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e3144393
编写于
3月 24, 2018
作者:
Y
Yu Yang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Extract Executors to indie modules
上级
c70b60dd
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
327 addition
and
214 deletion
+327
-214
paddle/fluid/framework/CMakeLists.txt
paddle/fluid/framework/CMakeLists.txt
+1
-2
paddle/fluid/framework/details/CMakeLists.txt
paddle/fluid/framework/details/CMakeLists.txt
+3
-0
paddle/fluid/framework/details/ssa_graph_executor.cc
paddle/fluid/framework/details/ssa_graph_executor.cc
+28
-0
paddle/fluid/framework/details/ssa_graph_executor.h
paddle/fluid/framework/details/ssa_graph_executor.h
+41
-0
paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
...le/fluid/framework/details/threaded_ssa_graph_executor.cc
+192
-0
paddle/fluid/framework/details/threaded_ssa_graph_executor.h
paddle/fluid/framework/details/threaded_ssa_graph_executor.h
+55
-0
paddle/fluid/framework/parallel_executor.cc
paddle/fluid/framework/parallel_executor.cc
+7
-212
未找到文件。
paddle/fluid/framework/CMakeLists.txt
浏览文件 @
e3144393
...
@@ -89,8 +89,7 @@ cc_library(executor SRCS executor.cc DEPS op_registry device_context scope
...
@@ -89,8 +89,7 @@ cc_library(executor SRCS executor.cc DEPS op_registry device_context scope
framework_proto backward glog lod_rank_table feed_fetch_method
)
framework_proto backward glog lod_rank_table feed_fetch_method
)
cc_library
(
parallel_executor SRCS parallel_executor.cc DEPS op_registry device_context scope
cc_library
(
parallel_executor SRCS parallel_executor.cc DEPS multi_devices_graph_builder threaded_ssa_graph_executor
)
backward glog lod_rank_table simple_threadpool multi_devices_graph_builder fetch_op_handle
)
cc_library
(
prune SRCS prune.cc DEPS framework_proto
)
cc_library
(
prune SRCS prune.cc DEPS framework_proto
)
cc_test
(
prune_test SRCS prune_test.cc DEPS op_info prune recurrent_op device_context
)
cc_test
(
prune_test SRCS prune_test.cc DEPS op_info prune recurrent_op device_context
)
...
...
paddle/fluid/framework/details/CMakeLists.txt
浏览文件 @
e3144393
...
@@ -10,3 +10,6 @@ cc_library(ssa_graph SRCS ssa_graph.cc DEPS var_handle op_handle_base)
...
@@ -10,3 +10,6 @@ cc_library(ssa_graph SRCS ssa_graph.cc DEPS var_handle op_handle_base)
cc_library
(
ssa_graph_builder SRCS ssa_graph_builder.cc DEPS ssa_graph
)
cc_library
(
ssa_graph_builder SRCS ssa_graph_builder.cc DEPS ssa_graph
)
cc_library
(
multi_devices_graph_builder SRCS multi_devices_graph_builder.cc DEPS ssa_graph_builder computation_op_handle
cc_library
(
multi_devices_graph_builder SRCS multi_devices_graph_builder.cc DEPS ssa_graph_builder computation_op_handle
nccl_all_reduce_op_handle scale_loss_grad_op_handle
)
nccl_all_reduce_op_handle scale_loss_grad_op_handle
)
cc_library
(
ssa_graph_executor SRCS ssa_graph_executor.cc DEPS ssa_graph
)
cc_library
(
threaded_ssa_graph_executor SRCS threaded_ssa_graph_executor.cc DEPS fetch_op_handle ssa_graph_executor scope
simple_threadpool device_context
)
paddle/fluid/framework/details/ssa_graph_executor.cc
0 → 100644
浏览文件 @
e3144393
// 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/ssa_graph_executor.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
SSAGraphExecutor
::
SSAGraphExecutor
(
std
::
unique_ptr
<
SSAGraph
>
&&
graph
)
:
graph_
(
std
::
move
(
graph
))
{}
SSAGraphExecutor
::~
SSAGraphExecutor
()
{}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/ssa_graph_executor.h
0 → 100644
浏览文件 @
e3144393
// 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 <memory>
#include "paddle/fluid/framework/details/ssa_graph.h"
#include "paddle/fluid/framework/feed_fetch_type.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
class
SSAGraphExecutor
{
DISABLE_COPY_AND_ASSIGN
(
SSAGraphExecutor
);
public:
// Steal graph inside
explicit
SSAGraphExecutor
(
std
::
unique_ptr
<
SSAGraph
>
&&
graph
);
virtual
~
SSAGraphExecutor
();
virtual
FeedFetchList
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
=
0
;
protected:
std
::
unique_ptr
<
SSAGraph
>
graph_
;
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
0 → 100644
浏览文件 @
e3144393
// 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/threaded_ssa_graph_executor.h"
#include "paddle/fluid/framework/details/fetch_op_handle.h"
#include "paddle/fluid/framework/scope.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
ThreadedSSAGraphExecutor
::
ThreadedSSAGraphExecutor
(
size_t
num_threads
,
bool
use_event
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
std
::
unique_ptr
<
SSAGraph
>
&&
graph
)
:
SSAGraphExecutor
(
std
::
move
(
graph
)),
pool_
(
num_threads
>=
2
?
new
::
ThreadPool
(
num_threads
)
:
nullptr
),
local_scopes_
(
local_scopes
),
places_
(
places
),
fetch_ctxs_
(
places
),
use_event_
(
use_event
)
{}
FeedFetchList
ThreadedSSAGraphExecutor
::
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
{
std
::
unordered_map
<
OpHandleBase
*
,
size_t
>
pending_ops
;
std
::
unordered_map
<
VarHandleBase
*
,
std
::
atomic
<
bool
>>
pending_vars
;
std
::
unordered_set
<
OpHandleBase
*>
ready_ops
;
auto
InsertPendingVar
=
[
&
pending_vars
](
VarHandleBase
&
var
)
{
pending_vars
[
&
var
]
=
var
.
generated_op_
==
nullptr
;
};
auto
InsertPendingOp
=
[
&
pending_ops
](
OpHandleBase
&
op_instance
)
{
pending_ops
.
insert
({
&
op_instance
,
op_instance
.
inputs_
.
size
()});
};
// Transform SSAGraph to pending_ops & pending_vars
for
(
auto
&
var_map
:
graph_
->
vars_
)
{
for
(
auto
&
name_pair
:
var_map
)
{
for
(
auto
&
version_pair
:
name_pair
.
second
)
{
InsertPendingVar
(
version_pair
.
second
);
}
}
}
for
(
auto
&
var
:
graph_
->
dep_vars_
)
{
InsertPendingVar
(
*
var
);
}
for
(
auto
&
op
:
graph_
->
ops_
)
{
if
(
op
->
inputs_
.
empty
())
{
// Special case, Op has no input.
ready_ops
.
insert
(
op
.
get
());
}
else
{
InsertPendingOp
(
*
op
);
}
}
// Step 2. Insert FetchOps
std
::
vector
<
FetchOpHandle
>
fetch_ops
;
std
::
vector
<
DummyVarHandle
>
dummy_vars
;
FeedFetchList
fetch_data
(
fetch_tensors
.
size
());
std
::
unordered_map
<
std
::
string
,
std
::
vector
<
VarHandleBase
*>>
fetched_vars
;
for
(
auto
&
fetch_var_name
:
fetch_tensors
)
{
for
(
auto
&
var_map
:
graph_
->
vars_
)
{
auto
it
=
var_map
.
find
(
fetch_var_name
);
if
(
it
!=
var_map
.
end
())
{
fetched_vars
[
fetch_var_name
].
push_back
(
&
it
->
second
.
rbegin
()
->
second
);
}
}
}
for
(
size_t
i
=
0
;
i
<
fetch_tensors
.
size
();
++
i
)
{
auto
&
var_name
=
fetch_tensors
[
i
];
auto
&
vars
=
fetched_vars
[
var_name
];
fetch_ops
.
emplace_back
(
&
fetch_data
,
i
,
&
local_scopes_
);
details
::
FetchOpHandle
*
op
=
&
fetch_ops
.
back
();
// FIXME: Use new device context
for
(
auto
&
p
:
places_
)
{
op
->
dev_ctx_
[
p
]
=
fetch_ctxs_
.
Get
(
p
);
}
for
(
auto
*
var
:
vars
)
{
op
->
AddInput
(
var
);
}
dummy_vars
.
emplace_back
();
auto
*
var
=
&
dummy_vars
.
back
();
var
->
generated_op_
=
nullptr
;
op
->
AddOutput
(
var
);
InsertPendingVar
(
*
var
);
InsertPendingOp
(
*
op
);
}
auto
run_all_ready_ops
=
[
&
]
{
for
(
auto
*
op
:
ready_ops
)
{
RunOp
(
pending_vars
,
op
);
}
ready_ops
.
clear
();
};
// Step 3. Execution
while
(
!
pending_vars
.
empty
())
{
// 1. Run All Ready ops
run_all_ready_ops
();
// 2. Find ready variable
VarHandleBase
*
ready_var
=
nullptr
;
for
(
auto
&
pair
:
pending_vars
)
{
if
(
pair
.
second
.
load
(
std
::
memory_order_acquire
))
{
ready_var
=
pair
.
first
;
break
;
}
}
// if there is no variable ready
if
(
ready_var
==
nullptr
)
{
// FIXME use conditional var instead of busy wait.
// if there is an exception, throw it
if
(
exception_
)
{
throw
*
exception_
;
}
// keep waiting the ready variables
continue
;
}
// 3. Remove the dependency of ready_var.
// Find the ready_ops after the ready_var.
pending_vars
.
erase
(
ready_var
);
for
(
auto
*
op
:
ready_var
->
pending_ops_
)
{
auto
&
deps
=
pending_ops
[
op
];
--
deps
;
if
(
deps
==
0
)
{
ready_ops
.
insert
(
op
);
}
}
// Keep loop until all vars are ready.
}
// Wait FetchOps.
for
(
auto
&
fetch_op
:
fetch_ops
)
{
fetch_op
.
WaitAndMergeCPUTensors
();
}
return
fetch_data
;
}
void
ThreadedSSAGraphExecutor
::
RunOp
(
std
::
unordered_map
<
VarHandleBase
*
,
std
::
atomic
<
bool
>>
&
pending_vars
,
details
::
OpHandleBase
*
op
)
{
std
::
vector
<
std
::
atomic
<
bool
>
*>
*
ready_buffer
=
new
std
::
vector
<
std
::
atomic
<
bool
>
*>
();
for
(
auto
*
var
:
op
->
outputs_
)
{
ready_buffer
->
emplace_back
(
&
pending_vars
[
var
]);
}
auto
op_run
=
[
ready_buffer
,
op
,
this
]
{
try
{
VLOG
(
10
)
<<
op
->
DebugString
();
op
->
Run
(
use_event_
);
for
(
auto
*
ready
:
*
ready_buffer
)
{
ready
->
store
(
true
,
std
::
memory_order_release
);
}
delete
ready_buffer
;
}
catch
(
platform
::
EnforceNotMet
ex
)
{
exception_
.
reset
(
new
platform
::
EnforceNotMet
(
ex
));
}
catch
(...)
{
LOG
(
FATAL
)
<<
"Unknown exception catched"
;
}
};
if
(
pool_
)
{
pool_
->
enqueue
(
op_run
);
}
else
{
op_run
();
}
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/threaded_ssa_graph_executor.h
0 → 100644
浏览文件 @
e3144393
// 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 "ThreadPool.h" // ThreadPool in thrird party
#include "paddle/fluid/framework/details/ssa_graph_executor.h"
namespace
paddle
{
namespace
framework
{
class
Scope
;
namespace
details
{
class
ThreadedSSAGraphExecutor
:
public
SSAGraphExecutor
{
public:
ThreadedSSAGraphExecutor
(
size_t
num_threads
,
bool
use_event
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
std
::
unique_ptr
<
SSAGraph
>
&&
graph
);
// Run a SSAGraph by a thread pool
// Use topological sort algorithm
FeedFetchList
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
override
;
~
ThreadedSSAGraphExecutor
()
{}
private:
void
RunOp
(
std
::
unordered_map
<
VarHandleBase
*
,
std
::
atomic
<
bool
>>
&
pending_vars
,
details
::
OpHandleBase
*
op
);
private:
std
::
unique_ptr
<::
ThreadPool
>
pool_
;
std
::
vector
<
Scope
*>
local_scopes_
;
std
::
vector
<
platform
::
Place
>
places_
;
platform
::
DeviceContextPool
fetch_ctxs_
;
const
bool
use_event_
;
std
::
unique_ptr
<
platform
::
EnforceNotMet
>
exception_
;
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/parallel_executor.cc
浏览文件 @
e3144393
...
@@ -13,221 +13,17 @@ See the License for the specific language governing permissions and
...
@@ -13,221 +13,17 @@ See the License for the specific language governing permissions and
limitations under the License. */
limitations under the License. */
#include "paddle/fluid/framework/parallel_executor.h"
#include "paddle/fluid/framework/parallel_executor.h"
#include "ThreadPool.h"
#include "ThreadPool.h"
#include "lod_tensor.h"
#include "op_registry.h"
#include "paddle/fluid/framework/details/fetch_op_handle.h"
#include "paddle/fluid/framework/details/multi_devices_graph_builder.h"
#include "paddle/fluid/framework/details/ssa_graph.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/framework/details/multi_devices_graph_builder.h"
#include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
namespace
paddle
{
namespace
paddle
{
namespace
framework
{
namespace
framework
{
using
details
::
DummyVarHandle
;
using
details
::
FetchOpHandle
;
using
details
::
OpHandleBase
;
using
details
::
SSAGraph
;
using
details
::
VarHandleBase
;
class
SSAGraphExecutor
{
DISABLE_COPY_AND_ASSIGN
(
SSAGraphExecutor
);
public:
// Steal graph inside
explicit
SSAGraphExecutor
(
std
::
unique_ptr
<
SSAGraph
>
&&
graph
)
:
graph_
(
std
::
move
(
graph
))
{}
virtual
~
SSAGraphExecutor
()
{}
virtual
FeedFetchList
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
=
0
;
protected:
std
::
unique_ptr
<
SSAGraph
>
graph_
;
};
class
ThreadedSSAGraphExecutor
:
public
SSAGraphExecutor
{
public:
ThreadedSSAGraphExecutor
(
size_t
num_threads
,
bool
use_event
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
std
::
unique_ptr
<
SSAGraph
>
&&
graph
)
:
SSAGraphExecutor
(
std
::
move
(
graph
)),
pool_
(
num_threads
>=
2
?
new
::
ThreadPool
(
num_threads
)
:
nullptr
),
local_scopes_
(
local_scopes
),
places_
(
places
),
fetch_ctxs_
(
places
),
use_event_
(
use_event
)
{}
// Run a SSAGraph by a thread pool
// Use topological sort algorithm
FeedFetchList
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
override
{
std
::
unordered_map
<
OpHandleBase
*
,
size_t
>
pending_ops
;
std
::
unordered_map
<
VarHandleBase
*
,
std
::
atomic
<
bool
>>
pending_vars
;
std
::
unordered_set
<
OpHandleBase
*>
ready_ops
;
auto
InsertPendingVar
=
[
&
pending_vars
](
VarHandleBase
&
var
)
{
pending_vars
[
&
var
]
=
var
.
generated_op_
==
nullptr
;
};
auto
InsertPendingOp
=
[
&
pending_ops
](
OpHandleBase
&
op_instance
)
{
pending_ops
.
insert
({
&
op_instance
,
op_instance
.
inputs_
.
size
()});
};
// Transform SSAGraph to pending_ops & pending_vars
for
(
auto
&
var_map
:
graph_
->
vars_
)
{
for
(
auto
&
name_pair
:
var_map
)
{
for
(
auto
&
version_pair
:
name_pair
.
second
)
{
InsertPendingVar
(
version_pair
.
second
);
}
}
}
for
(
auto
&
var
:
graph_
->
dep_vars_
)
{
InsertPendingVar
(
*
var
);
}
for
(
auto
&
op
:
graph_
->
ops_
)
{
if
(
op
->
inputs_
.
empty
())
{
// Special case, Op has no input.
ready_ops
.
insert
(
op
.
get
());
}
else
{
InsertPendingOp
(
*
op
);
}
}
// Step 2. Insert FetchOps
std
::
vector
<
FetchOpHandle
>
fetch_ops
;
std
::
vector
<
DummyVarHandle
>
dummy_vars
;
FeedFetchList
fetch_data
(
fetch_tensors
.
size
());
std
::
unordered_map
<
std
::
string
,
std
::
vector
<
VarHandleBase
*>>
fetched_vars
;
for
(
auto
&
fetch_var_name
:
fetch_tensors
)
{
for
(
auto
&
var_map
:
graph_
->
vars_
)
{
auto
it
=
var_map
.
find
(
fetch_var_name
);
if
(
it
!=
var_map
.
end
())
{
fetched_vars
[
fetch_var_name
].
push_back
(
&
it
->
second
.
rbegin
()
->
second
);
}
}
}
for
(
size_t
i
=
0
;
i
<
fetch_tensors
.
size
();
++
i
)
{
auto
&
var_name
=
fetch_tensors
[
i
];
auto
&
vars
=
fetched_vars
[
var_name
];
fetch_ops
.
emplace_back
(
&
fetch_data
,
i
,
&
local_scopes_
);
details
::
FetchOpHandle
*
op
=
&
fetch_ops
.
back
();
// FIXME: Use new device context
for
(
auto
&
p
:
places_
)
{
op
->
dev_ctx_
[
p
]
=
fetch_ctxs_
.
Get
(
p
);
}
for
(
auto
*
var
:
vars
)
{
op
->
AddInput
(
var
);
}
dummy_vars
.
emplace_back
();
auto
*
var
=
&
dummy_vars
.
back
();
var
->
generated_op_
=
nullptr
;
op
->
AddOutput
(
var
);
InsertPendingVar
(
*
var
);
InsertPendingOp
(
*
op
);
}
auto
run_all_ready_ops
=
[
&
]
{
for
(
auto
*
op
:
ready_ops
)
{
RunOp
(
pending_vars
,
op
);
}
ready_ops
.
clear
();
};
// Step 3. Execution
while
(
!
pending_vars
.
empty
())
{
// 1. Run All Ready ops
run_all_ready_ops
();
// 2. Find ready variable
VarHandleBase
*
ready_var
=
nullptr
;
for
(
auto
&
pair
:
pending_vars
)
{
if
(
pair
.
second
.
load
(
std
::
memory_order_acquire
))
{
ready_var
=
pair
.
first
;
break
;
}
}
// if there is no variable ready
if
(
ready_var
==
nullptr
)
{
// FIXME use conditional var instead of busy wait.
// if there is an exception, throw it
if
(
exception_
)
{
throw
*
exception_
;
}
// keep waiting the ready variables
continue
;
}
// 3. Remove the dependency of ready_var.
// Find the ready_ops after the ready_var.
pending_vars
.
erase
(
ready_var
);
for
(
auto
*
op
:
ready_var
->
pending_ops_
)
{
auto
&
deps
=
pending_ops
[
op
];
--
deps
;
if
(
deps
==
0
)
{
ready_ops
.
insert
(
op
);
}
}
// Keep loop until all vars are ready.
}
// Wait FetchOps.
for
(
auto
&
fetch_op
:
fetch_ops
)
{
fetch_op
.
WaitAndMergeCPUTensors
();
}
return
fetch_data
;
}
~
ThreadedSSAGraphExecutor
()
{}
private:
void
RunOp
(
std
::
unordered_map
<
VarHandleBase
*
,
std
::
atomic
<
bool
>>
&
pending_vars
,
details
::
OpHandleBase
*
op
)
{
std
::
vector
<
std
::
atomic
<
bool
>
*>
*
ready_buffer
=
new
std
::
vector
<
std
::
atomic
<
bool
>
*>
();
for
(
auto
*
var
:
op
->
outputs_
)
{
ready_buffer
->
emplace_back
(
&
pending_vars
[
var
]);
}
auto
op_run
=
[
ready_buffer
,
op
,
this
]
{
try
{
VLOG
(
10
)
<<
op
->
DebugString
();
op
->
Run
(
use_event_
);
for
(
auto
*
ready
:
*
ready_buffer
)
{
ready
->
store
(
true
,
std
::
memory_order_release
);
}
delete
ready_buffer
;
}
catch
(
platform
::
EnforceNotMet
ex
)
{
exception_
.
reset
(
new
platform
::
EnforceNotMet
(
ex
));
}
catch
(...)
{
LOG
(
FATAL
)
<<
"Unknown exception catched"
;
}
};
if
(
pool_
)
{
pool_
->
enqueue
(
op_run
);
}
else
{
op_run
();
}
}
private:
std
::
unique_ptr
<::
ThreadPool
>
pool_
;
std
::
vector
<
Scope
*>
local_scopes_
;
std
::
vector
<
platform
::
Place
>
places_
;
platform
::
DeviceContextPool
fetch_ctxs_
;
const
bool
use_event_
;
std
::
unique_ptr
<
platform
::
EnforceNotMet
>
exception_
;
};
class
ParallelExecutorPrivate
{
class
ParallelExecutorPrivate
{
public:
public:
explicit
ParallelExecutorPrivate
(
const
std
::
vector
<
platform
::
Place
>
&
places
)
explicit
ParallelExecutorPrivate
(
const
std
::
vector
<
platform
::
Place
>
&
places
)
...
@@ -239,8 +35,7 @@ class ParallelExecutorPrivate {
...
@@ -239,8 +35,7 @@ class ParallelExecutorPrivate {
Scope
*
global_scope_
;
Scope
*
global_scope_
;
std
::
unique_ptr
<
platform
::
NCCLContextMap
>
nccl_ctxs_
;
std
::
unique_ptr
<
platform
::
NCCLContextMap
>
nccl_ctxs_
;
std
::
unique_ptr
<
details
::
SSAGraphExecutor
>
executor_
;
std
::
unique_ptr
<
SSAGraphExecutor
>
executor_
;
};
};
ParallelExecutor
::
ParallelExecutor
(
ParallelExecutor
::
ParallelExecutor
(
...
@@ -274,7 +69,7 @@ ParallelExecutor::ParallelExecutor(
...
@@ -274,7 +69,7 @@ ParallelExecutor::ParallelExecutor(
member_
->
nccl_ctxs_
.
get
());
member_
->
nccl_ctxs_
.
get
());
auto
graph
=
builder
.
Build
(
main_program
);
auto
graph
=
builder
.
Build
(
main_program
);
member_
->
executor_
.
reset
(
new
ThreadedSSAGraphExecutor
(
member_
->
executor_
.
reset
(
new
details
::
ThreadedSSAGraphExecutor
(
num_threads
,
true
,
member_
->
local_scopes_
,
places
,
std
::
move
(
graph
)));
num_threads
,
true
,
member_
->
local_scopes_
,
places
,
std
::
move
(
graph
)));
// Step 3. Create vars in each scope;
// Step 3. Create vars in each scope;
...
...
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