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68a07328
编写于
1月 07, 2019
作者:
M
minqiyang
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 add_pyramid_dnn_support
test=develop
上级
00e4de04
317840d3
变更
56
展开全部
显示空白变更内容
内联
并排
Showing
56 changed file
with
1533 addition
and
978 deletion
+1533
-978
cmake/configure.cmake
cmake/configure.cmake
+1
-0
cmake/external/ngraph.cmake
cmake/external/ngraph.cmake
+1
-1
paddle/fluid/framework/details/build_strategy.cc
paddle/fluid/framework/details/build_strategy.cc
+39
-15
paddle/fluid/framework/details/build_strategy.h
paddle/fluid/framework/details/build_strategy.h
+6
-2
paddle/fluid/framework/details/multi_devices_graph_check_pass.cc
...fluid/framework/details/multi_devices_graph_check_pass.cc
+57
-47
paddle/fluid/framework/details/multi_devices_graph_pass.cc
paddle/fluid/framework/details/multi_devices_graph_pass.cc
+475
-389
paddle/fluid/framework/details/multi_devices_graph_pass.h
paddle/fluid/framework/details/multi_devices_graph_pass.h
+106
-38
paddle/fluid/framework/naive_executor.cc
paddle/fluid/framework/naive_executor.cc
+8
-8
paddle/fluid/framework/ngraph_operator.cc
paddle/fluid/framework/ngraph_operator.cc
+1
-1
paddle/fluid/inference/analysis/argument.h
paddle/fluid/inference/analysis/argument.h
+0
-2
paddle/fluid/inference/analysis/ir_pass_manager.cc
paddle/fluid/inference/analysis/ir_pass_manager.cc
+0
-10
paddle/fluid/inference/analysis/ir_passes/CMakeLists.txt
paddle/fluid/inference/analysis/ir_passes/CMakeLists.txt
+11
-7
paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
...id/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
+5
-3
paddle/fluid/inference/analysis/passes/ir_analysis_compose_pass.cc
...uid/inference/analysis/passes/ir_analysis_compose_pass.cc
+0
-23
paddle/fluid/inference/analysis/passes/ir_analysis_compose_pass.h
...luid/inference/analysis/passes/ir_analysis_compose_pass.h
+0
-2
paddle/fluid/inference/api/analysis_config.cc
paddle/fluid/inference/api/analysis_config.cc
+154
-66
paddle/fluid/inference/api/analysis_predictor.cc
paddle/fluid/inference/api/analysis_predictor.cc
+46
-37
paddle/fluid/inference/api/analysis_predictor_tester.cc
paddle/fluid/inference/api/analysis_predictor_tester.cc
+15
-15
paddle/fluid/inference/api/api_anakin_engine.h
paddle/fluid/inference/api/api_anakin_engine.h
+0
-2
paddle/fluid/inference/api/api_impl.cc
paddle/fluid/inference/api/api_impl.cc
+1
-1
paddle/fluid/inference/api/api_impl_tester.cc
paddle/fluid/inference/api/api_impl_tester.cc
+2
-1
paddle/fluid/inference/api/demo_ci/trt_mobilenet_demo.cc
paddle/fluid/inference/api/demo_ci/trt_mobilenet_demo.cc
+4
-5
paddle/fluid/inference/api/demo_ci/vis_demo.cc
paddle/fluid/inference/api/demo_ci/vis_demo.cc
+6
-7
paddle/fluid/inference/api/paddle_analysis_config.h
paddle/fluid/inference/api/paddle_analysis_config.h
+88
-21
paddle/fluid/inference/api/paddle_inference_api.h
paddle/fluid/inference/api/paddle_inference_api.h
+2
-3
paddle/fluid/inference/api/paddle_pass_builder.h
paddle/fluid/inference/api/paddle_pass_builder.h
+11
-1
paddle/fluid/inference/tensorrt/CMakeLists.txt
paddle/fluid/inference/tensorrt/CMakeLists.txt
+1
-0
paddle/fluid/inference/tensorrt/op_teller.cc
paddle/fluid/inference/tensorrt/op_teller.cc
+49
-0
paddle/fluid/inference/tensorrt/op_teller.h
paddle/fluid/inference/tensorrt/op_teller.h
+68
-0
paddle/fluid/inference/tests/api/analyzer_dam_tester.cc
paddle/fluid/inference/tests/api/analyzer_dam_tester.cc
+3
-6
paddle/fluid/inference/tests/api/analyzer_lac_tester.cc
paddle/fluid/inference/tests/api/analyzer_lac_tester.cc
+4
-5
paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc
paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc
+4
-5
paddle/fluid/inference/tests/api/analyzer_ner_tester.cc
paddle/fluid/inference/tests/api/analyzer_ner_tester.cc
+5
-6
paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
+4
-6
paddle/fluid/inference/tests/api/analyzer_rnn1_tester.cc
paddle/fluid/inference/tests/api/analyzer_rnn1_tester.cc
+14
-14
paddle/fluid/inference/tests/api/analyzer_rnn2_tester.cc
paddle/fluid/inference/tests/api/analyzer_rnn2_tester.cc
+4
-6
paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc
...le/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc
+4
-5
paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc
...le/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc
+3
-6
paddle/fluid/inference/tests/api/analyzer_text_classification_tester.cc
...nference/tests/api/analyzer_text_classification_tester.cc
+4
-5
paddle/fluid/inference/tests/api/analyzer_vis_tester.cc
paddle/fluid/inference/tests/api/analyzer_vis_tester.cc
+5
-6
paddle/fluid/inference/tests/api/config_printer.h
paddle/fluid/inference/tests/api/config_printer.h
+10
-6
paddle/fluid/inference/tests/api/tester_helper.h
paddle/fluid/inference/tests/api/tester_helper.h
+4
-1
paddle/fluid/inference/tests/api/trt_models_tester.cc
paddle/fluid/inference/tests/api/trt_models_tester.cc
+12
-12
paddle/fluid/operators/conv_mkldnn_op.cc
paddle/fluid/operators/conv_mkldnn_op.cc
+46
-23
paddle/fluid/operators/linear_chain_crf_op.cc
paddle/fluid/operators/linear_chain_crf_op.cc
+2
-0
paddle/fluid/operators/math/blas_impl.cu.h
paddle/fluid/operators/math/blas_impl.cu.h
+64
-70
paddle/fluid/operators/optimizers/adam_op.h
paddle/fluid/operators/optimizers/adam_op.h
+10
-3
paddle/fluid/platform/cuda_helper.h
paddle/fluid/platform/cuda_helper.h
+58
-0
paddle/fluid/platform/device_context.cc
paddle/fluid/platform/device_context.cc
+13
-5
paddle/fluid/platform/device_context.h
paddle/fluid/platform/device_context.h
+24
-52
paddle/fluid/platform/device_context_test.cu
paddle/fluid/platform/device_context_test.cu
+0
-3
paddle/fluid/platform/mkldnn_reuse.h
paddle/fluid/platform/mkldnn_reuse.h
+5
-3
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+4
-7
python/paddle/fluid/parallel_executor.py
python/paddle/fluid/parallel_executor.py
+14
-0
python/paddle/fluid/tests/unittests/test_conv2d_int8_mkldnn_op.py
...addle/fluid/tests/unittests/test_conv2d_int8_mkldnn_op.py
+56
-14
python/paddle/fluid/tests/unittests/test_reader_reset.py
python/paddle/fluid/tests/unittests/test_reader_reset.py
+0
-2
未找到文件。
cmake/configure.cmake
浏览文件 @
68a07328
...
...
@@ -134,6 +134,7 @@ if(WITH_GPU)
message
(
WARNING
"Anakin needs CUDNN >= 7.0 to compile. Force WITH_ANAKIN=OFF"
)
set
(
WITH_ANAKIN OFF CACHE STRING
"Anakin is valid only when CUDNN >= 7.0."
FORCE
)
endif
()
add_definitions
(
-DWITH_ANAKIN
)
endif
()
if
(
WITH_ANAKIN
)
# NOTICE(minqiyang): the end slash is important because $CUDNN_INCLUDE_DIR
...
...
cmake/external/ngraph.cmake
浏览文件 @
68a07328
...
...
@@ -37,7 +37,7 @@ INCLUDE(GNUInstallDirs)
INCLUDE
(
ExternalProject
)
SET
(
NGRAPH_PROJECT
"extern_ngraph"
)
SET
(
NGRAPH_GIT_TAG
"
v0.10.1
"
)
SET
(
NGRAPH_GIT_TAG
"
08851c2c45fcf9fa9c74871dd3dbc3fe38f37cc9
"
)
SET
(
NGRAPH_SOURCES_DIR
${
THIRD_PARTY_PATH
}
/ngraph
)
SET
(
NGRAPH_INSTALL_DIR
${
THIRD_PARTY_PATH
}
/install/ngraph
)
SET
(
NGRAPH_INC_DIR
${
NGRAPH_INSTALL_DIR
}
/include
)
...
...
paddle/fluid/framework/details/build_strategy.cc
浏览文件 @
68a07328
...
...
@@ -18,7 +18,7 @@ limitations under the License. */
#include <memory>
#include "paddle/fluid/framework/details/memory_reuse_types.h"
#include "paddle/fluid/framework/details/multi_devices_graph_
check_
pass.h"
#include "paddle/fluid/framework/details/multi_devices_graph_pass.h"
#include "paddle/fluid/framework/details/multi_devices_graph_print_pass.h"
#include "paddle/fluid/framework/details/reduce_op_handle.h"
#include "paddle/fluid/framework/details/sequential_execution_pass.h"
...
...
@@ -86,10 +86,8 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
if
(
strategy
.
memory_optimize_
)
{
auto
analysis_var_pass
=
AppendPass
(
"analysis_var_pass"
);
}
// Convert graph to run on multi-devices.
auto
multi_devices_pass
=
AppendPass
(
"multi_devices_pass"
);
multi_devices_pass
->
SetNotOwned
<
const
BuildStrategy
>
(
"strategy"
,
&
strategy_
);
AppendMultiDevPass
(
strategy
);
// Add a graph print pass to record a graph with device info.
if
(
!
strategy_
.
debug_graphviz_path_
.
empty
())
{
...
...
@@ -115,6 +113,25 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
}
}
// Convert graph to run on multi-devices.
void
AppendMultiDevPass
(
const
BuildStrategy
&
strategy
)
{
ir
::
Pass
*
multi_devices_pass
;
if
(
strategy_
.
is_distribution_
)
{
multi_devices_pass
=
AppendPass
(
"dist_multi_devices_pass"
).
get
();
}
else
{
if
(
strategy
.
reduce_
==
BuildStrategy
::
ReduceStrategy
::
kAllReduce
)
{
multi_devices_pass
=
AppendPass
(
"allreduce_mode_multi_devices_pass"
).
get
();
}
else
if
(
strategy
.
reduce_
==
BuildStrategy
::
ReduceStrategy
::
kReduce
)
{
multi_devices_pass
=
AppendPass
(
"reduce_mode_multi_devices_pass"
).
get
();
}
else
{
PADDLE_THROW
(
"Unknown reduce strategy."
);
}
}
multi_devices_pass
->
SetNotOwned
<
const
BuildStrategy
>
(
"strategy"
,
&
strategy_
);
}
private:
BuildStrategy
strategy_
;
};
...
...
@@ -131,6 +148,10 @@ std::shared_ptr<ir::PassBuilder> BuildStrategy::CreatePassesFromStrategy(
return
pass_builder_
;
}
bool
BuildStrategy
::
IsMultiDevPass
(
const
std
::
string
&
pass_name
)
const
{
return
framework
::
details
::
MultiDevSSAGraphBuilder
().
count
(
pass_name
)
>
0
;
}
std
::
unique_ptr
<
ir
::
Graph
>
BuildStrategy
::
Apply
(
const
ProgramDesc
&
main_program
,
const
std
::
vector
<
platform
::
Place
>
&
places
,
const
std
::
string
&
loss_var_name
,
const
std
::
vector
<
Scope
*>
&
local_scopes
,
...
...
@@ -145,22 +166,23 @@ std::unique_ptr<ir::Graph> BuildStrategy::Apply(
std
::
unique_ptr
<
ir
::
Graph
>
graph
(
new
ir
::
Graph
(
main_program
));
for
(
std
::
shared_ptr
<
ir
::
Pass
>
&
pass
:
pass_builder_
->
AllPasses
())
{
if
(
pass
->
Type
()
==
"multi_devices_pass"
)
{
pass
->
Erase
(
"places"
);
pass
->
SetNotOwned
<
const
std
::
vector
<
platform
::
Place
>>
(
"places"
,
&
places
);
pass
->
Erase
(
"loss_var_name"
);
pass
->
SetNotOwned
<
const
std
::
string
>
(
"loss_var_name"
,
&
loss_var_name
);
pass
->
Erase
(
"local_scopes"
);
pass
->
SetNotOwned
<
const
std
::
vector
<
Scope
*>>
(
"local_scopes"
,
if
(
IsMultiDevPass
(
pass
->
Type
())
)
{
pass
->
Erase
(
kPlaces
);
pass
->
SetNotOwned
<
const
std
::
vector
<
platform
::
Place
>>
(
kPlaces
,
&
places
);
pass
->
Erase
(
kLossVarName
);
pass
->
SetNotOwned
<
const
std
::
string
>
(
kLossVarName
,
&
loss_var_name
);
pass
->
Erase
(
kLocalScopes
);
pass
->
SetNotOwned
<
const
std
::
vector
<
Scope
*>>
(
kLocalScopes
,
&
local_scopes
);
pass
->
Erase
(
"nranks"
);
pass
->
Set
<
size_t
>
(
"nranks"
,
new
size_t
(
nranks
));
pass
->
Erase
(
kNRanks
);
pass
->
Set
<
size_t
>
(
kNRanks
,
new
size_t
(
nranks
));
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
platform
::
NCCLContextMap
*
nctx
=
use_cuda
?
nccl_ctxs
:
nullptr
;
pass
->
Erase
(
"nccl_ctxs"
);
pass
->
SetNotOwned
<
platform
::
NCCLContextMap
>
(
"nccl_ctxs"
,
nctx
);
#endif
}
else
if
(
pass
->
Type
()
==
"analysis_var_pass"
)
{
const
std
::
vector
<
OpDesc
*>
*
all_op_descs
=
new
std
::
vector
<
OpDesc
*>
(
main_program
.
Block
(
0
).
AllOps
());
...
...
@@ -201,7 +223,9 @@ std::unique_ptr<ir::Graph> BuildStrategy::Apply(
USE_PASS
(
fuse_elewise_add_act_pass
);
USE_PASS
(
graph_viz_pass
);
USE_PASS
(
multi_batch_merge_pass
);
USE_PASS
(
multi_devices_pass
);
USE_PASS
(
reduce_mode_multi_devices_pass
);
USE_PASS
(
allreduce_mode_multi_devices_pass
);
USE_PASS
(
dist_multi_devices_pass
);
USE_PASS
(
multi_devices_check_pass
);
USE_PASS
(
multi_devices_print_pass
);
USE_PASS
(
analysis_var_pass
);
...
...
paddle/fluid/framework/details/build_strategy.h
浏览文件 @
68a07328
...
...
@@ -74,8 +74,6 @@ struct BuildStrategy {
bool
fuse_elewise_add_act_ops_
{
false
};
bool
enable_data_balance_
{
false
};
bool
memory_optimize_
{
false
};
bool
memory_early_delete_
{
false
};
...
...
@@ -84,6 +82,10 @@ struct BuildStrategy {
bool
fuse_broadcast_op_
{
false
};
// FIXME(zcd): is_distribution_ is a temporary field, because in pserver mode,
// num_trainers is 1, so the current fields of build_strategy doesn't tell if
// it's distributed model.
bool
is_distribution_
{
false
};
int
num_trainers_
{
1
};
int
trainer_id_
{
0
};
std
::
vector
<
std
::
string
>
trainers_endpoints_
;
...
...
@@ -104,6 +106,8 @@ struct BuildStrategy {
bool
IsFinalized
()
const
{
return
is_finalized_
;
}
bool
IsMultiDevPass
(
const
std
::
string
&
pass_name
)
const
;
// Apply the passes built by the pass_builder_. The passes will be
// applied to the Program and output an ir::Graph.
std
::
unique_ptr
<
ir
::
Graph
>
Apply
(
const
ProgramDesc
&
main_program
,
...
...
paddle/fluid/framework/details/multi_devices_graph_check_pass.cc
浏览文件 @
68a07328
...
...
@@ -12,8 +12,8 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "paddle/fluid/framework/details/multi_devices_graph_check_pass.h"
#include <string>
#include "paddle/fluid/framework/details/multi_devices_helper.h"
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/graph_helper.h"
...
...
@@ -21,7 +21,15 @@ namespace paddle {
namespace
framework
{
namespace
details
{
bool
SSAGraghBuilderWithChecker
::
IsValidGraph
(
const
ir
::
Graph
*
graph
)
const
{
class
SSAGraghBuilderWithChecker
:
public
ir
::
Pass
{
protected:
std
::
unique_ptr
<
ir
::
Graph
>
ApplyImpl
(
std
::
unique_ptr
<
ir
::
Graph
>
graph
)
const
override
{
PADDLE_ENFORCE
(
IsValidGraph
(
graph
.
get
()));
return
graph
;
}
bool
IsValidGraph
(
const
ir
::
Graph
*
graph
)
const
{
std
::
unordered_map
<
OpHandleBase
*
,
size_t
>
pending_ops
;
std
::
unordered_set
<
VarHandleBase
*>
pending_vars
;
std
::
unordered_set
<
VarHandleBase
*>
ready_vars
;
...
...
@@ -82,7 +90,9 @@ bool SSAGraghBuilderWithChecker::IsValidGraph(const ir::Graph *graph) const {
ready_vars
.
clear
();
}
return
true
;
}
}
};
}
// namespace details
}
// namespace framework
}
// namespace paddle
...
...
paddle/fluid/framework/details/multi_devices_graph_pass.cc
浏览文件 @
68a07328
此差异已折叠。
点击以展开。
paddle/fluid/framework/details/multi_devices_graph_pass.h
浏览文件 @
68a07328
...
...
@@ -13,6 +13,7 @@
// limitations under the License.
#pragma once
#include <string>
#include <utility>
#include <vector>
...
...
@@ -30,78 +31,70 @@ namespace framework {
class
Scope
;
namespace
details
{
class
MultiDevSSAGraphBuilder
:
public
ir
::
Pass
{
constexpr
char
kLossVarName
[]
=
"loss_var_name"
;
constexpr
char
kPlaces
[]
=
"places"
;
constexpr
char
kLocalScopes
[]
=
"local_scopes"
;
constexpr
char
kStrategy
[]
=
"strategy"
;
constexpr
char
kNRanks
[]
=
"nranks"
;
class
MultiDevSSAGraphBuilderBase
:
public
ir
::
Pass
{
protected:
std
::
unique_ptr
<
ir
::
Graph
>
ApplyImpl
(
std
::
unique_ptr
<
ir
::
Graph
>
graph
)
const
override
;
private:
void
CreateOpHandleIOs
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
,
size_t
device_id
)
const
;
void
Init
()
const
;
virtual
void
Init
()
const
;
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
mutable
platform
::
NCCLContextMap
*
nccl_ctxs_
;
#endif
virtual
std
::
vector
<
ir
::
Node
*>
SortOperations
(
const
ir
::
Graph
&
graph
)
const
;
int
GetVarDeviceID
(
const
std
::
string
&
varname
,
const
std
::
unordered_map
<
std
::
string
,
int
>
&
sharded_var_device
)
const
;
virtual
void
InsertCollectiveOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
p_name
,
const
std
::
string
&
g_name
)
const
=
0
;
bool
IsScaleLossOp
(
ir
::
Node
*
node
)
const
;
virtual
bool
DealWithSpecialOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
)
const
=
0
;
virtual
void
InsertPostprocessOps
(
ir
::
Graph
*
result
)
const
=
0
;
int
CreateRPCOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
,
std
::
unordered_map
<
std
::
string
,
int
>
*
sharded_var_device
)
const
;
int
CreateDistTrainOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
,
std
::
unordered_map
<
std
::
string
,
int
>
*
sharded_var_device
)
const
;
bool
UseGPU
()
const
;
bool
NeedCollectiveOps
()
const
;
bool
IsScaleLossOp
(
ir
::
Node
*
node
)
const
;
void
CreateComputationalOps
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
,
size_t
num_places
)
const
;
void
CreateScaleLossGradOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
loss_grad_name
,
ir
::
Node
*
out_var_node
,
ir
::
Node
*
out_var_node
,
size_t
loss_scale
,
proto
::
VarType
::
Type
dtype
)
const
;
VarHandle
*
CreateReduceOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
og
,
int
dst_dev_id
)
const
;
void
CreateComputationalOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
,
int
dev_id
)
const
;
int
GetOpDeviceID
(
ir
::
Node
*
node
,
const
std
::
unordered_map
<
std
::
string
,
int
>
&
sharded_var_device
)
const
;
void
InsertAllReduceOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
og
)
const
;
bool
IsSparseGradient
(
const
std
::
string
&
og
)
const
;
void
InsertDataBalanceOp
(
ir
::
Graph
*
result
,
const
std
::
vector
<
std
::
string
>
&
datas
)
const
;
void
CreateAllReduceOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
og
)
const
;
void
CreateBroadcastOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
p_name
,
size_t
src_dev_id
)
const
;
void
InsertScaleLossGradOp
(
ir
::
Graph
*
result
,
const
ir
::
Node
*
node
)
const
;
void
CreateFusedBroadcastOp
(
ir
::
Graph
*
result
,
const
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
&
bcast_varnames
)
const
;
bool
IsSparseGradient
(
const
std
::
string
&
og
)
const
;
size_t
GetAppropriateDeviceID
(
const
std
::
vector
<
std
::
string
>
&
var_names
)
const
;
void
SetCommunicationContext
(
OpHandleBase
*
op_handle
,
const
platform
::
Place
&
p
)
const
;
std
::
vector
<
ir
::
Node
*>
SortForReduceMode
(
const
std
::
vector
<
ir
::
Node
*>
&
)
const
;
void
CreateOpHandleIOs
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
,
size_t
device_id
)
const
;
int
GetOpDeviceID
(
ir
::
Node
*
node
,
const
std
::
unordered_map
<
std
::
string
,
int
>
&
shared_var_device
,
std
::
unordered_map
<
std
::
string
,
std
::
vector
<
ir
::
Node
*>>
*
delay_ops
)
const
;
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
mutable
platform
::
NCCLContextMap
*
nccl_ctxs_
;
#endif
mutable
std
::
string
loss_var_name_
;
mutable
std
::
vector
<
platform
::
Place
>
places_
;
...
...
@@ -109,8 +102,83 @@ class MultiDevSSAGraphBuilder : public ir::Pass {
mutable
BuildStrategy
strategy_
;
mutable
std
::
unordered_map
<
std
::
string
,
VarDesc
*>
all_vars_
;
};
class
AllReduceSSAGraphBuilder
:
public
MultiDevSSAGraphBuilderBase
{
protected:
virtual
void
InsertCollectiveOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
p_name
,
const
std
::
string
&
g_name
)
const
;
virtual
bool
DealWithSpecialOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
)
const
{
return
false
;
}
virtual
void
InsertPostprocessOps
(
ir
::
Graph
*
result
)
const
{}
};
class
BalanceVarSSAGraphBuilder
:
public
MultiDevSSAGraphBuilderBase
{
protected:
int
GetVarDeviceID
(
const
std
::
string
&
varname
)
const
;
int
GetOpDeviceID
(
ir
::
Node
*
node
)
const
;
size_t
GetAppropriateDeviceID
(
const
std
::
vector
<
std
::
string
>
&
var_names
)
const
;
virtual
void
ResetState
()
const
;
mutable
std
::
unordered_map
<
std
::
string
,
int
>
sharded_var_device_
;
mutable
std
::
vector
<
int64_t
>
balance_vars_
;
};
class
ReduceSSAGraphBuilder
:
public
BalanceVarSSAGraphBuilder
{
protected:
virtual
void
Init
()
const
;
virtual
void
InsertCollectiveOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
p_name
,
const
std
::
string
&
g_name
)
const
;
virtual
bool
DealWithSpecialOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
)
const
;
virtual
void
InsertPostprocessOps
(
ir
::
Graph
*
result
)
const
;
virtual
std
::
vector
<
ir
::
Node
*>
SortOperations
(
const
ir
::
Graph
&
graph
)
const
;
virtual
void
ResetState
()
const
;
int
GetOpDeviceID
(
ir
::
Node
*
node
,
std
::
unordered_map
<
std
::
string
,
std
::
vector
<
ir
::
Node
*>>
*
delay_ops
)
const
;
std
::
vector
<
ir
::
Node
*>
SortForReduceMode
(
const
std
::
vector
<
ir
::
Node
*>
&
topo_ops
)
const
;
mutable
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
bcast_var_name_set_
;
};
class
DistSSAGraphBuilder
:
public
BalanceVarSSAGraphBuilder
{
protected:
virtual
void
Init
()
const
;
virtual
bool
DealWithSpecialOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
)
const
;
virtual
void
InsertPostprocessOps
(
ir
::
Graph
*
result
)
const
;
virtual
void
InsertCollectiveOp
(
ir
::
Graph
*
result
,
const
std
::
string
&
p_name
,
const
std
::
string
&
g_name
)
const
;
virtual
void
ResetState
()
const
;
int
CreateRPCOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
)
const
;
int
CreateDistTrainOp
(
ir
::
Graph
*
result
,
ir
::
Node
*
node
)
const
;
mutable
std
::
vector
<
std
::
unordered_set
<
std
::
string
>>
bcast_var_name_set_
;
mutable
bool
need_broadcast_var_
{
false
};
};
std
::
unordered_set
<
std
::
string
>
&
MultiDevSSAGraphBuilder
();
}
// namespace details
}
// namespace framework
}
// namespace paddle
paddle/fluid/framework/naive_executor.cc
浏览文件 @
68a07328
...
...
@@ -40,12 +40,12 @@ void NaiveExecutor::Prepare(Scope *scope, const ProgramDesc &program_desc,
void
NaiveExecutor
::
Run
()
{
#ifndef PADDLE_ON_INFERENCE
LOG_FIRST_N
(
WARNING
,
1
5
)
<<
"The NaiveExecutor can not work properly if the "
LOG_FIRST_N
(
WARNING
,
5
)
<<
"The NaiveExecutor can not work properly if the "
"cmake flag ON_INFER is not set."
;
LOG_FIRST_N
(
WARNING
,
1
5
)
<<
"Unlike the training phase, all the scopes and "
LOG_FIRST_N
(
WARNING
,
5
)
<<
"Unlike the training phase, all the scopes and "
"variables will be reused to save the allocation "
"overhead."
;
LOG_FIRST_N
(
WARNING
,
1
5
)
<<
"Please re-compile the inference library by "
LOG_FIRST_N
(
WARNING
,
5
)
<<
"Please re-compile the inference library by "
"setting the cmake flag ON_INFER=ON if you are "
"running Paddle Inference"
;
#endif // PADDLE_ON_INFERENCE
...
...
paddle/fluid/framework/ngraph_operator.cc
浏览文件 @
68a07328
...
...
@@ -539,7 +539,7 @@ void NgraphEngine::Run(const Scope& scope, const platform::Place& place) const {
}
}
backend_
->
call
(
ngraph_function_
,
t_out
,
t_in
);
backend_
->
call
(
backend_
->
compile
(
ngraph_function_
)
,
t_out
,
t_in
);
}
// NgraphEngine::RunImpl
}
// namespace framework
}
// namespace paddle
paddle/fluid/inference/analysis/argument.h
浏览文件 @
68a07328
...
...
@@ -123,8 +123,6 @@ struct Argument {
DECL_ARGUMENT_FIELD
(
use_gpu
,
UseGPU
,
bool
);
DECL_ARGUMENT_FIELD
(
gpu_device_id
,
GPUDeviceId
,
int
);
DECL_ARGUMENT_FIELD
(
use_tensorrt
,
UseTensorRT
,
bool
);
DECL_ARGUMENT_FIELD
(
tensorrt_node_teller
,
TensorRtNodeTeller
,
std
::
function
<
bool
(
const
framework
::
ir
::
Node
*
)
>
);
DECL_ARGUMENT_FIELD
(
tensorrt_max_batch_size
,
TensorRtMaxBatchSize
,
int
);
DECL_ARGUMENT_FIELD
(
tensorrt_workspace_size
,
TensorRtWorkspaceSize
,
int
);
DECL_ARGUMENT_FIELD
(
tensorrt_min_subgraph_size
,
TensorRtMinSubgraphSize
,
int
);
...
...
paddle/fluid/inference/analysis/ir_pass_manager.cc
浏览文件 @
68a07328
...
...
@@ -49,13 +49,6 @@ void IRPassManager::CreatePasses(Argument *argument,
for
(
const
std
::
string
&
pass_name
:
passes
)
{
auto
pass
=
framework
::
ir
::
PassRegistry
::
Instance
().
Get
(
pass_name
);
// Set some pass attributes.
if
(
pass_name
==
"ir_analysis_pass"
)
{
pass
->
Set
(
"tensorrt_node_teller"
,
new
SubgraphDetector
::
NodeInsideSubgraphTeller
(
argument
->
tensorrt_node_teller
()));
}
if
(
pass_name
==
"graph_viz_pass"
)
{
std
::
string
dot_file_path
=
std
::
to_string
(
pass_num
)
+
"_ir_"
+
(
pre_pass
.
empty
()
?
"origin"
:
pre_pass
)
+
...
...
@@ -70,9 +63,6 @@ void IRPassManager::CreatePasses(Argument *argument,
}
if
(
pass_name
==
"tensorrt_subgraph_pass"
)
{
PADDLE_ENFORCE
(
argument
->
tensorrt_node_teller_valid
());
pass
->
SetNotOwned
(
"tensorrt_node_teller"
,
argument
->
tensorrt_node_teller_ptr
());
pass
->
Set
(
"workspace_size"
,
new
int
(
argument
->
tensorrt_workspace_size
()));
pass
->
Set
(
"max_batch_size"
,
new
int
(
argument
->
tensorrt_max_batch_size
()));
pass
->
Set
(
"min_subgraph_size"
,
...
...
paddle/fluid/inference/analysis/ir_passes/CMakeLists.txt
浏览文件 @
68a07328
cc_library
(
subgraph_detector SRCS subgraph_detector.cc DEPS proto_desc
)
cc_library
(
tensorrt_subgraph_pass SRCS tensorrt_subgraph_pass.cc DEPS subgraph_detector
)
set
(
analysis_deps
${
analysis_deps
}
if
(
TENSORRT_FOUND
)
cc_library
(
tensorrt_subgraph_pass SRCS tensorrt_subgraph_pass.cc DEPS subgraph_detector tensorrt_op_teller
)
set
(
analysis_deps
${
analysis_deps
}
subgraph_detector tensorrt_subgraph_pass
CACHE INTERNAL
""
)
set
(
pass_file
${
PADDLE_BINARY_DIR
}
/paddle/fluid/inference/api/paddle_inference_pass.h
)
file
(
APPEND
${
pass_file
}
"USE_PASS(tensorrt_subgraph_pass);
\n
"
)
set
(
INFER_IR_PASSES
${
INFER_IR_PASSES
}
tensorrt_subgraph_pass CACHE INTERNAL
""
)
set
(
pass_file
${
PADDLE_BINARY_DIR
}
/paddle/fluid/inference/api/paddle_inference_pass.h
)
file
(
APPEND
${
pass_file
}
"USE_PASS(tensorrt_subgraph_pass);
\n
"
)
set
(
INFER_IR_PASSES
${
INFER_IR_PASSES
}
tensorrt_subgraph_pass CACHE INTERNAL
""
)
endif
()
paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc
浏览文件 @
68a07328
...
...
@@ -20,6 +20,7 @@
#include "paddle/fluid/inference/analysis/helper.h"
#include "paddle/fluid/inference/analysis/ir_passes/subgraph_detector.h"
#include "paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.h"
#include "paddle/fluid/inference/tensorrt/op_teller.h"
namespace
paddle
{
namespace
inference
{
...
...
@@ -35,8 +36,10 @@ std::unique_ptr<framework::ir::Graph> analysis::TensorRtSubgraphPass::ApplyImpl(
std
::
unique_ptr
<
framework
::
ir
::
Graph
>
graph
)
const
{
framework
::
ir
::
FusePassBase
::
Init
(
"tensorrt_subgraph_pass"
,
graph
.
get
());
auto
teller
=
Get
<
SubgraphDetector
::
NodeInsideSubgraphTeller
>
(
"tensorrt_node_teller"
);
auto
teller
=
[](
const
framework
::
ir
::
Node
*
node
)
{
if
(
!
node
->
IsOp
()
||
!
node
->
Op
())
return
false
;
return
tensorrt
::
OpTeller
::
Global
().
Tell
(
node
->
Op
()
->
Type
(),
*
node
->
Op
());
};
SubGraphFuser
fuser
(
graph
.
get
(),
teller
,
Get
<
int
>
(
"min_subgraph_size"
)
/*min subgraph size*/
);
...
...
@@ -232,7 +235,6 @@ std::vector<std::string> ExtractParameters(
REGISTER_PASS
(
tensorrt_subgraph_pass
,
paddle
::
inference
::
analysis
::
TensorRtSubgraphPass
)
.
RequirePassAttr
(
"tensorrt_node_teller"
)
.
RequirePassAttr
(
"max_batch_size"
)
.
RequirePassAttr
(
"workspace_size"
)
.
RequirePassAttr
(
"min_subgraph_size"
);
paddle/fluid/inference/analysis/passes/ir_analysis_compose_pass.cc
浏览文件 @
68a07328
...
...
@@ -27,9 +27,6 @@ namespace analysis {
void
IrAnalysisComposePass
::
RunImpl
(
Argument
*
argument
)
{
ARGUMENT_CHECK_FIELD
(
argument
,
ir_analysis_passes
);
if
(
argument
->
use_tensorrt_valid
()
&&
argument
->
use_tensorrt
())
{
InitTensorRTAttrs
(
argument
);
}
ApplyIrPasses
(
argument
);
CollectFusionStatis
(
argument
);
}
...
...
@@ -38,26 +35,6 @@ std::string IrAnalysisComposePass::repr() const {
return
"ir-analysis-compose-pass"
;
}
void
IrAnalysisComposePass
::
InitTensorRTAttrs
(
Argument
*
argument
)
{
if
(
argument
->
use_tensorrt_valid
()
&&
argument
->
use_tensorrt
())
{
LOG
(
INFO
)
<<
"Initing TensorRT pass"
;
argument
->
SetTensorRtNodeTeller
([](
const
framework
::
ir
::
Node
*
node
)
{
std
::
unordered_set
<
std
::
string
>
teller_set
(
{
"mul"
,
"conv2d"
,
"pool2d"
,
"relu"
,
"softmax"
,
"sigmoid"
,
"depthwise_conv2d"
,
"batch_norm"
,
"concat"
,
"tanh"
,
"pad"
,
"elementwise_add"
,
"elementwise_mul"
,
"dropout"
,
"split"
,
"prelu"
,
"conv2d_transpose"
,
"leaky_relu"
});
if
(
!
node
->
IsOp
())
return
false
;
if
(
teller_set
.
count
(
node
->
Op
()
->
Type
()))
{
return
true
;
}
else
{
return
false
;
}
});
}
}
void
IrAnalysisComposePass
::
ApplyIrPasses
(
Argument
*
argument
)
{
std
::
vector
<
std
::
string
>
passes
({
"ir_graph_build_pass"
,
"ir_analysis_pass"
,
...
...
paddle/fluid/inference/analysis/passes/ir_analysis_compose_pass.h
浏览文件 @
68a07328
...
...
@@ -33,8 +33,6 @@ class IrAnalysisComposePass : public AnalysisPass {
std
::
string
repr
()
const
override
;
private:
void
InitTensorRTAttrs
(
Argument
*
argument
);
void
ApplyIrPasses
(
Argument
*
argument
);
void
CollectFusionStatis
(
Argument
*
argument
);
...
...
paddle/fluid/inference/api/analysis_config.cc
浏览文件 @
68a07328
...
...
@@ -14,86 +14,101 @@
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/inference/api/paddle_analysis_config.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_pass_builder.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle
_pass_builder.h" // NOLINT
#include "paddle
/fluid/platform/gpu_info.h"
namespace
paddle
{
PassStrategy
*
contrib
::
AnalysisConfig
::
pass_builder
()
const
{
PADDLE_ENFORCE
(
pass_builder_
.
get
(),
"Should call constructor first, that will init the pass_builder_."
);
return
pass_builder_
.
get
();
}
contrib
::
AnalysisConfig
::
AnalysisConfig
(
bool
use_gpu
)
{
this
->
use_gpu
=
use_gpu
;
if
(
use_gpu
)
{
if
(
!
pass_builder_
.
get
())
{
if
(
use_gpu_
)
{
LOG
(
INFO
)
<<
"Create GPU IR passes"
;
pass_builder_
.
reset
(
new
GpuPassStrategy
);
}
else
{
LOG
(
INFO
)
<<
"Create CPU IR passes"
;
pass_builder_
.
reset
(
new
CpuPassStrategy
);
}
}
else
if
(
pass_builder_
->
use_gpu
()
^
use_gpu
())
{
LOG
(
WARNING
)
<<
"The use_gpu flag is not compatible between Config and "
"PassBuilder, the flags are "
<<
use_gpu
()
<<
" "
<<
pass_builder_
->
use_gpu
();
LOG
(
WARNING
)
<<
"Please make them compatible, still use the existing "
"PassBuilder."
;
}
return
pass_builder_
.
get
();
}
contrib
::
AnalysisConfig
::
AnalysisConfig
(
const
std
::
string
&
model_dir
)
{
model_dir_
=
model_dir
;
}
contrib
::
AnalysisConfig
::
AnalysisConfig
(
const
std
::
string
&
prog_file
,
const
std
::
string
&
params_file
)
{
prog_file_
=
prog_file
;
params_file_
=
params_file
;
}
void
contrib
::
AnalysisConfig
::
SetModel
(
const
std
::
string
&
prog_file_path
,
const
std
::
string
&
params_file_path
)
{
prog_file_
=
prog_file_path
;
params_file_
=
params_file_path
;
}
void
contrib
::
AnalysisConfig
::
EnableUseGpu
(
uint64_t
memory_pool_init_size_mb
,
int
device_id
)
{
#ifdef PADDLE_WITH_CUDA
use_gpu_
=
true
;
memory_pool_init_size_mb_
=
memory_pool_init_size_mb
;
device_id_
=
device_id
;
#else
LOG
(
ERROR
)
<<
"Please compile with gpu to EnableGpu"
;
use_gpu_
=
false
;
#endif
}
void
contrib
::
AnalysisConfig
::
DisableGpu
()
{
use_gpu_
=
false
;
}
contrib
::
AnalysisConfig
::
AnalysisConfig
(
const
contrib
::
AnalysisConfig
&
other
)
{
// fields from Config
model_dir
=
other
.
model_dir
;
// fields from NativeConfig
use_gpu
=
other
.
use_gpu
;
device
=
other
.
device
;
fraction_of_gpu_memory
=
other
.
fraction_of_gpu_memory
;
prog_file
=
other
.
prog_file
;
param_file
=
other
.
param_file
;
specify_input_name
=
other
.
specify_input_name
;
cpu_math_library_num_threads_
=
other
.
cpu_math_library_num_threads_
;
// fields from this.
enable_ir_optim
=
other
.
enable_ir_optim
;
// For mkldnn
use_mkldnn_
=
other
.
use_mkldnn_
;
mkldnn_enabled_op_types_
=
other
.
mkldnn_enabled_op_types_
;
use_feed_fetch_ops
=
other
.
use_feed_fetch_ops
;
use_tensorrt_
=
other
.
use_tensorrt_
;
tensorrt_max_batchsize_
=
other
.
tensorrt_max_batchsize_
;
tensorrt_workspace_size_
=
other
.
tensorrt_workspace_size_
;
tensorrt_min_subgraph_size_
=
other
.
tensorrt_min_subgraph_size_
;
model_from_memory_
=
other
.
model_from_memory_
;
if
(
use_gpu
)
{
#define CP_MEMBER(member__) member__ = other.member__;
// Model related.
CP_MEMBER
(
model_dir_
);
CP_MEMBER
(
prog_file_
);
CP_MEMBER
(
params_file_
);
CP_MEMBER
(
model_from_memory_
);
// the memory model reuses prog_file_ and
// params_file_ fields.
// Gpu releated.
CP_MEMBER
(
use_gpu_
);
CP_MEMBER
(
device_id_
);
CP_MEMBER
(
memory_pool_init_size_mb_
);
// TensorRT releated.
CP_MEMBER
(
use_tensorrt_
);
CP_MEMBER
(
tensorrt_workspace_size_
);
CP_MEMBER
(
tensorrt_max_batchsize_
);
CP_MEMBER
(
tensorrt_min_subgraph_size_
);
// MKLDNN releated.
CP_MEMBER
(
use_mkldnn_
);
CP_MEMBER
(
mkldnn_enabled_op_types_
);
// Ir related.
CP_MEMBER
(
enable_ir_optim_
);
CP_MEMBER
(
use_feed_fetch_ops_
);
CP_MEMBER
(
ir_debug_
);
CP_MEMBER
(
specify_input_name_
);
CP_MEMBER
(
cpu_math_library_num_threads_
);
CP_MEMBER
(
serialized_info_cache_
);
if
(
use_gpu_
)
{
pass_builder_
.
reset
(
new
GpuPassStrategy
(
*
static_cast
<
GpuPassStrategy
*>
(
other
.
pass_builder
())));
}
else
{
pass_builder_
.
reset
(
new
CpuPassStrategy
(
*
static_cast
<
CpuPassStrategy
*>
(
other
.
pass_builder
())));
}
}
contrib
::
AnalysisConfig
::
AnalysisConfig
(
contrib
::
AnalysisConfig
&&
other
)
{
// fields from Config
model_dir
=
other
.
model_dir
;
// fields from NativeConfig
use_gpu
=
other
.
use_gpu
;
device
=
other
.
device
;
fraction_of_gpu_memory
=
other
.
fraction_of_gpu_memory
;
prog_file
=
other
.
prog_file
;
param_file
=
other
.
param_file
;
specify_input_name
=
other
.
specify_input_name
;
cpu_math_library_num_threads_
=
other
.
cpu_math_library_num_threads_
;
// fields from this.
enable_ir_optim
=
other
.
enable_ir_optim
;
// For mkldnn
use_mkldnn_
=
other
.
use_mkldnn_
;
mkldnn_enabled_op_types_
=
other
.
mkldnn_enabled_op_types_
;
use_feed_fetch_ops
=
other
.
use_feed_fetch_ops
;
use_tensorrt_
=
other
.
use_tensorrt_
;
tensorrt_max_batchsize_
=
other
.
tensorrt_max_batchsize_
;
tensorrt_workspace_size_
=
other
.
tensorrt_workspace_size_
;
tensorrt_min_subgraph_size_
=
other
.
tensorrt_min_subgraph_size_
;
model_from_memory_
=
other
.
model_from_memory_
;
pass_builder_
=
std
::
move
(
other
.
pass_builder_
);
#undef CP_MEMBER
}
void
contrib
::
AnalysisConfig
::
EnableMKLDNN
()
{
...
...
@@ -112,17 +127,90 @@ void contrib::AnalysisConfig::EnableTensorRtEngine(int workspace_size,
use_tensorrt_
=
true
;
tensorrt_workspace_size_
=
workspace_size
;
tensorrt_max_batchsize_
=
max_batch_size
;
tensorrt_min_subgraph_size_
=
min_subgraph_size
;
// Append after the conv+affine_channel fuse pass.
pass_builder
()
->
InsertPass
(
3
,
"tensorrt_subgraph_pass"
);
}
void
contrib
::
AnalysisConfig
::
Update
()
{
auto
info
=
SerializeInfoCache
();
if
(
info
==
serialized_info_cache_
)
return
;
if
(
use_gpu_
)
{
pass_builder_
.
reset
(
new
GpuPassStrategy
);
}
else
{
pass_builder_
.
reset
(
new
CpuPassStrategy
);
}
if
(
use_tensorrt_
)
{
if
(
!
use_gpu_
)
{
LOG
(
ERROR
)
<<
"TensorRT engine is not available when EnableGpu() not actived."
;
}
else
{
// Append after the infer_clean pass.
pass_builder
()
->
InsertPass
(
1
,
"tensorrt_subgraph_pass"
);
}
}
if
(
use_mkldnn_
)
{
if
(
!
enable_ir_optim_
)
{
LOG
(
ERROR
)
<<
"EnableMKLDNN() only works when IR optimization is enabled."
;
}
#ifdef PADDLE_WITH_MKLDNN
pass_builder
()
->
EnableMKLDNN
();
use_mkldnn_
=
true
;
#else
LOG
(
ERROR
)
<<
"Please compile with MKLDNN first to use MKLDNN"
;
use_mkldnn_
=
false
;
#endif
}
if
(
ir_debug_
)
{
pass_builder
()
->
TurnOnDebug
();
}
}
std
::
string
contrib
::
AnalysisConfig
::
SerializeInfoCache
()
{
std
::
stringstream
ss
;
ss
<<
use_gpu_
;
ss
<<
memory_pool_init_size_mb_
;
ss
<<
use_tensorrt_
;
ss
<<
tensorrt_workspace_size_
;
ss
<<
tensorrt_max_batchsize_
;
ss
<<
use_mkldnn_
;
ss
<<
enable_ir_optim_
;
ss
<<
use_feed_fetch_ops_
;
ss
<<
ir_debug_
;
return
ss
.
str
();
}
void
contrib
::
AnalysisConfig
::
SetCpuMathLibraryNumThreads
(
int
cpu_math_library_num_threads
)
{
cpu_math_library_num_threads_
=
cpu_math_library_num_threads
;
}
float
contrib
::
AnalysisConfig
::
fraction_of_gpu_memory_for_pool
()
const
{
#ifdef PADDLE_WITH_CUDA
// Get the GPU memory details and calculate the fraction of memory for the
// GPU memory pool.
size_t
gpu_used
,
gpu_available
;
platform
::
GpuMemoryUsage
(
&
gpu_used
,
&
gpu_available
);
double
total_gpu_memory
=
(
gpu_used
+
gpu_available
)
/
1024.
/
1024.
;
float
fraction_of_gpu_memory
=
static_cast
<
double
>
(
memory_pool_init_size_mb
())
/
total_gpu_memory
;
return
fraction_of_gpu_memory
;
#else
return
0.
;
#endif
}
void
contrib
::
AnalysisConfig
::
SetModelBuffer
(
const
char
*
prog_buffer
,
size_t
prog_buffer_size
,
const
char
*
param_buffer
,
size_t
param_buffer_size
)
{
prog_file
=
std
::
string
(
prog_buffer
,
prog_buffer
+
prog_buffer_size
);
param
_file
=
std
::
string
(
param_buffer
,
param_buffer
+
param_buffer_size
);
prog_file
_
=
std
::
string
(
prog_buffer
,
prog_buffer
+
prog_buffer_size
);
param
s_file_
=
std
::
string
(
param_buffer
,
param_buffer
+
param_buffer_size
);
model_from_memory_
=
true
;
}
...
...
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @
68a07328
...
...
@@ -33,6 +33,7 @@
#include "paddle/fluid/inference/utils/singleton.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/platform/cpu_helper.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/profiler.h"
DECLARE_bool
(
profile
);
...
...
@@ -59,7 +60,7 @@ bool AnalysisPredictor::Init(
if
(
FLAGS_profile
)
{
LOG
(
WARNING
)
<<
"Profiler is actived, might affect the performance"
;
LOG
(
INFO
)
<<
"You can turn off by set gflags '-profile false'"
;
auto
tracking_device
=
config_
.
use_gpu
?
platform
::
ProfilerState
::
kAll
auto
tracking_device
=
config_
.
use_gpu
()
?
platform
::
ProfilerState
::
kAll
:
platform
::
ProfilerState
::
kCPU
;
platform
::
EnableProfiler
(
tracking_device
);
}
...
...
@@ -112,7 +113,7 @@ bool AnalysisPredictor::PrepareProgram(
// Optimize the program, and load parameters and modify them in the
// scope_.
// This will change the scope_ address.
if
(
config_
.
enable_ir_optim
)
{
if
(
config_
.
ir_optim
()
)
{
status_ir_optim_enabled_
=
true
;
OptimizeInferenceProgram
();
}
else
{
...
...
@@ -140,9 +141,9 @@ bool AnalysisPredictor::PrepareProgram(
return
true
;
}
bool
AnalysisPredictor
::
CreateExecutor
()
{
if
(
config_
.
use_gpu
)
{
if
(
config_
.
use_gpu
_
)
{
status_use_gpu_
=
true
;
place_
=
paddle
::
platform
::
CUDAPlace
(
config_
.
device
);
place_
=
paddle
::
platform
::
CUDAPlace
(
config_
.
device
_id_
);
}
else
{
place_
=
paddle
::
platform
::
CPUPlace
();
}
...
...
@@ -151,7 +152,7 @@ bool AnalysisPredictor::CreateExecutor() {
}
bool
AnalysisPredictor
::
PrepareExecutor
()
{
executor_
->
Prepare
(
sub_scope_
,
*
inference_program_
,
0
,
config_
.
use_feed_fetch_ops
);
config_
.
use_feed_fetch_ops
_
);
PADDLE_ENFORCE_NOT_NULL
(
sub_scope_
);
...
...
@@ -250,7 +251,7 @@ bool AnalysisPredictor::SetFeed(const std::vector<PaddleTensor> &inputs,
}
input
.
set_lod
(
lod
);
int
idx
=
-
1
;
if
(
config_
.
specify_input_name
)
{
if
(
config_
.
specify_input_name
_
)
{
auto
name
=
inputs
[
i
].
name
;
if
(
feed_names_
.
find
(
name
)
==
feed_names_
.
end
())
{
LOG
(
ERROR
)
<<
"feed names from program do not have name: ["
<<
name
...
...
@@ -314,22 +315,22 @@ bool AnalysisPredictor::GetFetch(std::vector<PaddleTensor> *outputs,
void
AnalysisPredictor
::
OptimizeInferenceProgram
()
{
status_program_optimized_
=
true
;
argument_
.
SetUseGPU
(
config_
.
use_gpu
);
argument_
.
SetGPUDeviceId
(
config_
.
device
);
argument_
.
SetUseGPU
(
config_
.
use_gpu
()
);
argument_
.
SetGPUDeviceId
(
config_
.
gpu_device_id
()
);
argument_
.
SetModelFromMemory
(
config_
.
model_from_memory_
);
// Analyze inference_program
if
(
!
config_
.
model_dir
.
empty
())
{
argument_
.
SetModelDir
(
config_
.
model_dir
);
if
(
!
config_
.
model_dir
()
.
empty
())
{
argument_
.
SetModelDir
(
config_
.
model_dir
()
);
}
else
{
PADDLE_ENFORCE
(
!
config_
.
param
_file
.
empty
(),
!
config_
.
param
s_file
()
.
empty
(),
"Either model_dir or (param_file, prog_file) should be set."
);
PADDLE_ENFORCE
(
!
config_
.
prog_file
.
empty
());
argument_
.
SetModelProgramPath
(
config_
.
prog_file
);
argument_
.
SetModelParamsPath
(
config_
.
param
_file
);
PADDLE_ENFORCE
(
!
config_
.
prog_file
()
.
empty
());
argument_
.
SetModelProgramPath
(
config_
.
prog_file
()
);
argument_
.
SetModelParamsPath
(
config_
.
param
s_file
()
);
}
if
(
config_
.
use_gpu
&&
config_
.
use_tensorrt_
)
{
if
(
config_
.
use_gpu
()
&&
config_
.
tensorrt_engine_enabled
()
)
{
argument_
.
SetUseTensorRT
(
true
);
argument_
.
SetTensorRtWorkspaceSize
(
config_
.
tensorrt_workspace_size_
);
argument_
.
SetTensorRtMaxBatchSize
(
config_
.
tensorrt_max_batchsize_
);
...
...
@@ -341,7 +342,7 @@ void AnalysisPredictor::OptimizeInferenceProgram() {
}
auto
passes
=
config_
.
pass_builder
()
->
AllPasses
();
if
(
!
config_
.
enable_ir_optim
)
passes
.
clear
();
if
(
!
config_
.
ir_optim
()
)
passes
.
clear
();
argument_
.
SetIrAnalysisPasses
(
passes
);
argument_
.
SetScopeNotOwned
(
const_cast
<
framework
::
Scope
*>
(
scope_
.
get
()));
Analyzer
().
Run
(
&
argument_
);
...
...
@@ -358,18 +359,26 @@ template <>
std
::
unique_ptr
<
PaddlePredictor
>
CreatePaddlePredictor
<
AnalysisConfig
,
PaddleEngineKind
::
kAnalysis
>
(
const
AnalysisConfig
&
config
)
{
VLOG
(
3
)
<<
"create AnalysisConfig"
;
if
(
config
.
use_gpu
)
{
if
(
config
.
use_gpu
()
)
{
// 1. GPU memeroy
PADDLE_ENFORCE_GT
(
config
.
fraction_of_gpu_memory
,
0.
f
,
"fraction_of_gpu_memory in the config should be set to range (0., 1.]"
);
PADDLE_ENFORCE_GE
(
config
.
device
,
0
,
"Invalid device id %d"
,
config
.
device
);
PADDLE_ENFORCE_GT
(
config
.
memory_pool_init_size_mb
(),
0.
f
);
PADDLE_ENFORCE_GE
(
config
.
gpu_device_id
(),
0
,
"Invalid device id %d"
,
config
.
gpu_device_id
());
std
::
vector
<
std
::
string
>
flags
;
if
(
config
.
fraction_of_gpu_memory
>=
0.0
f
||
config
.
fraction_of_gpu_memory
<=
0.95
f
)
{
float
fraction_of_gpu_memory
=
config
.
fraction_of_gpu_memory_for_pool
();
if
(
fraction_of_gpu_memory
>
0.95
f
)
{
LOG
(
ERROR
)
<<
"Allocate too much memory for the GPU memory pool, assigned "
<<
config
.
memory_pool_init_size_mb
()
<<
" MB"
;
LOG
(
ERROR
)
<<
"Try to shink the value by setting AnalysisConfig::EnableGpu(...)"
;
}
if
(
fraction_of_gpu_memory
>=
0.0
f
||
fraction_of_gpu_memory
<=
0.95
f
)
{
flags
.
push_back
(
"dummpy"
);
std
::
string
flag
=
"--fraction_of_gpu_memory_to_use="
+
std
::
to_string
(
config
.
fraction_of_gpu_memory
);
std
::
to_string
(
fraction_of_gpu_memory
);
flags
.
push_back
(
flag
);
VLOG
(
3
)
<<
"set flag: "
<<
flag
;
framework
::
InitGflags
(
flags
);
...
...
@@ -443,22 +452,22 @@ bool AnalysisPredictor::ZeroCopyRun() {
bool
AnalysisPredictor
::
LoadProgramDesc
()
{
// Initialize the inference program
std
::
string
filename
;
if
(
!
config_
.
model_dir
.
empty
())
{
filename
=
config_
.
model_dir
+
"/__model__"
;
}
else
if
(
!
config_
.
prog_file
.
empty
()
&&
!
config_
.
param_file
.
empty
())
{
if
(
!
config_
.
model_dir
()
.
empty
())
{
filename
=
config_
.
model_dir
()
+
"/__model__"
;
}
else
if
(
!
config_
.
prog_file
().
empty
()
&&
!
config_
.
params_file
()
.
empty
())
{
// All parameters are saved in a single file.
// The file names should be consistent with that used
// in Python API `fluid.io.save_inference_model`.
filename
=
config_
.
prog_file
;
filename
=
config_
.
prog_file
()
;
}
else
{
if
(
config_
.
model_dir
.
empty
()
&&
config_
.
prog_file
.
empty
())
{
if
(
config_
.
model_dir
().
empty
()
&&
config_
.
prog_file
()
.
empty
())
{
LOG
(
ERROR
)
<<
"Either model_dir or (prog_file, param_file) should be set."
;
return
false
;
}
LOG
(
ERROR
)
<<
string
::
Sprintf
(
"not valid model path '%s' or program path '%s'."
,
config_
.
model_dir
,
config_
.
param
_file
);
"not valid model path '%s' or program path '%s'."
,
config_
.
model_dir
()
,
config_
.
param
s_file
()
);
return
false
;
}
...
...
@@ -478,7 +487,7 @@ bool AnalysisPredictor::LoadProgramDesc() {
proto
.
ParseFromString
(
pb_content
);
}
else
{
proto
.
ParseFromString
(
config_
.
prog_file
);
proto
.
ParseFromString
(
config_
.
prog_file
()
);
}
inference_program_
.
reset
(
new
framework
::
ProgramDesc
(
proto
));
return
true
;
...
...
@@ -508,27 +517,27 @@ bool AnalysisPredictor::LoadParameters() {
new_var
->
SetLoDLevel
(
var
->
GetLoDLevel
());
new_var
->
SetPersistable
(
true
);
if
(
!
config_
.
param
_file
.
empty
())
{
if
(
!
config_
.
param
s_file
()
.
empty
())
{
params
.
push_back
(
new_var
->
Name
());
}
else
{
// append_op
framework
::
OpDesc
*
op
=
load_block
->
AppendOp
();
op
->
SetType
(
"load"
);
op
->
SetOutput
(
"Out"
,
{
new_var
->
Name
()});
op
->
SetAttr
(
"file_path"
,
{
config_
.
model_dir
+
"/"
+
new_var
->
Name
()});
op
->
SetAttr
(
"file_path"
,
{
config_
.
model_dir
()
+
"/"
+
new_var
->
Name
()});
op
->
CheckAttrs
();
}
}
}
if
(
!
config_
.
param
_file
.
empty
())
{
if
(
!
config_
.
param
s_file
()
.
empty
())
{
// sort paramlist to have consistent ordering
std
::
sort
(
params
.
begin
(),
params
.
end
());
// append just the load_combine op
framework
::
OpDesc
*
op
=
load_block
->
AppendOp
();
op
->
SetType
(
"load_combine"
);
op
->
SetOutput
(
"Out"
,
params
);
op
->
SetAttr
(
"file_path"
,
{
config_
.
param
_file
});
op
->
SetAttr
(
"file_path"
,
{
config_
.
param
s_file
()
});
op
->
CheckAttrs
();
}
...
...
paddle/fluid/inference/api/analysis_predictor_tester.cc
浏览文件 @
68a07328
...
...
@@ -25,9 +25,9 @@ namespace paddle {
using
contrib
::
AnalysisConfig
;
TEST
(
AnalysisPredictor
,
analysis_off
)
{
AnalysisConfig
config
(
false
)
;
config
.
model_dir
=
FLAGS_dirname
;
config
.
enable_ir_optim
=
false
;
AnalysisConfig
config
;
config
.
SetModel
(
FLAGS_dirname
)
;
config
.
SwitchIrOptim
(
false
)
;
auto
_predictor
=
CreatePaddlePredictor
<
AnalysisConfig
>
(
config
);
auto
*
predictor
=
static_cast
<
AnalysisPredictor
*>
(
_predictor
.
get
());
...
...
@@ -55,14 +55,14 @@ TEST(AnalysisPredictor, analysis_off) {
}
TEST
(
AnalysisPredictor
,
analysis_on
)
{
AnalysisConfig
config
;
config
.
SetModel
(
FLAGS_dirname
);
config
.
SwitchIrOptim
(
true
);
#ifdef PADDLE_WITH_CUDA
AnalysisConfig
config
(
true
);
config
.
fraction_of_gpu_memory
=
0.15
;
config
.
EnableUseGpu
(
100
,
0
);
#else
AnalysisConfig
config
;
config
.
DisableGpu
()
;
#endif
config
.
model_dir
=
FLAGS_dirname
;
config
.
enable_ir_optim
=
true
;
auto
_predictor
=
CreatePaddlePredictor
<
AnalysisConfig
>
(
config
);
auto
*
predictor
=
static_cast
<
AnalysisPredictor
*>
(
_predictor
.
get
());
...
...
@@ -89,7 +89,8 @@ TEST(AnalysisPredictor, analysis_on) {
}
// compare with NativePredictor
auto
naive_predictor
=
CreatePaddlePredictor
<
NativeConfig
>
(
config
);
auto
naive_predictor
=
CreatePaddlePredictor
<
NativeConfig
>
(
config
.
ToNativeConfig
());
std
::
vector
<
PaddleTensor
>
naive_outputs
;
ASSERT_TRUE
(
naive_predictor
->
Run
(
inputs
,
&
naive_outputs
));
ASSERT_EQ
(
naive_outputs
.
size
(),
1UL
);
...
...
@@ -98,9 +99,8 @@ TEST(AnalysisPredictor, analysis_on) {
TEST
(
AnalysisPredictor
,
ZeroCopy
)
{
AnalysisConfig
config
;
config
.
model_dir
=
FLAGS_dirname
;
config
.
use_feed_fetch_ops
=
false
;
config
.
SetModel
(
FLAGS_dirname
);
config
.
SwitchUseFeedFetchOps
(
false
);
auto
predictor
=
CreatePaddlePredictor
<
AnalysisConfig
>
(
config
);
auto
w0
=
predictor
->
GetInputTensor
(
"firstw"
);
...
...
@@ -137,9 +137,9 @@ TEST(AnalysisPredictor, ZeroCopy) {
TEST
(
AnalysisPredictor
,
Clone
)
{
AnalysisConfig
config
;
config
.
model_dir
=
FLAGS_dirname
;
config
.
use_feed_fetch_ops
=
true
;
config
.
enable_ir_optim
=
true
;
config
.
SetModel
(
FLAGS_dirname
)
;
config
.
SwitchUseFeedFetchOps
(
true
)
;
config
.
SwitchIrOptim
(
true
)
;
std
::
vector
<
std
::
unique_ptr
<
PaddlePredictor
>>
predictors
;
predictors
.
emplace_back
(
CreatePaddlePredictor
(
config
));
...
...
paddle/fluid/inference/api/api_anakin_engine.h
浏览文件 @
68a07328
...
...
@@ -19,8 +19,6 @@ limitations under the License. */
#pragma once
#define WITH_ANAKIN
#include <vector>
#include "framework/core/net/net.h"
...
...
paddle/fluid/inference/api/api_impl.cc
浏览文件 @
68a07328
...
...
@@ -288,7 +288,7 @@ std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
VLOG
(
3
)
<<
"create NativePaddlePredictor"
;
if
(
config
.
use_gpu
)
{
// 1. GPU memeroy
PADDLE_ENFORCE_G
T
(
PADDLE_ENFORCE_G
E
(
config
.
fraction_of_gpu_memory
,
0.
f
,
"fraction_of_gpu_memory in the config should be set to range (0., 1.]"
);
PADDLE_ENFORCE_GE
(
config
.
device
,
0
,
"Invalid device id %d"
,
config
.
device
);
...
...
paddle/fluid/inference/api/api_impl_tester.cc
浏览文件 @
68a07328
...
...
@@ -295,7 +295,8 @@ TEST(inference_api_native, image_classification_gpu) {
#endif
TEST
(
PassBuilder
,
Delete
)
{
contrib
::
AnalysisConfig
config
(
false
);
contrib
::
AnalysisConfig
config
;
config
.
DisableGpu
();
config
.
pass_builder
()
->
DeletePass
(
"attention_lstm_fuse_pass"
);
const
auto
&
passes
=
config
.
pass_builder
()
->
AllPasses
();
auto
it
=
std
::
find
(
passes
.
begin
(),
passes
.
end
(),
"attention_lstm_fuse_pass"
);
...
...
paddle/fluid/inference/api/demo_ci/trt_mobilenet_demo.cc
浏览文件 @
68a07328
...
...
@@ -36,12 +36,11 @@ namespace demo {
*/
void
Main
()
{
std
::
unique_ptr
<
PaddlePredictor
>
predictor
;
paddle
::
contrib
::
AnalysisConfig
config
(
true
)
;
config
.
param_file
=
FLAGS_modeldir
+
"/__params__"
;
config
.
prog_file
=
FLAGS_modeldir
+
"/__model__"
;
config
.
device
=
0
;
paddle
::
contrib
::
AnalysisConfig
config
;
config
.
EnableUseGpu
(
100
,
0
)
;
config
.
SetModel
(
FLAGS_modeldir
+
"/__params__"
,
FLAGS_modeldir
+
"/__model__"
)
;
config
.
EnableTensorRtEngine
();
config
.
fraction_of_gpu_memory
=
0.1
;
// set by yourself
predictor
=
CreatePaddlePredictor
(
config
);
VLOG
(
3
)
<<
"begin to process data"
;
...
...
paddle/fluid/inference/api/demo_ci/vis_demo.cc
浏览文件 @
68a07328
...
...
@@ -40,15 +40,14 @@ using contrib::AnalysisConfig;
*/
void
Main
(
bool
use_gpu
)
{
std
::
unique_ptr
<
PaddlePredictor
>
predictor
,
analysis_predictor
;
AnalysisConfig
config
(
use_gpu
);
config
.
param_file
=
FLAGS_modeldir
+
"/__params__"
;
config
.
prog_file
=
FLAGS_modeldir
+
"/__model__"
;
config
.
device
=
0
;
if
(
FLAGS_use_gpu
)
{
config
.
fraction_of_gpu_memory
=
0.1
;
// set by yourself
AnalysisConfig
config
;
if
(
use_gpu
)
{
config
.
EnableUseGpu
(
100
,
0
);
}
config
.
SetModel
(
FLAGS_modeldir
+
"/__model__"
,
FLAGS_modeldir
+
"/__params__"
);
predictor
=
CreatePaddlePredictor
<
NativeConfig
>
(
config
);
predictor
=
CreatePaddlePredictor
<
NativeConfig
>
(
config
.
ToNativeConfig
()
);
analysis_predictor
=
CreatePaddlePredictor
(
config
);
// Just a single batch of data.
...
...
paddle/fluid/inference/api/paddle_analysis_config.h
浏览文件 @
68a07328
...
...
@@ -34,26 +34,67 @@ class AnalysisPredictor;
namespace
contrib
{
// NOTE WIP, not stable yet.
struct
AnalysisConfig
:
public
NativeConfig
{
explicit
AnalysisConfig
(
bool
use_gpu
=
false
)
;
struct
AnalysisConfig
{
AnalysisConfig
()
=
default
;
explicit
AnalysisConfig
(
const
AnalysisConfig
&
other
);
explicit
AnalysisConfig
(
AnalysisConfig
&&
other
);
explicit
AnalysisConfig
(
const
std
::
string
&
model_dir
);
explicit
AnalysisConfig
(
const
std
::
string
&
prog_file
,
const
std
::
string
&
params_file
);
// Model path related.
void
SetModel
(
const
std
::
string
&
model_dir
)
{
model_dir_
=
model_dir
;
}
void
SetModel
(
const
std
::
string
&
prog_file_path
,
const
std
::
string
&
params_file_path
);
void
SetProgFile
(
const
std
::
string
&
x
)
{
prog_file_
=
x
;
}
void
SetParamsFile
(
const
std
::
string
&
x
)
{
params_file_
=
x
;
}
const
std
::
string
&
model_dir
()
const
{
return
model_dir_
;
}
const
std
::
string
&
prog_file
()
const
{
return
prog_file_
;
}
const
std
::
string
&
params_file
()
const
{
return
params_file_
;
}
// GPU related.
void
EnableUseGpu
(
uint64_t
memory_pool_init_size_mb
,
int
device_id
=
0
);
void
DisableGpu
();
bool
use_gpu
()
const
{
return
use_gpu_
;
}
int
gpu_device_id
()
const
{
return
device_id_
;
}
int
memory_pool_init_size_mb
()
const
{
return
memory_pool_init_size_mb_
;
}
float
fraction_of_gpu_memory_for_pool
()
const
;
// Determine whether to perform graph optimization.
bool
enable_ir_optim
=
true
;
void
SwitchIrOptim
(
int
x
=
true
)
{
enable_ir_optim_
=
x
;
}
bool
ir_optim
()
const
{
return
enable_ir_optim_
;
}
// Get a pass builder for customize the passes in IR analysis phase.
PassStrategy
*
pass_builder
()
const
;
void
SwitchUseFeedFetchOps
(
int
x
=
true
)
{
use_feed_fetch_ops_
=
x
;
}
bool
use_feed_fetch_ops_enabled
()
const
{
return
use_feed_fetch_ops_
;
}
// NOT stable yet.
bool
use_feed_fetch_ops
{
true
};
void
SwitchSpecifyInputNames
(
bool
x
=
true
)
{
specify_input_name_
=
x
;
}
bool
specify_input_name
()
const
{
return
specify_input_name_
;
}
void
EnableTensorRtEngine
(
int
workspace_size
=
1
<<
20
,
int
max_batch_size
=
1
,
int
min_subgraph_size
=
3
);
bool
use_tensorrt
()
const
{
return
use_tensorrt_
;
}
bool
tensorrt_engine_enabled
()
const
{
return
use_tensorrt_
;
}
void
SwitchIrDebug
(
int
x
=
true
)
{
ir_debug_
=
x
;
}
void
EnableMKLDNN
();
bool
use_mkldnn
()
const
{
return
use_mkldnn_
;
}
bool
mkldnn_enabled
()
const
{
return
use_mkldnn_
;
}
// Set and get the number of cpu math library threads.
void
SetCpuMathLibraryNumThreads
(
int
cpu_math_library_num_threads
);
int
cpu_math_library_num_threads
()
const
{
return
cpu_math_library_num_threads_
;
}
NativeConfig
ToNativeConfig
()
const
{
NativeConfig
config
;
config
.
model_dir
=
model_dir_
;
config
.
prog_file
=
prog_file_
;
config
.
param_file
=
params_file_
;
config
.
use_gpu
=
use_gpu_
;
config
.
device
=
device_id_
;
config
.
fraction_of_gpu_memory
=
fraction_of_gpu_memory_for_pool
();
config
.
specify_input_name
=
specify_input_name_
;
return
config
;
}
void
SetMKLDNNOp
(
std
::
unordered_set
<
std
::
string
>
op_list
)
{
mkldnn_enabled_op_types_
=
op_list
;
}
...
...
@@ -65,10 +106,29 @@ struct AnalysisConfig : public NativeConfig {
friend
class
::
paddle
::
AnalysisPredictor
;
// NOTE just for developer, not an official API, easily to be broken.
// Get a pass builder for customize the passes in IR analysis phase.
PassStrategy
*
pass_builder
()
const
;
protected:
// Update the config.
void
Update
();
std
::
string
SerializeInfoCache
();
protected:
// Model pathes.
std
::
string
model_dir_
;
std
::
string
prog_file_
;
std
::
string
params_file_
;
// GPU releated.
bool
use_gpu_
{
false
};
int
device_id_
{
0
};
uint64_t
memory_pool_init_size_mb_
{
100
};
// initial size is 100MB.
// TensorRT releated.
bool
use_tensorrt_
{
false
};
bool
use_mkldnn_
{
false
};
std
::
unordered_set
<
std
::
string
>
mkldnn_enabled_op_types_
;
// For workspace_size, refer it from here:
// https://docs.nvidia.com/deeplearning/sdk/tensorrt-developer-guide/index.html#troubleshooting
int
tensorrt_workspace_size_
;
...
...
@@ -82,17 +142,24 @@ struct AnalysisConfig : public NativeConfig {
// We set this variable to control the minimum number of nodes in the
// subgraph, 3 as default value.
int
tensorrt_min_subgraph_size_
{
3
};
std
::
unique_ptr
<
PassStrategy
>
pass_builder_
;
bool
use_mkldnn_
{
false
};
std
::
unordered_set
<
std
::
string
>
mkldnn_enabled_op_types_
;
bool
model_from_memory_
{
false
};
};
// Configurations for Anakin engine.
struct
AnakinConfig
:
public
PaddlePredictor
::
Config
{
enum
TargetType
{
NVGPU
=
0
,
X86
};
int
device
;
std
::
string
model_file
;
int
max_batch_size
{
-
1
};
TargetType
target_type
;
bool
enable_ir_optim_
{
true
};
bool
use_feed_fetch_ops_
{
true
};
bool
ir_debug_
{
false
};
bool
specify_input_name_
{
false
};
int
cpu_math_library_num_threads_
{
1
};
// A runtime cache, shouldn't be transferred to others.
std
::
string
serialized_info_cache_
;
mutable
std
::
unique_ptr
<
PassStrategy
>
pass_builder_
;
};
}
// namespace contrib
...
...
paddle/fluid/inference/api/paddle_inference_api.h
浏览文件 @
68a07328
...
...
@@ -26,9 +26,8 @@ limitations under the License. */
#include <string>
#include <vector>
#include "paddle_api.h" // NOLINT
#ifndef WITH_ANAKIN
#include "paddle_analysis_config.h" // NOLINT
#else
#include "paddle_api.h" // NOLINT
#ifdef WITH_ANAKIN
#include "paddle_anakin_config.h" // NOLINT
#endif
paddle/fluid/inference/api/paddle_pass_builder.h
浏览文件 @
68a07328
...
...
@@ -62,7 +62,12 @@ class PassStrategy : public PaddlePassBuilder {
// still some CPU kernels running in CPU mode.
virtual
void
EnableMKLDNN
()
=
0
;
bool
use_gpu
()
const
{
return
use_gpu_
;
}
virtual
~
PassStrategy
()
=
default
;
protected:
bool
use_gpu_
{
false
};
};
/*
...
...
@@ -88,6 +93,7 @@ class CpuPassStrategy : public PassStrategy {
"conv_eltwiseadd_bn_fuse_pass"
,
//
"is_test_pass"
,
//
});
use_gpu_
=
false
;
}
virtual
~
CpuPassStrategy
()
=
default
;
...
...
@@ -126,10 +132,14 @@ class GpuPassStrategy : public PassStrategy {
"conv_elementwise_add2_act_fuse_pass"
,
//
"conv_elementwise_add_fuse_pass"
,
//
});
use_gpu_
=
true
;
}
GpuPassStrategy
(
const
GpuPassStrategy
&
other
)
:
PassStrategy
(
other
.
AllPasses
())
{}
:
PassStrategy
(
other
.
AllPasses
())
{
use_gpu_
=
true
;
}
void
EnableMKLDNN
()
override
;
...
...
paddle/fluid/inference/tensorrt/CMakeLists.txt
浏览文件 @
68a07328
nv_library
(
tensorrt_engine SRCS engine.cc DEPS
${
GLOB_OPERATOR_DEPS
}
framework_proto device_context
)
nv_library
(
tensorrt_op_teller SRCS op_teller.cc DEPS framework_proto
)
nv_test
(
test_tensorrt SRCS test_tensorrt.cc DEPS dynload_cuda device_context dynamic_loader
)
nv_test
(
test_tensorrt_engine SRCS test_engine.cc DEPS dynload_cuda tensorrt_engine
)
add_subdirectory
(
plugin
)
...
...
paddle/fluid/inference/tensorrt/op_teller.cc
0 → 100644
浏览文件 @
68a07328
// Copyright (c) 2019 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/inference/tensorrt/op_teller.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
// Just tell by the op_types.
struct
SimpleOpTypeSetTeller
:
public
Teller
{
SimpleOpTypeSetTeller
()
{}
bool
operator
()(
const
std
::
string
&
op_type
,
const
framework
::
OpDesc
&
desc
)
override
{
return
teller_set
.
count
(
op_type
);
}
private:
std
::
unordered_set
<
std
::
string
>
teller_set
{
{
"mul"
,
"conv2d"
,
"pool2d"
,
"relu"
,
"softmax"
,
"sigmoid"
,
"depthwise_conv2d"
,
"batch_norm"
,
"concat"
,
"tanh"
,
"pad"
,
"elementwise_add"
,
"elementwise_mul"
,
"dropout"
,
"split"
,
"prelu"
,
"conv2d_transpose"
,
"leaky_relu"
}};
};
bool
OpTeller
::
Tell
(
const
std
::
string
&
op_type
,
const
framework
::
OpDesc
&
desc
)
{
for
(
auto
&
teller
:
tellers_
)
{
if
((
*
teller
)(
op_type
,
desc
))
return
true
;
}
return
false
;
}
OpTeller
::
OpTeller
()
{
tellers_
.
emplace_back
(
new
SimpleOpTypeSetTeller
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tensorrt/op_teller.h
0 → 100644
浏览文件 @
68a07328
// Copyright (c) 2019 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 "paddle/fluid/framework/op_desc.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
/*
* Single Op teller definition.
* One can override this and define a more complex tell logic, considerring more
* issues such as op_desc.
*/
struct
Teller
{
virtual
bool
operator
()(
const
std
::
string
&
op_type
,
const
framework
::
OpDesc
&
desc
)
=
0
;
virtual
~
Teller
()
=
default
;
};
/*
* A real example:
*
* struct SomeTeller : public Teller {
* bool operator()(const std::string& op_type,
* const framework::OpDesc& desc) override {
* return op_type == "fc" && desc.Inputs().size() == 2;
* }
*};
*/
/*
* class OpTeller helps to tell whether a fluid
* operator can be transformed to a TensorRT layer.
*/
class
OpTeller
{
public:
static
OpTeller
&
Global
()
{
static
std
::
unique_ptr
<
OpTeller
>
x
(
new
OpTeller
);
return
*
x
;
}
bool
Tell
(
const
std
::
string
&
op_type
,
const
framework
::
OpDesc
&
desc
);
private:
OpTeller
();
private:
std
::
vector
<
std
::
unique_ptr
<
Teller
>>
tellers_
;
};
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/analyzer_dam_tester.cc
浏览文件 @
68a07328
...
...
@@ -165,12 +165,9 @@ void PrepareInputs(std::vector<PaddleTensor> *input_slots, DataRecord *data,
}
void
SetConfig
(
contrib
::
AnalysisConfig
*
cfg
)
{
cfg
->
prog_file
=
FLAGS_infer_model
+
"/__model__"
;
cfg
->
param_file
=
FLAGS_infer_model
+
"/param"
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
+
"/__model__"
,
FLAGS_infer_model
+
"/param"
);
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
(
true
);
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_lac_tester.cc
浏览文件 @
68a07328
...
...
@@ -105,11 +105,10 @@ void GetOneBatch(std::vector<PaddleTensor> *input_slots, DataRecord *data,
}
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
model_dir
=
FLAGS_infer_model
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc
浏览文件 @
68a07328
...
...
@@ -76,11 +76,10 @@ void PrepareInputs(std::vector<PaddleTensor> *input_slots, DataRecord *data,
}
void
SetConfig
(
contrib
::
AnalysisConfig
*
cfg
)
{
cfg
->
model_dir
=
FLAGS_infer_model
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_ner_tester.cc
浏览文件 @
68a07328
...
...
@@ -84,13 +84,12 @@ void SetConfig(contrib::AnalysisConfig *cfg, bool memory_load = false) {
cfg
->
SetModelBuffer
(
&
buffer_prog
[
0
],
buffer_prog
.
size
(),
&
buffer_param
[
0
],
buffer_param
.
size
());
}
else
{
cfg
->
prog_file
=
FLAGS_infer_model
+
"/__model__"
;
cfg
->
param_file
=
FLAGS_infer_model
+
"/param"
;
cfg
->
SetModel
(
FLAGS_infer_model
+
"/__model__"
,
FLAGS_infer_model
+
"/param"
)
;
}
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
浏览文件 @
68a07328
...
...
@@ -21,12 +21,10 @@ namespace inference {
namespace
analysis
{
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
param_file
=
FLAGS_infer_model
+
"/params"
;
cfg
->
prog_file
=
FLAGS_infer_model
+
"/model"
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
specify_input_name
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
+
"/model"
,
FLAGS_infer_model
+
"/params"
);
cfg
->
DisableGpu
();
cfg
->
SwitchIrOptim
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SetCpuMathLibraryNumThreads
(
FLAGS_paddle_num_threads
);
}
...
...
paddle/fluid/inference/tests/api/analyzer_rnn1_tester.cc
浏览文件 @
68a07328
...
...
@@ -204,12 +204,10 @@ void PrepareZeroCopyInputs(ZeroCopyTensor *lod_attention_tensor,
}
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
prog_file
=
FLAGS_infer_model
+
"/__model__"
;
cfg
->
param_file
=
FLAGS_infer_model
+
"/param"
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
+
"/__model__"
,
FLAGS_infer_model
+
"/param"
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
@@ -225,10 +223,10 @@ void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
// Easy for profiling independently.
TEST
(
Analyzer_rnn1
,
profile
)
{
contrib
::
AnalysisConfig
cfg
(
false
)
;
contrib
::
AnalysisConfig
cfg
;
SetConfig
(
&
cfg
);
cfg
.
fraction_of_gpu_memory
=
0.1
;
cfg
.
pass_builder
()
->
TurnOn
Debug
();
cfg
.
DisableGpu
()
;
cfg
.
SwitchIr
Debug
();
std
::
vector
<
PaddleTensor
>
outputs
;
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
...
...
@@ -293,16 +291,18 @@ TEST(Analyzer_rnn1, multi_thread) {
TEST
(
Analyzer_rnn1
,
ZeroCopy
)
{
AnalysisConfig
config
;
SetConfig
(
&
config
);
config
.
use_feed_fetch_ops
=
false
;
config
.
SwitchUseFeedFetchOps
(
false
)
;
PaddlePlace
place
;
auto
predictor
=
CreatePaddlePredictor
<
AnalysisConfig
>
(
config
);
config
.
use_feed_fetch_ops
=
true
;
auto
native_predictor
=
CreatePaddlePredictor
<
NativeConfig
>
(
config
);
config
.
SwitchUseFeedFetchOps
(
true
);
auto
native_predictor
=
CreatePaddlePredictor
<
NativeConfig
>
(
config
.
ToNativeConfig
());
config
.
use_feed_fetch_ops
=
true
;
// the analysis predictor needs feed/fetch.
config
.
SwitchUseFeedFetchOps
(
true
);
// the analysis predictor needs feed/fetch.
auto
analysis_predictor
=
CreatePaddlePredictor
<
AnalysisConfig
>
(
config
);
#define NEW_TENSOR(name__) \
...
...
@@ -362,7 +362,7 @@ TEST(Analyzer_rnn1, ZeroCopy) {
TEST
(
Analyzer_rnn1
,
ZeroCopyMultiThread
)
{
AnalysisConfig
config
;
SetConfig
(
&
config
);
config
.
use_feed_fetch_ops
=
false
;
config
.
SwitchUseFeedFetchOps
(
false
)
;
#define NEW_TENSOR(name__) \
auto name__##_tensor = predictor->GetInputTensor(#name__);
...
...
paddle/fluid/inference/tests/api/analyzer_rnn2_tester.cc
浏览文件 @
68a07328
...
...
@@ -105,12 +105,10 @@ void PrepareInputs(std::vector<PaddleTensor> *input_slots, DataRecord *data,
}
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
prog_file
=
FLAGS_infer_model
+
"/__model__"
;
cfg
->
param_file
=
FLAGS_infer_model
+
"/param"
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
+
"/__model__"
,
FLAGS_infer_model
+
"/param"
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_seq_conv1_tester.cc
浏览文件 @
68a07328
...
...
@@ -89,11 +89,10 @@ void PrepareInputs(std::vector<PaddleTensor> *input_slots, DataRecord *data,
}
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
model_dir
=
FLAGS_infer_model
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc
浏览文件 @
68a07328
...
...
@@ -122,12 +122,9 @@ void PrepareInputs(std::vector<PaddleTensor> *input_slots, DataRecord *data) {
}
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
param_file
=
FLAGS_infer_model
+
"/params"
;
cfg
->
prog_file
=
FLAGS_infer_model
+
"/model"
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
specify_input_name
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
+
"/model"
,
FLAGS_infer_model
+
"/params"
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
pass_builder
()
->
TurnOnDebug
();
cfg
->
SetCpuMathLibraryNumThreads
(
FLAGS_paddle_num_threads
);
}
...
...
paddle/fluid/inference/tests/api/analyzer_text_classification_tester.cc
浏览文件 @
68a07328
...
...
@@ -47,11 +47,10 @@ struct DataReader {
};
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
model_dir
=
FLAGS_infer_model
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
specify_input_name
=
true
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
);
cfg
->
DisableGpu
();
cfg
->
SwitchSpecifyInputNames
();
cfg
->
SwitchIrOptim
();
}
void
SetInput
(
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
*
inputs
)
{
...
...
paddle/fluid/inference/tests/api/analyzer_vis_tester.cc
浏览文件 @
68a07328
...
...
@@ -51,12 +51,11 @@ Record ProcessALine(const std::string &line) {
}
void
SetConfig
(
AnalysisConfig
*
cfg
)
{
cfg
->
param_file
=
FLAGS_infer_model
+
"/__params__"
;
cfg
->
prog_file
=
FLAGS_infer_model
+
"/__model__"
;
cfg
->
use_gpu
=
false
;
cfg
->
device
=
0
;
cfg
->
enable_ir_optim
=
true
;
cfg
->
specify_input_name
=
true
;
cfg
->
SetModel
(
FLAGS_infer_model
+
"/__model__"
,
FLAGS_infer_model
+
"/__params__"
);
cfg
->
DisableGpu
();
cfg
->
SwitchIrDebug
();
cfg
->
SwitchSpecifyInputNames
();
// TODO(TJ): fix fusion gru
cfg
->
pass_builder
()
->
DeletePass
(
"fc_gru_fuse_pass"
);
}
...
...
paddle/fluid/inference/tests/api/config_printer.h
浏览文件 @
68a07328
...
...
@@ -64,19 +64,23 @@ std::ostream &operator<<(std::ostream &os,
num_spaces
++
;
os
<<
*
reinterpret_cast
<
const
NativeConfig
*>
(
&
config
);
if
(
!
config
.
model_from_memory
())
{
os
<<
GenSpaces
(
num_spaces
)
<<
"prog_file: "
<<
config
.
prog_file
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"param_file: "
<<
config
.
param_file
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"prog_file: "
<<
config
.
prog_file
()
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"param_file: "
<<
config
.
params_file
()
<<
"
\n
"
;
}
else
{
os
<<
GenSpaces
(
num_spaces
)
<<
"prog_file and param_file: load from memory
\n
"
;
}
os
<<
GenSpaces
(
num_spaces
)
<<
"enable_ir_optim: "
<<
config
.
enable_ir_optim
os
<<
GenSpaces
(
num_spaces
)
<<
"enable_ir_optim: "
<<
config
.
ir_optim
()
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"enable_ir_optim: "
<<
config
.
ir_optim
()
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"use_feed_fetch_ops: "
<<
config
.
use_feed_fetch_ops
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"use_tensorrt: "
<<
config
.
use_tensorrt
()
<<
"use_feed_fetch_ops: "
<<
config
.
use_feed_fetch_ops_enabled
()
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"use_tensorrt: "
<<
config
.
tensorrt_engine_enabled
()
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"use_mkldnn: "
<<
config
.
mkldnn_enabled
()
<<
"
\n
"
;
os
<<
GenSpaces
(
num_spaces
)
<<
"use_mkldnn: "
<<
config
.
use_mkldnn
()
<<
"
\n
"
;
num_spaces
--
;
os
<<
GenSpaces
(
num_spaces
)
<<
"}
\n
"
;
return
os
;
...
...
paddle/fluid/inference/tests/api/tester_helper.h
浏览文件 @
68a07328
...
...
@@ -328,7 +328,10 @@ void CompareNativeAndAnalysis(
const
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
&
inputs
)
{
PrintConfig
(
config
,
true
);
std
::
vector
<
PaddleTensor
>
native_outputs
,
analysis_outputs
;
TestOneThreadPrediction
(
config
,
inputs
,
&
native_outputs
,
false
);
const
auto
*
analysis_config
=
reinterpret_cast
<
const
contrib
::
AnalysisConfig
*>
(
config
);
auto
native_config
=
analysis_config
->
ToNativeConfig
();
TestOneThreadPrediction
(
&
native_config
,
inputs
,
&
native_outputs
,
false
);
TestOneThreadPrediction
(
config
,
inputs
,
&
analysis_outputs
,
true
);
CompareResult
(
analysis_outputs
,
native_outputs
);
}
...
...
paddle/fluid/inference/tests/api/trt_models_tester.cc
浏览文件 @
68a07328
...
...
@@ -46,22 +46,20 @@ void SetConfig<contrib::AnalysisConfig>(contrib::AnalysisConfig* config,
std
::
string
model_dir
,
bool
use_gpu
,
bool
use_tensorrt
,
int
batch_size
)
{
if
(
!
FLAGS_prog_filename
.
empty
()
&&
!
FLAGS_param_filename
.
empty
())
{
config
->
prog_file
=
model_dir
+
"/"
+
FLAGS_prog_filename
;
config
->
param_file
=
model_dir
+
"/"
+
FLAGS_param_filename
;
config
->
SetModel
(
model_dir
+
"/"
+
FLAGS_prog_filename
,
model_dir
+
"/"
+
FLAGS_param_filename
)
;
}
else
{
config
->
model_dir
=
model_dir
;
config
->
SetModel
(
model_dir
)
;
}
if
(
use_gpu
)
{
config
->
use_gpu
=
true
;
config
->
device
=
0
;
config
->
fraction_of_gpu_memory
=
0.15
;
config
->
EnableUseGpu
(
100
,
0
);
if
(
use_tensorrt
)
{
config
->
EnableTensorRtEngine
(
1
<<
10
,
batch_size
);
config
->
pass_builder
()
->
DeletePass
(
"conv_bn_fuse_pass"
);
config
->
pass_builder
()
->
DeletePass
(
"fc_fuse_pass"
);
config
->
pass_builder
()
->
TurnOnDebug
();
}
else
{
config
->
enable_ir_optim
=
true
;
config
->
SwitchIrOptim
()
;
}
}
}
...
...
@@ -77,7 +75,8 @@ void profile(std::string model_dir, bool use_analysis, bool use_tensorrt) {
std
::
vector
<
PaddleTensor
>
outputs
;
if
(
use_analysis
||
use_tensorrt
)
{
contrib
::
AnalysisConfig
config
(
true
);
contrib
::
AnalysisConfig
config
;
config
.
EnableUseGpu
(
100
,
0
);
config
.
pass_builder
()
->
TurnOnDebug
();
SetConfig
<
contrib
::
AnalysisConfig
>
(
&
config
,
model_dir
,
true
,
use_tensorrt
,
FLAGS_batch_size
);
...
...
@@ -109,7 +108,8 @@ void compare(std::string model_dir, bool use_tensorrt) {
&
native_outputs
,
false
);
std
::
vector
<
PaddleTensor
>
analysis_outputs
;
contrib
::
AnalysisConfig
analysis_config
(
true
);
contrib
::
AnalysisConfig
analysis_config
;
analysis_config
.
EnableUseGpu
(
50
,
0
);
SetConfig
<
contrib
::
AnalysisConfig
>
(
&
analysis_config
,
model_dir
,
true
,
use_tensorrt
,
FLAGS_batch_size
);
TestOneThreadPrediction
(
...
...
@@ -154,9 +154,9 @@ TEST(TensorRT_mobilenet, analysis) {
TEST
(
AnalysisPredictor
,
use_gpu
)
{
std
::
string
model_dir
=
FLAGS_infer_model
+
"/"
+
"mobilenet"
;
AnalysisConfig
config
(
true
)
;
config
.
model_dir
=
model_dir
;
config
.
fraction_of_gpu_memory
=
0.15
;
AnalysisConfig
config
;
config
.
EnableUseGpu
(
100
,
0
)
;
config
.
SetModel
(
model_dir
)
;
config
.
pass_builder
()
->
TurnOnDebug
();
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
inputs_all
;
...
...
paddle/fluid/operators/conv_mkldnn_op.cc
浏览文件 @
68a07328
...
...
@@ -319,6 +319,8 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
std
::
vector
<
int
>
dilations
=
ctx
.
Attr
<
std
::
vector
<
int
>>
(
"dilations"
);
int
groups
=
ctx
.
Attr
<
int
>
(
"groups"
);
bool
fuse_relu
=
ctx
.
Attr
<
bool
>
(
"fuse_relu"
);
bool
force_fp32_output
=
ctx
.
Attr
<
bool
>
(
"force_fp32_output"
);
bool
is_conv3d
=
strides
.
size
()
==
3U
;
...
...
@@ -329,6 +331,7 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
dilations
[
2
]
==
1
:
dilations
.
size
()
==
2
&&
dilations
[
0
]
==
1
&&
dilations
[
1
]
==
1
,
"dilation in convolution is not implemented yet"
);
PADDLE_ENFORCE
(
is_conv3d
!=
true
,
"int8 does not support conv3d currently"
);
const
T
*
input_data
=
input
->
data
<
T
>
();
...
...
@@ -340,15 +343,24 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
GetWeightsTz
(
weights_tz
,
g
,
is_conv3d
);
std
::
vector
<
int
>
dst_tz
=
paddle
::
framework
::
vectorize2int
(
output
->
dims
());
mkldnn
::
memory
::
data_type
src_dt
=
paddle
::
framework
::
ToMKLDNNDataType
(
input
->
type
());
auto
dst_dt
=
fuse_relu
?
paddle
::
framework
::
ToMKLDNNDataType
(
framework
::
DataTypeTrait
<
uint8_t
>::
DataType
)
:
paddle
::
framework
::
ToMKLDNNDataType
(
framework
::
DataTypeTrait
<
int8_t
>::
DataType
);
if
(
force_fp32_output
)
{
dst_dt
=
paddle
::
framework
::
ToMKLDNNDataType
(
framework
::
DataTypeTrait
<
float
>::
DataType
);
}
// Get unique name for storing MKLDNN primitives
std
::
string
key
;
key
.
reserve
(
MaxKeyLength
);
mkldnn
::
memory
::
data_type
src_dt
=
paddle
::
framework
::
ToMKLDNNDataType
(
input
->
type
());
platform
::
ConvMKLDNNHandler
::
AppendKey
(
&
key
,
src_tz
,
weights_tz
,
strides
,
paddings
,
dilations
,
groups
,
src_dt
,
input
->
format
(),
ctx
.
op
().
Output
(
"Output"
));
input
->
format
(),
dst_dt
,
ctx
.
op
().
Output
(
"Output"
));
const
std
::
string
key_conv_pd
=
key
+
"@conv_pd"
;
std
::
shared_ptr
<
mkldnn
::
convolution_forward
>
conv_p
=
nullptr
;
...
...
@@ -413,13 +425,6 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
platform
::
MKLDNNMemDesc
(
src_tz
,
src_dt
,
chosen_memory_format
);
auto
weights_md
=
platform
::
MKLDNNMemDesc
(
weights_tz
,
memory
::
data_type
::
s8
,
chosen_memory_format
);
auto
dst_dt
=
force_fp32_output
?
paddle
::
framework
::
ToMKLDNNDataType
(
framework
::
DataTypeTrait
<
float
>::
DataType
)
:
paddle
::
framework
::
ToMKLDNNDataType
(
framework
::
DataTypeTrait
<
int8_t
>::
DataType
);
auto
dst_md
=
platform
::
MKLDNNMemDesc
(
dst_tz
,
dst_dt
,
chosen_memory_format
);
// create a conv primitive descriptor and save it for usage in backward
...
...
@@ -429,11 +434,11 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
memory
::
format
::
x
);
conv_pd
=
ConvFwdPrimitiveDesc
(
src_md
,
weights_md
,
bias_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
output_shift_scale
,
is_test
);
fuse_relu
,
output_shift_scale
,
is_test
);
}
else
{
conv_pd
=
ConvFwdPrimitiveDesc
(
src_md
,
weights_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
output_shift_scale
,
is_test
);
conv_pd
=
ConvFwdPrimitiveDesc
(
src_md
,
weights_md
,
dst_md
,
strides
,
paddings
,
mkldnn_engine
,
fuse_relu
,
output_shift_scale
,
is_test
);
}
// Save conv_pd/src_memory/weights_memory for backward pass
dev_ctx
.
SetBlob
(
key_conv_pd
,
conv_pd
);
...
...
@@ -459,7 +464,11 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
mask_reorder
);
if
(
!
force_fp32_output
)
{
if
(
fuse_relu
)
{
dst_memory_p
=
platform
::
SetDstMemory
<
uint8_t
>
(
ctx
,
output
,
handler
);
}
else
{
dst_memory_p
=
platform
::
SetDstMemory
<
int8_t
>
(
ctx
,
output
,
handler
);
}
}
else
{
dst_memory_p
=
platform
::
SetDstMemory
<
float
>
(
ctx
,
output
,
handler
);
}
...
...
@@ -518,8 +527,13 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
mkldnn_engine
,
key
));
}
if
(
!
force_fp32_output
)
{
if
(
fuse_relu
)
{
dst_memory_p
=
platform
::
SetDstMemoryHandler
<
uint8_t
>
(
ctx
,
output
,
handler
);
}
else
{
dst_memory_p
=
platform
::
SetDstMemoryHandler
<
int8_t
>
(
ctx
,
output
,
handler
);
}
}
else
{
dst_memory_p
=
platform
::
SetDstMemoryHandler
<
float
>
(
ctx
,
output
,
handler
);
...
...
@@ -563,11 +577,18 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
}
mkldnn
::
primitive_attr
CreatePostOps
(
const
std
::
vector
<
float
>
output_shift_scale
)
const
{
bool
fuse_relu
,
const
std
::
vector
<
float
>
output_shift_scale
)
const
{
mkldnn
::
primitive_attr
conv_attr
;
mkldnn
::
post_ops
post_operations
;
int
mask
=
output_shift_scale
.
size
()
>
1
?
1
<<
1
:
0
;
conv_attr
.
set_output_scales
(
mask
,
output_shift_scale
);
if
(
fuse_relu
)
{
constexpr
float
scale
=
1.0
f
;
constexpr
float
negative_slope
=
0.0
f
;
constexpr
float
placeholder
=
1.0
f
;
// beta
post_operations
.
append_eltwise
(
scale
,
mkldnn
::
algorithm
::
eltwise_relu
,
negative_slope
,
placeholder
);
}
conv_attr
.
set_post_ops
(
post_operations
);
return
conv_attr
;
}
...
...
@@ -600,7 +621,7 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
ConvFwdPrimitiveDesc
(
const
memory
::
desc
&
src
,
const
memory
::
desc
&
weights
,
const
memory
::
desc
&
dst
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
mkldnn
::
engine
&
engine
,
const
mkldnn
::
engine
&
engine
,
const
bool
fuse_relu
,
const
std
::
vector
<
float
>
output_shift_scale
,
bool
is_test
)
const
{
memory
::
dims
stride_dims
=
{
strides
[
0
],
strides
[
1
]};
...
...
@@ -613,7 +634,8 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
propagation
,
mkldnn
::
convolution_direct
,
src
,
weights
,
dst
,
stride_dims
,
padding_dims
,
padding_dims
,
mkldnn
::
padding_kind
::
zero
);
mkldnn
::
primitive_attr
conv_attr
=
CreatePostOps
(
output_shift_scale
);
mkldnn
::
primitive_attr
conv_attr
=
CreatePostOps
(
fuse_relu
,
output_shift_scale
);
auto
p_conv_pd
=
new
mkldnn
::
convolution_forward
::
primitive_desc
(
conv_desc
,
conv_attr
,
engine
);
...
...
@@ -652,7 +674,7 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
const
memory
::
desc
&
bias
,
const
memory
::
desc
&
dst
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
mkldnn
::
engine
&
engine
,
const
mkldnn
::
engine
&
engine
,
const
bool
fuse_relu
,
const
std
::
vector
<
float
>
output_shift_scale
,
bool
is_test
)
const
{
memory
::
dims
stride_dims
=
{
strides
[
0
],
strides
[
1
]};
...
...
@@ -665,7 +687,8 @@ class ConvMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
propagation
,
mkldnn
::
convolution_direct
,
src
,
weights
,
bias
,
dst
,
stride_dims
,
padding_dims
,
padding_dims
,
mkldnn
::
padding_kind
::
zero
);
mkldnn
::
primitive_attr
conv_attr
=
CreatePostOps
(
output_shift_scale
);
mkldnn
::
primitive_attr
conv_attr
=
CreatePostOps
(
fuse_relu
,
output_shift_scale
);
auto
p_conv_pd
=
new
mkldnn
::
convolution_forward
::
primitive_desc
(
conv_desc
,
conv_attr
,
engine
);
...
...
paddle/fluid/operators/linear_chain_crf_op.cc
浏览文件 @
68a07328
...
...
@@ -230,10 +230,12 @@ class LinearChainCRFGradOp : public framework::OperatorWithKernel {
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"Emission"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Emission"
),
emission_exps_dims
);
ctx
->
ShareLoD
(
"Emission"
,
framework
::
GradVarName
(
"Emission"
));
}
if
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"Transition"
)))
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"Transition"
),
transition_exps_dims
);
ctx
->
ShareLoD
(
"Transition"
,
framework
::
GradVarName
(
"Transition"
));
}
}
...
...
paddle/fluid/operators/math/blas_impl.cu.h
浏览文件 @
68a07328
...
...
@@ -62,27 +62,19 @@ struct CUBlas<float> {
cudaDataType_t
Atype
,
int
lda
,
const
void
*
B
,
cudaDataType_t
Btype
,
int
ldb
,
const
float
*
beta
,
void
*
C
,
cudaDataType_t
Ctype
,
int
ldc
)
{
// Because the gcc 4.8 doesn't expand template parameter pack that
// appears in a lambda-expression, I can not use template parameter pack
// here.
auto
cublas_call
=
[
&
]()
{
// Because the gcc 4.8 doesn't expand template parameter pack that
// appears in a lambda-expression, I can not use template parameter pack
// here.
#if CUDA_VERSION >= 8000
VLOG
(
5
)
<<
"use_tensor_op_math: "
<<
(
platform
::
TensorCoreAvailable
()
?
"True"
:
"False"
);
<<
(
dev_ctx
->
tensor_core_available
()
?
"True"
:
"False"
);
dev_ctx
->
TensorCoreCublasCallIfAvailable
([
&
](
cublasHandle_t
handle
)
{
PADDLE_ENFORCE
(
platform
::
dynload
::
cublasSgemmEx
(
dev_ctx
->
cublas_handle
(),
transa
,
transb
,
m
,
n
,
k
,
alpha
,
A
,
Atype
,
lda
,
B
,
Btype
,
ldb
,
beta
,
C
,
Ctype
,
ldc
));
handle
,
transa
,
transb
,
m
,
n
,
k
,
alpha
,
A
,
Atype
,
lda
,
B
,
Btype
,
ldb
,
beta
,
C
,
Ctype
,
ldc
));
});
#else
PADDLE_THROW
(
"cublasSgemmEx is supported on cuda >= 8.0"
);
#endif
};
#if CUDA_VERSION >= 9000
// NOTES: To use Tensor Core, we should change the cublas config,
// but the cublas may be hold by multi-thread.
dev_ctx
->
CublasCall
(
cublas_call
,
CUBLAS_TENSOR_OP_MATH
);
#else
cublas_call
();
#endif
}
};
...
...
@@ -170,11 +162,10 @@ struct CUBlas<platform::float16> {
cudaDataType_t
Btype
,
int
ldb
,
const
void
*
beta
,
void
*
C
,
cudaDataType_t
Ctype
,
int
ldc
,
cudaDataType_t
computeType
)
{
auto
cublas_call
=
[
&
]()
{
#if CUDA_VERSION >= 8000
cublasGemmAlgo_t
algo
=
CUBLAS_GEMM_DFALT
;
#if CUDA_VERSION >= 9000
bool
use_tensor_op_math
=
platform
::
TensorCoreA
vailable
();
bool
use_tensor_op_math
=
dev_ctx
->
tensor_core_a
vailable
();
if
(
use_tensor_op_math
)
{
algo
=
CUBLAS_GEMM_DFALT_TENSOR_OP
;
}
...
...
@@ -182,20 +173,13 @@ struct CUBlas<platform::float16> {
<<
(
use_tensor_op_math
?
"True"
:
"False"
);
#endif // CUDA_VERSION >= 9000
dev_ctx
->
TensorCoreCublasCallIfAvailable
([
&
](
cublasHandle_t
handle
)
{
PADDLE_ENFORCE
(
platform
::
dynload
::
cublasGemmEx
(
dev_ctx
->
cublas_handle
(),
transa
,
transb
,
m
,
n
,
k
,
alpha
,
A
,
Atype
,
lda
,
B
,
Btype
,
ldb
,
beta
,
C
,
Ctype
,
ldc
,
computeType
,
algo
));
handle
,
transa
,
transb
,
m
,
n
,
k
,
alpha
,
A
,
Atype
,
lda
,
B
,
Btype
,
ldb
,
beta
,
C
,
Ctype
,
ldc
,
computeType
,
algo
));
});
#else
PADDLE_THROW
(
"cublasGemmEx is supported on cuda >= 8.0"
);
#endif
};
#if CUDA_VERSION >= 9000
// NOTES: To use Tensor Core, we should change the cublas config,
// but the cublas may be hold by multi-thread.
dev_ctx
->
CublasCall
(
cublas_call
,
CUBLAS_TENSOR_OP_MATH
);
#else
cublas_call
();
#endif
}
};
...
...
@@ -223,9 +207,10 @@ void Blas<platform::CUDADeviceContext>::GEMM(CBLAS_TRANSPOSE transA,
CUDA_R_32F
,
N
);
}
else
{
#endif // CUDA_VERSION >= 8000
CUBlas
<
T
>::
GEMM
(
context_
.
cublas_handle
(),
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
A
,
lda
,
&
beta
,
C
,
N
);
context_
.
CublasCall
([
&
](
cublasHandle_t
handle
)
{
CUBlas
<
T
>::
GEMM
(
handle
,
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
A
,
lda
,
&
beta
,
C
,
N
);
});
#if CUDA_VERSION >= 8000
}
...
...
@@ -266,9 +251,12 @@ inline void Blas<platform::CUDADeviceContext>::GEMM(
CUDA_R_16F
,
lda
,
&
h_beta
,
C
,
CUDA_R_16F
,
N
,
CUDA_R_32F
);
#else
// CUDA 7.5 does not support cublasGemmEx, hence we fall back to use hgemm
CUBlas
<
platform
::
float16
>::
GEMM
(
context_
.
cublas_handle
(),
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
h_alpha
,
h_B
,
ldb
,
h_A
,
lda
,
&
h_beta
,
h_C
,
N
);
context_
.
CublasCall
([
&
](
cublasHandle_t
handle
)
{
CUBlas
<
platform
::
float16
>::
GEMM
(
handle
,
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
h_alpha
,
h_B
,
ldb
,
h_A
,
lda
,
&
h_beta
,
h_C
,
N
);
});
#endif // CUDA_VERSION >= 8000
}
...
...
@@ -292,8 +280,10 @@ void Blas<platform::CUDADeviceContext>::GEMM(bool transA, bool transB, int M,
}
else
{
#endif // CUDA_VERSION >= 8000
CUBlas
<
T
>::
GEMM
(
context_
.
cublas_handle
(),
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
A
,
lda
,
&
beta
,
C
,
ldc
);
context_
.
CublasCall
([
&
](
cublasHandle_t
handle
)
{
CUBlas
<
T
>::
GEMM
(
handle
,
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
A
,
lda
,
&
beta
,
C
,
ldc
);
});
#if CUDA_VERSION >= 8000
}
...
...
@@ -311,16 +301,19 @@ inline void Blas<platform::CUDADeviceContext>::GEMM(
cublasOperation_t
cuTransA
=
transA
?
CUBLAS_OP_T
:
CUBLAS_OP_N
;
cublasOperation_t
cuTransB
=
transB
?
CUBLAS_OP_T
:
CUBLAS_OP_N
;
CUBlas
<
platform
::
float16
>::
GEMM
(
context_
.
cublas_handle
(),
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
A
,
lda
,
&
beta
,
C
,
ldc
);
context_
.
CublasCall
([
&
](
cublasHandle_t
handle
)
{
CUBlas
<
platform
::
float16
>::
GEMM
(
handle
,
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
A
,
lda
,
&
beta
,
C
,
ldc
);
});
}
template
<
>
template
<
typename
T
>
void
Blas
<
platform
::
CUDADeviceContext
>::
AXPY
(
int
n
,
T
alpha
,
const
T
*
x
,
T
*
y
)
const
{
CUBlas
<
T
>::
AXPY
(
context_
.
cublas_handle
(),
n
,
&
alpha
,
x
,
1
,
y
,
1
);
context_
.
CublasCall
([
&
](
cublasHandle_t
handle
)
{
CUBlas
<
T
>::
AXPY
(
handle
,
n
,
&
alpha
,
x
,
1
,
y
,
1
);
});
}
template
<
>
...
...
@@ -330,8 +323,9 @@ void Blas<platform::CUDADeviceContext>::GEMV(bool trans_a, int M, int N,
T
beta
,
T
*
C
)
const
{
cublasOperation_t
cuTransA
=
!
trans_a
?
CUBLAS_OP_T
:
CUBLAS_OP_N
;
CUBlas
<
T
>::
GEMV
(
context_
.
cublas_handle
(),
cuTransA
,
N
,
M
,
&
alpha
,
A
,
N
,
B
,
1
,
&
beta
,
C
,
1
);
context_
.
CublasCall
([
&
](
cublasHandle_t
handle
)
{
CUBlas
<
T
>::
GEMV
(
handle
,
cuTransA
,
N
,
M
,
&
alpha
,
A
,
N
,
B
,
1
,
&
beta
,
C
,
1
);
});
}
template
<
>
...
...
@@ -353,28 +347,28 @@ void Blas<platform::CUDADeviceContext>::BatchedGEMM(
#if CUDA_VERSION >= 9010
if
(
FLAGS_enable_cublas_tensor_op_math
&&
std
::
is_same
<
T
,
float
>::
value
)
{
auto
cublas_call
=
[
&
]()
{
cublasGemmAlgo_t
algo
=
CUBLAS_GEMM_DFALT
;
bool
use_tensor_op_math
=
platform
::
TensorCoreA
vailable
();
bool
use_tensor_op_math
=
context_
.
tensor_core_a
vailable
();
if
(
use_tensor_op_math
)
{
algo
=
CUBLAS_GEMM_DFALT_TENSOR_OP
;
}
VLOG
(
5
)
<<
"use_tensor_op_math: "
<<
(
use_tensor_op_math
?
"True"
:
"False"
);
context_
.
TensorCoreCublasCallIfAvailable
([
&
](
cublasHandle_t
handle
)
{
PADDLE_ENFORCE
(
platform
::
dynload
::
cublasGemmStridedBatchedEx
(
context_
.
cublas_handle
(),
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
CUDA_R_32F
,
ldb
,
strideB
,
A
,
CUDA_R_32F
,
lda
,
strideA
,
&
beta
,
C
,
CUDA_R_32F
,
ldc
,
strideC
,
batchCount
,
CUDA_R_32F
,
algo
));
};
auto
&
dev_ctx
=
const_cast
<
platform
::
CUDADeviceContext
&>
(
context_
);
dev_ctx
.
CublasCall
(
cublas_call
,
CUBLAS_TENSOR_OP_MATH
);
handle
,
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
CUDA_R_32F
,
ldb
,
strideB
,
A
,
CUDA_R_32F
,
lda
,
strideA
,
&
beta
,
C
,
CUDA_R_32F
,
ldc
,
strideC
,
batchCount
,
CUDA_R_32F
,
algo
));
});
}
else
{
#endif // CUDA_VERSION >= 9010
CUBlas
<
T
>::
GEMM_STRIDED_BATCH
(
context_
.
cublas_handle
(),
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
strideB
,
A
,
lda
,
strideA
,
&
beta
,
C
,
ldc
,
strideC
,
batchCount
);
context_
.
CublasCall
([
&
](
cublasHandle_t
handle
)
{
CUBlas
<
T
>::
GEMM_STRIDED_BATCH
(
handle
,
cuTransB
,
cuTransA
,
N
,
M
,
K
,
&
alpha
,
B
,
ldb
,
strideB
,
A
,
lda
,
strideA
,
&
beta
,
C
,
ldc
,
strideC
,
batchCount
);
});
#if CUDA_VERSION >= 9010
}
...
...
paddle/fluid/operators/optimizers/adam_op.h
浏览文件 @
68a07328
...
...
@@ -424,16 +424,23 @@ class AdamOpKernel : public framework::OpKernel<T> {
}
}
framework
::
SelectedRows
cpu_grad_merge
;
const
framework
::
SelectedRows
*
grad_merge_ptr
;
if
(
is_strict_sorted
)
{
grad_merge_ptr
=
&
grad
;
}
else
{
// merge duplicated rows if any.
// The rows of grad_merge have been sorted inside MergeAdd functor
framework
::
SelectedRows
*
grad_merge_var
;
scatter
::
MergeAdd
<
DeviceContext
,
T
>
merge_func
;
auto
*
grad_merge_var
=
const_cast
<
framework
::
Scope
&>
(
ctx
.
scope
())
if
(
platform
::
is_cpu_place
(
ctx
.
GetPlace
()))
{
grad_merge_var
=
&
cpu_grad_merge
;
}
else
{
// FIXME(qiao): GPU also need to fix this
grad_merge_var
=
const_cast
<
framework
::
Scope
&>
(
ctx
.
scope
())
.
Var
()
->
GetMutable
<
framework
::
SelectedRows
>
();
}
merge_func
(
ctx
.
template
device_context
<
DeviceContext
>(),
grad
,
grad_merge_var
,
true
);
grad_merge_ptr
=
grad_merge_var
;
...
...
paddle/fluid/
framework/details/multi_devices_graph_check_pass
.h
→
paddle/fluid/
platform/cuda_helper
.h
浏览文件 @
68a07328
// Copyright (c) 201
8
PaddlePaddle Authors. All Rights Reserved.
// Copyright (c) 201
9
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.
...
...
@@ -14,25 +14,45 @@
#pragma once
#include
"paddle/fluid/framework/details/multi_devices_helper.h"
#include
<mutex> // NOLINT
#include <string>
#include "paddle/fluid/platform/dynload/cublas.h"
#include "paddle/fluid/platform/macros.h"
#if CUDA_VERSION < 9000
enum
cublasMath_t
{
CUBLAS_DEFAULT_MATH
=
0
};
#endif
namespace
paddle
{
namespace
framework
{
namespace
details
{
class
SSAGraghBuilderWithChecker
:
public
ir
::
Pass
{
protected:
std
::
unique_ptr
<
ir
::
Graph
>
ApplyImpl
(
std
::
unique_ptr
<
ir
::
Graph
>
graph
)
const
override
{
PADDLE_ENFORCE
(
IsValidGraph
(
graph
.
get
()));
return
graph
;
namespace
platform
{
class
CublasHandleHolder
{
public:
CublasHandleHolder
(
cudaStream_t
stream
,
cublasMath_t
math_type
)
{
PADDLE_ENFORCE
(
dynload
::
cublasCreate
(
&
handle_
));
PADDLE_ENFORCE
(
dynload
::
cublasSetStream
(
handle_
,
stream
));
#if CUDA_VERSION >= 9000
if
(
math_type
==
CUBLAS_TENSOR_OP_MATH
)
{
PADDLE_ENFORCE
(
dynload
::
cublasSetMathMode
(
handle_
,
CUBLAS_TENSOR_OP_MATH
));
}
#endif
}
~
CublasHandleHolder
()
{
PADDLE_ENFORCE
(
dynload
::
cublasDestroy
(
handle_
));
}
template
<
typename
Callback
>
inline
void
Call
(
Callback
&&
callback
)
const
{
std
::
lock_guard
<
std
::
mutex
>
guard
(
mtx_
);
callback
(
handle_
);
}
private:
DISABLE_COPY_AND_ASSIGN
(
CublasHandleHolder
);
bool
IsValidGraph
(
const
ir
::
Graph
*
graph
)
const
;
cublasHandle_t
handle_
;
mutable
std
::
mutex
mtx_
;
};
}
// namespace details
}
// namespace framework
}
// namespace platform
}
// namespace paddle
paddle/fluid/platform/device_context.cc
浏览文件 @
68a07328
...
...
@@ -245,8 +245,15 @@ CUDADeviceContext::CUDADeviceContext(CUDAPlace place)
eigen_stream_
.
reset
(
new
EigenCudaStreamDevice
());
eigen_stream_
->
Reinitialize
(
&
stream_
,
place
);
eigen_device_
.
reset
(
new
Eigen
::
GpuDevice
(
eigen_stream_
.
get
()));
PADDLE_ENFORCE
(
dynload
::
cublasCreate
(
&
cublas_handle_
));
PADDLE_ENFORCE
(
dynload
::
cublasSetStream
(
cublas_handle_
,
stream_
));
cublas_handle_
.
reset
(
new
CublasHandleHolder
(
stream_
,
CUBLAS_DEFAULT_MATH
));
if
(
TensorCoreAvailable
())
{
#if CUDA_VERSION >= 9000
cublas_tensor_core_handle_
.
reset
(
new
CublasHandleHolder
(
stream_
,
CUBLAS_TENSOR_OP_MATH
));
#endif
}
if
(
dynload
::
HasCUDNN
())
{
cudnn_holder_
.
reset
(
new
CudnnHolder
(
&
stream_
,
place
));
}
...
...
@@ -306,7 +313,8 @@ CUDADeviceContext::~CUDADeviceContext() {
SetDeviceId
(
place_
.
device
);
Wait
();
WaitStreamCallback
();
PADDLE_ENFORCE
(
dynload
::
cublasDestroy
(
cublas_handle_
));
cublas_handle_
.
reset
();
cublas_tensor_core_handle_
.
reset
();
eigen_stream_
.
reset
();
eigen_device_
.
reset
();
PADDLE_ENFORCE
(
cudaStreamDestroy
(
stream_
));
...
...
@@ -335,8 +343,8 @@ Eigen::GpuDevice* CUDADeviceContext::eigen_device() const {
return
eigen_device_
.
get
();
}
cublasHandle_t
CUDADeviceContext
::
cublas_hand
le
()
const
{
return
cublas_
handle_
;
bool
CUDADeviceContext
::
tensor_core_availab
le
()
const
{
return
cublas_
tensor_core_handle_
!=
nullptr
;
}
cudnnHandle_t
CUDADeviceContext
::
cudnn_handle
()
const
{
...
...
paddle/fluid/platform/device_context.h
浏览文件 @
68a07328
...
...
@@ -20,6 +20,7 @@ limitations under the License. */
#include "paddle/fluid/memory/malloc.h"
#include "paddle/fluid/platform/temporary_allocator.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/cuda_helper.h"
#include "paddle/fluid/platform/dynload/cublas.h"
#include "paddle/fluid/platform/dynload/cudnn.h"
#include "paddle/fluid/platform/gpu_info.h"
...
...
@@ -209,39 +210,6 @@ class CudnnWorkspaceHandle {
std
::
unique_ptr
<
std
::
lock_guard
<
std
::
mutex
>>
guard_
;
};
#if CUDA_VERSION >= 9000
class
ScopedCublasMathMode
{
public:
ScopedCublasMathMode
(
cublasHandle_t
handle
,
cublasMath_t
new_math_mode
)
:
handle_
(
handle
)
{
need_reset
=
false
;
PADDLE_ENFORCE
(
platform
::
dynload
::
cublasGetMathMode
(
handle_
,
&
old_math_mode_
),
"Failed to get old cublas math mode"
);
if
(
old_math_mode_
!=
new_math_mode
)
{
PADDLE_ENFORCE
(
platform
::
dynload
::
cublasSetMathMode
(
handle_
,
new_math_mode
),
"Failed to set old cublas math mode"
);
need_reset
=
true
;
}
}
~
ScopedCublasMathMode
()
{
if
(
need_reset
)
{
PADDLE_ENFORCE
(
platform
::
dynload
::
cublasSetMathMode
(
handle_
,
old_math_mode_
),
"Failed to set old cublas math mode"
);
}
}
private:
cublasHandle_t
handle_
;
cublasMath_t
old_math_mode_
;
bool
need_reset
;
};
#endif
class
CUDADeviceContext
:
public
DeviceContext
{
public:
explicit
CUDADeviceContext
(
CUDAPlace
place
);
...
...
@@ -262,8 +230,25 @@ class CUDADeviceContext : public DeviceContext {
/*! \brief Return eigen device in the device context. */
Eigen
::
GpuDevice
*
eigen_device
()
const
;
/*! \brief Return cublas handle in the device context. */
cublasHandle_t
cublas_handle
()
const
;
/*! \brief Call cublas function safely. */
template
<
typename
Callback
>
inline
void
CublasCall
(
Callback
&&
callback
)
const
{
cublas_handle_
->
Call
(
std
::
forward
<
Callback
>
(
callback
));
}
/*! \brief Check whether tensor core is supported */
bool
tensor_core_available
()
const
;
/*! \brief Call cublas function with Tensor Core safely. If
Tensor Core is not available, use DEFAULT_MATH instead. */
template
<
typename
Callback
>
inline
void
TensorCoreCublasCallIfAvailable
(
Callback
&&
callback
)
const
{
if
(
cublas_tensor_core_handle_
)
{
cublas_tensor_core_handle_
->
Call
(
std
::
forward
<
Callback
>
(
callback
));
}
else
{
cublas_handle_
->
Call
(
std
::
forward
<
Callback
>
(
callback
));
}
}
/*! \brief Return cudnn handle in the device context. */
cudnnHandle_t
cudnn_handle
()
const
;
...
...
@@ -282,7 +267,6 @@ class CUDADeviceContext : public DeviceContext {
template
<
typename
Callback
>
void
RecordEvent
(
cudaEvent_t
ev
,
Callback
callback
)
{
std
::
lock_guard
<
std
::
mutex
>
guard
(
mtx_
);
callback
();
PADDLE_ENFORCE
(
cudaEventRecord
(
ev
,
stream_
));
}
...
...
@@ -294,18 +278,6 @@ class CUDADeviceContext : public DeviceContext {
void
WaitStreamCallback
()
const
{
callback_manager_
->
Wait
();
}
#if CUDA_VERSION >= 9000
/*! \brief CublasCall may need to change cublas's config,
* but the cublas may be hold by multi-thread, so we should
* add lock here. */
template
<
typename
Callback
>
void
CublasCall
(
Callback
callback
,
cublasMath_t
new_math
)
{
std
::
lock_guard
<
std
::
mutex
>
guard
(
cublas_mtx_
);
ScopedCublasMathMode
scoped_cublas_math
(
cublas_handle_
,
new_math
);
callback
();
}
#endif
private:
CUDAPlace
place_
;
...
...
@@ -313,7 +285,9 @@ class CUDADeviceContext : public DeviceContext {
std
::
unique_ptr
<
EigenCudaStreamDevice
>
eigen_stream_
;
std
::
unique_ptr
<
CudnnHolder
>
cudnn_holder_
;
cudaStream_t
stream_
;
cublasHandle_t
cublas_handle_
;
std
::
unique_ptr
<
CublasHandleHolder
>
cublas_handle_
;
std
::
unique_ptr
<
CublasHandleHolder
>
cublas_tensor_core_handle_
;
int
compute_capability_
;
int
runtime_version_
;
...
...
@@ -321,12 +295,10 @@ class CUDADeviceContext : public DeviceContext {
int
multi_process_
;
int
max_threads_per_mp_
;
mutable
std
::
mutex
mtx_
;
// StreamCallbackManager is thread-safe
std
::
unique_ptr
<
StreamCallbackManager
>
callback_manager_
;
mutable
std
::
mutex
cublas_mtx_
;
DISABLE_COPY_AND_ASSIGN
(
CUDADeviceContext
)
;
};
template
<
>
...
...
paddle/fluid/platform/device_context_test.cu
浏览文件 @
68a07328
...
...
@@ -43,9 +43,6 @@ TEST(Device, CUDADeviceContext) {
ASSERT_NE
(
nullptr
,
gpu_device
);
cudnnHandle_t
cudnn_handle
=
device_context
->
cudnn_handle
();
ASSERT_NE
(
nullptr
,
cudnn_handle
);
cublasHandle_t
cublas_handle
=
device_context
->
cublas_handle
();
ASSERT_NE
(
nullptr
,
cublas_handle
);
ASSERT_NE
(
nullptr
,
device_context
->
stream
());
delete
device_context
;
}
}
...
...
paddle/fluid/platform/mkldnn_reuse.h
浏览文件 @
68a07328
...
...
@@ -214,16 +214,18 @@ class MKLDNNHandler {
std
::
string
*
key
,
const
mkldnn
::
memory
::
dims
&
input_dims
,
const
mkldnn
::
memory
::
dims
&
weights_dims
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
int
>&
paddings
,
const
std
::
vector
<
int
>&
dilations
,
const
int
&
groups
,
const
mkldnn
::
memory
::
data_type
&
type
,
const
mkldnn
::
memory
::
format
&
format
,
const
std
::
string
&
suffix
)
{
const
int
&
groups
,
const
mkldnn
::
memory
::
data_type
&
srcdt
,
const
mkldnn
::
memory
::
format
&
format
,
const
mkldnn
::
memory
::
data_type
&
dstdt
,
const
std
::
string
&
suffix
)
{
AppendKeyDims
(
key
,
input_dims
);
AppendKeyDims
(
key
,
weights_dims
);
AppendKeyVec
(
key
,
strides
);
AppendKeyVec
(
key
,
paddings
);
AppendKeyVec
(
key
,
dilations
);
AppendKey
(
key
,
std
::
to_string
(
groups
));
AppendKey
(
key
,
std
::
to_string
(
type
));
AppendKey
(
key
,
std
::
to_string
(
srcdt
));
AppendKey
(
key
,
std
::
to_string
(
format
));
AppendKey
(
key
,
std
::
to_string
(
dstdt
));
AppendKey
(
key
,
suffix
);
}
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
68a07328
...
...
@@ -946,13 +946,6 @@ All parameter, weight, gradient are variables in Paddle.
R"DOC(The type is STR, debug_graphviz_path indicate the path that
writing the SSA Graph to file in the form of graphviz, you.
It is useful for debugging. Default "")DOC"
)
.
def_property
(
"enable_data_balance"
,
[](
const
BuildStrategy
&
self
)
{
return
self
.
enable_data_balance_
;
},
[](
BuildStrategy
&
self
,
bool
b
)
{
PADDLE_ENFORCE
(
!
self
.
IsFinalized
(),
"BuildStrategy is finlaized."
);
self
.
enable_data_balance_
=
b
;
})
// FIXME(chengudo): enable_data_balance seems not important
.
def_property
(
"enable_sequential_execution"
,
[](
const
BuildStrategy
&
self
)
{
...
...
@@ -1007,6 +1000,10 @@ All parameter, weight, gradient are variables in Paddle.
"memory_optimize"
,
[](
const
BuildStrategy
&
self
)
{
return
self
.
memory_optimize_
;
},
[](
BuildStrategy
&
self
,
bool
b
)
{
self
.
memory_optimize_
=
b
;
})
.
def_property
(
"is_distribution"
,
[](
const
BuildStrategy
&
self
)
{
return
self
.
is_distribution_
;
},
[](
BuildStrategy
&
self
,
bool
b
)
{
self
.
is_distribution_
=
b
;
})
.
def_property
(
"memory_early_delete"
,
[](
const
BuildStrategy
&
self
)
{
return
self
.
memory_early_delete_
;
},
...
...
python/paddle/fluid/parallel_executor.py
浏览文件 @
68a07328
...
...
@@ -29,6 +29,15 @@ ExecutionStrategy = core.ParallelExecutor.ExecutionStrategy
BuildStrategy
=
core
.
ParallelExecutor
.
BuildStrategy
def
_is_pserver_mode
(
main_program
):
main
=
main_program
if
main_program
\
else
framework
.
default_main_program
()
for
op
in
main
.
global_block
().
ops
:
if
op
.
type
in
[
"send"
,
"recv"
]:
return
True
return
False
class
ParallelExecutor
(
object
):
"""
ParallelExecutor is designed for data parallelism, which focuses on distributing
...
...
@@ -128,6 +137,11 @@ class ParallelExecutor(object):
build_strategy
=
BuildStrategy
()
build_strategy
.
num_trainers
=
num_trainers
build_strategy
.
trainer_id
=
trainer_id
# FIXME(zcd): is_distribution_ is a temporary field, because in pserver mode,
# num_trainers is 1, so the current fields of build_strategy doesn't tell if
# it's distributed model.
build_strategy
.
is_distribution
=
_is_pserver_mode
(
main_program
)
or
num_trainers
>
1
# step4: get main_program, scope, local_scopes
main
=
main_program
if
main_program
\
...
...
python/paddle/fluid/tests/unittests/test_conv2d_int8_mkldnn_op.py
浏览文件 @
68a07328
...
...
@@ -47,7 +47,8 @@ class TestConv2dInt8Op(TestConv2dOp):
self
.
init_group
()
self
.
init_dilation
()
self
.
init_test_case
()
self
.
init_dtype
()
self
.
init_fuse_relu
()
self
.
init_data_type
()
conv2d_param
=
{
'stride'
:
self
.
stride
,
...
...
@@ -78,6 +79,10 @@ class TestConv2dInt8Op(TestConv2dOp):
np
.
round
((
input_shift
)
*
self
.
scale_in
).
astype
(
np
.
int32
),
filter_int
,
self
.
groups
,
conv2d_param
).
astype
(
np
.
float32
)
*
scale_output_shift
if
self
.
fuse_relu
:
output
=
np
.
maximum
(
np
.
round
(
output1
-
output2
),
0
).
astype
(
self
.
dsttype
)
else
:
output
=
np
.
round
(
output1
-
output2
).
astype
(
self
.
dsttype
)
else
:
filter_int
=
np
.
round
(
filter
*
...
...
@@ -87,7 +92,15 @@ class TestConv2dInt8Op(TestConv2dOp):
output1
=
conv2d_forward_refer
(
input
.
astype
(
np
.
int32
),
filter_int
,
self
.
groups
,
conv2d_param
).
astype
(
np
.
float32
)
output
=
np
.
round
(
output1
*
scale_output_shift
).
astype
(
self
.
dsttype
)
if
self
.
fuse_relu
:
output
=
np
.
maximum
(
np
.
round
(
output1
*
(
self
.
scale_out
/
(
self
.
scale_in
*
self
.
scale_weights
[
0
]))),
0
).
astype
(
self
.
dsttype
)
else
:
output
=
np
.
round
(
output1
*
(
self
.
scale_out
/
(
self
.
scale_in
*
self
.
scale_weights
[
0
]))).
astype
(
self
.
dsttype
)
self
.
inputs
=
{
'Input'
:
...
...
@@ -106,6 +119,7 @@ class TestConv2dInt8Op(TestConv2dOp):
'Scale_in'
:
self
.
scale_in
,
'Scale_out'
:
self
.
scale_out
,
'Scale_weights'
:
self
.
scale_weights
,
'fuse_relu'
:
self
.
fuse_relu
}
self
.
outputs
=
{
'Output'
:
output
}
...
...
@@ -129,12 +143,15 @@ class TestConv2dInt8Op(TestConv2dOp):
self
.
scale_out
=
0.5
self
.
scale_weights
=
[
10.0
]
def
init_dtype
(
self
):
def
init_d
ata_
type
(
self
):
self
.
srctype
=
np
.
uint8
self
.
dsttype
=
np
.
int8
def
init_fuse_relu
(
self
):
self
.
fuse_relu
=
True
#--------------------test conv2d u8 in and
s
8 out--------------------
#--------------------test conv2d u8 in and
u
8 out--------------------
class
TestConv2d
(
TestConv2dInt8Op
):
...
...
@@ -203,18 +220,43 @@ class TestWithInput1x1Filter1x1(TestConv2dInt8Op):
self
.
groups
=
3
#--------------------test conv2d s8 in and s8 out--------------------
def
init_data_type_with_fusion
(
self
,
input_dt
,
fuse_relu
):
self
.
srctype
=
input_dt
self
.
dsttype
=
np
.
uint8
if
fuse_relu
else
np
.
int8
def
init_fuse_relu
(
self
):
self
.
fuse_relu
=
fuse_relu
def
create_test_int8_class
(
parent
):
class
TestInt8Case
(
parent
):
def
init_dtype
(
self
):
self
.
srctype
=
np
.
int8
self
.
dsttype
=
np
.
int8
cls_name
=
"{0}_{1}"
.
format
(
parent
.
__name__
,
"s8s8"
)
TestInt8Case
.
__name__
=
cls_name
globals
()[
cls_name
]
=
TestInt8Case
#--------------------test conv2d s8 in and u8 out--------------------
class
TestS8U8Case
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
int8
,
True
)
#--------------------test conv2d s8 in and s8 out--------------------
class
TestS8S8Case
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
int8
,
False
)
#--------------------test conv2d u8 in and s8 out--------------------
class
TestU8S8Case
(
parent
):
def
init_data_type
(
self
):
init_data_type_with_fusion
(
self
,
np
.
uint8
,
False
)
cls_name_s8u8
=
"{0}_relu_{1}"
.
format
(
parent
.
__name__
,
"1"
)
cls_name_s8s8
=
"{0}_relu_{1}"
.
format
(
parent
.
__name__
,
"0"
)
cls_name_u8s8
=
"{0}_relu_{1}"
.
format
(
parent
.
__name__
,
"0"
)
TestS8U8Case
.
__name__
=
cls_name_s8u8
TestS8S8Case
.
__name__
=
cls_name_s8s8
TestU8S8Case
.
__name__
=
cls_name_u8s8
globals
()[
cls_name_s8u8
]
=
TestS8U8Case
globals
()[
cls_name_s8s8
]
=
TestS8S8Case
globals
()[
cls_name_u8s8
]
=
TestU8S8Case
create_test_int8_class
(
TestConv2dInt8Op
)
...
...
python/paddle/fluid/tests/unittests/test_reader_reset.py
浏览文件 @
68a07328
...
...
@@ -75,8 +75,6 @@ class TestReaderReset(unittest.TestCase):
exe
.
run
(
startup_prog
)
build_strategy
=
fluid
.
BuildStrategy
()
if
with_double_buffer
:
build_strategy
.
enable_data_balance
=
True
exec_strategy
=
fluid
.
ExecutionStrategy
()
parallel_exe
=
fluid
.
ParallelExecutor
(
use_cuda
=
self
.
use_cuda
,
...
...
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