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体验新版 GitCode,发现更多精彩内容 >>
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提交
c5a45cc6
编写于
12月 06, 2022
作者:
Y
Yuanle Liu
提交者:
GitHub
12月 06, 2022
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电子邮件补丁
差异文件
[Paddle Inference] Add float_to_half_pass to support inference with mixed precision (#47993)
上级
54b756e2
变更
13
展开全部
隐藏空白更改
内联
并排
Showing
13 changed file
with
1185 addition
and
20 deletion
+1185
-20
paddle/fluid/framework/ir/CMakeLists.txt
paddle/fluid/framework/ir/CMakeLists.txt
+1
-0
paddle/fluid/framework/ir/float_to_half_pass.cc
paddle/fluid/framework/ir/float_to_half_pass.cc
+725
-0
paddle/fluid/framework/ir/float_to_half_pass.h
paddle/fluid/framework/ir/float_to_half_pass.h
+98
-0
paddle/fluid/inference/analysis/argument.h
paddle/fluid/inference/analysis/argument.h
+2
-0
paddle/fluid/inference/analysis/ir_pass_manager.cc
paddle/fluid/inference/analysis/ir_pass_manager.cc
+4
-0
paddle/fluid/inference/api/analysis_config.cc
paddle/fluid/inference/api/analysis_config.cc
+22
-5
paddle/fluid/inference/api/analysis_predictor.cc
paddle/fluid/inference/api/analysis_predictor.cc
+21
-4
paddle/fluid/inference/api/paddle_analysis_config.h
paddle/fluid/inference/api/paddle_analysis_config.h
+9
-3
paddle/fluid/inference/api/paddle_pass_builder.cc
paddle/fluid/inference/api/paddle_pass_builder.cc
+2
-1
paddle/fluid/inference/tests/api/CMakeLists.txt
paddle/fluid/inference/tests/api/CMakeLists.txt
+3
-0
paddle/fluid/inference/tests/api/gpu_ernie_half_test.cc
paddle/fluid/inference/tests/api/gpu_ernie_half_test.cc
+294
-0
paddle/fluid/inference/tests/api/paddle_infer_api_test.cc
paddle/fluid/inference/tests/api/paddle_infer_api_test.cc
+2
-6
paddle/fluid/pybind/inference_api.cc
paddle/fluid/pybind/inference_api.cc
+2
-1
未找到文件。
paddle/fluid/framework/ir/CMakeLists.txt
浏览文件 @
c5a45cc6
...
...
@@ -104,6 +104,7 @@ pass_library(delete_c_identity_op_pass inference)
pass_library
(
preln_residual_bias_fuse_pass inference
)
pass_library
(
delete_fill_constant_op_pass inference
)
pass_library
(
constant_folding_pass inference
)
pass_library
(
float_to_half_pass inference
)
pass_library
(
conv2d_fusion_layout_transfer_pass inference
)
pass_library
(
simplify_with_basic_ops_pass base
)
pass_library
(
fc_elementwise_layernorm_fuse_pass base
)
...
...
paddle/fluid/framework/ir/float_to_half_pass.cc
0 → 100644
浏览文件 @
c5a45cc6
此差异已折叠。
点击以展开。
paddle/fluid/framework/ir/float_to_half_pass.h
0 → 100644
浏览文件 @
c5a45cc6
// Copyright (c) 2022 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 <unordered_map>
#include <unordered_set>
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/node.h"
#include "paddle/phi/common/backend.h"
#include "paddle/phi/common/data_type.h"
#include "paddle/phi/common/float16.h"
#include "paddle/phi/common/layout.h"
#include "paddle/phi/common/place.h"
namespace
paddle
{
namespace
framework
{
namespace
ir
{
class
FloatToHalfPass
:
public
FusePassBase
{
public:
using
VarType
=
framework
::
proto
::
VarType
;
public:
FloatToHalfPass
()
=
default
;
~
FloatToHalfPass
()
=
default
;
protected:
void
ApplyImpl
(
Graph
*
graph
)
const
override
;
private:
void
Init
(
Graph
*
graph
)
const
;
void
SetDefaultBlacklist
()
const
;
bool
OpSupportPrecision
(
const
std
::
string
&
op_type
,
phi
::
DataType
precision
,
phi
::
Backend
backend
=
phi
::
Backend
::
GPU
)
const
;
void
SetOpUniqueType
()
const
;
void
RestoreOpOriginType
()
const
;
inline
std
::
string
GetOpOriginalType
(
const
std
::
string
&
op_type
)
const
;
void
GetOpPrecision
()
const
;
void
UpdateOpPrecision
()
const
;
void
InsertCastOp
()
const
;
void
ProcessOpWithDtypeAttr
()
const
;
bool
InputVarsNotConvert
(
Node
*
op_node
,
const
std
::
string
&
var_name
)
const
;
bool
OutputVarsNotConvert
(
Node
*
op_node
,
const
std
::
string
&
var_name
)
const
;
void
SetVarPrecision
()
const
;
void
ConvertWeightsData
()
const
;
private:
mutable
bool
keep_io_types_
;
// float16 or bfloat16 now
mutable
phi
::
DataType
half_precision_
;
mutable
std
::
unordered_set
<
std
::
string
>
black_list_
;
// subgraph id -> pointer to subgraph
mutable
std
::
vector
<
Graph
*>
subgraphes_
;
// var name -> real var node
mutable
std
::
unordered_map
<
std
::
string
,
Node
*>
real_vars_
;
// subgraph id -> all op nodes in subgraph
mutable
std
::
vector
<
std
::
vector
<
Node
*>>
all_op_nodes_
;
// op's unique type -> the op's origin type
mutable
std
::
unordered_map
<
std
::
string
,
std
::
string
>
op_original_type_
;
// op's unique type -> whether the op run at half precision
mutable
std
::
unordered_set
<
std
::
string
>
op_run_half_
;
mutable
std
::
unordered_set
<
std
::
string
>
vars_convert_to_half_
;
};
}
// namespace ir
}
// namespace framework
}
// namespace paddle
paddle/fluid/inference/analysis/argument.h
浏览文件 @
c5a45cc6
...
...
@@ -365,6 +365,8 @@ struct Argument {
DECL_ARGUMENT_FIELD
(
mixed_black_list
,
MixedBlackList
,
std
::
unordered_set
<
std
::
string
>
);
DECL_ARGUMENT_FIELD
(
enable_gpu_half
,
EnableGPUHalf
,
bool
);
DECL_ARGUMENT_FIELD
(
mixed_precision_mode
,
MixedPrecisionMode
,
int
);
private:
std
::
unordered_set
<
std
::
string
>
valid_fields_
;
...
...
paddle/fluid/inference/analysis/ir_pass_manager.cc
浏览文件 @
c5a45cc6
...
...
@@ -86,10 +86,14 @@ void IRPassManager::CreatePasses(Argument *argument,
argument
->
tensorrt_tuned_dynamic_shape
();
pass
->
Set
(
"with_dynamic_shape"
,
new
bool
(
with_dynamic_shape
));
// mixed precision related
pass
->
Set
(
"model_precision"
,
new
int
(
argument
->
model_precision
()));
pass
->
Set
(
"mixed_black_list"
,
new
std
::
unordered_set
<
std
::
string
>
(
argument
->
mixed_black_list
()));
pass
->
Set
(
"enable_gpu_half"
,
new
bool
(
argument
->
enable_gpu_half
()));
pass
->
Set
(
"mixed_precision_mode"
,
new
int
(
argument
->
mixed_precision_mode
()));
if
(
pass_name
==
"graph_viz_pass"
)
{
std
::
string
optim_cache_dir
=
argument
->
optim_cache_dir
();
...
...
paddle/fluid/inference/api/analysis_config.cc
浏览文件 @
c5a45cc6
...
...
@@ -85,16 +85,29 @@ void AnalysisConfig::SetModel(const std::string &prog_file_path,
Update
();
}
void
AnalysisConfig
::
EnableUseGpu
(
uint64_t
memory_pool_init_size_mb
,
int
device_id
)
{
int
device_id
,
Precision
precision_mode
)
{
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
use_gpu_
=
true
;
memory_pool_init_size_mb_
=
memory_pool_init_size_mb
;
FLAGS_initial_gpu_memory_in_mb
=
memory_pool_init_size_mb_
;
gpu_device_id_
=
device_id
;
mixed_precision_mode_
=
precision_mode
;
if
(
precision_mode
==
Precision
::
kFloat32
)
{
// default
}
else
if
(
precision_mode
==
Precision
::
kHalf
||
precision_mode
==
Precision
::
kBf16
)
{
enable_gpu_half_
=
true
;
}
else
{
LOG
(
ERROR
)
<<
"The Paddle-GPU inference currently only supports "
"float32/float16/bfloat16 precision. Please check the parameters "
"you specified in EnableUseGpu or enable_use_gpu function."
;
}
#else
LOG
(
ERROR
)
<<
"Please compile with gpu to EnableGpu()"
;
use_gpu_
=
false
;
LOG
(
ERROR
)
<<
"Please use PaddlePaddle with GPU version."
;
#endif
Update
();
...
...
@@ -381,8 +394,10 @@ AnalysisConfig::AnalysisConfig(const AnalysisConfig &other) {
CP_MEMBER
(
gpu_device_id_
);
CP_MEMBER
(
memory_pool_init_size_mb_
);
// Mixed related.
// Mixed
precision
related.
CP_MEMBER
(
mixed_black_list_
);
CP_MEMBER
(
enable_gpu_half_
);
CP_MEMBER
(
mixed_precision_mode_
);
CP_MEMBER
(
enable_memory_optim_
);
// TensorRT related.
...
...
@@ -996,6 +1011,7 @@ std::string AnalysisConfig::SerializeInfoCache() {
ss
<<
params_file_
;
ss
<<
use_gpu_
;
ss
<<
enable_gpu_half_
;
ss
<<
use_external_stream_
;
ss
<<
exec_stream_
;
ss
<<
use_fc_padding_
;
...
...
@@ -1212,6 +1228,7 @@ std::string AnalysisConfig::Summary() {
os
.
InsertRow
({
"use_gpu"
,
use_gpu_
?
"true"
:
"false"
});
if
(
use_gpu_
)
{
os
.
InsertRow
({
"gpu_device_id"
,
std
::
to_string
(
gpu_device_id_
)});
os
.
InsertRow
({
"enable_gpu_half_"
,
std
::
to_string
(
enable_gpu_half_
)});
os
.
InsertRow
({
"memory_pool_init_size"
,
std
::
to_string
(
memory_pool_init_size_mb_
)
+
"MB"
});
os
.
InsertRow
(
...
...
@@ -1407,7 +1424,7 @@ bool AnalysisConfig::trt_allow_build_at_runtime() const {
return
trt_allow_build_at_runtime_
;
}
void
AnalysisConfig
::
Exp_
SetBlackListOpsForMixedModel
(
void
AnalysisConfig
::
Exp_
DisableMixedInferOps
(
const
std
::
unordered_set
<
std
::
string
>
&
black_list
)
{
mixed_black_list_
=
black_list
;
}
...
...
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @
c5a45cc6
...
...
@@ -1257,12 +1257,26 @@ void AnalysisPredictor::PrepareArgument() {
}
}
}
if
(
config_
.
ir_debug_
)
{
pass_builder
->
TurnOnDebug
();
}
if
(
!
config_
.
ir_optim
())
{
argument_
.
SetEnableIrOptim
(
false
);
LOG
(
INFO
)
<<
"ir_optim is turned off, no IR pass will be executed"
;
if
(
config_
.
enable_gpu_half_
)
{
argument_
.
SetEnableIrOptim
(
true
);
pass_builder
->
ClearPasses
();
pass_builder
->
AppendPass
(
"float_to_half_pass"
);
LOG
(
INFO
)
<<
"This model run in Paddle-GPU mixed precision mode with no ir "
"optimization."
;
}
else
{
LOG
(
INFO
)
<<
"ir_optim is turned off, no IR pass will be executed."
;
}
}
else
{
if
(
config_
.
ir_debug_
)
{
pass_builder
->
TurnOnDebug
();
}
if
(
config_
.
enable_gpu_half_
)
{
LOG
(
INFO
)
<<
"This model run in Paddle-GPU mixed precision mode."
;
}
}
argument_
.
SetDisableLogs
(
config_
.
glog_info_disabled
());
argument_
.
SetIrAnalysisPasses
(
pass_builder
->
AllPasses
());
...
...
@@ -1272,6 +1286,9 @@ void AnalysisPredictor::PrepareArgument() {
// mixed precison.
argument_
.
SetModelPrecision
(
static_cast
<
int
>
(
model_precision_
));
argument_
.
SetMixedBlackList
(
config_
.
mixed_black_list_
);
argument_
.
SetEnableGPUHalf
(
config_
.
enable_gpu_half_
);
argument_
.
SetMixedPrecisionMode
(
static_cast
<
int
>
(
paddle
::
ConvertPrecision
(
config_
.
mixed_precision_mode_
)));
}
// NOTE All the members in AnalysisConfig should be copied to Argument.
...
...
paddle/fluid/inference/api/paddle_analysis_config.h
浏览文件 @
c5a45cc6
...
...
@@ -247,8 +247,12 @@ struct PD_INFER_DECL AnalysisConfig {
///
/// \param memory_pool_init_size_mb initial size of the GPU memory pool in MB.
/// \param device_id device_id the GPU card to use (default is 0).
/// \param precision the precision used in Paddle-GPU inference.
///
void
EnableUseGpu
(
uint64_t
memory_pool_init_size_mb
,
int
device_id
=
0
);
void
EnableUseGpu
(
uint64_t
memory_pool_init_size_mb
,
int
device_id
=
0
,
Precision
precision_mode
=
Precision
::
kFloat32
);
///
/// \brief Turn off GPU.
///
...
...
@@ -1005,7 +1009,7 @@ struct PD_INFER_DECL AnalysisConfig {
/// interface is in the experimental stage and may change in the future. Note
/// that the blacklist must be the same as the model conversion blacklist.
///
void
Exp_
SetBlackListOpsForMixedModel
(
void
Exp_
DisableMixedInferOps
(
const
std
::
unordered_set
<
std
::
string
>&
black_list
);
void
SetApplyOptim
(
bool
value
)
{
apply_optim_
=
value
;
}
...
...
@@ -1024,13 +1028,15 @@ struct PD_INFER_DECL AnalysisConfig {
mutable
std
::
string
prog_file_
;
mutable
std
::
string
params_file_
;
// Mixed precision.
// Mixed precision related.
Precision
mixed_precision_mode_
{
Precision
::
kFloat32
};
std
::
unordered_set
<
std
::
string
>
mixed_black_list_
;
// GPU related.
bool
use_gpu_
{
false
};
int
gpu_device_id_
{
0
};
uint64_t
memory_pool_init_size_mb_
{
100
};
// initial size is 100MB.
bool
enable_gpu_half_
{
false
};
bool
thread_local_stream_
{
false
};
bool
use_cudnn_
{
false
};
...
...
paddle/fluid/inference/api/paddle_pass_builder.cc
浏览文件 @
c5a45cc6
...
...
@@ -246,9 +246,10 @@ GpuPassStrategy::GpuPassStrategy() : PassStrategy({}) {
"conv_elementwise_add_fuse_pass"
,
//
#endif //
"transpose_flatten_concat_fuse_pass"
,
//
"constant_folding_pass"
,
"constant_folding_pass"
,
//
// following pass should be located in the last, since it will
// work on all fused ops.
"float_to_half_pass"
,
//
"runtime_context_cache_pass"
});
...
...
paddle/fluid/inference/tests/api/CMakeLists.txt
浏览文件 @
c5a45cc6
...
...
@@ -416,6 +416,9 @@ download_result(${ERNIE_INSTALL_DIR} "Ernie_result.txt.tar.gz"
if
(
WITH_GPU
)
inference_analysis_api_test
(
test_analyzer_ernie
${
ERNIE_INSTALL_DIR
}
analyzer_ernie_tester.cc
)
inference_analysis_api_test
(
gpu_ernie_half_test
${
ERNIE_INSTALL_DIR
}
gpu_ernie_half_test.cc
)
set_tests_properties
(
gpu_ernie_half_test PROPERTIES TIMEOUT 40
)
endif
()
inference_analysis_api_int8_test
(
test_analyzer_ernie_int8
${
ERNIE_INSTALL_DIR
}
analyzer_ernie_int8_tester.cc
)
...
...
paddle/fluid/inference/tests/api/gpu_ernie_half_test.cc
0 → 100644
浏览文件 @
c5a45cc6
// Copyright (c) 2022 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/api/paddle_inference_api.h"
#include "paddle/fluid/inference/tests/api/tester_helper.h"
namespace
paddle
{
namespace
inference
{
using
paddle
::
PaddleTensor
;
template
<
typename
T
>
void
GetValueFromStream
(
std
::
stringstream
*
ss
,
T
*
t
)
{
(
*
ss
)
>>
(
*
t
);
}
template
<
>
void
GetValueFromStream
<
std
::
string
>
(
std
::
stringstream
*
ss
,
std
::
string
*
t
)
{
*
t
=
ss
->
str
();
}
// Split string to vector
template
<
typename
T
>
void
Split
(
const
std
::
string
&
line
,
char
sep
,
std
::
vector
<
T
>
*
v
)
{
std
::
stringstream
ss
;
T
t
;
for
(
auto
c
:
line
)
{
if
(
c
!=
sep
)
{
ss
<<
c
;
}
else
{
GetValueFromStream
<
T
>
(
&
ss
,
&
t
);
v
->
push_back
(
std
::
move
(
t
));
ss
.
str
({});
ss
.
clear
();
}
}
if
(
!
ss
.
str
().
empty
())
{
GetValueFromStream
<
T
>
(
&
ss
,
&
t
);
v
->
push_back
(
std
::
move
(
t
));
ss
.
str
({});
ss
.
clear
();
}
}
// Parse tensor from string
template
<
typename
T
>
bool
ParseTensor
(
const
std
::
string
&
field
,
paddle
::
PaddleTensor
*
tensor
)
{
std
::
vector
<
std
::
string
>
data
;
Split
(
field
,
':'
,
&
data
);
if
(
data
.
size
()
<
2
)
return
false
;
std
::
string
shape_str
=
data
[
0
];
std
::
vector
<
int
>
shape
;
Split
(
shape_str
,
' '
,
&
shape
);
std
::
string
mat_str
=
data
[
1
];
std
::
vector
<
T
>
mat
;
Split
(
mat_str
,
' '
,
&
mat
);
tensor
->
shape
=
shape
;
auto
size
=
std
::
accumulate
(
shape
.
begin
(),
shape
.
end
(),
1
,
std
::
multiplies
<
int
>
())
*
sizeof
(
T
);
tensor
->
data
.
Resize
(
size
);
std
::
copy
(
mat
.
begin
(),
mat
.
end
(),
static_cast
<
T
*>
(
tensor
->
data
.
data
()));
tensor
->
dtype
=
GetPaddleDType
<
T
>
();
return
true
;
}
// Parse input tensors from string
bool
ParseLine
(
const
std
::
string
&
line
,
std
::
vector
<
paddle
::
PaddleTensor
>
*
tensors
)
{
std
::
vector
<
std
::
string
>
fields
;
Split
(
line
,
';'
,
&
fields
);
tensors
->
clear
();
tensors
->
reserve
(
4
);
int
i
=
0
;
auto
input_name
=
FLAGS_ernie_large
?
"eval_placeholder_"
:
"placeholder_"
;
for
(;
i
<
3
;
i
++
)
{
paddle
::
PaddleTensor
temp
;
ParseTensor
<
int64_t
>
(
fields
[
i
],
&
temp
);
temp
.
name
=
input_name
+
std
::
to_string
(
i
);
tensors
->
push_back
(
temp
);
}
// input_mask
paddle
::
PaddleTensor
input_mask
;
ParseTensor
<
float
>
(
fields
[
i
],
&
input_mask
);
input_mask
.
name
=
input_name
+
std
::
to_string
(
i
);
tensors
->
push_back
(
input_mask
);
return
true
;
}
bool
LoadInputData
(
std
::
vector
<
std
::
vector
<
paddle
::
PaddleTensor
>>
*
inputs
,
int
batch_size
=
1
)
{
if
(
FLAGS_infer_data
.
empty
())
{
LOG
(
ERROR
)
<<
"please set input data path"
;
return
false
;
}
std
::
ifstream
fin
(
FLAGS_infer_data
);
std
::
string
line
;
int
sample
=
0
;
// The unit-test dataset only have 10 samples, each sample have 5 feeds.
while
(
std
::
getline
(
fin
,
line
))
{
std
::
vector
<
paddle
::
PaddleTensor
>
feed_data
;
ParseLine
(
line
,
&
feed_data
);
inputs
->
push_back
(
std
::
move
(
feed_data
));
sample
++
;
if
(
!
FLAGS_test_all_data
&&
sample
==
batch_size
)
break
;
}
LOG
(
INFO
)
<<
"number of samples: "
<<
sample
;
return
true
;
}
// Compare results
TEST
(
Ernie_gpu_fp16_no_ir
,
compare_results
)
{
AnalysisConfig
config
;
config
.
SetModel
(
FLAGS_infer_model
);
config
.
EnableUseGpu
(
512
,
0
,
paddle_infer
::
PrecisionType
::
kHalf
);
config
.
SwitchIrOptim
(
false
);
auto
predictor
=
CreatePaddlePredictor
(
config
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
LoadInputData
(
&
input_slots_all
);
std
::
ifstream
fin
(
FLAGS_refer_result
);
std
::
string
line
;
std
::
vector
<
float
>
ref
;
while
(
std
::
getline
(
fin
,
line
))
{
Split
(
line
,
' '
,
&
ref
);
}
std
::
vector
<
PaddleTensor
>
outputs
;
for
(
size_t
i
=
0
;
i
<
input_slots_all
.
size
();
i
++
)
{
outputs
.
clear
();
predictor
->
Run
(
input_slots_all
[
i
],
&
outputs
);
auto
output
=
outputs
.
front
();
size_t
outputs_size
=
1
;
for
(
auto
dim
:
output
.
shape
)
{
outputs_size
*=
dim
;
}
float
*
result
=
reinterpret_cast
<
float
*>
(
output
.
data
.
data
());
for
(
size_t
j
=
0
;
j
<
outputs_size
;
++
j
)
{
EXPECT_NEAR
(
ref
[
i
*
outputs_size
+
j
],
result
[
j
],
5e-2
);
}
}
}
// Compare results
TEST
(
Ernie_gpu_fp16_with_ir
,
compare_results
)
{
AnalysisConfig
config
;
config
.
SetModel
(
FLAGS_infer_model
);
config
.
EnableUseGpu
(
512
,
0
,
paddle_infer
::
PrecisionType
::
kHalf
);
config
.
SwitchIrOptim
(
true
);
// The fc_fuse_pass has diff, which will be repaired later.
config
.
pass_builder
()
->
DeletePass
(
"fc_fuse_pass"
);
// There is a problem with the model itself, which has nothing to do with
// constant_folding_pass.
config
.
pass_builder
()
->
DeletePass
(
"constant_folding_pass"
);
auto
predictor
=
CreatePaddlePredictor
(
config
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
LoadInputData
(
&
input_slots_all
);
std
::
ifstream
fin
(
FLAGS_refer_result
);
std
::
string
line
;
std
::
vector
<
float
>
ref
;
while
(
std
::
getline
(
fin
,
line
))
{
Split
(
line
,
' '
,
&
ref
);
}
std
::
vector
<
PaddleTensor
>
outputs
;
for
(
size_t
i
=
0
;
i
<
input_slots_all
.
size
();
i
++
)
{
outputs
.
clear
();
predictor
->
Run
(
input_slots_all
[
i
],
&
outputs
);
auto
output
=
outputs
.
front
();
size_t
outputs_size
=
1
;
for
(
auto
dim
:
output
.
shape
)
{
outputs_size
*=
dim
;
}
float
*
result
=
reinterpret_cast
<
float
*>
(
output
.
data
.
data
());
for
(
size_t
j
=
0
;
j
<
outputs_size
;
++
j
)
{
EXPECT_NEAR
(
ref
[
i
*
outputs_size
+
j
],
result
[
j
],
5e-2
);
}
}
}
// Compare results
TEST
(
Ernie_gpu_bf16_no_ir
,
compare_results
)
{
AnalysisConfig
config
;
config
.
SetModel
(
FLAGS_infer_model
);
config
.
EnableUseGpu
(
512
,
0
,
paddle_infer
::
PrecisionType
::
kBf16
);
config
.
SwitchIrOptim
(
false
);
auto
predictor
=
CreatePaddlePredictor
(
config
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
LoadInputData
(
&
input_slots_all
);
std
::
ifstream
fin
(
FLAGS_refer_result
);
std
::
string
line
;
std
::
vector
<
float
>
ref
;
while
(
std
::
getline
(
fin
,
line
))
{
Split
(
line
,
' '
,
&
ref
);
}
std
::
vector
<
PaddleTensor
>
outputs
;
for
(
size_t
i
=
0
;
i
<
input_slots_all
.
size
();
i
++
)
{
outputs
.
clear
();
predictor
->
Run
(
input_slots_all
[
i
],
&
outputs
);
auto
output
=
outputs
.
front
();
size_t
outputs_size
=
1
;
for
(
auto
dim
:
output
.
shape
)
{
outputs_size
*=
dim
;
}
float
*
result
=
reinterpret_cast
<
float
*>
(
output
.
data
.
data
());
for
(
size_t
j
=
0
;
j
<
outputs_size
;
++
j
)
{
EXPECT_NEAR
(
ref
[
i
*
outputs_size
+
j
],
result
[
j
],
7e-2
);
}
}
}
// Compare results
TEST
(
Ernie_gpu_bf16_with_ir
,
compare_results
)
{
AnalysisConfig
config
;
config
.
SetModel
(
FLAGS_infer_model
);
config
.
EnableUseGpu
(
512
,
0
,
paddle_infer
::
PrecisionType
::
kBf16
);
config
.
SwitchIrOptim
(
true
);
// The fc_fuse_pass has diff, which will be repaired later.
config
.
pass_builder
()
->
DeletePass
(
"fc_fuse_pass"
);
// There is a problem with the model itself, which has nothing to do with
// constant_folding_pass.
config
.
pass_builder
()
->
DeletePass
(
"constant_folding_pass"
);
auto
predictor
=
CreatePaddlePredictor
(
config
);
std
::
vector
<
std
::
vector
<
PaddleTensor
>>
input_slots_all
;
LoadInputData
(
&
input_slots_all
);
std
::
ifstream
fin
(
FLAGS_refer_result
);
std
::
string
line
;
std
::
vector
<
float
>
ref
;
while
(
std
::
getline
(
fin
,
line
))
{
Split
(
line
,
' '
,
&
ref
);
}
std
::
vector
<
PaddleTensor
>
outputs
;
for
(
size_t
i
=
0
;
i
<
input_slots_all
.
size
();
i
++
)
{
outputs
.
clear
();
predictor
->
Run
(
input_slots_all
[
i
],
&
outputs
);
auto
output
=
outputs
.
front
();
size_t
outputs_size
=
1
;
for
(
auto
dim
:
output
.
shape
)
{
outputs_size
*=
dim
;
}
float
*
result
=
reinterpret_cast
<
float
*>
(
output
.
data
.
data
());
for
(
size_t
j
=
0
;
j
<
outputs_size
;
++
j
)
{
EXPECT_NEAR
(
ref
[
i
*
outputs_size
+
j
],
result
[
j
],
7e-2
);
}
}
}
}
// namespace inference
}
// namespace paddle
paddle/fluid/inference/tests/api/paddle_infer_api_test.cc
浏览文件 @
c5a45cc6
/* Copyright (c) 20
18
PaddlePaddle Authors. All Rights Reserved.
/* Copyright (c) 20
22
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.
...
...
@@ -12,15 +12,11 @@ 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 <cuda_runtime.h>
#include <glog/logging.h>
#include <gtest/gtest.h>
#include <cstring>
#include <numeric>
#include "gflags/gflags.h"
#include "paddle/fluid/inference/tests/api/t
rt_test
_helper.h"
#include "paddle/fluid/inference/tests/api/t
ester
_helper.h"
namespace
paddle_infer
{
...
...
paddle/fluid/pybind/inference_api.cc
浏览文件 @
c5a45cc6
...
...
@@ -644,7 +644,8 @@ void BindAnalysisConfig(py::module *m) {
.
def
(
"enable_use_gpu"
,
&
AnalysisConfig
::
EnableUseGpu
,
py
::
arg
(
"memory_pool_init_size_mb"
),
py
::
arg
(
"device_id"
)
=
0
)
py
::
arg
(
"device_id"
)
=
0
,
py
::
arg
(
"precision_mode"
)
=
AnalysisConfig
::
Precision
::
kFloat32
)
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
.
def
(
"set_exec_stream"
,
[](
AnalysisConfig
&
self
,
phi
::
CUDAStream
&
stream
)
{
...
...
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