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体验新版 GitCode,发现更多精彩内容 >>
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5a3c8bf8
编写于
6月 09, 2018
作者:
C
chengduoZH
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix in c++ side
上级
a56dcf51
变更
10
显示空白变更内容
内联
并排
Showing
10 changed file
with
127 addition
and
49 deletion
+127
-49
paddle/fluid/framework/details/CMakeLists.txt
paddle/fluid/framework/details/CMakeLists.txt
+2
-0
paddle/fluid/framework/details/graph_builder_factory.h
paddle/fluid/framework/details/graph_builder_factory.h
+5
-1
paddle/fluid/framework/details/multi_devices_graph_builder.cc
...le/fluid/framework/details/multi_devices_graph_builder.cc
+33
-11
paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc
paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc
+19
-4
paddle/fluid/framework/details/nccl_all_reduce_op_handle.h
paddle/fluid/framework/details/nccl_all_reduce_op_handle.h
+11
-3
paddle/fluid/framework/parallel_executor.cc
paddle/fluid/framework/parallel_executor.cc
+25
-15
python/paddle/fluid/tests/unittests/test_parallel_executor_fetch_feed.py
...luid/tests/unittests/test_parallel_executor_fetch_feed.py
+16
-8
python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py
...dle/fluid/tests/unittests/test_parallel_executor_mnist.py
+2
-0
python/paddle/fluid/tests/unittests/test_parallel_executor_test_while_train.py
...ests/unittests/test_parallel_executor_test_while_train.py
+12
-6
python/paddle/fluid/tests/unittests/test_parallel_executor_transformer.py
...uid/tests/unittests/test_parallel_executor_transformer.py
+2
-1
未找到文件。
paddle/fluid/framework/details/CMakeLists.txt
浏览文件 @
5a3c8bf8
...
...
@@ -19,6 +19,8 @@ if(WITH_GPU)
nv_library
(
broadcast_op_handle SRCS broadcast_op_handle.cc DEPS op_handle_base scope ddim memory variable_visitor dynload_cuda
)
else
()
cc_library
(
nccl_all_reduce_op_handle SRCS nccl_all_reduce_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
variable_visitor
)
set
(
multi_devices_graph_builder_deps
)
cc_library
(
reduce_op_handle SRCS reduce_op_handle.cc DEPS op_handle_base variable_visitor scope ddim
)
cc_library
(
broadcast_op_handle SRCS broadcast_op_handle.cc DEPS op_handle_base scope ddim memory variable_visitor
)
...
...
paddle/fluid/framework/details/graph_builder_factory.h
浏览文件 @
5a3c8bf8
...
...
@@ -40,7 +40,11 @@ class SSAGraphBuilderFactory {
loss_var_name_
(
loss_var_name
),
param_names_
(
param_names
),
local_scopes_
(
local_scopes
),
strategy_
(
strategy
)
{}
strategy_
(
strategy
)
{
#ifdef PADDLE_WITH_CUDA
nccl_ctxs_
=
nullptr
;
#endif
}
#ifdef PADDLE_WITH_CUDA
void
SetNCCLContextMap
(
platform
::
NCCLContextMap
*
nccl_ctxs
)
{
...
...
paddle/fluid/framework/details/multi_devices_graph_builder.cc
浏览文件 @
5a3c8bf8
...
...
@@ -20,16 +20,13 @@
#include "paddle/fluid/framework/details/broadcast_op_handle.h"
#include "paddle/fluid/framework/details/computation_op_handle.h"
#include "paddle/fluid/framework/details/multi_devices_graph_builder.h"
#include "paddle/fluid/framework/details/nccl_all_reduce_op_handle.h"
#include "paddle/fluid/framework/details/reduce_op_handle.h"
#include "paddle/fluid/framework/details/rpc_op_handle.h"
#include "paddle/fluid/framework/details/scale_loss_grad_op_handle.h"
#include "paddle/fluid/framework/op_info.h"
#include "paddle/fluid/framework/scope.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/framework/details/nccl_all_reduce_op_handle.h"
#endif
namespace
paddle
{
namespace
framework
{
namespace
details
{
...
...
@@ -305,7 +302,12 @@ void MultiDevSSAGraphBuilder::CreateBroadcastOp(SSAGraph *result,
auto
*
out_var
=
new
VarHandle
(
vars
.
size
(),
i
,
p_name
,
p
);
vars
.
emplace_back
(
out_var
);
op_handle
->
AddOutput
(
out_var
);
#ifndef ADDLE_WITH_CUDA
#ifdef PADDLE_WITH_CUDA
if
(
nccl_ctxs_
==
nullptr
)
{
op_handle
->
SetDeviceContext
(
p
,
platform
::
DeviceContextPool
::
Instance
().
Get
(
p
));
}
#else
op_handle
->
SetDeviceContext
(
p
,
platform
::
DeviceContextPool
::
Instance
().
Get
(
p
));
#endif
...
...
@@ -324,7 +326,10 @@ void MultiDevSSAGraphBuilder::InsertNCCLAllReduceOp(
SSAGraph
*
result
,
const
std
::
string
&
og
)
const
{
#ifdef PADDLE_WITH_CUDA
result
->
ops_
.
emplace_back
(
new
NCCLAllReduceOpHandle
(
local_scopes_
,
places_
,
*
nccl_ctxs_
));
new
NCCLAllReduceOpHandle
(
local_scopes_
,
places_
,
nccl_ctxs_
));
#else
result
->
ops_
.
emplace_back
(
new
NCCLAllReduceOpHandle
(
local_scopes_
,
places_
));
#endif
auto
*
op_handle
=
result
->
ops_
.
back
().
get
();
for
(
size_t
i
=
0
;
i
<
places_
.
size
();
++
i
)
{
...
...
@@ -334,13 +339,23 @@ void MultiDevSSAGraphBuilder::InsertNCCLAllReduceOp(
auto
&
prev_grad
=
vars
.
back
();
op_handle
->
AddInput
(
prev_grad
.
get
());
#ifdef PADDLE_WITH_CUDA
if
(
nccl_ctxs_
==
nullptr
)
{
op_handle
->
SetDeviceContext
(
p
,
platform
::
DeviceContextPool
::
Instance
().
Get
(
p
));
}
#else
op_handle
->
SetDeviceContext
(
p
,
platform
::
DeviceContextPool
::
Instance
().
Get
(
p
));
#endif
VLOG
(
4
)
<<
"NCCL - - - "
<<
p
;
op_handle
->
DeviceContext
(
p
)
->
Wait
();
VLOG
(
4
)
<<
"NCCL - - - "
<<
p
<<
" "
<<
op_handle
->
DeviceContext
(
p
);
auto
var
=
new
VarHandle
(
vars
.
size
()
-
1
,
i
,
og
,
p
);
vars
.
emplace_back
(
var
);
op_handle
->
AddOutput
(
var
);
}
#else
PADDLE_ENFORCE
(
"Not implemented"
);
#endif
}
bool
MultiDevSSAGraphBuilder
::
IsParameterGradientOnce
(
...
...
@@ -379,7 +394,9 @@ void MultiDevSSAGraphBuilder::CreateScaleLossGradOp(SSAGraph *result) const {
for
(
size_t
i
=
0
;
i
<
places_
.
size
();
++
i
)
{
// Insert ScaleCost OpHandle
#ifdef PADDLE_WITH_CUDA
auto
*
communication_dev_ctx
=
nccl_ctxs_
->
DevCtx
(
places_
[
i
]);
auto
*
communication_dev_ctx
=
nccl_ctxs_
?
nccl_ctxs_
->
DevCtx
(
places_
[
i
])
:
platform
::
DeviceContextPool
::
Instance
().
Get
(
places_
[
i
]);
#else
auto
*
communication_dev_ctx
=
platform
::
DeviceContextPool
::
Instance
().
Get
(
platform
::
CPUPlace
());
...
...
@@ -425,8 +442,13 @@ VarHandle *MultiDevSSAGraphBuilder::CreateReduceOp(SSAGraph *result,
for
(
size_t
i
=
0
;
i
<
places_
.
size
();
++
i
)
{
auto
&
vars
=
result
->
vars_
[
i
][
og
];
#ifndef PADDLE_WITH_CUDA
auto
&
p
=
places_
[
i
];
#ifdef PADDLE_WITH_CUDA
if
(
nccl_ctxs_
==
nullptr
)
{
op_handle
->
SetDeviceContext
(
p
,
platform
::
DeviceContextPool
::
Instance
().
Get
(
p
));
}
#else
op_handle
->
SetDeviceContext
(
p
,
platform
::
DeviceContextPool
::
Instance
().
Get
(
p
));
#endif
...
...
paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc
浏览文件 @
5a3c8bf8
...
...
@@ -21,15 +21,25 @@
namespace
paddle
{
namespace
framework
{
namespace
details
{
#ifdef PADDLE_WITH_CUDA
NCCLAllReduceOpHandle
::
NCCLAllReduceOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
platform
::
NCCLContextMap
&
ctxs
)
const
platform
::
NCCLContextMap
*
ctxs
)
:
local_scopes_
(
local_scopes
),
places_
(
places
),
nccl_ctxs_
(
ctxs
)
{
if
(
ctxs
)
{
for
(
auto
&
p
:
places_
)
{
this
->
dev_ctxes_
[
p
]
=
nccl_ctxs_
.
DevCtx
(
p
);
this
->
dev_ctxes_
[
p
]
=
nccl_ctxs_
->
DevCtx
(
p
);
}
}
}
#else
NCCLAllReduceOpHandle
::
NCCLAllReduceOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
)
:
local_scopes_
(
local_scopes
),
places_
(
places
)
{}
#endif
void
NCCLAllReduceOpHandle
::
RunImpl
()
{
if
(
NoDummyInputSize
()
==
1
)
{
...
...
@@ -58,6 +68,8 @@ void NCCLAllReduceOpHandle::RunImpl() {
}
if
(
platform
::
is_gpu_place
(
lod_tensors
[
0
]
->
place
()))
{
#ifdef PADDLE_WITH_CUDA
PADDLE_ENFORCE
(
nccl_ctxs_
);
int
dtype
=
-
1
;
size_t
numel
=
0
;
std
::
vector
<
std
::
function
<
void
()
>>
all_reduce_calls
;
...
...
@@ -75,7 +87,7 @@ void NCCLAllReduceOpHandle::RunImpl() {
}
int
dev_id
=
boost
::
get
<
platform
::
CUDAPlace
>
(
p
).
device
;
auto
&
nccl_ctx
=
nccl_ctxs_
.
at
(
dev_id
);
auto
&
nccl_ctx
=
nccl_ctxs_
->
at
(
dev_id
);
auto
stream
=
nccl_ctx
.
stream
();
auto
comm
=
nccl_ctx
.
comm_
;
all_reduce_calls
.
emplace_back
([
=
]
{
...
...
@@ -90,6 +102,9 @@ void NCCLAllReduceOpHandle::RunImpl() {
call
();
}
});
#else
PADDLE_THROW
(
"Not compiled with CUDA"
);
#endif
}
else
{
// Special handle CPU only Operator's gradient. Like CRF
auto
&
trg
=
*
this
->
local_scopes_
[
0
]
->
FindVar
(
kLocalExecScopeName
)
...
...
paddle/fluid/framework/details/nccl_all_reduce_op_handle.h
浏览文件 @
5a3c8bf8
...
...
@@ -20,17 +20,23 @@
#include "paddle/fluid/framework/details/op_handle_base.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/nccl_helper.h"
#endif
namespace
paddle
{
namespace
framework
{
namespace
details
{
struct
NCCLAllReduceOpHandle
:
public
OpHandleBase
{
#ifdef PADDLE_WITH_CUDA
NCCLAllReduceOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
platform
::
NCCLContextMap
&
ctxs
);
const
platform
::
NCCLContextMap
*
ctxs
);
#else
NCCLAllReduceOpHandle
(
const
std
::
vector
<
Scope
*>
&
local_scopes
,
const
std
::
vector
<
platform
::
Place
>
&
places
);
#endif
std
::
string
Name
()
const
override
;
// Delay and buffer nccl_all_reduce together can significantly increase
...
...
@@ -43,7 +49,9 @@ struct NCCLAllReduceOpHandle : public OpHandleBase {
private:
std
::
vector
<
Scope
*>
local_scopes_
;
std
::
vector
<
platform
::
Place
>
places_
;
const
platform
::
NCCLContextMap
&
nccl_ctxs_
;
#ifdef PADDLE_WITH_CUDA
const
platform
::
NCCLContextMap
*
nccl_ctxs_
;
#endif
};
}
// namespace details
...
...
paddle/fluid/framework/parallel_executor.cc
浏览文件 @
5a3c8bf8
...
...
@@ -44,6 +44,7 @@ class ParallelExecutorPrivate {
std
::
unique_ptr
<
platform
::
NCCLContextMap
>
nccl_ctxs_
;
#endif
bool
own_local_scope
;
bool
use_cuda
;
};
std
::
vector
<
Scope
*>
&
ParallelExecutor
::
GetLocalScopes
()
{
...
...
@@ -60,6 +61,7 @@ ParallelExecutor::ParallelExecutor(
size_t
num_trainers
,
size_t
trainer_id
)
:
member_
(
new
ParallelExecutorPrivate
(
places
))
{
member_
->
global_scope_
=
scope
;
member_
->
use_cuda
=
exec_strategy
.
use_event_
;
// Step 1. Bcast the params to devs.
// Create local scopes
...
...
@@ -77,6 +79,7 @@ ParallelExecutor::ParallelExecutor(
}
}
if
(
member_
->
use_cuda
)
{
// Bcast Parameters to all GPUs
#ifdef PADDLE_WITH_CUDA
auto
*
nccl_id_var
=
scope
->
FindVar
(
NCCL_ID_VARNAME
);
...
...
@@ -86,9 +89,12 @@ ParallelExecutor::ParallelExecutor(
}
member_
->
nccl_ctxs_
.
reset
(
new
platform
::
NCCLContextMap
(
member_
->
places_
,
nccl_id
,
num_trainers
,
trainer_id
));
#else
PADDLE_THROW
(
"Not compiled with CUDA"
);
#endif
if
(
platform
::
is_gpu_place
(
places
[
0
])
&&
member_
->
local_scopes_
.
size
()
!=
1
&&
local_scopes
.
empty
())
{
// Is CUDA
}
if
(
member_
->
local_scopes_
.
size
()
!=
1
&&
local_scopes
.
empty
())
{
BCastParamsToGPUs
(
bcast_vars
);
}
// Startup Program has been run. All local scopes has correct parameters.
...
...
@@ -108,9 +114,13 @@ ParallelExecutor::ParallelExecutor(
details
::
SSAGraphBuilderFactory
builder_factory
(
member_
->
places_
,
loss_var_name
,
params
,
member_
->
local_scopes_
,
build_strategy
);
if
(
member_
->
use_cuda
)
{
#ifdef PADDLE_WITH_CUDA
builder_factory
.
SetNCCLContextMap
(
member_
->
nccl_ctxs_
.
get
());
#else
PADDLE_THROW
(
"Not compiled with CUDA"
);
#endif
}
member_
->
executor_
.
reset
(
new
details
::
ThreadedSSAGraphExecutor
(
exec_strategy
,
member_
->
local_scopes_
,
places
,
...
...
@@ -123,7 +133,6 @@ ParallelExecutor::ParallelExecutor(
void
ParallelExecutor
::
BCastParamsToGPUs
(
const
std
::
unordered_set
<
std
::
string
>
&
vars
)
const
{
#ifdef PADDLE_WITH_CUDA
auto
*
main_scope
=
member_
->
local_scopes_
[
0
];
for
(
auto
&
var
:
vars
)
{
...
...
@@ -135,6 +144,7 @@ void ParallelExecutor::BCastParamsToGPUs(
auto
&
main_tensor
=
main_var
->
Get
<
LoDTensor
>
();
auto
&
dims
=
main_tensor
.
dims
();
if
(
paddle
::
platform
::
is_gpu_place
(
main_tensor
.
place
()))
{
#ifdef PADDLE_WITH_CUDA
size_t
numel
=
main_tensor
.
numel
();
ncclDataType_t
data_type
=
platform
::
ToNCCLDataType
(
main_tensor
.
type
());
platform
::
NCCLGroupGuard
guard
;
...
...
@@ -153,6 +163,10 @@ void ParallelExecutor::BCastParamsToGPUs(
platform
::
dynload
::
ncclBcast
(
buffer
,
numel
,
data_type
,
0
,
nccl_ctx
.
comm_
,
nccl_ctx
.
stream
());
}
member_
->
nccl_ctxs_
->
WaitAll
();
#else
PADDLE_THROW
(
"Not compiled with CUDA"
);
#endif
}
else
{
platform
::
CPUPlace
cpu
;
for
(
size_t
i
=
1
;
i
<
member_
->
places_
.
size
();
++
i
)
{
...
...
@@ -163,11 +177,7 @@ void ParallelExecutor::BCastParamsToGPUs(
paddle
::
framework
::
TensorCopy
(
main_tensor
,
cpu
,
t
);
}
}
member_
->
nccl_ctxs_
->
WaitAll
();
}
#else
PADDLE_THROW
(
"Not compiled with CUDA"
);
#endif
}
void
ParallelExecutor
::
Run
(
const
std
::
vector
<
std
::
string
>
&
fetch_tensors
,
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor_fetch_feed.py
浏览文件 @
5a3c8bf8
...
...
@@ -35,7 +35,7 @@ def Lenet(data, class_dim):
class
TestFetchOp
(
unittest
.
TestCase
):
def
parallel_exe
(
self
,
train_inputs
,
seed
):
def
parallel_exe
(
self
,
train_inputs
,
seed
,
use_cuda
):
main
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
startup
.
random_seed
=
seed
...
...
@@ -59,13 +59,13 @@ class TestFetchOp(unittest.TestCase):
# conv2d_1.b_0@GRAD. Those variables should not be pruned.
# fluid.memory_optimize(main)
place
=
fluid
.
CUDAPlace
(
0
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
startup
)
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
[
data
,
label
])
pe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
loss_name
=
loss
.
name
,
main_program
=
main
)
use_cuda
=
use_cuda
,
loss_name
=
loss
.
name
,
main_program
=
main
)
fetch_list
=
[]
all_vars
=
main
.
global_block
().
vars
...
...
@@ -88,14 +88,15 @@ class TestFetchOp(unittest.TestCase):
for
i
in
range
(
iters
):
train_inputs
.
append
(
tst_reader_iter
.
next
())
self
.
parallel_exe
(
train_inputs
,
seed
=
1
)
self
.
parallel_exe
(
train_inputs
,
seed
=
1
,
use_cuda
=
True
)
self
.
parallel_exe
(
train_inputs
,
seed
=
1
,
use_cuda
=
False
)
class
TestFeedParallel
(
unittest
.
TestCase
):
def
test_main
(
self
):
def
parallel_exe
(
self
,
use_cuda
,
seed
):
main
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
startup
.
random_seed
=
1
startup
.
random_seed
=
seed
with
fluid
.
scope_guard
(
fluid
.
core
.
Scope
()):
with
fluid
.
program_guard
(
main
,
startup
):
data
=
fluid
.
layers
.
data
(
...
...
@@ -111,15 +112,18 @@ class TestFeedParallel(unittest.TestCase):
regularization
=
fluid
.
regularizer
.
L2Decay
(
1e-4
))
opt
.
minimize
(
loss
)
place
=
fluid
.
CUDAPlace
(
0
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
feeder
=
fluid
.
DataFeeder
(
place
=
place
,
feed_list
=
[
data
,
label
])
reader
=
feeder
.
decorate_reader
(
paddle
.
batch
(
flowers
.
train
(),
batch_size
=
16
),
multi_devices
=
True
)
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
startup
)
pe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
loss_name
=
loss
.
name
,
main_program
=
main
)
use_cuda
=
use_cuda
,
loss_name
=
loss
.
name
,
main_program
=
main
)
for
batch_id
,
data
in
enumerate
(
reader
()):
loss_np
=
np
.
array
(
pe
.
run
(
feed
=
data
,
fetch_list
=
[
loss
.
name
])[
0
])
...
...
@@ -127,6 +131,10 @@ class TestFeedParallel(unittest.TestCase):
if
batch_id
==
2
:
break
def
test_feed_op
(
self
):
self
.
parallel_exe
(
use_cuda
=
True
,
seed
=
1
)
self
.
parallel_exe
(
use_cuda
=
False
,
seed
=
1
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py
浏览文件 @
5a3c8bf8
...
...
@@ -117,9 +117,11 @@ class TestMNIST(TestParallelExecutorBase):
def
test_simple_fc
(
self
):
self
.
check_simple_fc_convergence
(
False
,
use_cuda
=
True
)
self
.
check_simple_fc_convergence
(
False
,
use_cuda
=
False
)
def
test_simple_fc_with_new_strategy
(
self
):
self
.
check_simple_fc_convergence
(
True
,
use_cuda
=
True
)
self
.
check_simple_fc_convergence
(
True
,
use_cuda
=
False
)
def
check_simple_fc_parallel_accuracy
(
self
,
balance_parameter_opt_between_cards
,
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor_test_while_train.py
浏览文件 @
5a3c8bf8
...
...
@@ -35,7 +35,7 @@ def simple_fc_net():
class
ParallelExecutorTestingDuringTraining
(
unittest
.
TestCase
):
def
check_network_convergence
(
self
,
build_strategy
=
None
):
def
check_network_convergence
(
self
,
use_cuda
,
build_strategy
=
None
):
main
=
fluid
.
Program
()
startup
=
fluid
.
Program
()
with
fluid
.
program_guard
(
main
,
startup
):
...
...
@@ -49,19 +49,19 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
image
=
np
.
random
.
normal
(
size
=
(
batch_size
,
784
)).
astype
(
'float32'
)
label
=
np
.
random
.
randint
(
0
,
10
,
(
batch_size
,
1
),
dtype
=
"int64"
)
place
=
fluid
.
CUDAPlace
(
0
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
exe
.
run
(
startup
)
feed_dict
=
{
'image'
:
image
,
'label'
:
label
}
train_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
use_cuda
=
use_cuda
,
loss_name
=
loss
.
name
,
main_program
=
main
,
build_strategy
=
build_strategy
)
test_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
True
,
use_cuda
=
use_cuda
,
main_program
=
test_program
,
share_vars_from
=
train_exe
,
build_strategy
=
build_strategy
)
...
...
@@ -81,12 +81,18 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
def
test_parallel_testing
(
self
):
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
reduce_strategy
=
fluid
.
BuildStrategy
.
ReduceStrategy
.
AllReduce
self
.
check_network_convergence
(
build_strategy
)
self
.
check_network_convergence
(
use_cuda
=
True
,
build_strategy
=
build_strategy
)
self
.
check_network_convergence
(
use_cuda
=
False
,
build_strategy
=
build_strategy
)
def
test_parallel_testing_with_new_strategy
(
self
):
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
reduce_strategy
=
fluid
.
BuildStrategy
.
ReduceStrategy
.
Reduce
self
.
check_network_convergence
(
build_strategy
)
self
.
check_network_convergence
(
use_cuda
=
True
,
build_strategy
=
build_strategy
)
self
.
check_network_convergence
(
use_cuda
=
False
,
build_strategy
=
build_strategy
)
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor_transformer.py
浏览文件 @
5a3c8bf8
...
...
@@ -167,7 +167,8 @@ class TestTransformer(TestParallelExecutorBase):
@
unittest
.
skip
(
"transformer is buggy in multi gpu"
)
def
test_main
(
self
):
self
.
check_network_convergence
(
transformer
)
self
.
check_network_convergence
(
transformer
,
use_cuda
=
True
)
self
.
check_network_convergence
(
transformer
,
use_cuda
=
False
)
if
__name__
==
'__main__'
:
...
...
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