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82b8a3c5
编写于
9月 17, 2018
作者:
Y
yuyang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Move trainer to contrib
上级
3fbfcd9c
变更
5
展开全部
隐藏空白更改
内联
并排
Showing
5 changed file
with
1374 addition
and
1351 deletion
+1374
-1351
python/paddle/fluid/__init__.py
python/paddle/fluid/__init__.py
+0
-9
python/paddle/fluid/contrib/inferencer.py
python/paddle/fluid/contrib/inferencer.py
+112
-0
python/paddle/fluid/contrib/trainer.py
python/paddle/fluid/contrib/trainer.py
+1258
-0
python/paddle/fluid/inferencer.py
python/paddle/fluid/inferencer.py
+2
-98
python/paddle/fluid/trainer.py
python/paddle/fluid/trainer.py
+2
-1244
未找到文件。
python/paddle/fluid/__init__.py
浏览文件 @
82b8a3c5
...
...
@@ -19,17 +19,8 @@ from .framework import *
# import all class inside executor into fluid module
from
.
import
executor
from
.executor
import
*
from
.
import
trainer
from
.trainer
import
Trainer
from
.trainer
import
BeginEpochEvent
from
.trainer
import
EndEpochEvent
from
.trainer
import
BeginStepEvent
from
.trainer
import
EndStepEvent
from
.trainer
import
CheckpointConfig
from
.
import
inferencer
from
.inferencer
import
Inferencer
from
.
import
io
from
.
import
evaluator
...
...
python/paddle/fluid/contrib/inferencer.py
0 → 100644
浏览文件 @
82b8a3c5
# 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.
from
__future__
import
print_function
import
contextlib
from
..
import
core
from
..
import
executor
from
..
import
framework
from
..
import
io
from
..
import
parallel_executor
from
..
import
unique_name
from
.trainer
import
check_and_get_place
__all__
=
[
'Inferencer'
,
]
class
Inferencer
(
object
):
"""
Inferencer High Level API.
Args:
infer_func (Python func): Infer function that will return predict Variable
param_path (str): The path where the inference model is saved by fluid.io.save_params
place (Place): place to do the inference
parallel (bool): use parallel_executor to run the inference, it will use multi CPU/GPU.
Examples:
.. code-block:: python
def inference_program():
x = fluid.layers.data(name='x', shape=[13], dtype='float32')
y_predict = fluid.layers.fc(input=x, size=1, act=None)
return y_predict
place = fluid.CPUPlace()
inferencer = fluid.Inferencer(
infer_func=inference_program, param_path="/tmp/model", place=place)
"""
def
__init__
(
self
,
infer_func
,
param_path
,
place
=
None
,
parallel
=
False
):
self
.
param_path
=
param_path
self
.
scope
=
core
.
Scope
()
self
.
parallel
=
parallel
self
.
place
=
check_and_get_place
(
place
)
self
.
inference_program
=
framework
.
Program
()
with
framework
.
program_guard
(
self
.
inference_program
):
with
unique_name
.
guard
():
self
.
predict_var
=
infer_func
()
with
self
.
_prog_and_scope_guard
():
# load params from param_path into scope
io
.
load_params
(
executor
.
Executor
(
self
.
place
),
param_path
)
if
parallel
:
with
self
.
_prog_and_scope_guard
():
self
.
exe
=
parallel_executor
.
ParallelExecutor
(
use_cuda
=
isinstance
(
self
.
place
,
core
.
CUDAPlace
),
loss_name
=
self
.
predict_var
.
name
)
else
:
self
.
exe
=
executor
.
Executor
(
self
.
place
)
self
.
inference_program
=
self
.
inference_program
.
clone
(
for_test
=
True
)
def
infer
(
self
,
inputs
,
return_numpy
=
True
):
"""
Do Inference for Inputs
Args:
inputs (map): a map of {"input_name": input_var} that will be feed into the inference program
return_numpy (bool): transform return value into numpy or not
Returns:
Tensor or Numpy: the predict value of the inference model for the inputs
Examples:
.. code-block:: python
tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32")
results = inferencer.infer({'x': tensor_x})
"""
if
not
isinstance
(
inputs
,
dict
):
raise
ValueError
(
"inputs should be a map of {'input_name': input_var}"
)
with
self
.
_prog_and_scope_guard
():
results
=
self
.
exe
.
run
(
feed
=
inputs
,
fetch_list
=
[
self
.
predict_var
.
name
],
return_numpy
=
return_numpy
)
return
results
@
contextlib
.
contextmanager
def
_prog_and_scope_guard
(
self
):
with
framework
.
program_guard
(
main_program
=
self
.
inference_program
):
with
executor
.
scope_guard
(
self
.
scope
):
yield
python/paddle/fluid/contrib/trainer.py
0 → 100644
浏览文件 @
82b8a3c5
此差异已折叠。
点击以展开。
python/paddle/fluid/inferencer.py
浏览文件 @
82b8a3c5
...
...
@@ -12,101 +12,5 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from
__future__
import
print_function
import
contextlib
from
.
import
core
from
.
import
executor
from
.
import
framework
from
.
import
io
from
.
import
parallel_executor
from
.
import
unique_name
from
.trainer
import
check_and_get_place
__all__
=
[
'Inferencer'
,
]
class
Inferencer
(
object
):
"""
Inferencer High Level API.
Args:
infer_func (Python func): Infer function that will return predict Variable
param_path (str): The path where the inference model is saved by fluid.io.save_params
place (Place): place to do the inference
parallel (bool): use parallel_executor to run the inference, it will use multi CPU/GPU.
Examples:
.. code-block:: python
def inference_program():
x = fluid.layers.data(name='x', shape=[13], dtype='float32')
y_predict = fluid.layers.fc(input=x, size=1, act=None)
return y_predict
place = fluid.CPUPlace()
inferencer = fluid.Inferencer(
infer_func=inference_program, param_path="/tmp/model", place=place)
"""
def
__init__
(
self
,
infer_func
,
param_path
,
place
=
None
,
parallel
=
False
):
self
.
param_path
=
param_path
self
.
scope
=
core
.
Scope
()
self
.
parallel
=
parallel
self
.
place
=
check_and_get_place
(
place
)
self
.
inference_program
=
framework
.
Program
()
with
framework
.
program_guard
(
self
.
inference_program
):
with
unique_name
.
guard
():
self
.
predict_var
=
infer_func
()
with
self
.
_prog_and_scope_guard
():
# load params from param_path into scope
io
.
load_params
(
executor
.
Executor
(
self
.
place
),
param_path
)
if
parallel
:
with
self
.
_prog_and_scope_guard
():
self
.
exe
=
parallel_executor
.
ParallelExecutor
(
use_cuda
=
isinstance
(
self
.
place
,
core
.
CUDAPlace
),
loss_name
=
self
.
predict_var
.
name
)
else
:
self
.
exe
=
executor
.
Executor
(
self
.
place
)
self
.
inference_program
=
self
.
inference_program
.
clone
(
for_test
=
True
)
def
infer
(
self
,
inputs
,
return_numpy
=
True
):
"""
Do Inference for Inputs
Args:
inputs (map): a map of {"input_name": input_var} that will be feed into the inference program
return_numpy (bool): transform return value into numpy or not
Returns:
Tensor or Numpy: the predict value of the inference model for the inputs
Examples:
.. code-block:: python
tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32")
results = inferencer.infer({'x': tensor_x})
"""
if
not
isinstance
(
inputs
,
dict
):
raise
ValueError
(
"inputs should be a map of {'input_name': input_var}"
)
with
self
.
_prog_and_scope_guard
():
results
=
self
.
exe
.
run
(
feed
=
inputs
,
fetch_list
=
[
self
.
predict_var
.
name
],
return_numpy
=
return_numpy
)
return
results
@
contextlib
.
contextmanager
def
_prog_and_scope_guard
(
self
):
with
framework
.
program_guard
(
main_program
=
self
.
inference_program
):
with
executor
.
scope_guard
(
self
.
scope
):
yield
# NOTE: inferencer is moved into fluid.contrib.inferencer.
__all__
=
[]
python/paddle/fluid/trainer.py
浏览文件 @
82b8a3c5
此差异已折叠。
点击以展开。
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