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d60751fb
编写于
1月 21, 2019
作者:
F
flame
提交者:
GitHub
1月 21, 2019
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差异文件
add python inference api (#15248)
add python inference api
上级
59ab98c9
变更
9
隐藏空白更改
内联
并排
Showing
9 changed file
with
346 addition
and
9 deletion
+346
-9
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-0
paddle/fluid/inference/api/analysis_predictor.h
paddle/fluid/inference/api/analysis_predictor.h
+1
-1
paddle/fluid/pybind/CMakeLists.txt
paddle/fluid/pybind/CMakeLists.txt
+3
-2
paddle/fluid/pybind/inference_api.cc
paddle/fluid/pybind/inference_api.cc
+256
-0
paddle/fluid/pybind/inference_api.h
paddle/fluid/pybind/inference_api.h
+23
-0
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+2
-1
python/paddle/fluid/compiler.py
python/paddle/fluid/compiler.py
+26
-3
python/paddle/fluid/executor.py
python/paddle/fluid/executor.py
+7
-0
python/paddle/fluid/tests/book/test_word2vec.py
python/paddle/fluid/tests/book/test_word2vec.py
+27
-2
未找到文件。
paddle/fluid/API.spec
浏览文件 @
d60751fb
...
...
@@ -45,6 +45,7 @@ paddle.fluid.AsyncExecutor.save_model ArgSpec(args=['self', 'save_path'], vararg
paddle.fluid.AsyncExecutor.stop ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.CompiledProgram.__init__ ArgSpec(args=['self', 'program'], varargs=None, keywords=None, defaults=None)
paddle.fluid.CompiledProgram.with_data_parallel ArgSpec(args=['self', 'loss_name', 'build_strategy', 'exec_strategy', 'share_vars_from'], varargs=None, keywords=None, defaults=(None, None, None, None))
paddle.fluid.CompiledProgram.with_inference_optimize ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=None)
paddle.fluid.ExecutionStrategy.__init__ __init__(self: paddle.fluid.core.ParallelExecutor.ExecutionStrategy) -> None
paddle.fluid.BuildStrategy.GradientScaleStrategy.__init__ __init__(self: paddle.fluid.core.ParallelExecutor.BuildStrategy.GradientScaleStrategy, arg0: int) -> None
paddle.fluid.BuildStrategy.ReduceStrategy.__init__ __init__(self: paddle.fluid.core.ParallelExecutor.BuildStrategy.ReduceStrategy, arg0: int) -> None
...
...
paddle/fluid/inference/api/analysis_predictor.h
浏览文件 @
d60751fb
...
...
@@ -45,6 +45,7 @@ using contrib::AnalysisConfig;
class
AnalysisPredictor
:
public
PaddlePredictor
{
public:
explicit
AnalysisPredictor
(
const
AnalysisConfig
&
config
)
:
config_
(
config
)
{}
~
AnalysisPredictor
();
bool
Init
(
const
std
::
shared_ptr
<
framework
::
Scope
>
&
parent_scope
,
const
std
::
shared_ptr
<
framework
::
ProgramDesc
>
&
program
=
nullptr
);
...
...
@@ -95,7 +96,6 @@ class AnalysisPredictor : public PaddlePredictor {
template
<
typename
T
>
void
GetFetchOne
(
const
framework
::
LoDTensor
&
fetchs
,
PaddleTensor
*
output_data
);
~
AnalysisPredictor
();
// Some more detailed tests, they are made the friends of the predictor, so that
// the all the details can be tested.
...
...
paddle/fluid/pybind/CMakeLists.txt
浏览文件 @
d60751fb
set
(
PYBIND_DEPS pybind python proto_desc memory executor async_executor prune
feed_fetch_method pass_builder parallel_executor profiler layer scope_pool
tracer
)
tracer analysis_predictor
)
if
(
WITH_PYTHON
)
list
(
APPEND PYBIND_DEPS py_func_op
)
endif
()
set
(
PYBIND_SRCS pybind.cc exception.cc protobuf.cc const_value.cc recordio.cc async_executor_py.cc imperative.cc ir.cc
)
set
(
PYBIND_SRCS pybind.cc exception.cc protobuf.cc const_value.cc recordio.cc async_executor_py.cc imperative.cc ir.cc
inference_api.cc
)
if
(
WITH_PYTHON
)
if
(
WITH_AMD_GPU
)
...
...
paddle/fluid/pybind/inference_api.cc
0 → 100644
浏览文件 @
d60751fb
// 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/pybind/inference_api.h"
#include <pybind11/stl.h>
#include <cstring>
#include <iostream>
#include <string>
#include <vector>
#include "paddle/fluid/inference/api/analysis_predictor.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace
py
=
pybind11
;
namespace
paddle
{
namespace
pybind
{
using
paddle
::
PaddleDType
;
using
paddle
::
PaddleBuf
;
using
paddle
::
PaddleTensor
;
using
paddle
::
PaddlePlace
;
using
paddle
::
PaddlePredictor
;
using
paddle
::
NativeConfig
;
using
paddle
::
NativePaddlePredictor
;
using
paddle
::
AnalysisPredictor
;
using
paddle
::
contrib
::
AnalysisConfig
;
static
void
BindPaddleDType
(
py
::
module
*
m
);
static
void
BindPaddleBuf
(
py
::
module
*
m
);
static
void
BindPaddleTensor
(
py
::
module
*
m
);
static
void
BindPaddlePlace
(
py
::
module
*
m
);
static
void
BindPaddlePredictor
(
py
::
module
*
m
);
static
void
BindNativeConfig
(
py
::
module
*
m
);
static
void
BindNativePredictor
(
py
::
module
*
m
);
static
void
BindAnalysisConfig
(
py
::
module
*
m
);
static
void
BindAnalysisPredictor
(
py
::
module
*
m
);
void
BindInferenceApi
(
py
::
module
*
m
)
{
BindPaddleDType
(
m
);
BindPaddleBuf
(
m
);
BindPaddleTensor
(
m
);
BindPaddlePlace
(
m
);
BindPaddlePredictor
(
m
);
BindNativeConfig
(
m
);
BindNativePredictor
(
m
);
BindAnalysisConfig
(
m
);
BindAnalysisPredictor
(
m
);
m
->
def
(
"create_paddle_predictor"
,
&
paddle
::
CreatePaddlePredictor
<
AnalysisConfig
>
);
m
->
def
(
"create_paddle_predictor"
,
&
paddle
::
CreatePaddlePredictor
<
NativeConfig
>
);
m
->
def
(
"paddle_dtype_size"
,
&
paddle
::
PaddleDtypeSize
);
}
void
BindPaddleDType
(
py
::
module
*
m
)
{
py
::
enum_
<
PaddleDType
>
(
*
m
,
"PaddleDType"
)
.
value
(
"FLOAT32"
,
PaddleDType
::
FLOAT32
)
.
value
(
"INT64"
,
PaddleDType
::
INT64
);
}
void
BindPaddleBuf
(
py
::
module
*
m
)
{
py
::
class_
<
PaddleBuf
>
(
*
m
,
"PaddleBuf"
)
.
def
(
py
::
init
<
size_t
>
())
.
def
(
py
::
init
([](
std
::
vector
<
float
>
&
data
)
{
auto
buf
=
PaddleBuf
(
data
.
size
()
*
sizeof
(
float
));
std
::
memcpy
(
buf
.
data
(),
static_cast
<
void
*>
(
data
.
data
()),
buf
.
length
());
return
std
::
move
(
buf
);
}))
.
def
(
py
::
init
([](
std
::
vector
<
int64_t
>
&
data
)
{
auto
buf
=
PaddleBuf
(
data
.
size
()
*
sizeof
(
int64_t
));
std
::
memcpy
(
buf
.
data
(),
static_cast
<
void
*>
(
data
.
data
()),
buf
.
length
());
return
std
::
move
(
buf
);
}))
.
def
(
"resize"
,
&
PaddleBuf
::
Resize
)
.
def
(
"reset"
,
[](
PaddleBuf
&
self
,
std
::
vector
<
float
>
&
data
)
{
self
.
Resize
(
data
.
size
()
*
sizeof
(
float
));
std
::
memcpy
(
self
.
data
(),
data
.
data
(),
self
.
length
());
})
.
def
(
"reset"
,
[](
PaddleBuf
&
self
,
std
::
vector
<
int64_t
>
&
data
)
{
self
.
Resize
(
data
.
size
()
*
sizeof
(
int64_t
));
std
::
memcpy
(
self
.
data
(),
data
.
data
(),
self
.
length
());
})
.
def
(
"empty"
,
&
PaddleBuf
::
empty
)
.
def
(
"float_data"
,
[](
PaddleBuf
&
self
)
->
std
::
vector
<
float
>
{
auto
*
data
=
static_cast
<
float
*>
(
self
.
data
());
return
{
data
,
data
+
self
.
length
()
/
sizeof
(
*
data
)};
})
.
def
(
"int64_data"
,
[](
PaddleBuf
&
self
)
->
std
::
vector
<
int64_t
>
{
int64_t
*
data
=
static_cast
<
int64_t
*>
(
self
.
data
());
return
{
data
,
data
+
self
.
length
()
/
sizeof
(
*
data
)};
})
.
def
(
"length"
,
&
PaddleBuf
::
length
);
}
void
BindPaddleTensor
(
py
::
module
*
m
)
{
py
::
class_
<
PaddleTensor
>
(
*
m
,
"PaddleTensor"
)
.
def
(
py
::
init
<>
())
.
def_readwrite
(
"name"
,
&
PaddleTensor
::
name
)
.
def_readwrite
(
"shape"
,
&
PaddleTensor
::
shape
)
.
def_readwrite
(
"data"
,
&
PaddleTensor
::
data
)
.
def_readwrite
(
"dtype"
,
&
PaddleTensor
::
dtype
)
.
def_readwrite
(
"lod"
,
&
PaddleTensor
::
lod
);
}
void
BindPaddlePlace
(
py
::
module
*
m
)
{
py
::
enum_
<
PaddlePlace
>
(
*
m
,
"PaddlePlace"
)
.
value
(
"UNK"
,
PaddlePlace
::
kUNK
)
.
value
(
"CPU"
,
PaddlePlace
::
kCPU
)
.
value
(
"GPU"
,
PaddlePlace
::
kGPU
);
}
void
BindPaddlePredictor
(
py
::
module
*
m
)
{
auto
paddle_predictor
=
py
::
class_
<
PaddlePredictor
>
(
*
m
,
"PaddlePredictor"
);
paddle_predictor
.
def
(
"run"
,
[](
PaddlePredictor
&
self
,
const
std
::
vector
<
PaddleTensor
>
&
inputs
)
{
std
::
vector
<
PaddleTensor
>
outputs
;
self
.
Run
(
inputs
,
&
outputs
);
return
outputs
;
})
.
def
(
"get_input_tensor"
,
&
PaddlePredictor
::
GetInputTensor
)
.
def
(
"get_output_tensor"
,
&
PaddlePredictor
::
GetOutputTensor
)
.
def
(
"zero_copy_run"
,
&
PaddlePredictor
::
ZeroCopyRun
)
.
def
(
"clone"
,
&
PaddlePredictor
::
Clone
);
auto
config
=
py
::
class_
<
PaddlePredictor
::
Config
>
(
paddle_predictor
,
"Config"
);
config
.
def
(
py
::
init
<>
())
.
def_readwrite
(
"model_dir"
,
&
PaddlePredictor
::
Config
::
model_dir
);
}
void
BindNativeConfig
(
py
::
module
*
m
)
{
py
::
class_
<
NativeConfig
,
PaddlePredictor
::
Config
>
(
*
m
,
"NativeConfig"
)
.
def
(
py
::
init
<>
())
.
def_readwrite
(
"use_gpu"
,
&
NativeConfig
::
use_gpu
)
.
def_readwrite
(
"device"
,
&
NativeConfig
::
device
)
.
def_readwrite
(
"fraction_of_gpu_memory"
,
&
NativeConfig
::
fraction_of_gpu_memory
)
.
def_readwrite
(
"prog_file"
,
&
NativeConfig
::
prog_file
)
.
def_readwrite
(
"param_file"
,
&
NativeConfig
::
param_file
)
.
def_readwrite
(
"specify_input_name"
,
&
NativeConfig
::
specify_input_name
)
.
def
(
"set_cpu_math_library_num_threads"
,
&
NativeConfig
::
SetCpuMathLibraryNumThreads
)
.
def
(
"cpu_math_library_num_threads"
,
&
NativeConfig
::
cpu_math_library_num_threads
);
}
void
BindNativePredictor
(
py
::
module
*
m
)
{
py
::
class_
<
NativePaddlePredictor
,
PaddlePredictor
>
(
*
m
,
"NativePaddlePredictor"
)
.
def
(
py
::
init
<
const
NativeConfig
&>
())
.
def
(
"init"
,
&
NativePaddlePredictor
::
Init
)
.
def
(
"run"
,
[](
NativePaddlePredictor
&
self
,
const
std
::
vector
<
PaddleTensor
>
&
inputs
)
{
std
::
vector
<
PaddleTensor
>
outputs
;
self
.
Run
(
inputs
,
&
outputs
);
return
outputs
;
})
.
def
(
"get_input_tensor"
,
&
NativePaddlePredictor
::
GetInputTensor
)
.
def
(
"get_output_tensor"
,
&
NativePaddlePredictor
::
GetOutputTensor
)
.
def
(
"zero_copy_run"
,
&
NativePaddlePredictor
::
ZeroCopyRun
)
.
def
(
"clone"
,
&
NativePaddlePredictor
::
Clone
)
.
def
(
"scope"
,
&
NativePaddlePredictor
::
scope
,
py
::
return_value_policy
::
reference
);
}
void
BindAnalysisConfig
(
py
::
module
*
m
)
{
py
::
class_
<
AnalysisConfig
>
(
*
m
,
"AnalysisConfig"
)
.
def
(
py
::
init
<
const
AnalysisConfig
&>
())
.
def
(
py
::
init
<
const
std
::
string
&>
())
.
def
(
py
::
init
<
const
std
::
string
&
,
const
std
::
string
&>
())
.
def
(
"set_model"
,
(
void
(
AnalysisConfig
::*
)(
const
std
::
string
&
))
&
AnalysisConfig
::
SetModel
)
.
def
(
"set_model"
,
(
void
(
AnalysisConfig
::*
)(
const
std
::
string
&
,
const
std
::
string
&
))
&
AnalysisConfig
::
SetModel
)
.
def
(
"set_prog_file"
,
&
AnalysisConfig
::
SetProgFile
)
.
def
(
"set_params_file"
,
&
AnalysisConfig
::
SetParamsFile
)
.
def
(
"model_dir"
,
&
AnalysisConfig
::
model_dir
)
.
def
(
"prog_file"
,
&
AnalysisConfig
::
prog_file
)
.
def
(
"params_file"
,
&
AnalysisConfig
::
params_file
)
.
def
(
"enable_use_gpu"
,
&
AnalysisConfig
::
EnableUseGpu
,
py
::
arg
(
"memory_pool_init_size_mb"
),
py
::
arg
(
"device_id"
)
=
0
)
.
def
(
"disable_gpu"
,
&
AnalysisConfig
::
DisableGpu
)
.
def
(
"use_gpu"
,
&
AnalysisConfig
::
use_gpu
)
.
def
(
"gpu_device_id"
,
&
AnalysisConfig
::
gpu_device_id
)
.
def
(
"memory_pool_init_size_mb"
,
&
AnalysisConfig
::
memory_pool_init_size_mb
)
.
def
(
"fraction_of_gpu_memory_for_pool"
,
&
AnalysisConfig
::
fraction_of_gpu_memory_for_pool
)
.
def
(
"switch_ir_optim"
,
&
AnalysisConfig
::
SwitchIrOptim
,
py
::
arg
(
"x"
)
=
true
)
.
def
(
"ir_optim"
,
&
AnalysisConfig
::
ir_optim
)
.
def
(
"switch_use_feed_fetch_ops"
,
&
AnalysisConfig
::
SwitchUseFeedFetchOps
,
py
::
arg
(
"x"
)
=
true
)
.
def
(
"use_feed_fetch_ops_enabled"
,
&
AnalysisConfig
::
use_feed_fetch_ops_enabled
)
.
def
(
"switch_specify_input_names"
,
&
AnalysisConfig
::
SwitchSpecifyInputNames
,
py
::
arg
(
"x"
)
=
true
)
.
def
(
"specify_input_name"
,
&
AnalysisConfig
::
specify_input_name
)
.
def
(
"enable_tensorrt_engine"
,
&
AnalysisConfig
::
EnableTensorRtEngine
,
py
::
arg
(
"workspace_size"
)
=
1
<<
20
,
py
::
arg
(
"max_batch_size"
)
=
1
,
py
::
arg
(
"min_subgraph_size"
)
=
3
)
.
def
(
"tensorrt_engine_enabled"
,
&
AnalysisConfig
::
tensorrt_engine_enabled
)
.
def
(
"switch_ir_debug"
,
&
AnalysisConfig
::
SwitchIrDebug
,
py
::
arg
(
"x"
)
=
true
)
.
def
(
"enable_mkldnn"
,
&
AnalysisConfig
::
EnableMKLDNN
)
.
def
(
"mkldnn_enabled"
,
&
AnalysisConfig
::
mkldnn_enabled
)
.
def
(
"set_cpu_math_library_num_threads"
,
&
AnalysisConfig
::
SetCpuMathLibraryNumThreads
)
.
def
(
"cpu_math_library_num_threads"
,
&
AnalysisConfig
::
cpu_math_library_num_threads
)
.
def
(
"to_native_config"
,
&
AnalysisConfig
::
ToNativeConfig
)
.
def
(
"set_mkldnn_op"
,
&
AnalysisConfig
::
SetMKLDNNOp
)
.
def
(
"set_model_buffer"
,
&
AnalysisConfig
::
SetModelBuffer
)
.
def
(
"model_from_memory"
,
&
AnalysisConfig
::
model_from_memory
)
.
def
(
"pass_builder"
,
&
AnalysisConfig
::
pass_builder
,
py
::
return_value_policy
::
reference
);
}
void
BindAnalysisPredictor
(
py
::
module
*
m
)
{
py
::
class_
<
AnalysisPredictor
,
PaddlePredictor
>
(
*
m
,
"AnalysisPredictor"
)
.
def
(
py
::
init
<
const
AnalysisConfig
&>
())
.
def
(
"init"
,
&
AnalysisPredictor
::
Init
)
.
def
(
"run"
,
[](
AnalysisPredictor
&
self
,
const
std
::
vector
<
PaddleTensor
>
&
inputs
)
{
std
::
vector
<
PaddleTensor
>
outputs
;
self
.
Run
(
inputs
,
&
outputs
);
return
outputs
;
})
.
def
(
"get_input_tensor"
,
&
AnalysisPredictor
::
GetInputTensor
)
.
def
(
"get_output_tensor"
,
&
AnalysisPredictor
::
GetOutputTensor
)
.
def
(
"zero_copy_run"
,
&
AnalysisPredictor
::
ZeroCopyRun
)
.
def
(
"clone"
,
&
AnalysisPredictor
::
Clone
)
.
def
(
"scope"
,
&
AnalysisPredictor
::
scope
,
py
::
return_value_policy
::
reference
);
}
}
// namespace pybind
}
// namespace paddle
paddle/fluid/pybind/inference_api.h
0 → 100644
浏览文件 @
d60751fb
// 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.
#pragma once
#include <pybind11/pybind11.h>
namespace
paddle
{
namespace
pybind
{
void
BindInferenceApi
(
pybind11
::
module
*
m
);
}
// namespace pybind
}
// namespace paddle
paddle/fluid/pybind/pybind.cc
浏览文件 @
d60751fb
...
...
@@ -49,6 +49,7 @@ limitations under the License. */
#include "paddle/fluid/pybind/const_value.h"
#include "paddle/fluid/pybind/exception.h"
#include "paddle/fluid/pybind/imperative.h"
#include "paddle/fluid/pybind/inference_api.h"
#include "paddle/fluid/pybind/ir.h"
#include "paddle/fluid/pybind/protobuf.h"
#include "paddle/fluid/pybind/pybind.h" // NOLINT
...
...
@@ -1083,9 +1084,9 @@ All parameter, weight, gradient are variables in Paddle.
BindRecordIOWriter
(
&
m
);
BindAsyncExecutor
(
&
m
);
BindGraph
(
&
m
);
BindNode
(
&
m
);
BindInferenceApi
(
&
m
);
}
}
// namespace pybind
}
// namespace paddle
python/paddle/fluid/compiler.py
浏览文件 @
d60751fb
...
...
@@ -24,6 +24,8 @@ __all__ = ['CompiledProgram', 'ExecutionStrategy', 'BuildStrategy']
ExecutionStrategy
=
core
.
ParallelExecutor
.
ExecutionStrategy
BuildStrategy
=
core
.
ParallelExecutor
.
BuildStrategy
InferNativeConfig
=
core
.
NativeConfig
InferAnalysisConfig
=
core
.
AnalysisConfig
def
_place_obj
(
place
):
...
...
@@ -70,6 +72,7 @@ class CompiledProgram(object):
self
.
_executor
=
None
self
.
_compiled
=
False
self
.
_is_data_parallel
=
False
self
.
_is_inference
=
False
def
with_data_parallel
(
self
,
loss_name
=
None
,
...
...
@@ -109,10 +112,24 @@ class CompiledProgram(object):
self
.
_build_strategy
=
BuildStrategy
()
return
self
def
_with_distributed
(
self
):
raise
NotImplementedError
()
def
with_inference_optimize
(
self
,
config
):
""" Add inference optimize
Args:
config: instance of `NativeConfig` or `AnalysisConfig` to create predictor
Returns:
self
"""
assert
any
([
isinstance
(
config
,
InferNativeConfig
),
isinstance
(
config
,
InferAnalysisConfig
)
])
self
.
_is_data_parallel
=
False
self
.
_is_inference
=
True
self
.
_infer_config
=
config
return
self
def
_with_
inference_optimize
(
self
):
def
_with_
distributed
(
self
):
raise
NotImplementedError
()
def
_compile_data_parallel
(
self
):
...
...
@@ -177,6 +194,10 @@ class CompiledProgram(object):
if
self
.
_loss_name
else
six
.
u
(
''
),
self
.
_scope
,
self
.
_local_scopes
,
self
.
_exec_strategy
,
self
.
_build_strategy
)
def
_compile_inference
(
self
):
assert
self
.
_is_data_parallel
is
False
return
core
.
create_paddle_predictor
(
self
.
_infer_config
)
def
_compile
(
self
,
scope
,
place
):
"""Compile the program based on the configs.
...
...
@@ -200,6 +221,8 @@ class CompiledProgram(object):
self
.
_place
=
place
if
self
.
_is_data_parallel
:
self
.
_executor
=
self
.
_compile_data_parallel
()
elif
self
.
_is_inference
:
self
.
_executor
=
self
.
_compile_inference
()
else
:
p
=
_place_obj
(
self
.
_place
)
self
.
_executor
=
core
.
Executor
(
p
)
...
...
python/paddle/fluid/executor.py
浏览文件 @
d60751fb
...
...
@@ -27,6 +27,8 @@ from .. import compat as cpt
__all__
=
[
'Executor'
,
'global_scope'
,
'scope_guard'
]
g_scope
=
core
.
Scope
()
InferNativeConfig
=
core
.
NativeConfig
InferAnalysisConfig
=
core
.
AnalysisConfig
def
global_scope
():
...
...
@@ -533,6 +535,8 @@ class Executor(object):
fetch_list
=
fetch_list
,
fetch_var_name
=
fetch_var_name
,
return_numpy
=
return_numpy
)
elif
program
.
_is_inference
:
return
self
.
_run_inference
(
program
,
feed
)
else
:
# TODO(panyx0718): Can compile program to optimize executor
# performance.
...
...
@@ -590,3 +594,6 @@ class Executor(object):
if
return_numpy
:
outs
=
as_numpy
(
outs
)
return
outs
def
_run_inference
(
self
,
program
,
feed
):
return
self
.
executor
.
run
(
feed
)
python/paddle/fluid/tests/book/test_word2vec.py
浏览文件 @
d60751fb
...
...
@@ -195,9 +195,34 @@ def infer(use_cuda, save_dirname=None):
},
fetch_list
=
fetch_targets
,
return_numpy
=
False
)
print
(
results
[
0
].
recursive_sequence_lengths
())
def
to_infer_tensor
(
lod_tensor
):
infer_tensor
=
fluid
.
core
.
PaddleTensor
()
infer_tensor
.
lod
=
lod_tensor
.
lod
()
infer_tensor
.
data
=
fluid
.
core
.
PaddleBuf
(
np
.
array
(
lod_tensor
))
infer_tensor
.
shape
=
lod_tensor
.
shape
()
infer_tensor
.
dtype
=
fluid
.
core
.
PaddleDType
.
INT64
return
infer_tensor
infer_inputs
=
[
first_word
,
second_word
,
third_word
,
fourth_word
]
infer_inputs
=
[
to_infer_tensor
(
t
)
for
t
in
infer_inputs
]
infer_config
=
fluid
.
core
.
NativeConfig
()
infer_config
.
model_dir
=
'word2vec.inference.model'
infer_config
.
use_gpu
=
use_cuda
if
use_cuda
:
infer_config
.
device
=
0
infer_config
.
fraction_of_gpu_memory
=
0.15
compiled_program
=
fluid
.
compiler
.
CompiledProgram
(
inference_program
)
compiled_program
.
with_inference_optimize
(
infer_config
)
assert
compiled_program
.
_is_inference
is
True
infer_outputs
=
exe
.
run
(
compiled_program
,
feed
=
infer_inputs
)
np_data
=
np
.
array
(
results
[
0
])
print
(
"Inference Shape: "
,
np_data
.
shape
)
infer_out
=
infer_outputs
[
0
].
data
.
float_data
()
for
a
,
b
in
zip
(
np_data
[
0
],
infer_out
):
g_a
=
float
(
"{:.6g}"
.
format
(
a
))
g_b
=
float
(
"{:.6g}"
.
format
(
b
))
assert
g_a
==
g_b
def
main
(
use_cuda
,
is_sparse
,
is_parallel
):
...
...
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