sizeof
(
float
);
break
;
default:
LOG
(
FATAL
)
<<
"unsupported dtype"
;
}
return
size
;
}
py
::
array
ZeroCopyTensorToNumpy
(
ZeroCopyTensor
&
tensor
)
{
// NOLINT
py
::
dtype
dt
=
PaddleDTypeToNumpyDType
(
tensor
.
type
());
auto
tensor_shape
=
tensor
.
shape
();
py
::
array
::
ShapeContainer
shape
(
tensor_shape
.
begin
(),
tensor_shape
.
end
());
py
::
array
array
(
dt
,
std
::
move
(
shape
));
switch
(
tensor
.
type
())
{
case
PaddleDType
::
INT32
:
tensor
.
copy_to_cpu
(
static_cast
<
int32_t
*>
(
array
.
mutable_data
()));
break
;
case
PaddleDType
::
INT64
:
tensor
.
copy_to_cpu
(
static_cast
<
int64_t
*>
(
array
.
mutable_data
()));
break
;
case
PaddleDType
::
FLOAT32
:
tensor
.
copy_to_cpu
<
float
>
(
static_cast
<
float
*>
(
array
.
mutable_data
()));
break
;
default:
LOG
(
FATAL
)
<<
"unsupported dtype"
;
}
return
array
;
}
}
// namespace
...
...
@@ -140,6 +204,8 @@ void BindInferenceApi(py::module *m) {
BindNativePredictor
(
m
);
BindAnalysisConfig
(
m
);
BindAnalysisPredictor
(
m
);
BindZeroCopyTensor
(
m
);
BindPaddlePassBuilder
(
m
);
#ifdef PADDLE_WITH_MKLDNN
BindMkldnnQuantizerConfig
(
m
);
#endif
...
...
@@ -258,8 +324,11 @@ void BindPaddlePredictor(py::module *m) {
})
.
def
(
"get_input_tensor"
,
&
PaddlePredictor
::
GetInputTensor
)
.
def
(
"get_output_tensor"
,
&
PaddlePredictor
::
GetOutputTensor
)
.
def
(
"get_input_names"
,
&
PaddlePredictor
::
GetInputNames
)
.
def
(
"get_output_names"
,
&
PaddlePredictor
::
GetOutputNames
)
.
def
(
"zero_copy_run"
,
&
PaddlePredictor
::
ZeroCopyRun
)
.
def
(
"clone"
,
&
PaddlePredictor
::
Clone
);
.
def
(
"clone"
,
&
PaddlePredictor
::
Clone
)
.
def
(
"get_serialized_program"
,
&
PaddlePredictor
::
GetSerializedProgram
);
auto
config
=
py
::
class_
<
PaddlePredictor
::
Config
>
(
paddle_predictor
,
"Config"
);
config
.
def
(
py
::
init
<>
())
...
...
@@ -339,6 +408,7 @@ void BindAnalysisConfig(py::module *m) {
.
def
(
"enable_memory_optim"
,
&
AnalysisConfig
::
EnableMemoryOptim
)
.
def
(
"enable_profile"
,
&
AnalysisConfig
::
EnableProfile
)
.
def
(
"disable_glog_info"
,
&
AnalysisConfig
::
DisableGlogInfo
)
.
def
(
"glog_info_disabled"
,
&
AnalysisConfig
::
glog_info_disabled
)
.
def
(
"set_optim_cache_dir"
,
&
AnalysisConfig
::
SetOptimCacheDir
)
.
def
(
"switch_use_feed_fetch_ops"
,
&
AnalysisConfig
::
SwitchUseFeedFetchOps
,
py
::
arg
(
"x"
)
=
true
)
...
...
@@ -379,6 +449,10 @@ void BindAnalysisConfig(py::module *m) {
.
def
(
"set_mkldnn_op"
,
&
AnalysisConfig
::
SetMKLDNNOp
)
.
def
(
"set_model_buffer"
,
&
AnalysisConfig
::
SetModelBuffer
)
.
def
(
"model_from_memory"
,
&
AnalysisConfig
::
model_from_memory
)
.
def
(
"delete_pass"
,
[](
AnalysisConfig
&
self
,
const
std
::
string
&
pass
)
{
self
.
pass_builder
()
->
DeletePass
(
pass
);
})
.
def
(
"pass_builder"
,
&
AnalysisConfig
::
pass_builder
,
py
::
return_value_policy
::
reference
);
}
...
...
@@ -418,13 +492,88 @@ void BindAnalysisPredictor(py::module *m) {
})
.
def
(
"get_input_tensor"
,
&
AnalysisPredictor
::
GetInputTensor
)
.
def
(
"get_output_tensor"
,
&
AnalysisPredictor
::
GetOutputTensor
)
.
def
(
"get_input_names"
,
&
AnalysisPredictor
::
GetInputNames
)
.
def
(
"get_output_names"
,
&
AnalysisPredictor
::
GetOutputNames
)
.
def
(
"get_input_tensor_shape"
,
&
AnalysisPredictor
::
GetInputTensorShape
)
.
def
(
"zero_copy_run"
,
&
AnalysisPredictor
::
ZeroCopyRun
)
.
def
(
"create_feed_fetch_var"
,
&
AnalysisPredictor
::
CreateFeedFetchVar
)
.
def
(
"prepare_feed_fetch"
,
&
AnalysisPredictor
::
PrepareFeedFetch
)
.
def
(
"prepare_argument"
,
&
AnalysisPredictor
::
PrepareArgument
)
.
def
(
"optimize_inference_program"
,
&
AnalysisPredictor
::
OptimizeInferenceProgram
)
.
def
(
"analysis_argument"
,
&
AnalysisPredictor
::
analysis_argument
,
py
::
return_value_policy
::
reference
)
.
def
(
"clone"
,
&
AnalysisPredictor
::
Clone
)
.
def
(
"scope"
,
&
AnalysisPredictor
::
scope
,
py
::
return_value_policy
::
reference
)
.
def
(
"program"
,
&
AnalysisPredictor
::
program
,
py
::
return_value_policy
::
reference
)
.
def
(
"get_serialized_program"
,
&
AnalysisPredictor
::
GetSerializedProgram
)
.
def
(
"mkldnn_quantize"
,
&
AnalysisPredictor
::
MkldnnQuantize
)
.
def
(
"SaveOptimModel"
,
&
AnalysisPredictor
::
SaveOptimModel
,
py
::
arg
(
"dir"
));
}
void
BindZeroCopyTensor
(
py
::
module
*
m
)
{
py
::
class_
<
ZeroCopyTensor
>
(
*
m
,
"ZeroCopyTensor"
)
.
def
(
"reshape"
,
&
ZeroCopyTensor
::
Reshape
)
.
def
(
"copy_from_cpu"
,
&
ZeroCopyTensorCreate
<
int32_t
>
)
.
def
(
"copy_from_cpu"
,
&
ZeroCopyTensorCreate
<
int64_t
>
)
.
def
(
"copy_from_cpu"
,
&
ZeroCopyTensorCreate
<
float
>
)
.
def
(
"copy_to_cpu"
,
&
ZeroCopyTensorToNumpy
)
.
def
(
"shape"
,
&
ZeroCopyTensor
::
shape
)
.
def
(
"set_lod"
,
&
ZeroCopyTensor
::
SetLoD
)
.
def
(
"lod"
,
&
ZeroCopyTensor
::
lod
)
.
def
(
"type"
,
&
ZeroCopyTensor
::
type
);
}
void
BindPaddlePassBuilder
(
py
::
module
*
m
)
{
py
::
class_
<
PaddlePassBuilder
>
(
*
m
,
"PaddlePassBuilder"
)
.
def
(
py
::
init
<
const
std
::
vector
<
std
::
string
>
&>
())
.
def
(
"set_passes"
,
[](
PaddlePassBuilder
&
self
,
const
std
::
vector
<
std
::
string
>
&
passes
)
{
self
.
ClearPasses
();
for
(
auto
pass
:
passes
)
{
self
.
AppendPass
(
std
::
move
(
pass
));
}
})
.
def
(
"append_pass"
,
&
PaddlePassBuilder
::
AppendPass
)
.
def
(
"insert_pass"
,
&
PaddlePassBuilder
::
InsertPass
)
.
def
(
"delete_pass"
,
[](
PaddlePassBuilder
&
self
,
const
std
::
string
&
pass_type
)
{
self
.
DeletePass
(
pass_type
);
})
.
def
(
"append_analysis_pass"
,
&
PaddlePassBuilder
::
AppendAnalysisPass
)
.
def
(
"turn_on_debug"
,
&
PaddlePassBuilder
::
TurnOnDebug
)
.
def
(
"debug_string"
,
&
PaddlePassBuilder
::
DebugString
)
.
def
(
"all_passes"
,
&
PaddlePassBuilder
::
AllPasses
,
py
::
return_value_policy
::
reference
)
.
def
(
"analysis_passes"
,
&
PaddlePassBuilder
::
AnalysisPasses
);
py
::
class_
<
PassStrategy
,
PaddlePassBuilder
>
(
*
m
,
"PassStrategy"
)
.
def
(
py
::
init
<
const
std
::
vector
<
std
::
string
>
&>
())
.
def
(
"enable_cudnn"
,
&
PassStrategy
::
EnableCUDNN
)
.
def
(
"enable_mkldnn"
,
&
PassStrategy
::
EnableMKLDNN
)
.
def
(
"enable_ngraph"
,
&
PassStrategy
::
EnableNgraph
)
.
def
(
"enable_mkldnn_quantizer"
,
&
PassStrategy
::
EnableMkldnnQuantizer
)
.
def
(
"use_gpu"
,
&
PassStrategy
::
use_gpu
);
py
::
class_
<
CpuPassStrategy
,
PassStrategy
>
(
*
m
,
"CpuPassStrategy"
)
.
def
(
py
::
init
<>
())
.
def
(
py
::
init
<
const
CpuPassStrategy
&>
())
.
def
(
"enable_cudnn"
,
&
CpuPassStrategy
::
EnableCUDNN
)
.
def
(
"enable_mkldnn"
,
&
CpuPassStrategy
::
EnableMKLDNN
)
.
def
(
"enable_ngraph"
,
&
CpuPassStrategy
::
EnableNgraph
)
.
def
(
"enable_mkldnn_quantizer"
,
&
CpuPassStrategy
::
EnableMkldnnQuantizer
);
py
::
class_
<
GpuPassStrategy
,
PassStrategy
>
(
*
m
,
"GpuPassStrategy"
)
.
def
(
py
::
init
<>
())
.
def
(
py
::
init
<
const
GpuPassStrategy
&>
())
.
def
(
"enable_cudnn"
,
&
GpuPassStrategy
::
EnableCUDNN
)
.
def
(
"enable_mkldnn"
,
&
GpuPassStrategy
::
EnableMKLDNN
)
.
def
(
"enable_ngraph"
,
&
GpuPassStrategy
::
EnableNgraph
)
.
def
(
"enable_mkldnn_quantizer"
,
&
GpuPassStrategy
::
EnableMkldnnQuantizer
);
}
}
// namespace
}
// namespace pybind
}
// namespace paddle
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