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89f2c652
编写于
1月 05, 2023
作者:
S
sneaxiy
提交者:
GitHub
1月 05, 2023
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差异文件
remove paddle.fluid.distributed (#49517)
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python/paddle/fluid/distributed/__init__.py
python/paddle/fluid/distributed/__init__.py
+0
-12
python/paddle/fluid/distributed/downpour.py
python/paddle/fluid/distributed/downpour.py
+0
-200
python/paddle/fluid/distributed/fleet.py
python/paddle/fluid/distributed/fleet.py
+0
-82
python/paddle/fluid/distributed/helper.py
python/paddle/fluid/distributed/helper.py
+0
-91
python/paddle/fluid/distributed/node.py
python/paddle/fluid/distributed/node.py
+0
-196
python/paddle/fluid/distributed/ps_instance.py
python/paddle/fluid/distributed/ps_instance.py
+0
-160
python/paddle/fluid/distributed/ps_pb2.py
python/paddle/fluid/distributed/ps_pb2.py
+0
-2602
python/setup.py.in
python/setup.py.in
+0
-1
setup.py
setup.py
+0
-1
未找到文件。
python/paddle/fluid/distributed/__init__.py
已删除
100644 → 0
浏览文件 @
5defefd6
# 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
python/paddle/fluid/distributed/downpour.py
已删除
100644 → 0
浏览文件 @
5defefd6
# 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
from
.node
import
DownpourServer
from
.node
import
DownpourWorker
from
..backward
import
append_backward
import
ps_pb2
as
pslib
from
paddle.fluid.distribute_lookup_table
import
find_distributed_lookup_table
from
paddle.fluid.distribute_lookup_table
import
(
find_distributed_lookup_table_inputs
,
)
from
paddle.fluid.distribute_lookup_table
import
(
find_distributed_lookup_table_outputs
,
)
from
google.protobuf
import
text_format
class
DownpourSGD
:
r
"""
Distributed optimizer of downpour stochastic gradient descent
Standard implementation of Google's Downpour SGD
in Large Scale Distributed Deep Networks
Args:
learning_rate (float): the learning rate used to update parameters. \
Can be a float value
Examples:
.. code-block:: python
opt = fluid.DistributedOptimizer(sgd_opt)
opt.minimize()
downpour_sgd = fluid.distributed.DownpourSGD(learning_rate=0.2)
downpour_sgd.minimize(cost)
"""
def
__init__
(
self
,
learning_rate
=
0.001
,
window
=
1
):
# todo(guru4elephant): add more optimizers here as argument
# todo(guru4elephant): make learning_rate as a variable
self
.
learning_rate_
=
learning_rate
self
.
window_
=
window
self
.
type
=
"downpour"
self
.
data_norm_name
=
[
".batch_size"
,
".batch_square_sum"
,
".batch_sum"
,
".batch_size@GRAD"
,
".batch_square_sum@GRAD"
,
".batch_sum@GRAD"
,
]
def
minimize
(
self
,
losses
,
startup_program
=
None
,
parameter_list
=
None
,
no_grad_set
=
None
,
):
"""
DownpounSGD is a distributed optimizer so
that user can call minimize to generate backward
operators and optimization operators within minimize function
Args:
loss(Variable): loss variable defined by user
startup_program(Program): startup program that defined by user
parameter_list(str list): parameter names defined by users
no_grad_set(set): a set of variables that is defined by users
so that these variables do not need gradient computation
Returns:
[ps_param, worker_skipped_ops]
ps_param: parameter server protobuf desc
worker_skipped_ops: operator names that need
to be skipped during execution
"""
if
not
isinstance
(
losses
,
list
):
raise
ValueError
(
'losses is a list, just lick [model.cost]'
)
table_name
=
find_distributed_lookup_table
(
losses
[
0
].
block
.
program
)
prefetch_slots
=
find_distributed_lookup_table_inputs
(
losses
[
0
].
block
.
program
,
table_name
)
prefetch_slots_emb
=
find_distributed_lookup_table_outputs
(
losses
[
0
].
block
.
program
,
table_name
)
ps_param
=
pslib
.
PSParameter
()
server
=
DownpourServer
()
worker
=
DownpourWorker
(
self
.
window_
)
sparse_table_index
=
0
server
.
add_sparse_table
(
sparse_table_index
,
self
.
learning_rate_
,
prefetch_slots
,
prefetch_slots_emb
,
)
worker
.
add_sparse_table
(
sparse_table_index
,
self
.
learning_rate_
,
prefetch_slots
,
prefetch_slots_emb
,
)
dense_table_index
=
1
program_configs
=
[]
param_grads_list
=
[]
for
loss_index
in
range
(
len
(
losses
)):
program_config
=
ps_param
.
trainer_param
.
program_config
.
add
()
program_config
.
program_id
=
str
(
id
(
losses
[
loss_index
].
block
.
program
)
)
program_config
.
pull_sparse_table_id
.
extend
([
sparse_table_index
])
program_config
.
push_sparse_table_id
.
extend
([
sparse_table_index
])
params_grads
=
sorted
(
append_backward
(
losses
[
loss_index
],
parameter_list
,
no_grad_set
),
key
=
lambda
x
:
x
[
0
].
name
,
)
param_grads_list
.
append
(
params_grads
)
params
=
[]
grads
=
[]
data_norm_params
=
[]
data_norm_grads
=
[]
for
i
in
params_grads
:
is_data_norm_data
=
False
for
data_norm_name
in
self
.
data_norm_name
:
if
i
[
0
].
name
.
endswith
(
data_norm_name
):
is_data_norm_data
=
True
data_norm_params
.
append
(
i
[
0
])
if
not
is_data_norm_data
:
params
.
append
(
i
[
0
])
for
i
in
params_grads
:
is_data_norm_data
=
False
for
data_norm_grad
in
self
.
data_norm_name
:
if
i
[
0
].
name
.
endswith
(
data_norm_grad
):
is_data_norm_data
=
True
data_norm_grads
.
append
(
i
[
1
])
if
not
is_data_norm_data
:
grads
.
append
(
i
[
1
])
server
.
add_dense_table
(
dense_table_index
,
self
.
learning_rate_
,
params
,
grads
)
worker
.
add_dense_table
(
dense_table_index
,
self
.
learning_rate_
,
params
,
grads
)
program_config
.
pull_dense_table_id
.
extend
([
dense_table_index
])
program_config
.
push_dense_table_id
.
extend
([
dense_table_index
])
if
len
(
data_norm_params
)
!=
0
and
len
(
data_norm_grads
)
!=
0
:
dense_table_index
+=
1
server
.
add_data_norm_table
(
dense_table_index
,
self
.
learning_rate_
,
data_norm_params
,
data_norm_grads
,
)
worker
.
add_dense_table
(
dense_table_index
,
self
.
learning_rate_
,
data_norm_params
,
data_norm_grads
,
)
program_config
.
pull_dense_table_id
.
extend
([
dense_table_index
])
program_config
.
push_dense_table_id
.
extend
([
dense_table_index
])
dense_table_index
+=
1
program_configs
.
append
(
program_config
)
ps_param
.
server_param
.
CopyFrom
(
server
.
get_desc
())
ps_param
.
trainer_param
.
CopyFrom
(
worker
.
get_desc
())
for
program_config
in
program_configs
:
ps_param
.
trainer_param
.
program_config
.
extend
([
program_config
])
# Todo(guru4elephant): figure out how to support more sparse parameters
# currently only support lookup_table
worker_skipped_ops
=
[
"lookup_table"
,
"lookup_table_grad"
]
ps_param
.
trainer_param
.
skip_op
.
extend
(
worker_skipped_ops
)
# all fleet operations should be defined in operators in the future
# we want to return an object here containing:
# 1) worker execution strategy
# 2) pserver execution strategy
# 3) fleet configurations
# 4) skipped operators in runtime
# 5) distributed optimization
opt_info
=
{}
opt_info
[
"trainer"
]
=
"DistMultiTrainer"
opt_info
[
"device_worker"
]
=
"DownpourSGD"
opt_info
[
"optimizer"
]
=
"DownpourSGD"
opt_info
[
"fleet_desc"
]
=
ps_param
opt_info
[
"worker_skipped_ops"
]
=
worker_skipped_ops
for
loss
in
losses
:
loss
.
block
.
program
.
_fleet_opt
=
opt_info
return
None
,
param_grads_list
python/paddle/fluid/distributed/fleet.py
已删除
100644 → 0
浏览文件 @
5defefd6
# 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
import
sys
from
..
import
core
from
.
import
ps_instance
from
google.protobuf
import
text_format
__all__
=
[
'Fleet'
]
class
Fleet
:
""" """
def
__init__
(
self
):
self
.
instance_
=
ps_instance
.
PaddlePSInstance
()
self
.
fleet_
=
core
.
FleetWrapper
()
def
stop
(
self
):
self
.
instance_
.
barrier_worker
()
if
self
.
instance
.
is_first_worker
():
self
.
fleet_
.
stop_server
()
self
.
instance_
.
barrier_worker
()
self
.
instance_
.
barrier_all
()
self
.
instance
.
finalize
()
def
init_pserver
(
self
,
opt_info
):
if
"fleet_desc"
in
opt_info
:
self
.
dist_desc_str_
=
text_format
.
MessageToString
(
opt_info
[
"fleet_desc"
]
)
self
.
dist_desc_
=
opt_info
[
"fleet_desc"
]
else
:
print
(
"You should run distributed optimization to get opt_info first"
)
sys
.
exit
(
-
1
)
self
.
fleet_
.
init_server
(
self
.
dist_desc_str_
)
ip
=
self
.
fleet_
.
start_server
()
self
.
instance_
.
set_ip
(
ip
)
self
.
instance
.
barrier_all
()
ips
=
self
.
instance
.
gather_ips
()
self
.
fleet
.
gather_servers
(
ips
,
self
.
instance_
.
get_node_cnt
())
self
.
instance_
.
barrier_all
()
def
init_worker
(
self
,
opt_info
):
if
"fleet_desc"
in
opt_info
:
self
.
dist_desc_str_
=
text_format
.
MessageToString
(
opt_info
[
"fleet_desc"
]
)
self
.
dist_desc_
=
opt_info
[
"fleet_desc"
]
else
:
print
(
"You should run distributed optimization to get opt_info first"
)
sys
.
exit
(
-
1
)
self
.
instance_
.
barrier_all
()
ips
=
self
.
instance
.
gather_ips
()
self
.
fleet_
.
init_worker
(
self
.
dist_desc_str_
,
ips
,
self
.
instance_
.
get_node_cnt
(),
self
.
instance
.
_rankid
,
)
self
.
instance
.
barrier_worker
()
def
init_pserver_model
(
self
):
if
self
.
instance_
.
is_first_worker
():
self
.
fleet_
.
init_model
()
self
.
instance_
.
barrier_worker
()
def
save_pserver_model
(
self
,
save_path
):
self
.
fleet_
.
save_model
(
save_path
)
python/paddle/fluid/distributed/helper.py
已删除
100644 → 0
浏览文件 @
5defefd6
# 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.
class
FileSystem
:
"""
A file system that support hadoop client desc.
Args:
fs_type (string): fs_type, for example is "afs"
user (string): hadoop param
passwd (string): hadoop param
hadoop bin (string): hadoop param
Examples:
fs = FileSystm()
"""
def
__init__
(
self
,
fs_type
=
"afs"
,
uri
=
"afs://xx"
,
user
=
None
,
passwd
=
None
,
hadoop_bin
=
""
,
):
assert
user
is
not
None
assert
passwd
is
not
None
assert
hadoop_bin
is
not
None
import
ps_pb2
as
pslib
self
.
fs_client
=
pslib
.
FsClientParameter
()
self
.
fs_client
.
uri
=
uri
self
.
fs_client
.
user
=
user
self
.
fs_client
.
passwd
=
passwd
# self.fs_client.buffer_size = 0
self
.
fs_client
.
hadoop_bin
=
hadoop_bin
# self.fs_client.afs_conf = afs_conf if not afs_conf else ""
def
get_desc
(
self
):
"""
get hadoop desc.
"""
return
self
.
fs_client
class
MPIHelper
:
"""
MPIHelper is a wrapper of mpi4py, support get_rank get_size etc.
Args:
No params
Examples:
mh = MPIHelper()
mh.get_ip()
"""
def
__init__
(
self
):
from
mpi4py
import
MPI
self
.
comm
=
MPI
.
COMM_WORLD
self
.
MPI
=
MPI
def
get_rank
(
self
):
return
self
.
comm
.
Get_rank
()
def
get_size
(
self
):
return
self
.
comm
.
Get_size
()
def
get_ip
(
self
):
import
socket
local_ip
=
socket
.
gethostbyname
(
socket
.
gethostname
())
return
local_ip
def
get_hostname
(
self
):
import
socket
return
socket
.
gethostname
()
def
finalize
(
self
):
self
.
MPI
.
Finalize
()
python/paddle/fluid/distributed/node.py
已删除
100644 → 0
浏览文件 @
5defefd6
# 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
import
ps_pb2
as
pslib
# NOTE: reduce removed in fuctools in python3
from
functools
import
reduce
class
Server
:
"""
A Server basic class.
"""
def
__init__
(
self
):
pass
class
Worker
:
"""
A Worker basic class.
"""
def
__init__
(
self
):
pass
class
DownpourServer
(
Server
):
"""
DownpourServer class is used to generate server program_desc
Args:
server: it is pslib.ServerParameter()
Examples:
server = DownpourServer()
"""
def
__init__
(
self
):
self
.
server_
=
pslib
.
ServerParameter
()
self
.
server_
.
downpour_server_param
.
service_param
.
start_server_port
=
0
self
.
server_
.
downpour_server_param
.
service_param
.
server_class
=
(
"DownpourBrpcPsServer"
)
self
.
server_
.
downpour_server_param
.
service_param
.
client_class
=
(
"DownpourBrpcPsClient"
)
self
.
server_
.
downpour_server_param
.
service_param
.
service_class
=
(
"DownpourPsService"
)
self
.
server_
.
downpour_server_param
.
service_param
.
server_thread_num
=
12
def
add_sparse_table
(
self
,
table_id
,
learning_rate
,
slot_key_vars
,
slot_value_var
):
r
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
slot_key_vars(string): slot key id
slot_value_var(string): slot key value after embedding
Returns:
return None
"""
table
=
self
.
server_
.
downpour_server_param
.
downpour_table_param
.
add
()
table
.
table_id
=
table_id
table
.
table_class
=
"DownpourSparseTable"
table
.
type
=
pslib
.
PS_SPARSE_TABLE
table
.
accessor
.
accessor_class
=
"DownpourFeatureValueAccessor"
table
.
accessor
.
sparse_sgd_param
.
learning_rate
=
learning_rate
table
.
accessor
.
sparse_sgd_param
.
initial_g2sum
=
3
table
.
accessor
.
sparse_sgd_param
.
initial_range
=
1e-4
table
.
accessor
.
sparse_sgd_param
.
weight_bounds
.
extend
([
-
10
,
10
])
table
.
accessor
.
embedx_dim
=
8
table
.
accessor
.
embedx_threshold
=
5
table
.
accessor
.
fea_dim
=
11
table
.
accessor
.
downpour_accessor_param
.
nonclk_coeff
=
0.1
table
.
accessor
.
downpour_accessor_param
.
click_coeff
=
2
table
.
accessor
.
downpour_accessor_param
.
base_threshold
=
0.2
table
.
accessor
.
downpour_accessor_param
.
delta_threshold
=
0.15
table
.
accessor
.
downpour_accessor_param
.
delta_keep_days
=
31
table
.
accessor
.
downpour_accessor_param
.
show_click_decay_rate
=
0.999
table
.
accessor
.
downpour_accessor_param
.
delete_threshold
=
0.8
def
add_dense_table
(
self
,
table_id
,
learning_rate
,
param_var
,
grad_var
):
r
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
param_var(list): all dense param. it is a list.
grad_var(list): all dense grad parm it is a list.
Returns:
return None
"""
table
=
self
.
server_
.
downpour_server_param
.
downpour_table_param
.
add
()
table
.
table_id
=
table_id
table
.
table_class
=
"DownpourDenseTable"
table
.
type
=
pslib
.
PS_DENSE_TABLE
table
.
accessor
.
accessor_class
=
"DownpourDenseValueAccessor"
table
.
accessor
.
dense_sgd_param
.
name
=
"adam"
table
.
accessor
.
dense_sgd_param
.
adam
.
learning_rate
=
learning_rate
table
.
accessor
.
dense_sgd_param
.
adam
.
avg_decay_rate
=
0.999993
table
.
accessor
.
dense_sgd_param
.
adam
.
ada_decay_rate
=
0.9999
table
.
accessor
.
dense_sgd_param
.
adam
.
ada_epsilon
=
1e-8
table
.
accessor
.
dense_sgd_param
.
adam
.
mom_decay_rate
=
0.99
table
.
accessor
.
dense_sgd_param
.
naive
.
learning_rate
=
0.0002
fea_dim
=
0
for
param
in
filter
(
lambda
x
:
x
.
name
.
find
(
"embedding"
)
==
-
1
,
param_var
):
fea_dim
+=
reduce
(
lambda
x
,
y
:
x
*
y
,
param
.
shape
,
1
)
table
.
accessor
.
fea_dim
=
fea_dim
def
get_desc
(
self
):
"""
Return downpour server program_desc
"""
return
self
.
server_
class
DownpourWorker
(
Worker
):
"""
DownpourWorker class is used to generate worker program_desc
Args:
window (int): push params frequency
worker: it is pslib.DownpourTrainerParameter
Examples:
worker = DownpourWorker(1)
"""
def
__init__
(
self
,
window
):
self
.
window
=
window
self
.
worker_
=
pslib
.
DownpourTrainerParameter
()
def
add_sparse_table
(
self
,
table_id
,
learning_rate
,
slot_key_vars
,
slot_value_vars
):
r
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
slot_key_vars(string): slot key id
slot_value_var(string): slot key value after embedding
Returns:
return None
"""
table
=
self
.
worker_
.
sparse_table
.
add
()
table
.
table_id
=
table_id
table
.
slot_key
.
extend
([
var
.
name
for
var
in
slot_key_vars
])
table
.
slot_value
.
extend
([
var
.
name
for
var
in
slot_value_vars
])
table
.
slot_gradient
.
extend
(
[
var
.
name
+
"@GRAD"
for
var
in
slot_value_vars
]
)
def
add_dense_table
(
self
,
table_id
,
learning_rate
,
param_vars
,
grad_vars
):
r
"""
Args:
table_id(int): id of sparse params table
learning_rate(float): the learning rate used to update parameters. \
Can be a float value
param_var(list): all dense param. it is a list.
grad_var(list): all dense grad parm it is a list.
Returns:
return None
"""
table
=
self
.
worker_
.
dense_table
.
add
()
table
.
table_id
=
table_id
table
.
dense_variable_name
.
extend
(
filter
(
lambda
x
:
x
.
find
(
"embedding"
)
==
-
1
,
[
p
.
name
for
p
in
param_vars
],
)
)
table
.
dense_gradient_variable_name
.
extend
(
filter
(
lambda
x
:
x
.
find
(
"embedding"
)
==
-
1
,
[
g
.
name
for
g
in
grad_vars
]
)
)
def
get_desc
(
self
):
"""
Return downpour worker program_desc
"""
return
self
.
worker_
python/paddle/fluid/distributed/ps_instance.py
已删除
100644 → 0
浏览文件 @
5defefd6
# 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
from
.helper
import
MPIHelper
class
PaddlePSInstance
:
"""
PaddlePSInstance class is used to generate A instance of server or worker
Args:
server_worker_mode: is a value 0 or 1, default is 1
proc_per_node: process per node, default is 2
Examples:
instance = PaddlePSInstance(1, 2)
"""
def
__init__
(
self
,
server_worker_mode
=
1
,
proc_per_node
=
2
):
self
.
dh
=
MPIHelper
()
self
.
_rankid
=
self
.
dh
.
get_rank
()
self
.
_server_worker_mode
=
server_worker_mode
self
.
_proc_per_node
=
proc_per_node
self
.
_nodes
=
self
.
dh
.
get_size
()
self
.
_ip
=
0
self
.
_worker_num
=
self
.
_nodes
*
self
.
_proc_per_node
/
2
self
.
_server_num
=
self
.
_nodes
*
self
.
_proc_per_node
/
2
self
.
_total_server_worker
=
self
.
_worker_num
+
self
.
_server_num
self
.
_node_type
=
None
# IDLE=-1, WORKER=1, SERVER=0
self
.
_set_nodetype
()
self
.
_comm
=
None
self
.
_split_comm
()
def
_set_nodetype
(
self
):
if
self
.
_server_worker_mode
==
0
:
if
self
.
_rankid
<
self
.
_server_num
:
self
.
_node_type
=
1
elif
self
.
_rankid
<
self
.
_total_server_worker
:
self
.
_node_type
=
0
else
:
self
.
_node_type
=
-
1
elif
self
.
_server_worker_mode
==
1
:
if
self
.
_rankid
<
self
.
_total_server_worker
:
if
0
==
self
.
_rankid
%
self
.
_proc_per_node
%
2
:
self
.
_node_type
=
0
else
:
self
.
_node_type
=
1
else
:
self
.
_node_type
=
-
1
else
:
self
.
_node_type
=
-
1
def
_split_comm
(
self
):
if
self
.
is_server
():
self
.
_comm
=
self
.
dh
.
comm
.
Split
(
self
.
_node_type
)
elif
self
.
is_worker
():
self
.
_comm
=
self
.
dh
.
comm
.
Split
(
self
.
_node_type
)
pass
def
get_worker_id
(
self
):
"""
Return worker index
"""
if
self
.
_server_worker_mode
==
0
:
return
self
.
_rankid
==
self
.
server_num
else
:
return
self
.
_rankid
/
self
.
_proc_per_node
def
get_server_id
(
self
):
"""
Return server index
"""
if
self
.
_server_worker_mode
==
0
:
return
self
.
rank_id
else
:
return
self
.
rank_id
/
self
.
_proc_per_node
def
is_worker
(
self
):
"""
Return instance is worker or not
"""
return
self
.
_node_type
==
1
def
is_server
(
self
):
"""
Return instance is server or not
"""
return
self
.
_node_type
==
0
def
is_first_worker
(
self
):
"""
Return instance is first worker or not
"""
return
self
.
is_worker
()
and
0
==
self
.
get_worker_id
()
def
set_ip
(
self
,
ip
):
"""
set server ip
"""
self
.
_ip
=
ip
def
gather_ips
(
self
):
"""
Return all servers and workers ip through mpi allgather
"""
self
.
_ips
=
self
.
dh
.
comm
.
allgather
(
self
.
_ip
)
return
self
.
_ips
def
get_node_cnt
(
self
):
"""
Return node cnt
"""
return
self
.
_nodes
def
get_worker_num
(
self
):
"""
Return worker num
"""
return
self
.
_worker_num
def
get_server_num
(
self
):
"""
Return server num
"""
return
self
.
_server_num
def
barrier_all
(
self
):
"""
barrier workers and servers
"""
self
.
dh
.
comm
.
barrier
()
def
barrier_worker
(
self
):
"""
barrier workers
"""
if
self
.
is_worker
():
self
.
_comm
.
barrier
()
pass
def
finalize
(
self
):
"""
MPI finalize
"""
self
.
dh
.
finalize
()
pass
if
__name__
==
"__main__"
:
instance
=
PaddlePSInstance
(
1
,
2
)
instance
.
barrier_all
()
python/paddle/fluid/distributed/ps_pb2.py
已删除
100644 → 0
浏览文件 @
5defefd6
# 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
# limitations under the License.
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: ps.proto
import
sys
_b
=
sys
.
version_info
[
0
]
<
3
and
(
lambda
x
:
x
)
or
(
lambda
x
:
x
.
encode
(
'latin1'
))
from
google.protobuf.internal
import
enum_type_wrapper
from
google.protobuf
import
descriptor
as
_descriptor
from
google.protobuf
import
message
as
_message
from
google.protobuf
import
reflection
as
_reflection
from
google.protobuf
import
symbol_database
as
_symbol_database
from
google.protobuf
import
descriptor_pb2
# @@protoc_insertion_point(imports)
_sym_db
=
_symbol_database
.
Default
()
DESCRIPTOR
=
_descriptor
.
FileDescriptor
(
name
=
'ps.proto'
,
package
=
'paddle'
,
syntax
=
'proto2'
,
serialized_pb
=
_b
(
'
\n\x08
ps.proto
\x12\x06
paddle
\"\x9e\x02\n\x0b
PSParameter
\x12\x14\n\x0c
worker_class
\x18\x01
\x01
(
\t\x12\x14\n\x0c
server_class
\x18\x02
\x01
(
\t\x12\x16\n\x0e
instance_class
\x18\x03
\x01
(
\t\x12
-
\n\x0c
worker_param
\x18\x65
\x01
(
\x0b\x32\x17
.paddle.WorkerParameter
\x12
-
\n\x0c
server_param
\x18\x66
\x01
(
\x0b\x32\x17
.paddle.ServerParameter
\x12\x38\n\r
trainer_param
\x18\xad\x02
\x01
(
\x0b\x32
.paddle.DownpourTrainerParameter
\x12\x33\n\x0f\x66
s_client_param
\x18\xf5\x03
\x01
(
\x0b\x32\x19
.paddle.FsClientParameter
\"
Q
\n\x0f
WorkerParameter
\x12
>
\n\x15\x64
ownpour_worker_param
\x18\x01
\x01
(
\x0b\x32\x1f
.paddle.DownpourWorkerParameter
\"
Q
\n\x0f
ServerParameter
\x12
>
\n\x15\x64
ownpour_server_param
\x18\x01
\x01
(
\x0b\x32\x1f
.paddle.DownpourServerParameter
\"
O
\n\x17\x44
ownpourWorkerParameter
\x12\x34\n\x14\x64
ownpour_table_param
\x18\x01
\x03
(
\x0b\x32\x16
.paddle.TableParameter
\"\xfd\x01\n\x18\x44
ownpourTrainerParameter
\x12\x30\n\x0b\x64\x65
nse_table
\x18\x01
\x03
(
\x0b\x32\x1b
.paddle.DenseTableParameter
\x12\x32\n\x0c
sparse_table
\x18\x02
\x03
(
\x0b\x32\x1c
.paddle.SparseTableParameter
\x12\x1d\n\x15
push_sparse_per_batch
\x18\x03
\x01
(
\x05\x12\x1c\n\x14
push_dense_per_batch
\x18\x04
\x01
(
\x05\x12\x0f\n\x07
skip_op
\x18\x05
\x03
(
\t\x12
-
\n\x0e
program_config
\x18\x06
\x03
(
\x0b\x32\x15
.paddle.ProgramConfig
\"\x99\x01\n\r
ProgramConfig
\x12\x12\n\n
program_id
\x18\x01
\x02
(
\t\x12\x1c\n\x14
push_sparse_table_id
\x18\x02
\x03
(
\x05\x12\x1b\n\x13
push_dense_table_id
\x18\x03
\x03
(
\x05\x12\x1c\n\x14
pull_sparse_table_id
\x18\x04
\x03
(
\x05\x12\x1b\n\x13
pull_dense_table_id
\x18\x05
\x03
(
\x05\"
{
\n\x13\x44\x65
nseTableParameter
\x12\x10\n\x08
table_id
\x18\x01
\x01
(
\x05\x12\x1b\n\x13\x64\x65
nse_variable_name
\x18\x02
\x03
(
\t\x12
$
\n\x1c\x64\x65
nse_gradient_variable_name
\x18\x03
\x03
(
\t\x12\x0f\n\x07\x66\x65\x61
_dim
\x18\x04
\x01
(
\x05\"
z
\n\x14
SparseTableParameter
\x12\x10\n\x08
table_id
\x18\x01
\x01
(
\x05\x12\x13\n\x0b\x66\x65\x61
ture_dim
\x18\x02
\x01
(
\x05\x12\x10\n\x08
slot_key
\x18\x03
\x03
(
\t\x12\x12\n\n
slot_value
\x18\x04
\x03
(
\t\x12\x15\n\r
slot_gradient
\x18\x05
\x03
(
\t\"\x86\x01\n\x17\x44
ownpourServerParameter
\x12\x34\n\x14\x64
ownpour_table_param
\x18\x01
\x03
(
\x0b\x32\x16
.paddle.TableParameter
\x12\x35\n\r
service_param
\x18\x02
\x01
(
\x0b\x32\x1e
.paddle.ServerServiceParameter
\"\xd7\x01\n\x16
ServerServiceParameter
\x12
*
\n\x0c
server_class
\x18\x01
\x01
(
\t
:
\x14\x44
ownpourBrpcPsServer
\x12
*
\n\x0c\x63
lient_class
\x18\x02
\x01
(
\t
:
\x14\x44
ownpourBrpcPsClient
\x12
(
\n\r
service_class
\x18\x03
\x01
(
\t
:
\x11\x44
ownpourPsService
\x12\x1c\n\x11
start_server_port
\x18\x04
\x01
(
\r
:
\x01\x30\x12\x1d\n\x11
server_thread_num
\x18\x05
\x01
(
\r
:
\x02\x31\x32\"\xbf\x01\n\x0e
TableParameter
\x12\x10\n\x08
table_id
\x18\x01
\x01
(
\x04\x12\x13\n\x0b
table_class
\x18\x02
\x01
(
\t\x12\x12\n\n
shared_num
\x18\x03
\x01
(
\x04\x12\x30\n\x08\x61\x63\x63\x65
ssor
\x18\x04
\x01
(
\x0b\x32\x1e
.paddle.TableAccessorParameter
\x12\x1f\n\x04
type
\x18\x05
\x01
(
\x0e\x32\x11
.paddle.TableType
\x12\x1f\n\x10\x63
ompress_in_save
\x18\x06
\x01
(
\x08
:
\x05\x66\x61
lse
\"\xf1\x02\n\x16
TableAccessorParameter
\x12\x16\n\x0e\x61\x63\x63\x65
ssor_class
\x18\x01
\x01
(
\t\x12\x38\n\x10
sparse_sgd_param
\x18\x02
\x01
(
\x0b\x32\x1e
.paddle.SparseSGDRuleParameter
\x12\x36\n\x0f\x64\x65
nse_sgd_param
\x18\x03
\x01
(
\x0b\x32\x1d
.paddle.DenseSGDRuleParameter
\x12\x0f\n\x07\x66\x65\x61
_dim
\x18\x04
\x01
(
\r\x12\x12\n\n
embedx_dim
\x18\x05
\x01
(
\r\x12\x18\n\x10\x65
mbedx_threshold
\x18\x06
\x01
(
\r\x12
G
\n\x17\x64
ownpour_accessor_param
\x18\x07
\x01
(
\x0b\x32
&.paddle.DownpourTableAccessorParameter
\x12\x45\n\x19
table_accessor_save_param
\x18\x08
\x03
(
\x0b\x32\"
.paddle.TableAccessorSaveParameter
\"\xce\x01\n\x1e\x44
ownpourTableAccessorParameter
\x12\x14\n\x0c
nonclk_coeff
\x18\x01
\x01
(
\x02\x12\x13\n\x0b\x63
lick_coeff
\x18\x02
\x01
(
\x02\x12\x16\n\x0e\x62\x61
se_threshold
\x18\x03
\x01
(
\x02\x12\x17\n\x0f\x64\x65
lta_threshold
\x18\x04
\x01
(
\x02\x12\x17\n\x0f\x64\x65
lta_keep_days
\x18\x05
\x01
(
\x02\x12\x1d\n\x15
show_click_decay_rate
\x18\x06
\x01
(
\x02\x12\x18\n\x10\x64\x65
lete_threshold
\x18\x07
\x01
(
\x02\"
S
\n\x1a
TableAccessorSaveParameter
\x12\r\n\x05
param
\x18\x01
\x01
(
\r\x12\x11\n\t
converter
\x18\x02
\x01
(
\t\x12\x13\n\x0b\x64\x65\x63
onverter
\x18\x03
\x01
(
\t\"
e
\n\x10
PsRequestMessage
\x12\x0e\n\x06\x63
md_id
\x18\x01
\x02
(
\r\x12\x10\n\x08
table_id
\x18\x02
\x01
(
\r\x12\x0e\n\x06
params
\x18\x03
\x03
(
\x0c\x12\x11\n\t
client_id
\x18\x04
\x01
(
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I
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S
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EnumTypeWrapper
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EnumValueDescriptor
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EnumValueDescriptor
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EnumTypeWrapper
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FieldDescriptor
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FieldDescriptor
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FieldDescriptor
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FieldDescriptor
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Descriptor
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Descriptor
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Descriptor
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_SPARSESGDRULEPARAMETER
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Descriptor
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=
[
_FSCLIENTPARAMETER_FSAPITYPE
,
],
options
=
None
,
is_extendable
=
False
,
syntax
=
'proto2'
,
extension_ranges
=
[],
oneofs
=
[],
serialized_start
=
3274
,
serialized_end
=
3487
,
)
_PSPARAMETER
.
fields_by_name
[
'worker_param'
].
message_type
=
_WORKERPARAMETER
_PSPARAMETER
.
fields_by_name
[
'server_param'
].
message_type
=
_SERVERPARAMETER
_PSPARAMETER
.
fields_by_name
[
'trainer_param'
].
message_type
=
_DOWNPOURTRAINERPARAMETER
_PSPARAMETER
.
fields_by_name
[
'fs_client_param'
].
message_type
=
_FSCLIENTPARAMETER
_WORKERPARAMETER
.
fields_by_name
[
'downpour_worker_param'
].
message_type
=
_DOWNPOURWORKERPARAMETER
_SERVERPARAMETER
.
fields_by_name
[
'downpour_server_param'
].
message_type
=
_DOWNPOURSERVERPARAMETER
_DOWNPOURWORKERPARAMETER
.
fields_by_name
[
'downpour_table_param'
].
message_type
=
_TABLEPARAMETER
_DOWNPOURTRAINERPARAMETER
.
fields_by_name
[
'dense_table'
].
message_type
=
_DENSETABLEPARAMETER
_DOWNPOURTRAINERPARAMETER
.
fields_by_name
[
'sparse_table'
].
message_type
=
_SPARSETABLEPARAMETER
_DOWNPOURTRAINERPARAMETER
.
fields_by_name
[
'program_config'
].
message_type
=
_PROGRAMCONFIG
_DOWNPOURSERVERPARAMETER
.
fields_by_name
[
'downpour_table_param'
].
message_type
=
_TABLEPARAMETER
_DOWNPOURSERVERPARAMETER
.
fields_by_name
[
'service_param'
].
message_type
=
_SERVERSERVICEPARAMETER
_TABLEPARAMETER
.
fields_by_name
[
'accessor'
].
message_type
=
_TABLEACCESSORPARAMETER
_TABLEPARAMETER
.
fields_by_name
[
'type'
].
enum_type
=
_TABLETYPE
_TABLEACCESSORPARAMETER
.
fields_by_name
[
'sparse_sgd_param'
].
message_type
=
_SPARSESGDRULEPARAMETER
_TABLEACCESSORPARAMETER
.
fields_by_name
[
'dense_sgd_param'
].
message_type
=
_DENSESGDRULEPARAMETER
_TABLEACCESSORPARAMETER
.
fields_by_name
[
'downpour_accessor_param'
].
message_type
=
_DOWNPOURTABLEACCESSORPARAMETER
_TABLEACCESSORPARAMETER
.
fields_by_name
[
'table_accessor_save_param'
].
message_type
=
_TABLEACCESSORSAVEPARAMETER
_DENSESGDRULEPARAMETER
.
fields_by_name
[
'adam'
].
message_type
=
_ADAMSGDPARAMETER
_DENSESGDRULEPARAMETER
.
fields_by_name
[
'naive'
].
message_type
=
_NAIVESGDPARAMETER
_DENSESGDRULEPARAMETER
.
fields_by_name
[
'summary'
].
message_type
=
_SUMMARYSGDPARAMETER
_DENSESGDRULEPARAMETER
.
fields_by_name
[
'moving_average'
].
message_type
=
_MOVINGAVERAGERULEPARAMETER
_FSCLIENTPARAMETER
.
fields_by_name
[
'fs_type'
].
enum_type
=
_FSCLIENTPARAMETER_FSAPITYPE
_FSCLIENTPARAMETER_FSAPITYPE
.
containing_type
=
_FSCLIENTPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'PSParameter'
]
=
_PSPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'WorkerParameter'
]
=
_WORKERPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'ServerParameter'
]
=
_SERVERPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'DownpourWorkerParameter'
]
=
_DOWNPOURWORKERPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'DownpourTrainerParameter'
]
=
_DOWNPOURTRAINERPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'ProgramConfig'
]
=
_PROGRAMCONFIG
DESCRIPTOR
.
message_types_by_name
[
'DenseTableParameter'
]
=
_DENSETABLEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'SparseTableParameter'
]
=
_SPARSETABLEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'DownpourServerParameter'
]
=
_DOWNPOURSERVERPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'ServerServiceParameter'
]
=
_SERVERSERVICEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'TableParameter'
]
=
_TABLEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'TableAccessorParameter'
]
=
_TABLEACCESSORPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'DownpourTableAccessorParameter'
]
=
_DOWNPOURTABLEACCESSORPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'TableAccessorSaveParameter'
]
=
_TABLEACCESSORSAVEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'PsRequestMessage'
]
=
_PSREQUESTMESSAGE
DESCRIPTOR
.
message_types_by_name
[
'SparseSGDRuleParameter'
]
=
_SPARSESGDRULEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'DenseSGDRuleParameter'
]
=
_DENSESGDRULEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'AdamSGDParameter'
]
=
_ADAMSGDPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'NaiveSGDParameter'
]
=
_NAIVESGDPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'SummarySGDParameter'
]
=
_SUMMARYSGDPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'MovingAverageRuleParameter'
]
=
_MOVINGAVERAGERULEPARAMETER
DESCRIPTOR
.
message_types_by_name
[
'PsResponseMessage'
]
=
_PSRESPONSEMESSAGE
DESCRIPTOR
.
message_types_by_name
[
'FsClientParameter'
]
=
_FSCLIENTPARAMETER
DESCRIPTOR
.
enum_types_by_name
[
'TableType'
]
=
_TABLETYPE
DESCRIPTOR
.
enum_types_by_name
[
'PsCmdID'
]
=
_PSCMDID
PSParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'PSParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_PSPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.PSParameter)
),
)
_sym_db
.
RegisterMessage
(
PSParameter
)
WorkerParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'WorkerParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_WORKERPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.WorkerParameter)
),
)
_sym_db
.
RegisterMessage
(
WorkerParameter
)
ServerParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'ServerParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_SERVERPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.ServerParameter)
),
)
_sym_db
.
RegisterMessage
(
ServerParameter
)
DownpourWorkerParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'DownpourWorkerParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_DOWNPOURWORKERPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.DownpourWorkerParameter)
),
)
_sym_db
.
RegisterMessage
(
DownpourWorkerParameter
)
DownpourTrainerParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'DownpourTrainerParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_DOWNPOURTRAINERPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.DownpourTrainerParameter)
),
)
_sym_db
.
RegisterMessage
(
DownpourTrainerParameter
)
ProgramConfig
=
_reflection
.
GeneratedProtocolMessageType
(
'ProgramConfig'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_PROGRAMCONFIG
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.ProgramConfig)
),
)
_sym_db
.
RegisterMessage
(
ProgramConfig
)
DenseTableParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'DenseTableParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_DENSETABLEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.DenseTableParameter)
),
)
_sym_db
.
RegisterMessage
(
DenseTableParameter
)
SparseTableParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'SparseTableParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_SPARSETABLEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.SparseTableParameter)
),
)
_sym_db
.
RegisterMessage
(
SparseTableParameter
)
DownpourServerParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'DownpourServerParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_DOWNPOURSERVERPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.DownpourServerParameter)
),
)
_sym_db
.
RegisterMessage
(
DownpourServerParameter
)
ServerServiceParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'ServerServiceParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_SERVERSERVICEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.ServerServiceParameter)
),
)
_sym_db
.
RegisterMessage
(
ServerServiceParameter
)
TableParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'TableParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_TABLEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.TableParameter)
),
)
_sym_db
.
RegisterMessage
(
TableParameter
)
TableAccessorParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'TableAccessorParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_TABLEACCESSORPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.TableAccessorParameter)
),
)
_sym_db
.
RegisterMessage
(
TableAccessorParameter
)
DownpourTableAccessorParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'DownpourTableAccessorParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_DOWNPOURTABLEACCESSORPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.DownpourTableAccessorParameter)
),
)
_sym_db
.
RegisterMessage
(
DownpourTableAccessorParameter
)
TableAccessorSaveParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'TableAccessorSaveParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_TABLEACCESSORSAVEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.TableAccessorSaveParameter)
),
)
_sym_db
.
RegisterMessage
(
TableAccessorSaveParameter
)
PsRequestMessage
=
_reflection
.
GeneratedProtocolMessageType
(
'PsRequestMessage'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_PSREQUESTMESSAGE
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.PsRequestMessage)
),
)
_sym_db
.
RegisterMessage
(
PsRequestMessage
)
SparseSGDRuleParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'SparseSGDRuleParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_SPARSESGDRULEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.SparseSGDRuleParameter)
),
)
_sym_db
.
RegisterMessage
(
SparseSGDRuleParameter
)
DenseSGDRuleParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'DenseSGDRuleParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_DENSESGDRULEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.DenseSGDRuleParameter)
),
)
_sym_db
.
RegisterMessage
(
DenseSGDRuleParameter
)
AdamSGDParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'AdamSGDParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_ADAMSGDPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.AdamSGDParameter)
),
)
_sym_db
.
RegisterMessage
(
AdamSGDParameter
)
NaiveSGDParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'NaiveSGDParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_NAIVESGDPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.NaiveSGDParameter)
),
)
_sym_db
.
RegisterMessage
(
NaiveSGDParameter
)
SummarySGDParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'SummarySGDParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_SUMMARYSGDPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.SummarySGDParameter)
),
)
_sym_db
.
RegisterMessage
(
SummarySGDParameter
)
MovingAverageRuleParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'MovingAverageRuleParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_MOVINGAVERAGERULEPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.MovingAverageRuleParameter)
),
)
_sym_db
.
RegisterMessage
(
MovingAverageRuleParameter
)
PsResponseMessage
=
_reflection
.
GeneratedProtocolMessageType
(
'PsResponseMessage'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_PSRESPONSEMESSAGE
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.PsResponseMessage)
),
)
_sym_db
.
RegisterMessage
(
PsResponseMessage
)
FsClientParameter
=
_reflection
.
GeneratedProtocolMessageType
(
'FsClientParameter'
,
(
_message
.
Message
,),
dict
(
DESCRIPTOR
=
_FSCLIENTPARAMETER
,
__module__
=
'ps_pb2'
# @@protoc_insertion_point(class_scope:paddle.FsClientParameter)
),
)
_sym_db
.
RegisterMessage
(
FsClientParameter
)
DESCRIPTOR
.
has_options
=
True
DESCRIPTOR
.
_options
=
_descriptor
.
_ParseOptions
(
descriptor_pb2
.
FileOptions
(),
_b
(
'
\200\001\001
'
)
)
# @@protoc_insertion_point(module_scope)
python/setup.py.in
浏览文件 @
89f2c652
...
...
@@ -333,7 +333,6 @@ packages=['paddle',
'paddle.fluid.dygraph',
'paddle.fluid.proto',
'paddle.fluid.proto.profiler',
'paddle.fluid.distributed',
'paddle.fluid.layers',
'paddle.fluid.dataloader',
'paddle.fluid.contrib',
...
...
setup.py
浏览文件 @
89f2c652
...
...
@@ -1232,7 +1232,6 @@ def get_setup_parameters():
'paddle.fluid.dygraph'
,
'paddle.fluid.proto'
,
'paddle.fluid.proto.profiler'
,
'paddle.fluid.distributed'
,
'paddle.fluid.layers'
,
'paddle.fluid.dataloader'
,
'paddle.fluid.contrib'
,
...
...
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