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ddd60444
编写于
4月 14, 2020
作者:
C
Chengmo
提交者:
GitHub
4月 14, 2020
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差异文件
Fix judge pslib transpiler (#23720)
* fix judge pslib & ranspiler
上级
de3e299d
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
74 addition
and
16 deletion
+74
-16
python/paddle/fluid/device_worker.py
python/paddle/fluid/device_worker.py
+14
-7
python/paddle/fluid/incubate/fleet/base/fleet_base.py
python/paddle/fluid/incubate/fleet/base/fleet_base.py
+5
-9
python/paddle/fluid/incubate/fleet/base/mode.py
python/paddle/fluid/incubate/fleet/base/mode.py
+26
-0
python/setup.py.in
python/setup.py.in
+29
-0
未找到文件。
python/paddle/fluid/device_worker.py
浏览文件 @
ddd60444
...
...
@@ -13,6 +13,10 @@
# limitations under the License.
"""Defination of device workers."""
from
__future__
import
print_function
from
paddle.fluid.incubate.fleet.parameter_server
import
version
__all__
=
[
'DeviceWorker'
,
'Hogwild'
,
'DownpourSGD'
,
'Section'
,
'DownpourSGDOPT'
]
...
...
@@ -33,7 +37,7 @@ class DeviceWorker(object):
def
_set_infer
(
self
,
infer
=
False
):
"""
set inference flag for current device worker
Args:
infer(bool): whether to do inference
"""
...
...
@@ -101,6 +105,9 @@ class Hogwild(DeviceWorker):
if
not
opt_info
:
return
if
version
.
is_transpiler
()
and
"fleet_desc"
not
in
opt_info
:
return
program_configs
=
opt_info
[
"program_configs"
]
downpour
=
trainer_desc
.
downpour_param
hogwild
=
trainer_desc
.
hogwild_param
...
...
@@ -149,7 +156,7 @@ class Hogwild(DeviceWorker):
i
].
slot_gradient
)
sparse_table
.
fea_dim
=
\
self
.
_fleet_desc
.
server_param
.
downpour_server_param
.
downpour_table_param
[
i
].
accessor
.
fea_dim
i
].
accessor
.
fea_dim
# not use emb_dim
sparse_table
.
emb_dim
=
-
1
# not use hard code click
...
...
@@ -246,12 +253,12 @@ class DownpourSGD(DeviceWorker):
"no_cvm"
]
==
True
:
sparse_table
.
emb_dim
=
\
self
.
_fleet_desc
.
server_param
.
downpour_server_param
.
downpour_table_param
[
i
].
accessor
.
fea_dim
i
].
accessor
.
fea_dim
sparse_table
.
fea_dim
=
sparse_table
.
emb_dim
else
:
sparse_table
.
emb_dim
=
\
self
.
_fleet_desc
.
server_param
.
downpour_server_param
.
downpour_table_param
[
i
].
accessor
.
fea_dim
-
2
i
].
accessor
.
fea_dim
-
2
sparse_table
.
fea_dim
=
sparse_table
.
emb_dim
+
2
# TODO(guru4elephant): hard code here, need to improve
sparse_table
.
label_var_name
=
"click"
...
...
@@ -346,12 +353,12 @@ class DownpourSGDOPT(DeviceWorker):
"no_cvm"
]
==
True
:
sparse_table
.
emb_dim
=
\
self
.
_fleet_desc
.
server_param
.
downpour_server_param
.
downpour_table_param
[
i
].
accessor
.
fea_dim
i
].
accessor
.
fea_dim
sparse_table
.
fea_dim
=
sparse_table
.
emb_dim
else
:
sparse_table
.
emb_dim
=
\
self
.
_fleet_desc
.
server_param
.
downpour_server_param
.
downpour_table_param
[
i
].
accessor
.
fea_dim
-
2
i
].
accessor
.
fea_dim
-
2
sparse_table
.
fea_dim
=
sparse_table
.
emb_dim
+
2
# TODO(guru4elephant): hard code here, need to improve
sparse_table
.
label_var_name
=
"click"
...
...
@@ -406,7 +413,7 @@ class Section(DeviceWorker):
cfg
.
program_desc
.
ParseFromString
(
program
[
"program"
].
_get_desc
()
.
serialize_to_string
())
# TODO: why does not work
#cfg.program_desc.CopyFrom(program.program._get_desc())
#
cfg.program_desc.CopyFrom(program.program._get_desc())
place
=
pipeline_opt
[
"place_list"
][
i
]
if
isinstance
(
place
,
core
.
CPUPlace
):
cfg
.
place
=
cfg
.
CPUPlace
...
...
python/paddle/fluid/incubate/fleet/base/fleet_base.py
浏览文件 @
ddd60444
...
...
@@ -20,19 +20,15 @@ import paddle.fluid as fluid
from
paddle.fluid.executor
import
Executor
from
paddle.fluid.optimizer
import
SGD
from
paddle.fluid.incubate.fleet.base.mode
import
Mode
from
paddle.fluid.incubate.fleet.base.role_maker
import
MPISymetricRoleMaker
from
paddle.fluid.incubate.fleet.base.role_maker
import
RoleMakerBase
from
paddle.fluid.incubate.fleet.base.role_maker
import
UserDefinedRoleMaker
from
paddle.fluid.contrib.mixed_precision.decorator
import
OptimizerWithMixedPrecision
from
.
import
mode
class
Mode
:
"""
There are various mode for fleet, each of them is designed for different model.
"""
TRANSPILER
=
1
PSLIB
=
2
COLLECTIVE
=
3
__all__
=
[
'Fleet'
,
'DistributedOptimizer'
]
__all__
+=
mode
.
__all__
class
Fleet
(
object
):
...
...
@@ -275,7 +271,7 @@ class DistributedOptimizer(object):
def
__init__
(
self
,
optimizer
,
strategy
=
None
):
if
not
isinstance
(
optimizer
,
SGD
.
__bases__
)
\
and
not
isinstance
(
optimizer
,
OptimizerWithMixedPrecision
):
and
not
isinstance
(
optimizer
,
OptimizerWithMixedPrecision
):
raise
TypeError
(
"optimizer must be an instance of Optimizer"
)
self
.
_optimizer
=
optimizer
...
...
python/paddle/fluid/incubate/fleet/base/mode.py
0 → 100644
浏览文件 @
ddd60444
# 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.
from
__future__
import
print_function
__all__
=
[
'Mode'
]
class
Mode
:
"""
There are various mode for fleet, each of them is designed for different model.
"""
TRANSPILER
=
1
PSLIB
=
2
COLLECTIVE
=
3
python/setup.py.in
浏览文件 @
ddd60444
...
...
@@ -5,6 +5,7 @@ import re
import shutil
import sys
import fnmatch
import errno
from contextlib import contextmanager
from setuptools import Command
...
...
@@ -103,6 +104,34 @@ def mkl():
write_version_py(filename='@PADDLE_BINARY_DIR@/python/paddle/version.py')
def write_distributed_training_mode_py(filename='paddle/fluid/incubate/fleet/parameter_server/version.py'):
cnt = '''from __future__ import print_function
# THIS FILE IS GENERATED FROM PADDLEPADDLE SETUP.PY
from paddle.fluid.incubate.fleet.base.mode import Mode
BUILD_MODE=Mode.%(mode)s
def is_transpiler():
return Mode.TRANSPILER == BUILD_MODE
'''
dirname = os.path.dirname(filename)
try:
os.makedirs(dirname)
except OSError as e:
if e.errno != errno.EEXIST:
raise
with open(filename, 'w') as f:
f.write(cnt % {
'mode': 'PSLIB' if '${WITH_PSLIB}' == 'ON' else 'TRANSPILER'
})
write_distributed_training_mode_py(filename='@PADDLE_BINARY_DIR@/python/paddle/fluid/incubate/fleet/parameter_server/version.py')
packages=['paddle',
'paddle.libs',
...
...
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