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体验新版 GitCode,发现更多精彩内容 >>
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f40a50d1
编写于
7月 31, 2020
作者:
L
lilong12
提交者:
GitHub
7月 31, 2020
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差异文件
add pipeline optimizer for fleet (#25768)
* add pipeline optimizer
上级
f6ac5990
变更
5
显示空白变更内容
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5 changed file
with
126 addition
and
0 deletion
+126
-0
python/paddle/fleet/base/meta_optimizer_factory.py
python/paddle/fleet/base/meta_optimizer_factory.py
+2
-0
python/paddle/fleet/meta_optimizers/__init__.py
python/paddle/fleet/meta_optimizers/__init__.py
+2
-0
python/paddle/fleet/meta_optimizers/pipeline_optimizer.py
python/paddle/fleet/meta_optimizers/pipeline_optimizer.py
+60
-0
python/paddle/fluid/tests/unittests/CMakeLists.txt
python/paddle/fluid/tests/unittests/CMakeLists.txt
+2
-0
python/paddle/fluid/tests/unittests/test_fleet_pipeline_meta_optimizer.py
...uid/tests/unittests/test_fleet_pipeline_meta_optimizer.py
+60
-0
未找到文件。
python/paddle/fleet/base/meta_optimizer_factory.py
浏览文件 @
f40a50d1
...
...
@@ -15,6 +15,7 @@
from
..meta_optimizers
import
RecomputeOptimizer
from
..meta_optimizers
import
GradientMergeOptimizer
from
..meta_optimizers
import
GraphExecutionOptimizer
from
..meta_optimizers
import
PipelineOptimizer
__all__
=
[
"MetaOptimizerFactory"
]
...
...
@@ -22,6 +23,7 @@ meta_optimizer_names = [
"RecomputeOptimizer"
,
"GradientMergeOptimizer"
,
"GraphExecutionOptimizer"
,
"PipelineOptimizer"
,
]
...
...
python/paddle/fleet/meta_optimizers/__init__.py
浏览文件 @
f40a50d1
...
...
@@ -14,8 +14,10 @@
from
.recompute_optimizer
import
RecomputeOptimizer
from
.gradient_merge_optimizer
import
GradientMergeOptimizer
from
.graph_execution_optimizer
import
GraphExecutionOptimizer
from
.pipeline_optimizer
import
PipelineOptimizer
__all__
=
[
'RecomputeOptimizer'
,
'GradientMergeOptimizer'
,
'PipelineOptimizer'
,
]
python/paddle/fleet/meta_optimizers/pipeline_optimizer.py
0 → 100644
浏览文件 @
f40a50d1
# 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
from
paddle.fluid.optimizer
import
PipelineOptimizer
as
PO
from
.meta_optimizer_base
import
MetaOptimizerBase
__all__
=
[
"PipelineOptimizer"
]
class
PipelineOptimizer
(
MetaOptimizerBase
):
def
__init__
(
self
,
optimizer
):
super
(
PipelineOptimizer
,
self
).
__init__
(
optimizer
)
self
.
inner_opt
=
optimizer
# we do not allow meta optimizer to be inner optimizer currently
self
.
meta_optimizers_white_list
=
[]
def
_set_basic_info
(
self
,
loss
,
role_maker
,
user_defined_optimizer
,
user_defined_strategy
):
super
(
PipelineOptimizer
,
self
).
_set_basic_info
(
loss
,
role_maker
,
user_defined_optimizer
,
user_defined_strategy
)
num_microbatches
=
user_defined_strategy
.
pipeline_configs
[
'micro_batch'
]
self
.
wrapped_opt
=
PO
(
self
.
inner_opt
,
num_microbatches
=
num_microbatches
)
def
_can_apply
(
self
):
if
self
.
user_defined_strategy
.
pipeline
==
True
:
return
True
return
False
def
_disable_strategy
(
self
,
dist_strategy
):
dist_strategy
.
pipeline
=
False
dist_strategy
.
pipeline_configs
=
{
"micro_batch"
:
1
}
def
backward
(
self
,
loss
,
startup_program
=
None
,
parameter_list
=
None
,
no_grad_set
=
None
,
callbacks
=
None
):
return
self
.
wrapped_opt
.
backward
(
loss
,
startup_program
,
parameter_list
,
no_grad_set
,
callbacks
)
def
minimize_impl
(
self
,
loss
,
startup_program
=
None
,
parameter_list
=
None
,
no_grad_set
=
None
):
optimize_ops
,
params_grads
,
prog_list
=
\
self
.
wrapped_opt
.
minimize
(
loss
,
startup_program
,
parameter_list
,
no_grad_set
)
return
optimize_ops
,
params_grads
python/paddle/fluid/tests/unittests/CMakeLists.txt
浏览文件 @
f40a50d1
...
...
@@ -32,6 +32,7 @@ list(APPEND MIXED_DIST_TEST_OPS test_fleet_checkpoint)
list
(
APPEND MIXED_DIST_TEST_OPS test_collective_optimizer
)
list
(
APPEND MIXED_DIST_TEST_OPS test_fleet_base
)
list
(
APPEND MIXED_DIST_TEST_OPS test_fleet_meta_optimizer
)
list
(
APPEND MIXED_DIST_TEST_OPS test_fleet_pipeline_meta_optimizer
)
list
(
APPEND MIXED_DIST_TEST_OPS test_fleet_gradient_merge_meta_optimizer
)
list
(
APPEND MIXED_DIST_TEST_OPS test_fleet_private_function
)
foreach
(
TEST_OP
${
MIXED_DIST_TEST_OPS
}
)
...
...
@@ -364,6 +365,7 @@ if(WITH_DISTRIBUTE)
if
(
NOT APPLE
)
py_test_modules
(
test_fleet_base MODULES test_fleet_base ENVS
${
dist_ENVS
}
)
py_test_modules
(
test_fleet_meta_optimizer MODULES test_fleet_meta_optimizer ENVS
${
dist_ENVS
}
)
py_test_modules
(
test_fleet_pipeline_meta_optimizer MODULES test_fleet_pipeline_meta_optimizer ENVS
${
dist_ENVS
}
)
py_test_modules
(
test_fleet_gradient_merge_meta_optimizer MODULES test_fleet_gradient_merge_meta_optimizer ENVS
${
dist_ENVS
}
)
py_test_modules
(
test_fleet_private_function MODULES test_fleet_private_function ENVS
${
dist_ENVS
}
)
endif
(
NOT APPLE
)
...
...
python/paddle/fluid/tests/unittests/test_fleet_pipeline_meta_optimizer.py
0 → 100644
浏览文件 @
f40a50d1
# Copyright (c) 2020 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.
import
unittest
import
paddle
import
os
class
TestFleetMetaOptimizer
(
unittest
.
TestCase
):
def
setUp
(
self
):
os
.
environ
[
"PADDLE_TRAINER_ENDPOINTS"
]
=
"127.0.0.1:36001"
def
test_pipeline_optimizer
(
self
):
import
paddle.fleet
as
fleet
import
paddle.fluid.incubate.fleet.base.role_maker
as
role_maker
role
=
role_maker
.
PaddleCloudRoleMaker
(
is_collective
=
True
)
fleet
.
init
(
role
)
with
paddle
.
fluid
.
device_guard
(
"cpu"
):
input_x
=
paddle
.
fluid
.
layers
.
data
(
name
=
"x"
,
shape
=
[
32
],
dtype
=
'float32'
)
input_y
=
paddle
.
fluid
.
layers
.
data
(
name
=
"y"
,
shape
=
[
1
],
dtype
=
'int64'
)
data_loader
=
paddle
.
fluid
.
io
.
DataLoader
.
from_generator
(
feed_list
=
[
input_x
,
input_y
],
capacity
=
64
,
use_double_buffer
=
True
,
iterable
=
False
)
fc_1
=
paddle
.
fluid
.
layers
.
fc
(
input
=
input_x
,
size
=
64
,
act
=
'tanh'
)
with
paddle
.
fluid
.
device_guard
(
"gpu:0"
):
fc_2
=
paddle
.
fluid
.
layers
.
fc
(
input
=
fc_1
,
size
=
64
,
act
=
'tanh'
)
prediction
=
paddle
.
fluid
.
layers
.
fc
(
input
=
[
fc_2
],
size
=
2
,
act
=
'softmax'
)
cost
=
paddle
.
fluid
.
layers
.
cross_entropy
(
input
=
prediction
,
label
=
input_y
)
avg_cost
=
paddle
.
fluid
.
layers
.
mean
(
x
=
cost
)
strategy
=
paddle
.
fleet
.
DistributedStrategy
()
strategy
.
pipeline
=
True
strategy
.
pipeline_configs
=
{
'micro_batch'
:
2
}
optimizer
=
paddle
.
optimizer
.
SGD
(
learning_rate
=
0.01
)
optimizer
=
fleet
.
distributed_optimizer
(
optimizer
,
strategy
=
strategy
)
optimizer
.
minimize
(
avg_cost
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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