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7a993ee4
编写于
4月 20, 2018
作者:
Q
Qiao Longfei
提交者:
GitHub
4月 20, 2018
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差异文件
Merge pull request #10080 from jacquesqiao/refine-listen-and-serve-op
Refine listen and serve op
上级
f2e400d6
0f5a9cc9
变更
4
显示空白变更内容
内联
并排
Showing
4 changed file
with
68 addition
and
70 deletion
+68
-70
paddle/fluid/operators/detail/grpc_server.h
paddle/fluid/operators/detail/grpc_server.h
+1
-4
paddle/fluid/operators/listen_and_serv_op.cc
paddle/fluid/operators/listen_and_serv_op.cc
+55
-59
paddle/fluid/operators/listen_and_serv_op.h
paddle/fluid/operators/listen_and_serv_op.h
+11
-6
paddle/fluid/operators/send_recv_op_test.cc
paddle/fluid/operators/send_recv_op_test.cc
+1
-1
未找到文件。
paddle/fluid/operators/detail/grpc_server.h
浏览文件 @
7a993ee4
...
...
@@ -59,15 +59,13 @@ class AsyncGRPCServer final {
void
SetProgram
(
framework
::
ProgramDesc
*
program
)
{
program_
=
program
;
}
void
SetPrefetchBlkdId
(
int
blkid
)
{
prefetch_blk_id_
=
blkid
;
}
void
SetExecutor
(
framework
::
Executor
*
executor
)
{
executor_
=
executor
;
}
void
SetPrefetchPreparedCtx
(
framework
::
ExecutorPrepareContext
*
prepared
)
{
prefetch_ctx_
=
prepared
;
}
int
GetSelectedPort
()
{
return
selected_port_
;
}
int
GetSelectedPort
()
const
{
return
selected_port_
;
}
const
ReceivedMessage
Get
()
{
return
this
->
var_recv_queue_
.
Pop
();
}
...
...
@@ -114,7 +112,6 @@ class AsyncGRPCServer final {
std
::
unique_ptr
<
std
::
thread
>
t_get_
;
std
::
unique_ptr
<
std
::
thread
>
t_prefetch_
;
int
prefetch_blk_id_
;
framework
::
ExecutorPrepareContext
*
prefetch_ctx_
;
framework
::
ProgramDesc
*
program_
;
framework
::
Executor
*
executor_
;
...
...
paddle/fluid/operators/listen_and_serv_op.cc
浏览文件 @
7a993ee4
...
...
@@ -27,20 +27,6 @@ void RunServer(std::shared_ptr<detail::AsyncGRPCServer> service) {
VLOG
(
4
)
<<
"RunServer thread end"
;
}
static
void
CreateTensorFromMessageType
(
framework
::
Variable
*
var
,
sendrecv
::
VarType
var_type
)
{
if
(
var_type
==
sendrecv
::
VarType
::
LOD_TENSOR
)
{
var
->
GetMutable
<
framework
::
LoDTensor
>
();
}
else
if
(
var_type
==
sendrecv
::
VarType
::
SELECTED_ROWS
)
{
var
->
GetMutable
<
framework
::
SelectedRows
>
();
}
else
{
PADDLE_THROW
(
"VariableMessage type %d is not in "
"[LoDTensor, SelectedRows]"
,
var_type
);
}
}
static
void
ParallelExecuteBlocks
(
const
std
::
vector
<
size_t
>
&
parallel_blkids
,
framework
::
Executor
*
executor
,
const
std
::
vector
<
std
::
shared_ptr
<
framework
::
ExecutorPrepareContext
>>
...
...
@@ -62,6 +48,13 @@ static void ParallelExecuteBlocks(
for
(
size_t
i
=
0
;
i
<
fs
.
size
();
++
i
)
fs
[
i
].
wait
();
}
static
void
SavePort
(
std
::
shared_ptr
<
detail
::
AsyncGRPCServer
>
rpc_service
)
{
std
::
ofstream
port_file
;
port_file
.
open
(
"/tmp/paddle.selected_port"
);
port_file
<<
rpc_service
->
GetSelectedPort
();
port_file
.
close
();
}
ListenAndServOp
::
ListenAndServOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
...
...
@@ -77,59 +70,26 @@ void ListenAndServOp::Stop() {
server_thread_
->
join
();
}
void
ListenAndServOp
::
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
dev_place
)
const
{
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
&
dev_ctx
=
*
pool
.
Get
(
dev_place
);
framework
::
Scope
&
recv_scope
=
scope
.
NewScope
();
if
(
!
rpc_service_
)
{
std
::
string
endpoint
=
Attr
<
std
::
string
>
(
"endpoint"
);
rpc_service_
.
reset
(
new
detail
::
AsyncGRPCServer
(
endpoint
));
}
auto
ins
=
Inputs
(
"X"
);
void
ListenAndServOp
::
RunSyncLoop
(
framework
::
Executor
*
executor
,
framework
::
ProgramDesc
*
program
,
framework
::
Scope
*
recv_scope
,
framework
::
BlockDesc
*
prefetch_block
)
const
{
auto
fan_in
=
Attr
<
int
>
(
"Fanin"
);
auto
*
optimize_block
=
Attr
<
framework
::
BlockDesc
*>
(
kOptimizeBlock
);
auto
*
prefetch_block
=
Attr
<
framework
::
BlockDesc
*>
(
kPrefetchBlock
);
auto
*
program
=
optimize_block
->
Program
();
size_t
num_blocks
=
program
->
Size
();
PADDLE_ENFORCE_GE
(
num_blocks
,
2
,
"server program should have at least 2 blocks"
);
framework
::
Executor
executor
(
dev_place
);
std
::
vector
<
int
>
block_list
;
for
(
size_t
blkid
=
1
;
blkid
<
num_blocks
;
++
blkid
)
{
if
(
blkid
!=
static_cast
<
size_t
>
(
prefetch_block
->
ID
()))
{
block_list
.
push_back
(
blkid
);
}
}
auto
optimize_prepared
=
executor
.
Prepare
(
*
program
,
block_list
);
auto
optimize_prepared
=
executor
->
Prepare
(
*
program
,
block_list
);
// Insert placeholder for block0 which holds current op itself.
optimize_prepared
.
insert
(
optimize_prepared
.
begin
(),
std
::
shared_ptr
<
framework
::
ExecutorPrepareContext
>
(
nullptr
));
rpc_service_
->
SetScope
(
&
recv_scope
);
rpc_service_
->
SetDevCtx
(
&
dev_ctx
);
// TODO(qiao) set proper fields for table lookup and update
rpc_service_
->
SetExecutor
(
&
executor
);
VLOG
(
3
)
<<
"prefetch block id is "
<<
prefetch_block
->
ID
();
auto
prefetch_prepared
=
executor
.
Prepare
(
*
program
,
prefetch_block
->
ID
());
rpc_service_
->
SetPrefetchBlkdId
(
prefetch_block
->
ID
());
rpc_service_
->
SetPrefetchPreparedCtx
(
prefetch_prepared
.
get
());
prefetch_prepared
.
release
();
rpc_service_
->
SetProgram
(
program
);
// start the server listening after all member initialized.
server_thread_
.
reset
(
new
std
::
thread
(
RunServer
,
rpc_service_
));
VLOG
(
3
)
<<
"wait server thread to become ready..."
;
sleep
(
5
);
// Write to a file of server selected port for python use.
std
::
ofstream
port_file
;
port_file
.
open
(
"/tmp/paddle.selected_port"
);
port_file
<<
rpc_service_
->
GetSelectedPort
();
port_file
.
close
();
bool
exit_flag
=
false
;
// Record received sparse variables, so that
// we could reset those after execute optimize program
...
...
@@ -170,7 +130,7 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
break
;
}
// NOTE: if is_gpu_place, CUDA kernels are lau
g
ched by multiple threads
// NOTE: if is_gpu_place, CUDA kernels are lau
n
ched by multiple threads
// and this will still work.
// The optimize blocks which have the same parent ID would run parallel
...
...
@@ -182,16 +142,16 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
for
(
size_t
blkid
=
2
;
blkid
<
num_blocks
;
++
blkid
)
{
if
(
blkid
!=
static_cast
<
size_t
>
(
prefetch_block
->
ID
()))
{
if
(
program
->
Block
(
blkid
).
Parent
()
!=
last_parent_blkid
)
{
ParallelExecuteBlocks
(
parallel_blkids
,
&
executor
,
optimize_prepared
,
program
,
&
recv_scope
);
ParallelExecuteBlocks
(
parallel_blkids
,
executor
,
optimize_prepared
,
program
,
recv_scope
);
parallel_blkids
.
clear
();
last_parent_blkid
=
program
->
Block
(
blkid
).
Parent
();
}
parallel_blkids
.
push_back
(
blkid
);
}
}
ParallelExecuteBlocks
(
parallel_blkids
,
&
executor
,
optimize_prepared
,
program
,
&
recv_scope
);
ParallelExecuteBlocks
(
parallel_blkids
,
executor
,
optimize_prepared
,
program
,
recv_scope
);
VLOG
(
2
)
<<
"run all blocks spent "
<<
detail
::
GetTimestamp
()
-
ts
<<
"(ms)"
;
// Reset the received sparse variables, the sum operator would not
...
...
@@ -209,6 +169,42 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
}
// while(true)
}
void
ListenAndServOp
::
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
dev_place
)
const
{
platform
::
DeviceContextPool
&
pool
=
platform
::
DeviceContextPool
::
Instance
();
auto
&
dev_ctx
=
*
pool
.
Get
(
dev_place
);
framework
::
Scope
&
recv_scope
=
scope
.
NewScope
();
PADDLE_ENFORCE
(
!
rpc_service_
);
std
::
string
endpoint
=
Attr
<
std
::
string
>
(
"endpoint"
);
rpc_service_
.
reset
(
new
detail
::
AsyncGRPCServer
(
endpoint
));
auto
*
optimize_block
=
Attr
<
framework
::
BlockDesc
*>
(
kOptimizeBlock
);
auto
*
prefetch_block
=
Attr
<
framework
::
BlockDesc
*>
(
kPrefetchBlock
);
auto
*
program
=
optimize_block
->
Program
();
framework
::
Executor
executor
(
dev_place
);
// prepare rpc_service
rpc_service_
->
SetScope
(
&
recv_scope
);
rpc_service_
->
SetDevCtx
(
&
dev_ctx
);
rpc_service_
->
SetProgram
(
program
);
rpc_service_
->
SetExecutor
(
&
executor
);
// prepare for prefetch
VLOG
(
3
)
<<
"prefetch block id is "
<<
prefetch_block
->
ID
();
auto
prefetch_prepared
=
executor
.
Prepare
(
*
program
,
prefetch_block
->
ID
());
rpc_service_
->
SetPrefetchPreparedCtx
(
prefetch_prepared
.
get
());
prefetch_prepared
.
release
();
// start the server listening after all member initialized.
server_thread_
.
reset
(
new
std
::
thread
(
RunServer
,
rpc_service_
));
VLOG
(
3
)
<<
"wait server thread to become ready..."
;
sleep
(
5
);
// Write to a file of server selected port for python use.
SavePort
(
rpc_service_
);
RunSyncLoop
(
&
executor
,
program
,
&
recv_scope
,
prefetch_block
);
}
class
ListenAndServOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ListenAndServOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
...
...
paddle/fluid/operators/listen_and_serv_op.h
浏览文件 @
7a993ee4
...
...
@@ -34,17 +34,22 @@ void RunServer(std::shared_ptr<detail::AsyncGRPCServer> service);
class
ListenAndServOp
:
public
framework
::
OperatorBase
{
public:
ListenAndServOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
);
ListenAndServOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
);
int
GetSelectedPort
()
const
;
void
RunSyncLoop
(
framework
::
Executor
*
executor
,
framework
::
ProgramDesc
*
program
,
framework
::
Scope
*
recv_scope
,
framework
::
BlockDesc
*
prefetch_block
)
const
;
void
Stop
()
override
;
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
dev_place
)
const
override
;
void
RunImpl
(
const
framework
::
Scope
&
scope
,
const
platform
::
Place
&
dev_place
)
const
override
;
protected:
mutable
std
::
shared_ptr
<
detail
::
AsyncGRPCServer
>
rpc_service_
;
...
...
paddle/fluid/operators/send_recv_op_test.cc
浏览文件 @
7a993ee4
...
...
@@ -127,7 +127,7 @@ void StartServerNet(bool is_sparse) {
const
auto
&
root_block
=
program
.
Block
(
0
);
auto
*
optimize_block
=
program
.
AppendBlock
(
root_block
);
auto
*
prefetch_block
=
program
.
AppendBlock
(
root_block
);
// X for server side tensors, RX for received tens
e
rs, must be of same shape.
// X for server side tensors, RX for received tens
o
rs, must be of same shape.
AddOp
(
"sum"
,
{{
"X"
,
{
"x0"
,
"x1"
}}},
{{
"Out"
,
{
"Out"
}}},
{},
optimize_block
);
f
::
AttributeMap
attrs
;
...
...
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