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体验新版 GitCode,发现更多精彩内容 >>
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01566fb6
编写于
7月 25, 2018
作者:
N
nhzlx
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
1. support mutil batch utest 2. support pool op
上级
21890ca0
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
73 addition
and
25 deletion
+73
-25
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
paddle/fluid/inference/tensorrt/convert/pool2d_op.cc
+2
-0
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
...le/fluid/inference/tensorrt/convert/test_activation_op.cc
+3
-2
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
+4
-4
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
+2
-1
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
+10
-11
paddle/fluid/inference/tensorrt/convert/ut_helper.h
paddle/fluid/inference/tensorrt/convert/ut_helper.h
+20
-6
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/pool2d_op.cc
浏览文件 @
01566fb6
...
...
@@ -43,6 +43,8 @@ class Pool2dOpConverter : public OpConverter {
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
pool_t
=
nvinfer1
::
PoolingType
::
kMAX
;
if
(
pool_type
==
"max"
)
{
pool_t
=
nvinfer1
::
PoolingType
::
kMAX
;
...
...
paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
浏览文件 @
01566fb6
...
...
@@ -23,7 +23,8 @@ namespace tensorrt {
TEST
(
ReluOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
int
runtime_batch
=
3
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
,
runtime_batch
);
validator
.
DeclInputVar
(
"relu-X"
,
nvinfer1
::
Dims2
(
10
,
6
));
validator
.
DeclOutputVar
(
"relu-Out"
,
nvinfer1
::
Dims2
(
10
,
6
));
...
...
@@ -37,7 +38,7 @@ TEST(ReluOpConverter, main) {
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
1
);
validator
.
Execute
(
runtime_batch
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_fc_op.cc
浏览文件 @
01566fb6
...
...
@@ -23,10 +23,10 @@ namespace tensorrt {
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
::
Dims4
(
1
,
10
,
1
,
1
));
int
runtime_batch
=
2
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
,
runtime_batch
);
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims3
(
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 +38,7 @@ TEST(fc_op, test) {
validator
.
SetOp
(
*
desc
.
Proto
());
validator
.
Execute
(
1
);
validator
.
Execute
(
runtime_batch
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/test_mul_op.cc
浏览文件 @
01566fb6
...
...
@@ -23,7 +23,8 @@ namespace tensorrt {
TEST
(
MulOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
int
runtime_batch
=
0
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
,
runtime_batch
);
validator
.
DeclInputVar
(
"mul-X"
,
nvinfer1
::
Dims2
(
10
,
6
));
validator
.
DeclInputVar
(
"mul-Y"
,
nvinfer1
::
Dims2
(
6
,
10
));
validator
.
DeclOutputVar
(
"mul-Out"
,
nvinfer1
::
Dims2
(
10
,
10
));
...
...
paddle/fluid/inference/tensorrt/convert/test_pool2d_op.cc
浏览文件 @
01566fb6
...
...
@@ -23,9 +23,14 @@ namespace tensorrt {
TEST
(
Pool2dOpConverter
,
main
)
{
framework
::
Scope
scope
;
std
::
unordered_set
<
std
::
string
>
parameters
;
TRTConvertValidation
validator
(
10
,
parameters
,
scope
,
1000
);
validator
.
DeclInputVar
(
"pool2d-X"
,
nvinfer1
::
Dims4
(
10
,
3
,
2
,
2
));
validator
.
DeclOutputVar
(
"pool2d-Out"
,
nvinfer1
::
Dims4
(
10
,
3
,
1
,
1
));
int
runtime_batch
=
3
;
TRTConvertValidation
validator
(
5
,
parameters
,
scope
,
1
<<
15
,
runtime_batch
);
// We have already set the runtime batchsize, so the
// Dims should not contain the batch size.
// 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
;
...
...
@@ -34,7 +39,7 @@ TEST(Pool2dOpConverter, main) {
desc
.
SetOutput
(
"Out"
,
{
"pool2d-Out"
});
std
::
vector
<
int
>
ksize
({
2
,
2
});
std
::
vector
<
int
>
strides
({
1
,
1
});
std
::
vector
<
int
>
strides
({
2
,
2
});
std
::
vector
<
int
>
paddings
({
0
,
0
});
std
::
string
pooling_t
=
"max"
;
...
...
@@ -42,18 +47,12 @@ TEST(Pool2dOpConverter, main) {
desc
.
SetAttr
(
"ksize"
,
ksize
);
desc
.
SetAttr
(
"strides"
,
strides
);
desc
.
SetAttr
(
"paddings"
,
paddings
);
// std::string temp = "";
// (*desc.Proto()).SerializeToString(&temp);
// std::cout << temp << std::endl;
// std::ofstream f("__temp__", std::ios::out);
// f << temp;
LOG
(
INFO
)
<<
"set OP"
;
validator
.
SetOp
(
*
desc
.
Proto
());
LOG
(
INFO
)
<<
"execute"
;
validator
.
Execute
(
10
);
validator
.
Execute
(
runtime_batch
);
}
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/convert/ut_helper.h
浏览文件 @
01566fb6
...
...
@@ -63,13 +63,15 @@ 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
,
int
runtime_batch_size
=
1
)
:
parameters_
(
parameters
),
scope_
(
scope
),
runtime_batch_size_
(
runtime_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 +86,7 @@ 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 +94,20 @@ 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 batch size
// greater than 0,
// add the batchsize to dim_vec.
if
(
is_param
!=
true
&&
runtime_batch_size_
>
0
)
dim_vec
.
insert
(
dim_vec
.
begin
(),
runtime_batch_size_
);
auto
*
x
=
scope_
.
Var
(
name
);
auto
*
x_tensor
=
x
->
GetMutable
<
framework
::
LoDTensor
>
();
x_tensor
->
Resize
(
framework
::
make_ddim
(
dim_vec
));
...
...
@@ -167,6 +177,10 @@ class TRTConvertValidation {
std
::
unique_ptr
<
framework
::
OpDesc
>
op_desc_
;
const
std
::
unordered_set
<
std
::
string
>&
parameters_
;
framework
::
Scope
&
scope_
;
// It represents the runtime batchsize when we test.
// If the value greater than 0, we add this to
// the first dimension of tensor's shape of fluid.
int
runtime_batch_size_
;
};
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/test_engine.cc
浏览文件 @
01566fb6
...
...
@@ -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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