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005fc8f4
编写于
11月 07, 2018
作者:
W
wangguibao
浏览文件
操作
浏览文件
下载
差异文件
Merge branch 'develop' of
https://github.com/PaddlePaddle/Paddle
into async_executor
上级
4faf6612
0953cd3e
变更
23
隐藏空白更改
内联
并排
Showing
23 changed file
with
436 addition
and
118 deletion
+436
-118
paddle/fluid/framework/details/CMakeLists.txt
paddle/fluid/framework/details/CMakeLists.txt
+9
-5
paddle/fluid/framework/details/build_strategy.cc
paddle/fluid/framework/details/build_strategy.cc
+5
-0
paddle/fluid/framework/details/build_strategy.h
paddle/fluid/framework/details/build_strategy.h
+2
-0
paddle/fluid/framework/details/computation_op_handle.cc
paddle/fluid/framework/details/computation_op_handle.cc
+8
-2
paddle/fluid/framework/details/computation_op_handle.h
paddle/fluid/framework/details/computation_op_handle.h
+3
-0
paddle/fluid/framework/details/modify_op_lock_and_record_event_pass.cc
...framework/details/modify_op_lock_and_record_event_pass.cc
+59
-0
paddle/fluid/framework/details/modify_op_lock_and_record_event_pass.h
.../framework/details/modify_op_lock_and_record_event_pass.h
+32
-0
paddle/fluid/framework/details/op_graph_view.cc
paddle/fluid/framework/details/op_graph_view.cc
+77
-0
paddle/fluid/framework/details/op_graph_view.h
paddle/fluid/framework/details/op_graph_view.h
+54
-0
paddle/fluid/framework/details/reference_count_op_handle.h
paddle/fluid/framework/details/reference_count_op_handle.h
+2
-2
paddle/fluid/framework/details/reference_count_pass.cc
paddle/fluid/framework/details/reference_count_pass.cc
+19
-12
paddle/fluid/operators/conv_cudnn_op.cu.cc
paddle/fluid/operators/conv_cudnn_op.cu.cc
+5
-3
paddle/fluid/operators/conv_transpose_cudnn_op.cu.cc
paddle/fluid/operators/conv_transpose_cudnn_op.cu.cc
+5
-3
paddle/fluid/operators/math/CMakeLists.txt
paddle/fluid/operators/math/CMakeLists.txt
+8
-3
paddle/fluid/operators/math/jit_kernel_blas.cc
paddle/fluid/operators/math/jit_kernel_blas.cc
+13
-1
paddle/fluid/operators/rmsprop_op.h
paddle/fluid/operators/rmsprop_op.h
+6
-6
paddle/fluid/platform/device_context.cc
paddle/fluid/platform/device_context.cc
+22
-47
paddle/fluid/platform/device_context.h
paddle/fluid/platform/device_context.h
+62
-5
paddle/fluid/platform/stream_callback_manager.h
paddle/fluid/platform/stream_callback_manager.h
+22
-18
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+18
-7
python/paddle/fluid/tests/unittests/CMakeLists.txt
python/paddle/fluid/tests/unittests/CMakeLists.txt
+2
-0
python/paddle/fluid/tests/unittests/parallel_executor_test_base.py
...ddle/fluid/tests/unittests/parallel_executor_test_base.py
+3
-0
python/paddle/fluid/tests/unittests/test_parallel_executor_crf.py
...addle/fluid/tests/unittests/test_parallel_executor_crf.py
+0
-4
未找到文件。
paddle/fluid/framework/details/CMakeLists.txt
浏览文件 @
005fc8f4
cc_library
(
var_handle SRCS var_handle.cc DEPS place framework_proto node
)
cc_library
(
op_handle_base SRCS op_handle_base.cc DEPS var_handle device_context lod_tensor
)
cc_library
(
op_graph_view SRCS op_graph_view.cc DEPS op_handle_base
)
cc_library
(
scale_loss_grad_op_handle SRCS scale_loss_grad_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
)
cc_library
(
fetch_op_handle SRCS fetch_op_handle.cc DEPS op_handle_base scope lod_tensor ddim memory
)
cc_library
(
computation_op_handle SRCS computation_op_handle.cc DEPS framework_proto scope place operator op_registry
)
...
...
@@ -30,7 +31,9 @@ cc_library(data_balance_op_handle SRCS data_balance_op_handle.cc DEPS op_handle_
cc_library
(
gather_op_handle SRCS gather_op_handle.cc DEPS op_handle_base scope ddim memory variable_visitor
)
cc_library
(
fuse_vars_op_handle SRCS fuse_vars_op_handle.cc DEPS op_handle_base scope
)
if
(
WITH_GPU
)
cc_library
(
modify_op_lock_and_record_event_pass SRCS modify_op_lock_and_record_event_pass.cc DEPS computation_op_handle op_graph_view multi_devices_helper
)
if
(
WITH_GPU
)
cc_library
(
reference_count_pass SRCS reference_count_pass.cc DEPS computation_op_handle scale_loss_grad_op_handle rpc_op_handle
all_reduce_op_handle reduce_op_handle broadcast_op_handle data_balance_op_handle graph graph_helper pass
)
endif
()
...
...
@@ -40,12 +43,13 @@ cc_library(sequential_execution_pass SRCS sequential_execution_pass.cc DEPS grap
cc_library
(
multi_devices_graph_pass SRCS multi_devices_graph_pass.cc DEPS multi_devices_helper computation_op_handle
scale_loss_grad_op_handle rpc_op_handle all_reduce_op_handle reduce_op_handle broadcast_op_handle data_balance_op_handle fused_broadcast_op_handle
)
if
(
WITH_GPU
)
cc_library
(
ssa_graph_executor SRCS ssa_graph_executor.cc DEPS graph framework_proto reference_count_pass sequential_execution_pass
)
else
()
cc_library
(
ssa_graph_executor SRCS ssa_graph_executor.cc DEPS graph framework_proto sequential_execution_pass
)
set
(
SSA_GRAPH_EXECUTOR_DEPS graph framework_proto sequential_execution_pass modify_op_lock_and_record_event_pass
)
if
(
WITH_GPU
)
list
(
APPEND SSA_GRAPH_EXECUTOR_DEPS reference_count_pass
)
endif
()
cc_library
(
ssa_graph_executor SRCS ssa_graph_executor.cc DEPS
${
SSA_GRAPH_EXECUTOR_DEPS
}
)
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/build_strategy.cc
浏览文件 @
005fc8f4
...
...
@@ -69,6 +69,10 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
// Verify that the graph is correct for multi-device executor.
AppendPass
(
"multi_devices_check_pass"
);
if
(
strategy_
.
remove_unnecessary_lock_
)
{
AppendPass
(
"modify_op_lock_and_record_event_pass"
);
}
}
private:
...
...
@@ -136,3 +140,4 @@ USE_PASS(multi_devices_pass);
USE_PASS
(
multi_devices_check_pass
);
USE_PASS
(
multi_devices_print_pass
);
USE_PASS
(
sequential_execution_pass
);
USE_PASS
(
modify_op_lock_and_record_event_pass
);
paddle/fluid/framework/details/build_strategy.h
浏览文件 @
005fc8f4
...
...
@@ -73,6 +73,8 @@ struct BuildStrategy {
bool
fuse_broadcast_op_
{
false
};
bool
remove_unnecessary_lock_
{
false
};
// User normally doesn't need to call this API.
// The PassBuilder allows for more customized insert, remove of passes
// from python side.
...
...
paddle/fluid/framework/details/computation_op_handle.cc
浏览文件 @
005fc8f4
...
...
@@ -29,9 +29,15 @@ ComputationOpHandle::ComputationOpHandle(ir::Node *node, Scope *scope,
void
ComputationOpHandle
::
RunImpl
()
{
WaitInputVarGenerated
(
place_
);
this
->
RunAndRecordEvent
([
this
]
{
auto
run_func
=
[
this
]()
{
op_
->
Run
(
*
scope_
->
FindVar
(
kLocalExecScopeName
)
->
Get
<
Scope
*>
(),
place_
);
});
};
if
(
is_lock_and_record_event_free_
)
{
run_func
();
}
else
{
this
->
RunAndRecordEvent
(
run_func
);
}
}
bool
ComputationOpHandle
::
NeedWait
(
VarHandleBase
*
in_var
)
{
...
...
paddle/fluid/framework/details/computation_op_handle.h
浏览文件 @
005fc8f4
...
...
@@ -36,6 +36,8 @@ struct ComputationOpHandle : public OpHandleBase {
const
platform
::
Place
&
GetPlace
()
const
{
return
place_
;
}
void
SetLockAndRecordEventFree
(
bool
b
)
{
is_lock_and_record_event_free_
=
b
;
}
protected:
void
RunImpl
()
override
;
...
...
@@ -45,6 +47,7 @@ struct ComputationOpHandle : public OpHandleBase {
std
::
unique_ptr
<
OperatorBase
>
op_
;
Scope
*
scope_
;
platform
::
Place
place_
;
bool
is_lock_and_record_event_free_
{
false
};
};
}
// namespace details
}
// namespace framework
...
...
paddle/fluid/framework/details/modify_op_lock_and_record_event_pass.cc
0 → 100644
浏览文件 @
005fc8f4
// 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/modify_op_lock_and_record_event_pass.h"
#include "paddle/fluid/framework/details/computation_op_handle.h"
#include "paddle/fluid/framework/details/multi_devices_helper.h"
#include "paddle/fluid/framework/details/op_graph_view.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
static
bool
IsLockAndRecordEventFreeComputationOpHandle
(
ComputationOpHandle
*
op
,
const
OpGraphView
&
graph_view
)
{
if
(
!
platform
::
is_gpu_place
(
op
->
GetPlace
()))
return
false
;
for
(
auto
&
pending_op
:
graph_view
.
PendingOps
(
op
))
{
auto
*
tmp
=
dynamic_cast
<
ComputationOpHandle
*>
(
pending_op
);
if
(
tmp
==
nullptr
||
!
(
tmp
->
GetPlace
()
==
op
->
GetPlace
()))
{
return
false
;
}
}
return
true
;
}
std
::
unique_ptr
<
ir
::
Graph
>
ModifyOpLockAndRecordEventPass
::
ApplyImpl
(
std
::
unique_ptr
<
ir
::
Graph
>
ir_graph
)
const
{
auto
&
all_ops
=
ir_graph
->
Get
<
GraphOps
>
(
kGraphOps
);
OpGraphView
graph_view
(
all_ops
);
for
(
auto
&
op
:
all_ops
)
{
auto
*
compute_op
=
dynamic_cast
<
ComputationOpHandle
*>
(
op
.
get
());
if
(
compute_op
==
nullptr
)
continue
;
bool
is_lock_and_record_event_free
=
IsLockAndRecordEventFreeComputationOpHandle
(
compute_op
,
graph_view
);
compute_op
->
SetLockAndRecordEventFree
(
is_lock_and_record_event_free
);
if
(
is_lock_and_record_event_free
)
{
VLOG
(
10
)
<<
"Set is_lock_and_record_event_free be true in op "
<<
compute_op
->
DebugString
();
}
}
return
ir_graph
;
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
REGISTER_PASS
(
modify_op_lock_and_record_event_pass
,
paddle
::
framework
::
details
::
ModifyOpLockAndRecordEventPass
);
paddle/fluid/framework/details/modify_op_lock_and_record_event_pass.h
0 → 100644
浏览文件 @
005fc8f4
// 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 "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/pass.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
class
ModifyOpLockAndRecordEventPass
:
public
ir
::
Pass
{
protected:
std
::
unique_ptr
<
ir
::
Graph
>
ApplyImpl
(
std
::
unique_ptr
<
ir
::
Graph
>
graph
)
const
override
;
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/op_graph_view.cc
0 → 100644
浏览文件 @
005fc8f4
// 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/op_graph_view.h"
#include <queue>
#include <utility>
namespace
paddle
{
namespace
framework
{
namespace
details
{
OpGraphView
::
OpGraphView
(
const
std
::
vector
<
std
::
unique_ptr
<
OpHandleBase
>>
&
ops
)
{
Build
(
ops
);
}
void
OpGraphView
::
Build
(
const
std
::
vector
<
std
::
unique_ptr
<
OpHandleBase
>>
&
ops
)
{
for
(
auto
&
op
:
ops
)
{
preceding_ops_
[
op
.
get
()];
pending_ops_
[
op
.
get
()];
for
(
auto
&
var
:
op
->
Outputs
())
{
for
(
auto
&
pending_op
:
var
->
PendingOps
())
{
preceding_ops_
[
pending_op
].
insert
(
op
.
get
());
pending_ops_
[
op
.
get
()].
insert
(
pending_op
);
}
}
}
PADDLE_ENFORCE
(
preceding_ops_
.
size
()
==
ops
.
size
()
&&
pending_ops_
.
size
()
==
ops
.
size
(),
"There are duplicate ops in graph."
);
}
size_t
OpGraphView
::
OpNumber
()
const
{
return
preceding_ops_
.
size
();
}
std
::
unordered_set
<
OpHandleBase
*>
OpGraphView
::
AllOps
()
const
{
std
::
unordered_set
<
OpHandleBase
*>
ret
;
for
(
auto
&
pair
:
preceding_ops_
)
{
ret
.
insert
(
pair
.
first
);
}
return
ret
;
}
bool
OpGraphView
::
HasOp
(
OpHandleBase
*
op
)
const
{
return
preceding_ops_
.
count
(
op
)
!=
0
;
}
void
OpGraphView
::
EnforceHasOp
(
OpHandleBase
*
op
)
const
{
PADDLE_ENFORCE
(
HasOp
(
op
),
"Cannot find op %s in OpGraphView"
,
op
==
nullptr
?
"nullptr"
:
op
->
DebugString
());
}
const
std
::
unordered_set
<
OpHandleBase
*>
&
OpGraphView
::
PrecedingOps
(
OpHandleBase
*
op
)
const
{
EnforceHasOp
(
op
);
return
preceding_ops_
.
at
(
op
);
}
const
std
::
unordered_set
<
OpHandleBase
*>
&
OpGraphView
::
PendingOps
(
OpHandleBase
*
op
)
const
{
EnforceHasOp
(
op
);
return
pending_ops_
.
at
(
op
);
}
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/op_graph_view.h
0 → 100644
浏览文件 @
005fc8f4
// 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 <unordered_map>
#include <unordered_set>
#include <vector>
#include "paddle/fluid/framework/details/op_handle_base.h"
namespace
paddle
{
namespace
framework
{
namespace
details
{
class
OpGraphView
{
public:
explicit
OpGraphView
(
const
std
::
vector
<
std
::
unique_ptr
<
OpHandleBase
>>
&
ops
);
size_t
OpNumber
()
const
;
std
::
unordered_set
<
OpHandleBase
*>
AllOps
()
const
;
const
std
::
unordered_set
<
OpHandleBase
*>
&
PrecedingOps
(
OpHandleBase
*
op
)
const
;
const
std
::
unordered_set
<
OpHandleBase
*>
&
PendingOps
(
OpHandleBase
*
op
)
const
;
bool
HasOp
(
OpHandleBase
*
op
)
const
;
private:
void
Build
(
const
std
::
vector
<
std
::
unique_ptr
<
OpHandleBase
>>
&
ops
);
void
EnforceHasOp
(
OpHandleBase
*
op
)
const
;
std
::
unordered_map
<
OpHandleBase
*
,
std
::
unordered_set
<
OpHandleBase
*>>
preceding_ops_
;
std
::
unordered_map
<
OpHandleBase
*
,
std
::
unordered_set
<
OpHandleBase
*>>
pending_ops_
;
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/details/reference_count_op_handle.h
浏览文件 @
005fc8f4
...
...
@@ -51,7 +51,7 @@ class ReferenceCountOpHandle : public OpHandleBase {
dev_ctx_
=
static_cast
<
platform
::
CUDADeviceContext
*>
(
platform
::
DeviceContextPool
::
Instance
().
Get
(
place
));
if
(
IsStreamGarabageCollector
())
{
PADDLE_ENFORCE
(
cudaSetDevice
(
place
.
device
)
);
platform
::
SetDeviceId
(
place
.
device
);
PADDLE_ENFORCE
(
cudaEventCreateWithFlags
(
&
event_
,
cudaEventDisableTiming
));
}
...
...
@@ -61,7 +61,7 @@ class ReferenceCountOpHandle : public OpHandleBase {
~
ReferenceCountOpHandle
()
{
if
(
IsStreamGarabageCollector
())
{
auto
gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
dev_ctx_
->
GetPlace
());
PADDLE_ENFORCE
(
cudaSetDevice
(
gpu_place
.
device
)
);
platform
::
SetDeviceId
(
gpu_place
.
device
);
PADDLE_ENFORCE
(
cudaEventDestroy
(
event_
));
}
}
...
...
paddle/fluid/framework/details/reference_count_pass.cc
浏览文件 @
005fc8f4
...
...
@@ -43,6 +43,23 @@ static ComputationOpHandle *FindNextComputationOpHandle(VarHandle *var_in) {
return
nullptr
;
}
static
void
AddDependencyBetween
(
OpHandleBase
*
in
,
OpHandleBase
*
out
,
ir
::
Graph
*
graph
)
{
auto
it
=
std
::
find_if
(
in
->
Outputs
().
begin
(),
in
->
Outputs
().
end
(),
[](
VarHandleBase
*
var
)
{
return
dynamic_cast
<
DummyVarHandle
*>
(
var
)
!=
nullptr
;
});
if
(
it
!=
in
->
Outputs
().
end
())
{
out
->
AddInput
(
*
it
);
}
else
{
auto
*
dep_var
=
new
DummyVarHandle
(
graph
->
CreateControlDepVar
());
graph
->
Get
<
GraphDepVars
>
(
kGraphDepVars
).
emplace
(
dep_var
);
in
->
AddOutput
(
dep_var
);
out
->
AddInput
(
dep_var
);
}
}
std
::
unique_ptr
<
ir
::
Graph
>
ReferenceCountPass
::
ApplyImpl
(
std
::
unique_ptr
<
ir
::
Graph
>
graph
)
const
{
auto
&
ref_cnts
=
Get
<
DeviceReferenceCountMap
>
(
kGlobalReferenceCount
);
...
...
@@ -133,12 +150,7 @@ std::unique_ptr<ir::Graph> ReferenceCountPass::ApplyImpl(
auto
*
ref_cnt_handle
=
new
ReferenceCountOpHandle
(
ref_cnt_node
,
next_compute_op
->
GetScope
(),
place
,
{
var_name
},
gcs
[
place
.
device
].
get
(),
cur_ref_cnts
[
place
.
device
].
get
());
if
(
next_compute_op
->
Outputs
().
empty
())
{
auto
*
dep_var
=
new
DummyVarHandle
(
graph
->
CreateControlDepVar
());
next_compute_op
->
AddOutput
(
dep_var
);
graph
->
Get
<
GraphDepVars
>
(
kGraphDepVars
).
emplace
(
dep_var
);
}
ref_cnt_handle
->
AddInput
(
next_compute_op
->
Outputs
().
front
());
AddDependencyBetween
(
next_compute_op
,
ref_cnt_handle
,
graph
.
get
());
compute_ref_cnt_map
[
next_compute_op
].
reset
(
ref_cnt_handle
);
}
}
...
...
@@ -160,12 +172,7 @@ std::unique_ptr<ir::Graph> ReferenceCountPass::ApplyImpl(
auto
*
ref_cnt_handle
=
new
ReferenceCountOpHandle
(
ref_cnt_node
,
compute_op
->
GetScope
(),
place
,
in_var_names
,
gcs
[
place
.
device
].
get
(),
cur_ref_cnts
[
place
.
device
].
get
());
if
(
compute_op
->
Outputs
().
empty
())
{
auto
*
dep_var
=
new
DummyVarHandle
(
graph
->
CreateControlDepVar
());
compute_op
->
AddOutput
(
dep_var
);
graph
->
Get
<
GraphDepVars
>
(
kGraphDepVars
).
emplace
(
dep_var
);
}
ref_cnt_handle
->
AddInput
(
compute_op
->
Outputs
().
front
());
AddDependencyBetween
(
compute_op
,
ref_cnt_handle
,
graph
.
get
());
compute_ref_cnt_map
[
compute_op
].
reset
(
ref_cnt_handle
);
}
...
...
paddle/fluid/operators/conv_cudnn_op.cu.cc
浏览文件 @
005fc8f4
...
...
@@ -160,6 +160,7 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
// ------------------- cudnn conv forward ---------------------
ScalingParamType
<
T
>
alpha
=
1.0
f
,
beta
=
0.0
f
;
auto
workspace_handle
=
dev_ctx
.
cudnn_workspace_handle
();
for
(
int
i
=
0
;
i
<
groups
;
i
++
)
{
auto
cudnn_func
=
[
&
](
void
*
cudnn_workspace
)
{
CUDNN_ENFORCE
(
platform
::
dynload
::
cudnnConvolutionForward
(
...
...
@@ -168,7 +169,7 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
cudnn_conv_desc
,
algo
,
cudnn_workspace
,
workspace_size_in_bytes
,
&
beta
,
cudnn_output_desc
,
output_data
+
i
*
group_offset_out
));
};
dev_ctx
.
RunCudnnFuncWithWorkspace
(
cudnn_func
,
workspace_size_in_bytes
);
workspace_handle
.
RunFunc
(
cudnn_func
,
workspace_size_in_bytes
);
}
}
};
...
...
@@ -314,6 +315,7 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
// ------------------- cudnn conv backward data ---------------------
ScalingParamType
<
T
>
alpha
=
1.0
f
,
beta
=
0.0
f
;
auto
workspace_handle
=
dev_ctx
.
cudnn_workspace_handle
();
if
(
input_grad
)
{
T
*
input_grad_data
=
input_grad
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
// Because beta is zero, it is unnecessary to reset input_grad.
...
...
@@ -327,7 +329,7 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
data_algo
,
cudnn_workspace
,
workspace_size_in_bytes
,
&
beta
,
cudnn_input_desc
,
input_grad_data
+
i
*
group_offset_in
));
};
dev_ctx
.
RunCudnnFuncWithWorkspace
(
cudnn_func
,
workspace_size_in_bytes
);
workspace_handle
.
RunFunc
(
cudnn_func
,
workspace_size_in_bytes
);
}
}
// ------------------- cudnn conv backward filter ---------------------
...
...
@@ -343,7 +345,7 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
filter_algo
,
cudnn_workspace
,
workspace_size_in_bytes
,
&
beta
,
cudnn_filter_desc
,
filter_grad_data
+
i
*
group_offset_filter
));
};
dev_ctx
.
RunCudnnFuncWithWorkspace
(
cudnn_func
,
workspace_size_in_bytes
);
workspace_handle
.
RunFunc
(
cudnn_func
,
workspace_size_in_bytes
);
}
}
}
...
...
paddle/fluid/operators/conv_transpose_cudnn_op.cu.cc
浏览文件 @
005fc8f4
...
...
@@ -104,6 +104,7 @@ class CUDNNConvTransposeOpKernel : public framework::OpKernel<T> {
int
output_offset
=
output
->
numel
()
/
output
->
dims
()[
0
]
/
groups
;
int
filter_offset
=
filter
->
numel
()
/
groups
;
T
alpha
=
1.0
f
,
beta
=
0.0
f
;
auto
workspace_handle
=
dev_ctx
.
cudnn_workspace_handle
();
for
(
int
g
=
0
;
g
<
groups
;
g
++
)
{
auto
cudnn_func
=
[
&
](
void
*
cudnn_workspace
)
{
CUDNN_ENFORCE
(
platform
::
dynload
::
cudnnConvolutionBackwardData
(
...
...
@@ -112,7 +113,7 @@ class CUDNNConvTransposeOpKernel : public framework::OpKernel<T> {
algo
,
cudnn_workspace
,
workspace_size_in_bytes
,
&
beta
,
cudnn_output_desc
,
output_data
+
output_offset
*
g
));
};
dev_ctx
.
RunCudnnFuncWithWorkspace
(
cudnn_func
,
workspace_size_in_bytes
);
workspace_handle
.
RunFunc
(
cudnn_func
,
workspace_size_in_bytes
);
}
}
};
...
...
@@ -208,6 +209,7 @@ class CUDNNConvTransposeGradOpKernel : public framework::OpKernel<T> {
output_grad
->
numel
()
/
output_grad
->
dims
()[
0
]
/
groups
;
int
filter_offset
=
filter
->
numel
()
/
groups
;
T
alpha
=
1.0
f
,
beta
=
0.0
f
;
auto
workspace_handle
=
dev_ctx
.
cudnn_workspace_handle
();
if
(
input_grad
)
{
T
*
input_grad_data
=
input_grad
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
// Because beta is zero, it is unnecessary to reset input_grad.
...
...
@@ -220,7 +222,7 @@ class CUDNNConvTransposeGradOpKernel : public framework::OpKernel<T> {
cudnn_workspace
,
workspace_size_in_bytes
,
&
beta
,
cudnn_input_desc
,
input_grad_data
+
input_offset
*
g
));
};
dev_ctx
.
RunCudnnFuncWithWorkspace
(
cudnn_func
,
workspace_size_in_bytes
);
workspace_handle
.
RunFunc
(
cudnn_func
,
workspace_size_in_bytes
);
}
}
...
...
@@ -238,7 +240,7 @@ class CUDNNConvTransposeGradOpKernel : public framework::OpKernel<T> {
cudnn_workspace
,
workspace_size_in_bytes
,
&
beta
,
cudnn_filter_desc
,
filter_grad_data
+
filter_offset
*
g
));
};
dev_ctx
.
RunCudnnFuncWithWorkspace
(
cudnn_func
,
workspace_size_in_bytes
);
workspace_handle
.
RunFunc
(
cudnn_func
,
workspace_size_in_bytes
);
}
}
}
...
...
paddle/fluid/operators/math/CMakeLists.txt
浏览文件 @
005fc8f4
...
...
@@ -75,7 +75,12 @@ if(WITH_GPU)
endif
()
cc_test
(
concat_test SRCS concat_test.cc DEPS concat_and_split
)
cc_test
(
cpu_vec_test SRCS cpu_vec_test.cc DEPS blas cpu_info
)
cc_library
(
jit_kernel
SRCS jit_kernel.cc jit_gen.cc jit_code.cc jit_kernel_blas.cc jit_kernel_exp.cc jit_kernel_rnn.cc jit_kernel_crf_decode.cc
DEPS cpu_info cblas gflags enforce
)
set
(
JIT_KERNEL_SRCS jit_kernel.cc jit_kernel_blas.cc jit_kernel_exp.cc jit_kernel_rnn.cc jit_kernel_crf_decode.cc
)
set
(
JIT_KERNEL_DEPS cpu_info cblas gflags enforce
)
if
(
WITH_XBYAK
)
list
(
APPEND JIT_KERNEL_SRCS jit_gen.cc jit_code.cc
)
list
(
APPEND JIT_KERNEL_DEPS xbyak
)
endif
()
cc_library
(
jit_kernel SRCS
${
JIT_KERNEL_SRCS
}
DEPS
${
JIT_KERNEL_DEPS
}
)
cc_test
(
jit_kernel_test SRCS jit_kernel_test.cc DEPS jit_kernel
)
paddle/fluid/operators/math/jit_kernel_blas.cc
浏览文件 @
005fc8f4
...
...
@@ -14,10 +14,13 @@ limitations under the License. */
#include "paddle/fluid/operators/math/jit_kernel.h"
#include <string>
#include "paddle/fluid/operators/math/jit_code.h"
#include "paddle/fluid/operators/math/jit_kernel_macro.h"
#include "paddle/fluid/platform/enforce.h"
#ifdef PADDLE_WITH_XBYAK
#include "paddle/fluid/operators/math/jit_code.h"
#endif
#ifdef PADDLE_WITH_MKLML
#include "paddle/fluid/platform/dynload/mklml.h"
#endif
...
...
@@ -64,6 +67,7 @@ class VMulKernelImpl : public VMulKernel<T> {
static
inline
bool
useMKL
(
int
d
)
{
return
false
;
}
explicit
VMulKernelImpl
(
int
d
)
:
VMulKernel
<
T
>
()
{
#ifdef PADDLE_WITH_XBYAK
if
(
useJIT
(
d
))
{
// roughly estimate the size of code
size_t
sz
=
96
+
d
/
AVX_FLOAT_BLOCK
*
4
*
8
;
...
...
@@ -72,6 +76,7 @@ class VMulKernelImpl : public VMulKernel<T> {
jitcode_
->
getCode
<
void
(
*
)(
const
T
*
,
const
T
*
,
T
*
,
int
)
>
();
return
;
}
#endif
#ifdef PADDLE_WITH_MKLML
if
(
useMKL
(
d
))
{
this
->
Compute
=
VMulMKL
<
T
>
;
...
...
@@ -81,15 +86,21 @@ class VMulKernelImpl : public VMulKernel<T> {
this
->
Compute
=
VMulRefer
<
T
>
;
}
#ifdef PADDLE_WITH_XBYAK
private:
std
::
unique_ptr
<
gen
::
VMulJitCode
>
jitcode_
{
nullptr
};
#endif
};
#ifdef PADDLE_WITH_XBYAK
template
<
>
bool
VMulKernelImpl
<
float
>::
useJIT
(
int
d
)
{
return
gen
::
VMulJitCode
::
init
(
d
);
}
#endif
#ifdef PADDLE_WITH_MKLML
template
<
>
bool
VMulKernelImpl
<
float
>::
useMKL
(
int
d
)
{
return
jit
::
MayIUse
(
jit
::
avx512f
)
&&
d
>
512
;
...
...
@@ -99,6 +110,7 @@ template <>
bool
VMulKernelImpl
<
double
>::
useMKL
(
int
d
)
{
return
true
;
}
#endif
REGISTER_JITKERNEL
(
vmul
,
VMulKernel
);
...
...
paddle/fluid/operators/rmsprop_op.h
浏览文件 @
005fc8f4
...
...
@@ -179,8 +179,8 @@ class RmspropOpKernel : public framework::OpKernel<T> {
auto
&
mg_tensor
=
*
ctx
.
Input
<
LoDTensor
>
(
"MeanGrad"
);
auto
mg
=
EigenVector
<
T
>::
Flatten
(
mg_tensor
);
auto
*
mean_grad_out
=
ctx
.
Output
<
LoDTensor
>
(
"MeanGradOut"
);
PADDLE_ENFORCE
(
&
mg_tensor
,
mean_grad_out
,
"MeanGrad and MeanGradOut must be the same Tensor"
);
PADDLE_ENFORCE
_EQ
(
&
mg_tensor
,
mean_grad_out
,
"MeanGrad and MeanGradOut must be the same Tensor"
);
auto
mg_out
=
EigenVector
<
T
>::
Flatten
(
*
mean_grad_out
);
mg_out
.
device
(
place
)
=
rho
*
mg
+
(
1
-
rho
)
*
g
;
...
...
@@ -198,8 +198,8 @@ class RmspropOpKernel : public framework::OpKernel<T> {
if
(
centered
)
{
auto
&
mg_tensor
=
*
ctx
.
Input
<
LoDTensor
>
(
"MeanGrad"
);
auto
*
mean_grad_out
=
ctx
.
Output
<
LoDTensor
>
(
"MeanGradOut"
);
PADDLE_ENFORCE
(
&
mg_tensor
,
mean_grad_out
,
"MeanGrad and MeanGradOut must be the same Tensor"
);
PADDLE_ENFORCE
_EQ
(
&
mg_tensor
,
mean_grad_out
,
"MeanGrad and MeanGradOut must be the same Tensor"
);
for_range
(
CenteredRmspropFunctor
<
T
,
DenseRmspropGradFunctor
<
T
>>
(
param_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
()),
mean_square_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
()),
...
...
@@ -243,8 +243,8 @@ class RmspropOpKernel : public framework::OpKernel<T> {
if
(
centered
)
{
auto
&
mg_tensor
=
*
ctx
.
Input
<
LoDTensor
>
(
"MeanGrad"
);
auto
*
mean_grad_out
=
ctx
.
Output
<
LoDTensor
>
(
"MeanGradOut"
);
PADDLE_ENFORCE
(
&
mg_tensor
,
mean_grad_out
,
"MeanGrad and MeanGradOut must be the same Tensor"
);
PADDLE_ENFORCE
_EQ
(
&
mg_tensor
,
mean_grad_out
,
"MeanGrad and MeanGradOut must be the same Tensor"
);
for_range
(
CenteredRmspropFunctor
<
T
,
SparseRmspropGradFunctor
<
T
>>
(
param_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
()),
mean_square_out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
()),
...
...
paddle/fluid/platform/device_context.cc
浏览文件 @
005fc8f4
...
...
@@ -153,55 +153,31 @@ class EigenCudaStreamDevice : public Eigen::StreamInterface {
mutable
unsigned
int
*
semaphore_
;
};
class
CudnnHolder
{
public:
CudnnHolder
(
const
cudaStream_t
*
stream
,
const
CUDAPlace
&
place
)
:
workspace_
(
nullptr
),
workspace_len_
(
0
),
stream_
(
stream
),
place_
(
place
)
{
PADDLE_ENFORCE
(
dynload
::
cudnnCreate
(
&
cudnn_handle_
));
PADDLE_ENFORCE
(
dynload
::
cudnnSetStream
(
cudnn_handle_
,
*
stream_
));
}
cudnnHandle_t
cudnn_handle
()
const
{
return
cudnn_handle_
;
}
CudnnHolder
::
CudnnHolder
(
const
cudaStream_t
*
stream
,
const
CUDAPlace
&
place
)
:
workspace_
(
nullptr
),
workspace_len_
(
0
),
stream_
(
stream
),
place_
(
place
)
{
PADDLE_ENFORCE
(
dynload
::
cudnnCreate
(
&
cudnn_handle_
));
PADDLE_ENFORCE
(
dynload
::
cudnnSetStream
(
cudnn_handle_
,
*
stream_
));
}
void
RunFunc
(
const
std
::
function
<
void
(
void
*
)
>&
cudnn_func
,
size_t
required_workspace_len
)
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
mtx_
);
if
(
required_workspace_len
>
workspace_len_
)
{
ReallocateWorkspace
(
required_workspace_len
);
}
cudnn_func
(
workspace_
);
CudnnHolder
::~
CudnnHolder
()
{
PADDLE_ENFORCE
(
dynload
::
cudnnDestroy
(
cudnn_handle_
));
if
(
workspace_
!=
nullptr
)
{
paddle
::
memory
::
Free
(
place_
,
workspace_
);
}
}
~
CudnnHolder
()
{
PADDLE_ENFORCE
(
dynload
::
cudnnDestroy
(
cudnn_handle_
));
if
(
workspace_
!=
nullptr
)
{
paddle
::
memory
::
Free
(
place_
,
workspace_
);
}
void
CudnnHolder
::
ReallocateWorkspace
(
size_t
required_workspace_len
)
{
if
(
required_workspace_len
<=
workspace_len_
)
{
return
;
}
private:
void
ReallocateWorkspace
(
size_t
required_workspace_len
)
{
if
(
required_workspace_len
<=
workspace_len_
)
{
return
;
}
if
(
workspace_
!=
nullptr
)
{
// Maybe someone is using the current workspace
PADDLE_ENFORCE
(
cudaStreamSynchronize
(
*
stream_
));
paddle
::
memory
::
Free
(
place_
,
workspace_
);
}
workspace_
=
paddle
::
memory
::
Alloc
(
place_
,
required_workspace_len
);
workspace_len_
=
required_workspace_len
;
if
(
workspace_
!=
nullptr
)
{
// Maybe someone is using the current workspace
PADDLE_ENFORCE
(
cudaStreamSynchronize
(
*
stream_
));
paddle
::
memory
::
Free
(
place_
,
workspace_
);
}
cudnnHandle_t
cudnn_handle_
;
void
*
workspace_
;
size_t
workspace_len_
;
const
cudaStream_t
*
stream_
;
// not owned;
const
CUDAPlace
place_
;
std
::
mutex
mtx_
;
};
workspace_
=
paddle
::
memory
::
Alloc
(
place_
,
required_workspace_len
);
workspace_len_
=
required_workspace_len
;
}
CUDADeviceContext
::
CUDADeviceContext
(
CUDAPlace
place
)
:
place_
(
place
),
cudnn_holder_
(
nullptr
)
{
...
...
@@ -269,9 +245,8 @@ cudnnHandle_t CUDADeviceContext::cudnn_handle() const {
return
cudnn_holder_
->
cudnn_handle
();
}
void
CUDADeviceContext
::
RunCudnnFuncWithWorkspace
(
const
std
::
function
<
void
(
void
*
)
>&
cudnn_func
,
size_t
workspace_len
)
const
{
cudnn_holder_
->
RunFunc
(
cudnn_func
,
workspace_len
);
CudnnWorkspaceHandle
CUDADeviceContext
::
cudnn_workspace_handle
()
const
{
return
CudnnWorkspaceHandle
(
cudnn_holder_
.
get
());
}
cudaStream_t
CUDADeviceContext
::
stream
()
const
{
return
stream_
;
}
...
...
paddle/fluid/platform/device_context.h
浏览文件 @
005fc8f4
...
...
@@ -73,7 +73,60 @@ struct DefaultDeviceContextType<platform::CPUPlace> {
#ifdef PADDLE_WITH_CUDA
class
EigenCudaStreamDevice
;
class
CudnnHolder
;
class
CudnnHolder
{
public:
CudnnHolder
(
const
cudaStream_t
*
stream
,
const
CUDAPlace
&
place
);
~
CudnnHolder
();
cudnnHandle_t
cudnn_handle
()
const
{
return
cudnn_handle_
;
}
private:
friend
class
CudnnWorkspaceHandle
;
void
ReallocateWorkspace
(
size_t
required_workspace_len
);
template
<
typename
Callback
>
void
RunFuncImpl
(
Callback
&&
cudnn_func
,
size_t
required_workspace_len
)
{
if
(
required_workspace_len
>
workspace_len_
)
{
ReallocateWorkspace
(
required_workspace_len
);
}
cudnn_func
(
workspace_
);
}
std
::
mutex
&
Mutex
()
{
return
mtx_
;
}
cudnnHandle_t
cudnn_handle_
;
void
*
workspace_
;
size_t
workspace_len_
;
const
cudaStream_t
*
stream_
;
// not owned;
const
CUDAPlace
place_
;
std
::
mutex
mtx_
;
};
class
CudnnWorkspaceHandle
{
public:
/*! \brief The lock would not be acquired when constructor calls.
* The lock would be acquired when RunFunc() is called first time. */
inline
explicit
CudnnWorkspaceHandle
(
CudnnHolder
*
holder
)
:
holder_
(
holder
)
{}
/*! \brief Thread which call RunFunc() would acquire the lock first
* before invoking cudnn functions. */
template
<
typename
Callback
>
inline
void
RunFunc
(
Callback
&&
cudnn_func
,
size_t
required_workspace_len
)
{
if
(
!
guard_
)
{
guard_
.
reset
(
new
std
::
lock_guard
<
std
::
mutex
>
(
holder_
->
Mutex
()));
}
holder_
->
RunFuncImpl
(
std
::
forward
<
Callback
>
(
cudnn_func
),
required_workspace_len
);
}
CudnnWorkspaceHandle
(
CudnnWorkspaceHandle
&&
)
=
default
;
CudnnWorkspaceHandle
&
operator
=
(
CudnnWorkspaceHandle
&&
)
=
delete
;
private:
CudnnHolder
*
holder_
;
// not own
std
::
unique_ptr
<
std
::
lock_guard
<
std
::
mutex
>>
guard_
;
};
class
CUDADeviceContext
:
public
DeviceContext
{
public:
...
...
@@ -101,10 +154,14 @@ class CUDADeviceContext : public DeviceContext {
/*! \brief Return cudnn handle in the device context. */
cudnnHandle_t
cudnn_handle
()
const
;
/*! \brief Run a cudnn function with the workspace provided by
* CUDADeviceContext */
void
RunCudnnFuncWithWorkspace
(
const
std
::
function
<
void
(
void
*
)
>&
cudnn_func
,
size_t
workspace_len
)
const
;
/*! \brief Return a cudnn workspace handle to call multiple cudnn
* functions without interrupting by other threads.
* Once the first cudnn function is called by the handle, a lock
* would be acquired to prevent other threads from accessing the
* workspace. Once the handle is destructed, the lock would be released.
* CudnnWorkspaceHandle is an RAII object to implement thread-safe
* sequential cudnn function calls. */
CudnnWorkspaceHandle
cudnn_workspace_handle
()
const
;
/*! \brief Return cuda stream in the device context. */
cudaStream_t
stream
()
const
;
...
...
paddle/fluid/platform/stream_callback_manager.h
浏览文件 @
005fc8f4
...
...
@@ -24,8 +24,6 @@
namespace
paddle
{
namespace
platform
{
using
StreamCallback
=
std
::
function
<
void
(
cudaStream_t
,
cudaError_t
)
>
;
class
StreamCallbackManager
;
struct
StreamCallbackContext
{
...
...
@@ -35,7 +33,7 @@ struct StreamCallbackContext {
:
manager_
(
manager
),
callback_
(
callback
)
{}
const
StreamCallbackManager
*
manager_
;
// do not own
StreamCallback
callback_
;
std
::
function
<
void
()
>
callback_
;
};
class
StreamCallbackManager
{
...
...
@@ -45,16 +43,18 @@ class StreamCallbackManager {
template
<
typename
Callback
>
inline
void
AddCallback
(
Callback
&&
callback
)
const
{
AddCallbackWithStreamAndErrorInfo
(
[
=
](
cudaStream_t
,
cudaError_t
)
{
callback
();
});
}
template
<
typename
Callback
>
inline
void
AddCallbackWithStreamAndErrorInfo
(
Callback
&&
callback
)
const
{
auto
*
stream_callback_context
=
new
StreamCallbackContext
(
this
,
callback
);
PADDLE_ENFORCE
(
cudaStreamAddCallback
(
stream_
,
StreamCallbackManager
::
StreamCallbackFunc
,
stream_callback_context
,
0
));
auto
*
stream_callback_context
=
new
StreamCallbackContext
(
this
,
std
::
forward
<
Callback
>
(
callback
));
PADDLE_ENFORCE
(
#if CUDA_VERSION >= 10000
cudaLaunchHostFunc
(
stream_
,
StreamCallbackManager
::
StreamCallbackFunc
,
stream_callback_context
)
#else
cudaStreamAddCallback
(
stream_
,
StreamCallbackManager
::
StreamCallbackFunc
,
stream_callback_context
,
0
)
#endif
);
// NOLINT
}
void
Wait
()
const
{
thread_pool_
.
reset
(
new
ThreadPool
(
1
));
}
...
...
@@ -63,17 +63,21 @@ class StreamCallbackManager {
const
cudaStream_t
stream_
;
mutable
std
::
unique_ptr
<
ThreadPool
>
thread_pool_
;
// cudaStreamCallback cannot call CUDA API inside, so we have to use
// thread_pool here
// cudaStreamCallback cannot call CUDA API inside, so we have to use
// thread_pool here
#if CUDA_VERSION >= 10000
static
void
CUDART_CB
StreamCallbackFunc
(
void
*
user_data
)
#else
static
void
CUDART_CB
StreamCallbackFunc
(
cudaStream_t
stream
,
cudaError_t
status
,
void
*
user_data
)
{
cudaError_t
status
,
void
*
user_data
)
#endif
{
auto
*
callback_context_ptr
=
reinterpret_cast
<
StreamCallbackContext
*>
(
user_data
);
callback_context_ptr
->
manager_
->
thread_pool_
->
enqueue
([
=
]()
{
std
::
unique_ptr
<
StreamCallbackContext
>
callback_context
(
callback_context_ptr
);
callback_context
->
callback_
(
stream
,
status
);
callback_context
->
callback_
();
});
}
};
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
005fc8f4
...
...
@@ -822,13 +822,24 @@ All parameter, weight, gradient are variables in Paddle.
[](
BuildStrategy
&
self
,
bool
b
)
{
self
.
enable_data_balance_
=
b
;
})
// FIXME(chengudo): enable_data_balance seems not important
.
def_property
(
"enable_sequential_execution"
,
[](
const
BuildStrategy
&
self
)
{
return
self
.
enable_sequential_execution_
;
},
[](
BuildStrategy
&
self
,
bool
b
)
{
self
.
enable_sequential_execution_
=
b
;
})
.
def_property
(
"enable_sequential_execution"
,
[](
const
BuildStrategy
&
self
)
{
return
self
.
enable_sequential_execution_
;
},
[](
BuildStrategy
&
self
,
bool
b
)
{
self
.
enable_sequential_execution_
=
b
;
},
R"DOC(The type is BOOL. If set True, the execution order of ops would be the same as what is in the program. Default False.)DOC"
)
.
def_property
(
"remove_unnecessary_lock"
,
[](
const
BuildStrategy
&
self
)
{
return
self
.
remove_unnecessary_lock_
;
},
[](
BuildStrategy
&
self
,
bool
b
)
{
self
.
remove_unnecessary_lock_
=
b
;
},
R"DOC(The type is BOOL. If set True, some locks in GPU ops would be released and ParallelExecutor would run faster. Default False.)DOC"
)
.
def_property
(
"fuse_elewise_add_act_ops"
,
[](
const
BuildStrategy
&
self
)
{
...
...
python/paddle/fluid/tests/unittests/CMakeLists.txt
浏览文件 @
005fc8f4
...
...
@@ -86,6 +86,8 @@ if(WITH_DISTRIBUTE)
# FIXME(typhoonzero): add this back
#py_test_modules(test_dist_transformer MODULES test_dist_transformer)
#set_tests_properties(test_dist_transformer PROPERTIES TIMEOUT 1000)
# TODO(typhoonzero): make dist test parallel when fix port management issue
set_tests_properties
(
test_dist_mnist test_dist_word2vec test_dist_se_resnext test_dist_ctr test_dist_simnet_bow test_dist_save_load test_dist_text_classification test_dist_mnist_batch_merge PROPERTIES RUN_SERIAL TRUE
)
endif
(
NOT APPLE
)
py_test_modules
(
test_dist_transpiler MODULES test_dist_transpiler
)
endif
()
...
...
python/paddle/fluid/tests/unittests/parallel_executor_test_base.py
浏览文件 @
005fc8f4
...
...
@@ -18,6 +18,7 @@ import multiprocessing
import
os
import
unittest
import
paddle.fluid
as
fluid
import
paddle.fluid.core
as
core
import
time
import
numpy
as
np
import
math
...
...
@@ -82,6 +83,8 @@ class TestParallelExecutorBase(unittest.TestCase):
if
use_reduce
else
fluid
.
BuildStrategy
.
ReduceStrategy
.
AllReduce
build_strategy
.
fuse_elewise_add_act_ops
=
fuse_elewise_add_act_ops
build_strategy
.
enable_sequential_execution
=
enable_sequential_execution
if
use_cuda
and
core
.
is_compiled_with_cuda
():
build_strategy
.
remove_unnecessary_lock
=
True
if
use_parallel_executor
:
exe
=
fluid
.
ParallelExecutor
(
...
...
python/paddle/fluid/tests/unittests/test_parallel_executor_crf.py
浏览文件 @
005fc8f4
...
...
@@ -174,7 +174,6 @@ class TestCRFModel(unittest.TestCase):
print
(
pe
.
run
(
feed
=
feeder
.
feed
(
cur_batch
),
fetch_list
=
[
avg_cost
.
name
])[
0
])
@
unittest
.
skip
(
reason
=
"CI hangs"
)
def
test_update_sparse_parameter_all_reduce
(
self
):
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
reduce_strategy
=
fluid
.
BuildStrategy
.
ReduceStrategy
.
AllReduce
...
...
@@ -183,7 +182,6 @@ class TestCRFModel(unittest.TestCase):
self
.
check_network_convergence
(
is_sparse
=
True
,
build_strategy
=
build_strategy
,
use_cuda
=
False
)
@
unittest
.
skip
(
reason
=
"CI hangs"
)
def
test_update_dense_parameter_all_reduce
(
self
):
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
reduce_strategy
=
fluid
.
BuildStrategy
.
ReduceStrategy
.
AllReduce
...
...
@@ -192,7 +190,6 @@ class TestCRFModel(unittest.TestCase):
self
.
check_network_convergence
(
is_sparse
=
False
,
build_strategy
=
build_strategy
,
use_cuda
=
False
)
@
unittest
.
skip
(
reason
=
"CI hangs"
)
def
test_update_sparse_parameter_reduce
(
self
):
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
reduce_strategy
=
fluid
.
BuildStrategy
.
ReduceStrategy
.
Reduce
...
...
@@ -201,7 +198,6 @@ class TestCRFModel(unittest.TestCase):
self
.
check_network_convergence
(
is_sparse
=
True
,
build_strategy
=
build_strategy
,
use_cuda
=
False
)
@
unittest
.
skip
(
reason
=
"CI hangs"
)
def
test_update_dense_parameter_reduce
(
self
):
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
reduce_strategy
=
fluid
.
BuildStrategy
.
ReduceStrategy
.
Reduce
...
...
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