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体验新版 GitCode,发现更多精彩内容 >>
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315e44ac
编写于
5月 15, 2018
作者:
Y
Yancey1989
浏览文件
操作
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电子邮件补丁
差异文件
add fetch_barrier_op
上级
b35ea1a4
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
126 addition
and
48 deletion
+126
-48
paddle/fluid/framework/executor.cc
paddle/fluid/framework/executor.cc
+1
-1
paddle/fluid/operators/CMakeLists.txt
paddle/fluid/operators/CMakeLists.txt
+3
-1
paddle/fluid/operators/fetch_barrier_op.cc
paddle/fluid/operators/fetch_barrier_op.cc
+101
-0
python/paddle/fluid/transpiler/distribute_transpiler.py
python/paddle/fluid/transpiler/distribute_transpiler.py
+21
-46
未找到文件。
paddle/fluid/framework/executor.cc
浏览文件 @
315e44ac
...
...
@@ -353,7 +353,7 @@ void Executor::RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope,
scope
->
DeleteScope
(
local_scope
);
}
else
{
// Delete the local scopes created in operators.
scope
->
DropKids
();
//
scope->DropKids();
}
if
(
FLAGS_benchmark
)
{
VLOG
(
2
)
<<
"-------------------------------------------------------"
;
...
...
paddle/fluid/operators/CMakeLists.txt
浏览文件 @
315e44ac
...
...
@@ -199,11 +199,13 @@ if(WITH_DISTRIBUTE)
op_library
(
send_vars_op DEPS
${
DISTRIBUTE_DEPS
}
)
set_source_files_properties
(
send_vars_op.cc PROPERTIES COMPILE_FLAGS
${
DISTRIBUTE_COMPILE_FLAGS
}
)
op_library
(
send_barrier_op DEPS
${
DISTRIBUTE_DEPS
}
)
op_library
(
fetch_barrier_op DEPS
${
DISTRIBUTE_DEPS
}
)
set_source_files_properties
(
send_barrier_op.cc PROPERTIES COMPILE_FLAGS
${
DISTRIBUTE_COMPILE_FLAGS
}
)
set_source_files_properties
(
fetch_barrier_op.cc PROPERTIES COMPILE_FLAGS
${
DISTRIBUTE_COMPILE_FLAGS
}
)
set_source_files_properties
(
send_recv_op_test.cc PROPERTIES COMPILE_FLAGS
${
DISTRIBUTE_COMPILE_FLAGS
}
)
cc_test
(
test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor
)
else
()
set
(
DEPS_OPS
${
DEPS_OPS
}
send_op prefetch_op recv_op listen_and_serv_op send_vars_op send_barrier_op
)
set
(
DEPS_OPS
${
DEPS_OPS
}
send_op prefetch_op recv_op listen_and_serv_op send_vars_op send_barrier_op
fetch_barrier_op
)
endif
()
op_library
(
cross_entropy_op DEPS cross_entropy
)
...
...
paddle/fluid/operators/fetch_barrier_op.cc
0 → 100644
浏览文件 @
315e44ac
/* Copyright (c) 2016 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 <future> // NOLINT
#include <ostream>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/grpc_client.h"
namespace
paddle
{
namespace
operators
{
class
FetchBarrierOp
:
public
framework
::
OperatorBase
{
public:
FetchBarrierOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorBase
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
place
)
const
override
{
std
::
vector
<
std
::
string
>
eps
=
Attr
<
std
::
vector
<
std
::
string
>>
(
"endpoints"
);
auto
client_var_name
=
Output
(
"RPCClient"
);
PADDLE_ENFORCE_NOT_NULL
(
scope
.
FindVar
(
client_var_name
),
"Can not find variable '%s' in the scope."
,
client_var_name
);
auto
*
client_var
=
scope
.
FindVar
(
client_var_name
);
detail
::
RPCClient
*
rpc_client
=
client_var
->
GetMutable
<
detail
::
RPCClient
>
();
PADDLE_ENFORCE
(
rpc_client
->
Wait
());
for
(
auto
&
ep
:
eps
)
{
VLOG
(
3
)
<<
"fetch barrier, ep: "
<<
ep
;
rpc_client
->
AsyncSendFetchBarrier
(
ep
);
}
PADDLE_ENFORCE
(
rpc_client
->
Wait
());
}
};
class
FetchBarrierOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
{
AddOutput
(
"RPCClient"
,
"(RPCClient) The RPC client object which is"
"initialized at most once."
);
AddComment
(
R"DOC(
SendBarrier operator
This operator will send a send barrier signal to list_and_serv op, so that
the Parameter Server would knew all variables have been sent.
)DOC"
);
AddAttr
<
std
::
vector
<
std
::
string
>>
(
"endpoints"
,
"(string vector, default 127.0.0.1:6164)"
"Server endpoints to send variables to."
)
.
SetDefault
({
"127.0.0.1:6164"
});
}
};
class
FetchBarrierOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
out_var_name
=
op_desc
.
Output
(
"RPCClient"
).
front
();
auto
&
out_var
=
block
->
FindRecursiveOrCreateVar
(
out_var_name
);
auto
var_type
=
framework
::
proto
::
VarType
::
RAW
;
out_var
.
SetType
(
var_type
);
}
};
class
FetchBarrierOpShapeInference
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
ctx
)
const
override
{}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
fetch_barrier
,
ops
::
FetchBarrierOp
,
paddle
::
framework
::
EmptyGradOpMaker
,
ops
::
FetchBarrierOpMaker
,
ops
::
FetchBarrierOpVarTypeInference
,
ops
::
FetchBarrierOpShapeInference
);
python/paddle/fluid/transpiler/distribute_transpiler.py
浏览文件 @
315e44ac
...
...
@@ -315,12 +315,22 @@ class DistributeTranspiler:
# step 3.1: insert send op to send gradient vars to parameter servers
ps_dispatcher
.
reset
()
send_vars
=
[]
for
varname
,
splited_vars
in
grad_var_mapping
.
items
():
index
=
find_op_by_output_arg
(
program
.
global_block
(),
varname
)
for
orig_varname
,
splited_vars
in
grad_var_mapping
.
items
():
eplist
=
ps_dispatcher
.
dispatch
(
splited_vars
)
if
len
(
splited_vars
)
>
1
:
self
.
_insert_split_op
(
program
,
varname
,
splited_vars
)
if
len
(
splited_vars
)
==
1
:
orig_varname
=
splited_vars
[
0
].
name
index
=
find_op_by_output_arg
(
program
.
global_block
(),
orig_varname
)
elif
len
(
splited_vars
)
>
1
:
orig_var
=
program
.
global_block
().
vars
[
orig_varname
]
index
=
find_op_by_output_arg
(
program
.
global_block
(),
orig_varname
)
self
.
_insert_split_op
(
program
,
orig_var
,
index
,
splited_vars
)
index
+=
1
else
:
AssertionError
(
"Can not insert the send op by original "
"variable name :"
,
orig_varname
)
program
.
global_block
().
insert_op
(
index
=
index
+
1
,
type
=
"send_vars"
,
...
...
@@ -351,6 +361,12 @@ class DistributeTranspiler:
"RPCClient"
:
rpc_client_var
},
attrs
=
{
"epmap"
:
eplist
})
program
.
global_block
().
append_op
(
type
=
"fetch_barrier"
,
inputs
=
{},
outputs
=
{
"RPCClient"
:
rpc_client_var
},
attrs
=
{
"endpoints"
:
pserver_endpoints
})
for
i
,
ep
in
enumerate
(
eplist
):
self
.
param_grad_ep_mapping
[
ep
][
"params"
].
append
(
recv_vars
[
i
])
self
.
param_grad_ep_mapping
[
ep
][
"grads"
].
append
(
send_vars
[
i
])
...
...
@@ -859,9 +875,7 @@ class DistributeTranspiler:
lod_level
=
var
.
lod_level
,
persistable
=
persistable
)
def
_insert_split_op
(
self
,
program
,
orig_varname
,
splited_vars
):
orig_var
=
program
.
global_block
().
vars
[
orig_varname
]
index
=
find_op_by_output_arg
(
program
.
global_block
(),
orig_varname
)
def
_insert_split_op
(
self
,
program
,
orig_var
,
index
,
splited_vars
):
if
orig_var
.
type
==
core
.
VarDesc
.
VarType
.
SELECTED_ROWS
:
height_sections
=
[]
for
v
in
splited_vars
:
...
...
@@ -887,45 +901,6 @@ class DistributeTranspiler:
AssertionError
(
"Variable type should be in set "
"[LOD_TENSOR, SELECTED_ROWS]"
)
def
_append_split_op
(
self
,
program
,
gradblocks
):
# Split variables that need to be split and append respective ops
add_suffix
=
False
if
self
.
trainer_num
>
1
:
add_suffix
=
True
var_mapping
=
self
.
_create_vars_from_blocklist
(
program
,
gradblocks
,
add_trainer_suffix
=
add_suffix
)
for
varname
,
splited_vars
in
var_mapping
.
iteritems
():
# variable that don't need to split have empty splited_vars
if
len
(
splited_vars
)
<=
1
:
continue
orig_var
=
program
.
global_block
().
vars
[
varname
]
index
=
find_op_by_output_arg
(
program
.
global_block
(),
orig_var
.
name
)
if
orig_var
.
type
==
core
.
VarDesc
.
VarType
.
SELECTED_ROWS
:
height_sections
=
[]
for
v
in
splited_vars
:
height_sections
.
append
(
v
.
shape
[
0
])
program
.
global_block
().
insert_op
(
index
=
index
+
1
,
type
=
"split_selected_rows"
,
inputs
=
{
"X"
:
orig_var
},
outputs
=
{
"Out"
:
splited_vars
},
attrs
=
{
"height_sections"
:
height_sections
})
elif
orig_var
.
type
==
core
.
VarDesc
.
VarType
.
LOD_TENSOR
:
sections
=
[]
for
v
in
splited_vars
:
sections
.
append
(
v
.
shape
[
0
])
program
.
global_block
().
insert_op
(
index
=
index
+
1
,
type
=
"split_byref"
,
inputs
=
{
"X"
:
orig_var
},
outputs
=
{
"Out"
:
splited_vars
},
attrs
=
{
"sections"
:
sections
}
# assume split evenly
)
else
:
AssertionError
(
"Variable type should be in set "
"[LOD_TENSOR, SELECTED_ROWS]"
)
return
var_mapping
def
_get_optimizer_input_shape
(
self
,
op_type
,
varkey
,
orig_shape
,
param_shape
):
"""
...
...
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