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体验新版 GitCode,发现更多精彩内容 >>
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85c49127
编写于
7月 27, 2018
作者:
Z
Zhaolong Xing
提交者:
GitHub
7月 27, 2018
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差异文件
Merge pull request #12355 from NHZlX/add_tensorrt_pooling_converter
Add tensorrt pooling converter
上级
5bea9c14
4f71a3b1
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
210 addition
and
15 deletion
+210
-15
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+4
-1
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
+80
-0
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
...le/fluid/inference/tensorrt/convert/test_activation_op.cc
+1
-1
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
+2
-3
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
+2
-2
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
+60
-0
paddle/fluid/inference/tensorrt/convert/ut_helper.h
paddle/fluid/inference/tensorrt/convert/ut_helper.h
+29
-7
paddle/fluid/inference/tensorrt/test_engine.cc
paddle/fluid/inference/tensorrt/test_engine.cc
+32
-1
未找到文件。
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
浏览文件 @
85c49127
# Add TRT tests
nv_library
(
tensorrt_converter
SRCS mul_op.cc conv2d_op.cc fc_op.cc
SRCS mul_op.cc conv2d_op.cc fc_op.cc
pool2d_op.cc
DEPS tensorrt_engine mul_op
)
nv_test
(
test_op_converter SRCS test_op_converter.cc DEPS
...
...
@@ -13,3 +13,6 @@ nv_test(test_trt_fc_op SRCS test_fc_op.cc fc_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine mul_op SERIAL
)
nv_test
(
test_trt_activation_op SRCS test_activation_op.cc activation_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine activation_op SERIAL
)
nv_test
(
test_trt_pool2d_op SRCS test_pool2d_op.cc pool2d_op.cc
DEPS
${
FLUID_CORE_MODULES
}
tensorrt_engine pool_op SERIAL
)
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
0 → 100644
浏览文件 @
85c49127
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
/*
* Pool2dOp, IPoolingLayer in TRT. This Layer doesn't has weights.
*/
class
Pool2dOpConverter
:
public
OpConverter
{
public:
void
operator
()(
const
framework
::
proto
::
OpDesc
&
op
,
const
framework
::
Scope
&
scope
,
bool
test_mode
)
override
{
VLOG
(
4
)
<<
"convert a fluid pool2d op to tensorrt pool2d layer without bias"
;
framework
::
OpDesc
op_desc
(
op
,
nullptr
);
// Declare inputs
PADDLE_ENFORCE_EQ
(
op_desc
.
Input
(
"X"
).
size
(),
1
);
PADDLE_ENFORCE_EQ
(
op_desc
.
Output
(
"Out"
).
size
(),
1
);
auto
*
input1
=
engine_
->
GetITensor
(
op_desc
.
Input
(
"X"
)[
0
]);
std
::
string
pool_type
=
boost
::
get
<
std
::
string
>
(
op_desc
.
GetAttr
(
"pooling_type"
));
std
::
vector
<
int
>
ksize
=
boost
::
get
<
std
::
vector
<
int
>>
(
op_desc
.
GetAttr
(
"ksize"
));
std
::
vector
<
int
>
strides
=
boost
::
get
<
std
::
vector
<
int
>>
(
op_desc
.
GetAttr
(
"strides"
));
std
::
vector
<
int
>
paddings
=
boost
::
get
<
std
::
vector
<
int
>>
(
op_desc
.
GetAttr
(
"paddings"
));
const
nvinfer1
::
DimsHW
nv_ksize
(
ksize
[
0
],
ksize
[
1
]);
const
nvinfer1
::
DimsHW
nv_strides
(
strides
[
0
],
strides
[
1
]);
const
nvinfer1
::
DimsHW
nv_paddings
(
paddings
[
0
],
paddings
[
1
]);
PADDLE_ENFORCE_EQ
(
input1
->
getDimensions
().
nbDims
,
3UL
);
nvinfer1
::
PoolingType
nv_pool_type
=
nvinfer1
::
PoolingType
::
kMAX
;
if
(
pool_type
==
"max"
)
{
nv_pool_type
=
nvinfer1
::
PoolingType
::
kMAX
;
}
else
if
(
pool_type
==
"avg"
)
{
nv_pool_type
=
nvinfer1
::
PoolingType
::
kAVERAGE
;
}
else
{
PADDLE_THROW
(
"TensorRT unsupported pooling type!"
);
}
auto
*
layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Pooling
,
*
const_cast
<
nvinfer1
::
ITensor
*>
(
input1
),
nv_pool_type
,
nv_ksize
);
PADDLE_ENFORCE_NOT_NULL
(
layer
,
"pool layer could not be created."
);
layer
->
setStride
(
nv_strides
);
layer
->
setPadding
(
nv_paddings
);
auto
output_name
=
op_desc
.
Output
(
"Out"
)[
0
];
engine_
->
SetITensor
(
output_name
,
layer
->
getOutput
(
0
));
if
(
test_mode
)
{
engine_
->
DeclareOutput
(
output_name
);
}
}
};
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
pool2d
);
REGISTER_TRT_OP_CONVERTER
(
pool2d
,
Pool2dOpConverter
);
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
浏览文件 @
85c49127
...
...
@@ -37,7 +37,7 @@ TEST(ReluOpConverter, main) {
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
1
);
validator
.
Execute
(
5
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
浏览文件 @
85c49127
...
...
@@ -24,9 +24,8 @@ TEST(fc_op, test) {
std
::
unordered_set
<
std
::
string
>
parameters
({
"mul-Y"
});
framework
::
Scope
scope
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims
4
(
1
,
10
,
1
,
1
));
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims
3
(
10
,
1
,
1
));
validator
.
DeclParamVar
(
"mul-Y"
,
nvinfer1
::
Dims2
(
10
,
2
));
// validator.DeclParamVar("mul-Y", nvinfer1::Dims2(8, 2));
validator
.
DeclOutputVar
(
"mul-Out"
,
nvinfer1
::
Dims2
(
1
,
2
));
// Prepare Op description
...
...
@@ -38,7 +37,7 @@ TEST(fc_op, test) {
validator
.
SetOp
(
*
desc
.
Proto
());
validator
.
Execute
(
1
);
validator
.
Execute
(
1
0
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
浏览文件 @
85c49127
...
...
@@ -23,7 +23,7 @@ namespace tensorrt {
TEST
(
MulOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
,
false
);
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims2
(
10
,
6
));
validator
.
DeclInputVar
(
"mul-Y"
,
nvinfer1
::
Dims2
(
6
,
10
));
validator
.
DeclOutputVar
(
"mul-Out"
,
nvinfer1
::
Dims2
(
10
,
10
));
...
...
@@ -39,7 +39,7 @@ TEST(MulOpConverter, main) {
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
1
);
validator
.
Execute
(
2
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
0 → 100644
浏览文件 @
85c49127
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <gtest/gtest.h>
#include <fstream>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
namespace
paddle
{
namespace
inference
{
namespace
tensorrt
{
TEST
(
Pool2dOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
5
,
parameters
,
scope
,
1
<<
15
);
// The ITensor's Dims should not contain the batch size.
// So, the ITensor's Dims of input and output should be C * H * W.
validator
.
DeclInputVar
(
"pool2d-X"
,
nvinfer1
::
Dims3
(
3
,
4
,
4
));
validator
.
DeclOutputVar
(
"pool2d-Out"
,
nvinfer1
::
Dims3
(
3
,
2
,
2
));
// Prepare Op description
framework
::
OpDesc
desc
;
desc
.
SetType
(
"pool2d"
);
desc
.
SetInput
(
"X"
,
{
"pool2d-X"
});
desc
.
SetOutput
(
"Out"
,
{
"pool2d-Out"
});
std
::
vector
<
int
>
ksize
({
2
,
2
});
std
::
vector
<
int
>
strides
({
2
,
2
});
std
::
vector
<
int
>
paddings
({
0
,
0
});
std
::
string
pooling_t
=
"max"
;
desc
.
SetAttr
(
"pooling_type"
,
pooling_t
);
desc
.
SetAttr
(
"ksize"
,
ksize
);
desc
.
SetAttr
(
"strides"
,
strides
);
desc
.
SetAttr
(
"paddings"
,
paddings
);
LOG
(
INFO
)
<<
"set OP"
;
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
3
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
USE_OP
(
pool2d
);
paddle/fluid/inference/tensorrt/convert/ut_helper.h
浏览文件 @
85c49127
...
...
@@ -63,13 +63,16 @@ class TRTConvertValidation {
public:
TRTConvertValidation
()
=
delete
;
TRTConvertValidation
(
int
batch_size
,
TRTConvertValidation
(
int
max_
batch_size
,
const
std
::
unordered_set
<
std
::
string
>&
parameters
,
framework
::
Scope
&
scope
,
// NOLINT
int
workspace_size
=
1
<<
10
)
:
parameters_
(
parameters
),
scope_
(
scope
)
{
int
workspace_size
=
1
<<
10
,
bool
if_add_batch
=
true
)
:
parameters_
(
parameters
),
scope_
(
scope
),
if_add_batch_
(
if_add_batch
),
max_batch_size_
(
max_batch_size
)
{
// create engine.
engine_
.
reset
(
new
TensorRTEngine
(
batch_size
,
workspace_size
,
&
stream_
));
engine_
.
reset
(
new
TensorRTEngine
(
max_
batch_size
,
workspace_size
,
&
stream_
));
engine_
->
InitNetwork
();
PADDLE_ENFORCE_EQ
(
cudaStreamCreate
(
&
stream_
),
0
);
...
...
@@ -84,7 +87,7 @@ class TRTConvertValidation {
// Declare a parameter varaible in the scope.
void
DeclParamVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
DeclVar
(
name
,
dims
);
DeclVar
(
name
,
dims
,
true
);
}
void
DeclOutputVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
...
...
@@ -92,12 +95,18 @@ class TRTConvertValidation {
}
// Declare a variable in a fluid Scope.
void
DeclVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
)
{
void
DeclVar
(
const
std
::
string
&
name
,
const
nvinfer1
::
Dims
&
dims
,
bool
is_param
=
false
)
{
platform
::
CPUPlace
place
;
platform
::
CPUDeviceContext
ctx
(
place
);
// Init Fluid tensor.
std
::
vector
<
int
>
dim_vec
(
dims
.
d
,
dims
.
d
+
dims
.
nbDims
);
// There is no batchsize in ITensor's shape, but We should add it to
// tensor's shape of fluid. If the variable is not parameter and the
// if_add_batch_ flag is true, add the max batchsize to dim_vec.
if
(
is_param
!=
true
&&
if_add_batch_
==
true
)
dim_vec
.
insert
(
dim_vec
.
begin
(),
max_batch_size_
);
auto
*
x
=
scope_
.
Var
(
name
);
auto
*
x_tensor
=
x
->
GetMutable
<
framework
::
LoDTensor
>
();
x_tensor
->
Resize
(
framework
::
make_ddim
(
dim_vec
));
...
...
@@ -131,6 +140,7 @@ class TRTConvertValidation {
void
Execute
(
int
batch_size
)
{
// Execute Fluid Op
PADDLE_ENFORCE_LE
(
batch_size
,
max_batch_size_
);
platform
::
CPUPlace
place
;
platform
::
CPUDeviceContext
ctx
(
place
);
op_
->
Run
(
scope_
,
place
);
...
...
@@ -149,9 +159,15 @@ class TRTConvertValidation {
auto
*
var
=
scope_
.
FindVar
(
output
);
auto
tensor
=
var
->
GetMutable
<
framework
::
LoDTensor
>
();
framework
::
TensorToVector
(
*
tensor
,
ctx
,
&
fluid_out
);
size_t
fluid_out_size
=
fluid_out
.
size
();
if
(
if_add_batch_
==
true
)
{
fluid_out_size
=
batch_size
*
(
framework
::
product
(
tensor
->
dims
())
/
max_batch_size_
);
}
// Compare two output
ASSERT_FALSE
(
fluid_out
.
empty
());
for
(
size_t
i
=
0
;
i
<
fluid_out
.
size
()
;
i
++
)
{
for
(
size_t
i
=
0
;
i
<
fluid_out
_size
;
i
++
)
{
// Loose the threshold for CI in different machine model.
EXPECT_LT
(
std
::
abs
(
fluid_out
[
i
]
-
trt_out
[
i
]),
2e-5
);
}
...
...
@@ -167,6 +183,12 @@ class TRTConvertValidation {
std
::
unique_ptr
<
framework
::
OpDesc
>
op_desc_
;
const
std
::
unordered_set
<
std
::
string
>&
parameters_
;
framework
::
Scope
&
scope_
;
// The ITensor of trt does not cotain the batch size,
// bug, in most cases, we need to set batch size for
// fluid's tensor shape. This variable indicates
// whether to add batch size to tensor shape of fluid.
bool
if_add_batch_
;
int
max_batch_size_
;
};
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/test_engine.cc
浏览文件 @
85c49127
...
...
@@ -113,7 +113,7 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
ASSERT_EQ
(
y_cpu
[
1
],
14.5
);
}
TEST_F
(
TensorRTEngineTest
,
test_conv2d
_temp
)
{
TEST_F
(
TensorRTEngineTest
,
test_conv2d
)
{
// Weight in CPU memory.
float
raw_weight
[
9
]
=
{
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
};
float
raw_bias
[
1
]
=
{
0
};
...
...
@@ -146,6 +146,37 @@ TEST_F(TensorRTEngineTest, test_conv2d_temp) {
ASSERT_EQ
(
y_cpu
[
1
],
6.0
);
}
TEST_F
(
TensorRTEngineTest
,
test_pool2d
)
{
// Weight in CPU memory.
auto
*
x
=
engine_
->
DeclareInput
(
"x"
,
nvinfer1
::
DataType
::
kFLOAT
,
nvinfer1
::
Dims3
{
1
,
2
,
2
});
nvinfer1
::
PoolingType
pool_t
=
nvinfer1
::
PoolingType
::
kAVERAGE
;
auto
*
pool_layer
=
TRT_ENGINE_ADD_LAYER
(
engine_
,
Pooling
,
*
const_cast
<
nvinfer1
::
ITensor
*>
(
x
),
pool_t
,
nvinfer1
::
DimsHW
{
2
,
2
});
PADDLE_ENFORCE
(
pool_layer
!=
nullptr
);
pool_layer
->
setStride
(
nvinfer1
::
DimsHW
{
1
,
1
});
pool_layer
->
setPadding
(
nvinfer1
::
DimsHW
{
0
,
0
});
engine_
->
DeclareOutput
(
pool_layer
,
0
,
"y"
);
engine_
->
FreezeNetwork
();
ASSERT_EQ
(
engine_
->
engine
()
->
getNbBindings
(),
2
);
float
x_v
[
8
]
=
{
1.0
,
2.0
,
5.0
,
0.0
,
2.0
,
3.0
,
5.0
,
10.0
};
engine_
->
SetInputFromCPU
(
"x"
,
reinterpret_cast
<
void
*>
(
&
x_v
),
8
*
sizeof
(
float
));
engine_
->
Execute
(
2
);
LOG
(
INFO
)
<<
"to get output"
;
float
*
y_cpu
=
new
float
[
2
];
engine_
->
GetOutputInCPU
(
"y"
,
&
y_cpu
[
0
],
2
*
sizeof
(
float
));
ASSERT_EQ
(
y_cpu
[
0
],
2.0
);
ASSERT_EQ
(
y_cpu
[
1
],
5.0
);
}
}
// namespace tensorrt
}
// namespace inference
}
// namespace paddle
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