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d49763a8
编写于
8月 14, 2018
作者:
Y
yuyang18
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5 changed file
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242 addition
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0 deletion
+242
-0
paddle/fluid/framework/details/CMakeLists.txt
paddle/fluid/framework/details/CMakeLists.txt
+2
-0
paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.cc
...uid/framework/details/fast_threaded_ssa_graph_executor.cc
+166
-0
paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.h
...luid/framework/details/fast_threaded_ssa_graph_executor.h
+62
-0
paddle/fluid/framework/details/op_handle_base.cc
paddle/fluid/framework/details/op_handle_base.cc
+10
-0
paddle/fluid/framework/details/op_handle_base.h
paddle/fluid/framework/details/op_handle_base.h
+2
-0
未找到文件。
paddle/fluid/framework/details/CMakeLists.txt
浏览文件 @
d49763a8
...
...
@@ -42,3 +42,5 @@ cc_test(gather_op_test SRCS gather_op_handle_test.cc DEPS var_handle op_handle_b
cc_library
(
scope_buffered_ssa_graph_executor SRCS scope_buffered_ssa_graph_executor.cc DEPS ssa_graph_executor
)
#cc_test(reduce_op_handle_test SRCS reduce_op_handle_test.cc DEPS var_handle op_handle_base scope ddim memory
# device_context reduce_op_handle )
cc_library
(
fast_threaded_ssa_graph_executor SRCS fast_threaded_ssa_graph_executor.cc
DEPS fetch_op_handle ssa_graph_executor scope simple_threadpool device_context
)
paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.cc
0 → 100644
浏览文件 @
d49763a8
// 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.
#include "paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.h"
#include <string>
#include <vector>
#include "paddle/fluid/framework/details/fetch_op_handle.h"
#include "paddle/fluid/framework/details/multi_devices_helper.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
FastThreadedSSAGraphExecutor
::
FastThreadedSSAGraphExecutor
(
const
ExecutionStrategy
&
strategy
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
std
::
unique_ptr
<
ir
::
Graph
>
&&
graph
)
:
strategy_
(
strategy
),
local_scopes_
(
local_scopes
),
places_
(
places
),
graph_
(
std
::
move
(
graph
)),
pool_
(
strategy
.
num_threads_
+
1
),
// add one more thread for generate op_deps
fetch_ctxs_
(
places
)
{
auto
&
ops
=
graph_
->
Get
<
details
::
GraphOps
>
(
"ops"
);
for
(
auto
&
op
:
ops
)
{
int
dep
=
static_cast
<
int
>
(
op
->
NotReadyInputSize
());
op_deps_
.
emplace
(
op
.
get
(),
dep
);
if
(
dep
==
0
)
{
bootstrap_ops_
.
emplace_back
(
op
.
get
());
}
}
PrepareAtomicOpDeps
();
}
FeedFetchList
FastThreadedSSAGraphExecutor
::
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
{
std
::
unique_ptr
<
std
::
unordered_map
<
OpHandleBase
*
,
std
::
atomic
<
int
>>>
op_deps
=
atomic_op_deps_
.
get
();
PrepareAtomicOpDeps
();
paddle
::
framework
::
FeedFetchList
fetches
;
fetches
.
resize
(
fetch_tensors
.
size
());
std
::
unordered_map
<
std
::
string
,
std
::
vector
<
VarHandleBase
*>>
fetched_vars
;
std
::
vector
<
std
::
unique_ptr
<
ir
::
Node
>>
fetch_nodes
;
std
::
vector
<
std
::
unique_ptr
<
FetchOpHandle
>>
fetch_ops
;
for
(
auto
&
fetch_var_name
:
fetch_tensors
)
{
for
(
auto
&
var_map
:
graph_
->
Get
<
details
::
GraphVars
>
(
"vars"
))
{
auto
it
=
var_map
.
find
(
fetch_var_name
);
if
(
it
!=
var_map
.
end
())
{
fetched_vars
[
fetch_var_name
].
push_back
(
it
->
second
.
rbegin
()
->
get
());
}
}
}
for
(
size_t
i
=
0
;
i
<
fetch_tensors
.
size
();
++
i
)
{
auto
&
var_name
=
fetch_tensors
[
i
];
auto
fetched_var_it
=
fetched_vars
.
find
(
var_name
);
PADDLE_ENFORCE
(
fetched_var_it
!=
fetched_vars
.
end
(),
"Cannot find fetched variable.(Perhaps the main_program "
"is not set to ParallelExecutor)"
);
auto
&
vars
=
fetched_var_it
->
second
;
fetch_nodes
.
emplace_back
(
new
ir
::
Node
(
"fetch"
,
ir
::
Node
::
Type
::
kOperation
));
auto
*
op
=
new
FetchOpHandle
(
fetch_nodes
.
back
().
get
(),
&
fetches
,
i
,
&
local_scopes_
);
fetch_ops
.
emplace_back
(
op
);
for
(
auto
&
p
:
places_
)
{
op
->
SetDeviceContext
(
p
,
fetch_ctxs_
.
Get
(
p
));
}
for
(
auto
*
var
:
vars
)
{
op
->
AddInput
(
var
);
}
(
*
op_deps
)[
op
]
=
static_cast
<
int
>
(
op
->
NotReadyInputSize
());
}
size_t
num_complete
=
0
;
remaining_
=
0
;
BlockingQueue
<
size_t
>
complete_q
;
for
(
auto
op
:
bootstrap_ops_
)
{
RunOpAsync
(
op_deps
.
get
(),
op
,
&
complete_q
);
}
while
(
num_complete
!=
op_deps
->
size
())
{
size_t
num_comp
=
complete_q
.
Pop
();
if
(
num_comp
==
-
1UL
)
{
int
remaining
=
remaining_
;
for
(
int
i
=
0
;
i
<
remaining
;
++
i
)
{
complete_q
.
Pop
();
}
LOG
(
FATAL
)
<<
"On exception thrown, not implemented"
;
}
num_complete
+=
num_comp
;
}
// Wait FetchOps.
if
(
!
fetch_ops
.
empty
())
{
fetch_ops
.
clear
();
}
return
fetches
;
}
void
FastThreadedSSAGraphExecutor
::
RunOpAsync
(
std
::
unordered_map
<
OpHandleBase
*
,
std
::
atomic
<
int
>>
*
op_deps
,
OpHandleBase
*
op
,
BlockingQueue
<
size_t
>
*
complete_q
)
{
++
remaining_
;
this
->
pool_
.
enqueue
([
=
]
{
OpHandleBase
*
op_to_run
=
op
;
size_t
complete
=
0
;
while
(
op_to_run
!=
nullptr
)
{
try
{
op_to_run
->
Run
(
strategy_
.
use_cuda_
);
++
complete
;
}
catch
(...)
{
--
remaining_
;
complete_q
->
Push
(
-
1UL
);
return
;
}
auto
&
outputs
=
op_to_run
->
Outputs
();
op_to_run
=
nullptr
;
for
(
auto
&
output
:
outputs
)
{
for
(
auto
&
pending_op
:
output
->
PendingOps
())
{
std
::
atomic
<
int
>
&
deps
=
op_deps
->
at
(
pending_op
);
if
(
deps
.
fetch_sub
(
1
)
==
1
)
{
// pending_op ready
if
(
op_to_run
==
nullptr
)
{
op_to_run
=
pending_op
;
}
else
{
this
->
RunOpAsync
(
op_deps
,
pending_op
,
complete_q
);
}
}
}
}
}
--
remaining_
;
complete_q
->
Push
(
complete
);
});
}
void
FastThreadedSSAGraphExecutor
::
PrepareAtomicOpDeps
()
{
atomic_op_deps_
=
pool_
.
enqueue
([
&
]
{
std
::
unordered_map
<
OpHandleBase
*
,
std
::
atomic
<
int
>>
*
op_deps
=
new
std
::
unordered_map
<
OpHandleBase
*
,
std
::
atomic
<
int
>>
;
for
(
auto
&
pair
:
op_deps_
)
{
(
*
op_deps
)[
pair
.
first
]
=
pair
.
second
;
}
return
std
::
unique_ptr
<
std
::
unordered_map
<
OpHandleBase
*
,
std
::
atomic
<
int
>>>
(
op_deps
);
});
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.h
0 → 100644
浏览文件 @
d49763a8
// 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.
#pragma once
#include <string>
#include <vector>
#include "ThreadPool.h"
#include "paddle/fluid/framework/blocking_queue.h"
#include "paddle/fluid/framework/details/exception_holder.h"
#include "paddle/fluid/framework/details/execution_strategy.h"
#include "paddle/fluid/framework/details/ssa_graph_executor.h"
namespace
paddle
{
namespace
framework
{
class
Scope
;
namespace
details
{
class
OpHandleBase
;
class
FastThreadedSSAGraphExecutor
:
public
SSAGraphExecutor
{
public:
FastThreadedSSAGraphExecutor
(
const
ExecutionStrategy
&
strategy
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
std
::
unique_ptr
<
ir
::
Graph
>
&&
graph
);
FeedFetchList
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
override
;
private:
ExecutionStrategy
strategy_
;
std
::
vector
<
Scope
*>
local_scopes_
;
std
::
vector
<
platform
::
Place
>
places_
;
std
::
unique_ptr
<
ir
::
Graph
>
graph_
;
std
::
unordered_map
<
OpHandleBase
*
,
int
>
op_deps_
;
std
::
vector
<
OpHandleBase
*>
bootstrap_ops_
;
::
ThreadPool
pool_
;
platform
::
DeviceContextPool
fetch_ctxs_
;
std
::
atomic
<
int
>
remaining_
;
void
RunOpAsync
(
std
::
unordered_map
<
OpHandleBase
*
,
std
::
atomic
<
int
>>
*
op_deps
,
OpHandleBase
*
op
,
BlockingQueue
<
size_t
>
*
complete_q
);
void
PrepareAtomicOpDeps
();
std
::
future
<
std
::
unique_ptr
<
std
::
unordered_map
<
OpHandleBase
*
,
std
::
atomic
<
int
>>>>
atomic_op_deps_
;
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/op_handle_base.cc
浏览文件 @
d49763a8
...
...
@@ -158,6 +158,16 @@ void OpHandleBase::RunAndRecordEvent(platform::Place p,
#endif
}
size_t
OpHandleBase
::
NotReadyInputSize
()
const
{
std
::
unordered_set
<
VarHandleBase
*>
res
;
for
(
auto
*
var
:
inputs_
)
{
if
(
var
->
GeneratedOp
()
!=
nullptr
)
{
res
.
emplace
(
var
);
}
}
return
res
.
size
();
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/op_handle_base.h
浏览文件 @
d49763a8
...
...
@@ -81,6 +81,8 @@ class OpHandleBase {
return
res
.
size
();
}
size_t
NotReadyInputSize
()
const
;
const
std
::
vector
<
VarHandleBase
*>
&
Outputs
()
const
{
return
outputs_
;
}
size_t
NoDummyInputSize
()
const
;
...
...
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