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9cb8f503
编写于
3月 19, 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
Complete fetch op
上级
254d7ff4
变更
6
隐藏空白更改
内联
并排
Showing
6 changed file
with
124 addition
and
22 deletion
+124
-22
paddle/fluid/framework/CMakeLists.txt
paddle/fluid/framework/CMakeLists.txt
+1
-1
paddle/fluid/framework/parallel_executor.cc
paddle/fluid/framework/parallel_executor.cc
+105
-18
paddle/fluid/framework/parallel_executor.h
paddle/fluid/framework/parallel_executor.h
+2
-1
paddle/fluid/operators/math/concat.h
paddle/fluid/operators/math/concat.h
+1
-0
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+1
-1
python/paddle/fluid/tests/unittests/test_parallel_executor.py
...on/paddle/fluid/tests/unittests/test_parallel_executor.py
+14
-1
未找到文件。
paddle/fluid/framework/CMakeLists.txt
浏览文件 @
9cb8f503
...
...
@@ -87,7 +87,7 @@ cc_library(feed_fetch_method SRCS feed_fetch_method.cc DEPS lod_tensor scope glo
cc_library
(
executor SRCS executor.cc DEPS op_registry device_context scope
framework_proto backward glog lod_rank_table feed_fetch_method
)
cc_library
(
parallel_executor SRCS parallel_executor.cc DEPS op_registry device_context scope
framework_proto backward glog lod_rank_table feed_fetch_method executor simple_threadpool
)
framework_proto backward glog lod_rank_table feed_fetch_method executor simple_threadpool
concat
)
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
)
...
...
paddle/fluid/framework/parallel_executor.cc
浏览文件 @
9cb8f503
...
...
@@ -16,7 +16,9 @@ limitations under the License. */
#include "ThreadPool.h"
#include "executor.h"
#include "lod_tensor.h"
#include "lod_tensor_array.h"
#include "op_registry.h"
#include "paddle/fluid/operators/math/concat.h"
namespace
paddle
{
namespace
framework
{
...
...
@@ -34,7 +36,7 @@ struct VarHandleBase {
virtual
std
::
string
DebugString
()
const
=
0
;
OpHandle
*
generated_op_
;
std
::
vector
<
OpHandle
*>
pending_ops_
;
std
::
unordered_set
<
OpHandle
*>
pending_ops_
;
};
struct
VarHandle
:
public
VarHandleBase
{
...
...
@@ -93,7 +95,6 @@ struct ComputationOpHandle : public OpHandle {
void
Run
()
override
{
// Wait other op if necessary
LOG
(
INFO
)
<<
"Run "
<<
this
<<
" "
<<
DebugString
();
auto
*
cur_ctx
=
dev_ctx_
[
place_
];
for
(
auto
*
in
:
inputs_
)
{
if
(
in
->
generated_op_
&&
in
->
generated_op_
->
dev_ctx_
[
place_
]
!=
cur_ctx
)
{
...
...
@@ -102,7 +103,6 @@ struct ComputationOpHandle : public OpHandle {
}
op_
->
Run
(
*
scope_
,
place_
);
LOG
(
INFO
)
<<
"Done "
<<
this
;
}
void
Wait
(
platform
::
DeviceContext
*
waited_dev
)
override
{
...
...
@@ -122,8 +122,6 @@ struct ScaleLossGradOpHandle : public OpHandle {
place_
(
place
)
{}
void
Run
()
override
{
LOG
(
INFO
)
<<
"Run Scale Loss Grad"
;
std
::
string
var_name
=
static_cast
<
VarHandle
*>
(
this
->
outputs_
[
0
])
->
name_
;
float
*
tmp
=
scope_
->
FindVar
(
var_name
)
...
...
@@ -146,6 +144,64 @@ struct ScaleLossGradOpHandle : public OpHandle {
}
};
struct
FetchedData
{
public:
std
::
vector
<
framework
::
LoDTensor
>
tensors_
;
explicit
FetchedData
(
size_t
num_fetched
)
{
tensors_
.
resize
(
num_fetched
);
}
};
struct
FetchOpHandle
:
public
OpHandle
{
std
::
shared_ptr
<
FetchedData
>
data_
;
size_t
offset_
;
std
::
vector
<
Scope
*>
*
local_scopes_
;
std
::
vector
<
LoDTensor
>
tensors_
;
~
FetchOpHandle
()
{
for
(
auto
*
input_var
:
inputs_
)
{
input_var
->
pending_ops_
.
erase
(
this
);
}
for
(
auto
&
pair
:
dev_ctx_
)
{
pair
.
second
->
Wait
();
}
// Lazily merge tensors. Will faster code.
MergeTensors
();
}
void
Run
()
override
{
tensors_
.
resize
(
inputs_
.
size
());
auto
*
var
=
static_cast
<
VarHandle
*>
(
inputs_
[
0
]);
auto
&
var_name
=
var
->
name_
;
platform
::
CPUPlace
cpu
;
auto
&
scopes
=
*
local_scopes_
;
for
(
size_t
i
=
0
;
i
<
scopes
.
size
();
++
i
)
{
auto
&
scope
=
scopes
[
i
];
auto
&
t
=
scope
->
FindVar
(
var_name
)
->
Get
<
framework
::
LoDTensor
>
();
if
(
platform
::
is_gpu_place
(
var
->
place_
))
{
TensorCopy
(
t
,
cpu
,
*
dev_ctx_
[
t
.
place
()],
&
tensors_
[
i
]);
}
else
{
tensors_
[
i
].
ShareDataWith
(
t
);
tensors_
[
i
].
set_lod
(
t
.
lod
());
}
}
}
void
Wait
(
platform
::
DeviceContext
*
waited_dev
)
override
{
PADDLE_THROW
(
"Nobody should wait FetchOp. Unexpceted Error"
);
}
private:
void
MergeTensors
()
const
{
std
::
vector
<
const
LoDTensor
*>
tensors_ptr
;
for
(
auto
&
t
:
tensors_
)
{
tensors_ptr
.
emplace_back
(
&
t
);
}
data_
->
tensors_
[
offset_
].
MergeLoDTensor
(
tensors_ptr
,
platform
::
CPUPlace
());
}
};
class
ParallelExecutorPrivate
{
public:
explicit
ParallelExecutorPrivate
(
size_t
num_threads
=
12
)
...
...
@@ -154,6 +210,7 @@ class ParallelExecutorPrivate {
std
::
vector
<
platform
::
Place
>
places_
;
std
::
vector
<
Scope
*>
local_scopes_
;
Scope
*
global_scope_
;
#ifdef PADDLE_WITH_CUDA
struct
NCCLContext
{
...
...
@@ -297,7 +354,7 @@ ParallelExecutor::ParallelExecutor(
const
std
::
string
&
loss_var_name
,
Scope
*
scope
)
:
member_
(
new
ParallelExecutorPrivate
())
{
member_
->
places_
=
places
;
member_
->
global_scope_
=
scope
;
// Step 1. RunStartupProgram and Bcast the params to devs.
Executor
exe
(
places
[
0
]);
exe
.
Run
(
startup_program
,
scope
,
0
);
...
...
@@ -308,9 +365,9 @@ ParallelExecutor::ParallelExecutor(
member_
->
main_place_
=
places
[
0
];
// Bcast Parameters to all GPUs
BuildNCCLCommunicator
();
if
(
platform
::
is_gpu_place
(
member_
->
main_place_
)
&&
member_
->
local_scopes_
.
size
()
!=
1
)
{
// Is CUDA
BuildNCCLCommunicator
();
BCastParamsToGPUs
(
startup_program
);
}
// Startup Program has been run. All local scopes has correct parameters.
...
...
@@ -365,7 +422,7 @@ void ParallelExecutor::ConstructDependencyGraph(
for
(
auto
&
each_var_name
:
var_names
)
{
VarHandle
*
var
=
GetVarHandle
(
each_var_name
,
p
);
op_handle
->
inputs_
.
emplace_back
(
var
);
var
->
pending_ops_
.
emplace
_back
(
op_handle
);
var
->
pending_ops_
.
emplace
(
op_handle
);
}
var_names
=
op
->
OutputArgumentNames
();
...
...
@@ -390,7 +447,6 @@ void ParallelExecutor::ConstructDependencyGraph(
GenerateVar
(
op_handle
,
loss_var_name
+
"@GRAD"
,
p
);
change_forward
=
true
;
LOG
(
INFO
)
<<
"Scale Loss "
<<
op_handle
->
DebugString
();
}
}
}
...
...
@@ -416,7 +472,7 @@ void ParallelExecutor::ConstructDependencyGraph(
}
auto
*
prev_grad
=
&
vars
[
vars
.
size
()
-
1
];
op_handle
->
inputs_
.
emplace_back
(
prev_grad
);
prev_grad
->
pending_ops_
.
emplace
_back
(
op_handle
);
prev_grad
->
pending_ops_
.
emplace
(
op_handle
);
auto
&
var
=
vars
[
vars
.
size
()];
var
.
place_
=
p
;
var
.
generated_op_
=
op_handle
;
...
...
@@ -463,10 +519,6 @@ void ParallelExecutor::PolishGraphToSupportDataHarzaeds() const {
continue
;
}
LOG
(
INFO
)
<<
"Link "
<<
it_new
->
second
.
DebugString
()
<<
" From "
<<
it_old
->
second
.
version_
<<
" To "
<<
it_new
->
second
.
version_
;
for
(
auto
*
read_op
:
read_ops
)
{
// Manually add a dependency var from read_op to write_op;
if
(
read_op
==
write_op
)
{
...
...
@@ -479,7 +531,7 @@ void ParallelExecutor::PolishGraphToSupportDataHarzaeds() const {
dep_var
->
generated_op_
=
read_op
;
read_op
->
outputs_
.
emplace_back
(
dep_var
);
dep_var
->
pending_ops_
.
emplace
_back
(
write_op
);
dep_var
->
pending_ops_
.
emplace
(
write_op
);
write_op
->
inputs_
.
emplace_back
(
dep_var
);
member_
->
dep_vars_
.
emplace
(
dep_var
);
}
...
...
@@ -572,8 +624,9 @@ void ParallelExecutor::BuildNCCLCommunicator() const {
#endif
}
std
::
vector
<
LoDTensor
>
ParallelExecutor
::
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
)
{
void
ParallelExecutor
::
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
,
const
std
::
string
&
fetched_var_name
)
{
auto
fetched_data
=
std
::
make_shared
<
FetchedData
>
(
fetch_tensors
.
size
());
// Version --> VarHandle
member_
->
exception_
.
reset
();
std
::
unordered_map
<
VarHandleBase
*
,
bool
>
pending_vars
;
...
...
@@ -602,6 +655,38 @@ std::vector<LoDTensor> ParallelExecutor::Run(
}
}
std
::
unordered_map
<
std
::
string
,
std
::
vector
<
VarHandleBase
*>>
fetched_vars
;
for
(
auto
&
fetch_var_name
:
fetch_tensors
)
{
for
(
auto
&
pair
:
member_
->
vars_
)
{
auto
it
=
pair
.
second
.
find
(
fetch_var_name
);
if
(
it
!=
pair
.
second
.
end
())
{
fetched_vars
[
fetch_var_name
].
push_back
(
&
it
->
second
.
rbegin
()
->
second
);
}
}
}
std
::
vector
<
FetchOpHandle
>
fetch_ops
;
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
();
FetchOpHandle
*
op
=
&
fetch_ops
.
back
();
op
->
data_
=
fetched_data
;
op
->
offset_
=
i
;
op
->
local_scopes_
=
&
member_
->
local_scopes_
;
for
(
auto
&
p
:
member_
->
places_
)
{
op
->
dev_ctx_
[
p
]
=
this
->
member_
->
GetNCCLCtx
(
p
).
ctx_
.
get
();
}
for
(
auto
*
var
:
vars
)
{
var
->
pending_ops_
.
emplace
(
op
);
op
->
inputs_
.
emplace_back
(
var
);
}
pending_ops
.
insert
({
op
,
op
->
inputs_
.
size
()});
}
for
(
auto
*
op
:
to_run
)
{
RunOp
(
pending_vars
,
op
);
}
...
...
@@ -642,7 +727,9 @@ std::vector<LoDTensor> ParallelExecutor::Run(
RunOp
(
pending_vars
,
op
);
}
}
return
std
::
vector
<
LoDTensor
>
();
fetch_ops
.
clear
();
*
member_
->
global_scope_
->
Var
(
fetched_var_name
)
->
GetMutable
<
LoDTensorArray
>
()
=
fetched_data
->
tensors_
;
}
void
ParallelExecutor
::
RunOp
(
...
...
paddle/fluid/framework/parallel_executor.h
浏览文件 @
9cb8f503
...
...
@@ -40,7 +40,8 @@ class ParallelExecutor {
const
ProgramDesc
&
main_program
,
const
std
::
string
&
loss_var_name
,
Scope
*
scope
);
std
::
vector
<
LoDTensor
>
Run
(
const
std
::
vector
<
std
::
string
>&
fetch_tensors
);
void
Run
(
const
std
::
vector
<
std
::
string
>&
fetch_tensors
,
const
std
::
string
&
fetched_var_name
=
"fetched_var"
);
private:
ParallelExecutorPrivate
*
member_
;
...
...
paddle/fluid/operators/math/concat.h
浏览文件 @
9cb8f503
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/framework/tensor.h"
namespace
paddle
{
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
9cb8f503
...
...
@@ -508,7 +508,7 @@ All parameter, weight, gradient are variables in Paddle.
new
(
&
self
)
ParallelExecutor
(
places
,
params
,
startup_program
,
main_program
,
loss_var_name
,
scope
);
})
.
def
(
"run"
,
[](
ParallelExecutor
&
self
)
{
self
.
Run
({});
}
);
.
def
(
"run"
,
&
ParallelExecutor
::
Run
);
BindRecordIOWriter
(
m
);
return
m
.
ptr
();
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor.py
浏览文件 @
9cb8f503
...
...
@@ -16,6 +16,7 @@ import unittest
import
paddle.fluid
as
fluid
import
paddle.v2
as
paddle
import
paddle.v2.dataset.mnist
as
mnist
import
numpy
class
ParallelExecutor
(
unittest
.
TestCase
):
...
...
@@ -66,4 +67,16 @@ class ParallelExecutor(unittest.TestCase):
act_places
,
set
([
p
.
name
for
p
in
main
.
global_block
().
iter_parameters
()]),
startup
.
desc
,
main
.
desc
,
loss
.
name
,
fluid
.
global_scope
())
exe
.
run
()
exe
.
run
([
loss
.
name
],
'fetched_var'
)
first_loss
=
numpy
.
array
(
fluid
.
global_scope
().
find_var
(
'fetched_var'
)
.
get_lod_tensor_array
()[
0
])
for
i
in
xrange
(
10
):
exe
.
run
([],
'fetched_var'
)
exe
.
run
([
loss
.
name
],
'fetched_var'
)
last_loss
=
numpy
.
array
(
fluid
.
global_scope
().
find_var
(
'fetched_var'
)
.
get_lod_tensor_array
()[
0
])
print
first_loss
,
last_loss
self
.
assertGreater
(
first_loss
[
0
],
last_loss
[
0
])
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