Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
Paddle
提交
c15e53d6
P
Paddle
项目概览
PaddlePaddle
/
Paddle
大约 1 年 前同步成功
通知
2298
Star
20931
Fork
5422
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
1423
列表
看板
标记
里程碑
合并请求
543
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
Paddle
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
1,423
Issue
1,423
列表
看板
标记
里程碑
合并请求
543
合并请求
543
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
体验新版 GitCode,发现更多精彩内容 >>
未验证
提交
c15e53d6
编写于
6月 07, 2023
作者:
周
周周周
提交者:
GitHub
6月 07, 2023
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
commit (#54339)
上级
cb2476cf
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
343 addition
and
0 deletion
+343
-0
paddle/fluid/inference/tensorrt/dynamic_shape_infermeta.cc
paddle/fluid/inference/tensorrt/dynamic_shape_infermeta.cc
+340
-0
paddle/fluid/inference/tensorrt/dynamic_shape_infermeta_registry.h
...uid/inference/tensorrt/dynamic_shape_infermeta_registry.h
+3
-0
未找到文件。
paddle/fluid/inference/tensorrt/dynamic_shape_infermeta.cc
浏览文件 @
c15e53d6
...
@@ -21,6 +21,122 @@ namespace paddle {
...
@@ -21,6 +21,122 @@ namespace paddle {
namespace
inference
{
namespace
inference
{
namespace
tensorrt
{
namespace
tensorrt
{
class
ExprWrapper
{
public:
ExprWrapper
()
{}
ExprWrapper
(
const
nvinfer1
::
IDimensionExpr
*
expr
,
nvinfer1
::
IExprBuilder
*
expr_builder
)
{
this
->
expr
=
expr
;
this
->
expr_builder
=
expr_builder
;
}
ExprWrapper
(
int
value
,
nvinfer1
::
IExprBuilder
*
expr_builder
)
{
this
->
expr
=
expr_builder
->
constant
(
value
);
this
->
expr_builder
=
expr_builder
;
}
const
nvinfer1
::
IDimensionExpr
*
extract_expr
()
const
{
return
expr
;
}
public:
friend
ExprWrapper
BinaryOp
(
const
ExprWrapper
&
a
,
const
ExprWrapper
&
b
,
nvinfer1
::
DimensionOperation
op
)
{
ExprWrapper
result
;
if
(
a
.
expr_builder
)
{
result
.
expr_builder
=
a
.
expr_builder
;
}
if
(
b
.
expr_builder
)
{
result
.
expr_builder
=
b
.
expr_builder
;
}
assert
(
result
.
expr
);
result
.
expr
=
result
.
expr_builder
->
operation
(
op
,
*
a
.
expr
,
*
b
.
expr
);
return
result
;
}
friend
ExprWrapper
BinaryOp
(
const
ExprWrapper
&
a
,
int
b_value
,
nvinfer1
::
DimensionOperation
op
)
{
assert
(
a
.
expr_builder
);
ExprWrapper
b
;
b
.
expr_builder
=
a
.
expr_builder
;
b
.
expr
=
b
.
expr_builder
->
constant
(
b_value
);
return
BinaryOp
(
a
,
b
,
op
);
}
friend
ExprWrapper
operator
+
(
const
ExprWrapper
&
a
,
const
ExprWrapper
&
b
)
{
return
BinaryOp
(
a
,
b
,
nvinfer1
::
DimensionOperation
::
kSUM
);
}
friend
ExprWrapper
operator
+
(
const
ExprWrapper
&
a
,
int
b_value
)
{
return
BinaryOp
(
a
,
b_value
,
nvinfer1
::
DimensionOperation
::
kSUM
);
}
friend
ExprWrapper
operator
+
(
int
a_value
,
const
ExprWrapper
&
b
)
{
return
a_value
+
b
;
}
friend
ExprWrapper
operator
-
(
const
ExprWrapper
&
a
,
const
ExprWrapper
&
b
)
{
return
BinaryOp
(
a
,
b
,
nvinfer1
::
DimensionOperation
::
kSUB
);
}
friend
ExprWrapper
operator
-
(
const
ExprWrapper
&
a
,
int
b_value
)
{
return
BinaryOp
(
a
,
b_value
,
nvinfer1
::
DimensionOperation
::
kSUB
);
}
friend
ExprWrapper
operator
*
(
const
ExprWrapper
&
a
,
const
ExprWrapper
&
b
)
{
return
BinaryOp
(
a
,
b
,
nvinfer1
::
DimensionOperation
::
kPROD
);
}
friend
ExprWrapper
operator
*
(
const
ExprWrapper
&
a
,
int
b_value
)
{
return
BinaryOp
(
a
,
b_value
,
nvinfer1
::
DimensionOperation
::
kPROD
);
}
friend
ExprWrapper
operator
*
(
int
a_value
,
const
ExprWrapper
&
b
)
{
return
b
*
a_value
;
}
friend
ExprWrapper
operator
/
(
const
ExprWrapper
&
a
,
const
ExprWrapper
&
b
)
{
return
BinaryOp
(
a
,
b
,
nvinfer1
::
DimensionOperation
::
kFLOOR_DIV
);
}
friend
ExprWrapper
operator
/
(
const
ExprWrapper
&
a
,
int
b_value
)
{
return
BinaryOp
(
a
,
b_value
,
nvinfer1
::
DimensionOperation
::
kFLOOR_DIV
);
}
friend
ExprWrapper
max
(
const
ExprWrapper
&
a
,
const
ExprWrapper
&
b
)
{
return
BinaryOp
(
a
,
b
,
nvinfer1
::
DimensionOperation
::
kMAX
);
}
friend
ExprWrapper
max
(
const
ExprWrapper
&
a
,
int
b_value
)
{
return
BinaryOp
(
a
,
b_value
,
nvinfer1
::
DimensionOperation
::
kMAX
);
}
public:
const
nvinfer1
::
IDimensionExpr
*
expr
;
nvinfer1
::
IExprBuilder
*
expr_builder
;
};
static
std
::
vector
<
ExprWrapper
>
DimsExprs2VecExprWrapper
(
const
nvinfer1
::
DimsExprs
&
x_dims
,
nvinfer1
::
IExprBuilder
&
expr_builder
// NOLINT
)
{
std
::
vector
<
ExprWrapper
>
x_dims_wrap
;
for
(
int
i
=
0
;
i
<
x_dims
.
nbDims
;
i
++
)
{
x_dims_wrap
.
push_back
(
ExprWrapper
(
x_dims
.
d
[
i
],
&
expr_builder
));
}
return
x_dims_wrap
;
}
static
nvinfer1
::
DimsExprs
VecExprWrapper2DimsExprs
(
const
std
::
vector
<
ExprWrapper
>&
output_dims_wrapper
)
{
nvinfer1
::
DimsExprs
output_dims
;
output_dims
.
nbDims
=
output_dims_wrapper
.
size
();
for
(
int
i
=
0
;
i
<
output_dims
.
nbDims
;
i
++
)
{
output_dims
.
d
[
i
]
=
output_dims_wrapper
[
i
].
extract_expr
();
}
return
output_dims
;
}
nvinfer1
::
DimsExprs
GatherNdInferMeta
(
nvinfer1
::
DimsExprs
GatherNdInferMeta
(
int
output_index
,
int
output_index
,
const
nvinfer1
::
DimsExprs
*
inputs
,
const
nvinfer1
::
DimsExprs
*
inputs
,
...
@@ -417,6 +533,148 @@ nvinfer1::DimsExprs GridSamplerInferMeta(
...
@@ -417,6 +533,148 @@ nvinfer1::DimsExprs GridSamplerInferMeta(
return
output
;
return
output
;
}
}
inline
const
void
UpdatePaddingAndDilation
(
std
::
vector
<
ExprWrapper
>*
paddings_wrap
,
std
::
vector
<
int
>*
dilation
,
const
std
::
string
padding_algorithm
,
const
std
::
vector
<
ExprWrapper
>&
hw_dims
,
const
std
::
vector
<
int
>&
strides
,
const
std
::
vector
<
ExprWrapper
>&
k_dims
,
nvinfer1
::
IExprBuilder
&
expr_builder
// NOLINT
)
{
if
(
paddings_wrap
->
size
()
==
hw_dims
.
size
())
{
for
(
size_t
i
=
0
;
i
<
hw_dims
.
size
();
++
i
)
{
auto
copy_pad
=
*
(
paddings_wrap
->
begin
()
+
2
*
i
);
paddings_wrap
->
insert
(
paddings_wrap
->
begin
()
+
2
*
i
+
1
,
copy_pad
);
}
}
else
{
CHECK_EQ
(
hw_dims
.
size
()
==
paddings_wrap
->
size
(),
true
);
}
// when padding_algorithm is "VALID" or "SAME"
if
(
padding_algorithm
==
"SAME"
)
{
for
(
size_t
i
=
0
;
i
<
hw_dims
.
size
();
++
i
)
{
auto
out_size
=
(
hw_dims
[
i
]
+
strides
[
i
]
-
1
)
/
strides
[
i
];
auto
pad_sum
=
max
((
out_size
-
1
)
*
strides
[
i
]
+
k_dims
[
i
]
-
hw_dims
[
i
],
0
);
auto
pad_0
=
pad_sum
/
2
;
auto
pad_1
=
pad_sum
-
pad_0
;
*
(
paddings_wrap
->
begin
()
+
i
*
2
)
=
pad_0
;
*
(
paddings_wrap
->
begin
()
+
i
*
2
+
1
)
=
pad_1
;
// dilation
*
(
dilation
->
begin
()
+
i
)
=
1
;
}
}
else
if
(
padding_algorithm
==
"VALID"
)
{
for
(
auto
it
=
paddings_wrap
->
begin
();
it
!=
paddings_wrap
->
end
();
it
++
)
{
*
it
=
ExprWrapper
(
0
,
&
expr_builder
);
}
}
}
// Here are all examples of using h(height), ok for weight too.
inline
ExprWrapper
ConvOutputSize
(
ExprWrapper
ih
,
ExprWrapper
kh
,
int
dilation_h
,
ExprWrapper
pad_h0
,
ExprWrapper
pad_h1
,
int
stride_h
)
{
ExprWrapper
oh
=
(
ih
+
pad_h0
+
pad_h1
-
dilation_h
*
(
kh
-
1
)
-
1
)
/
stride_h
+
1
;
return
oh
;
}
nvinfer1
::
DimsExprs
Conv2dFusionInferMeta
(
int
output_index
,
const
nvinfer1
::
DimsExprs
*
inputs
,
int
nb_inputs
,
nvinfer1
::
IExprBuilder
&
expr_builder
,
// NOLINT
const
framework
::
OpDesc
&
op_desc
)
{
// we may update dilations.
std
::
vector
<
int
>
dilations
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"dilations"
));
const
std
::
vector
<
int
>
strides
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"strides"
));
std
::
vector
<
int
>
paddings
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"paddings"
));
std
::
string
padding_algorithm
=
"EXPLICIT"
;
if
(
op_desc
.
HasAttr
(
"padding_algorithm"
))
padding_algorithm
=
PADDLE_GET_CONST
(
std
::
string
,
op_desc
.
GetAttr
(
"padding_algorithm"
));
if
(
padding_algorithm
==
"VALID"
)
{
for
(
size_t
i
=
0
;
i
<
paddings
.
size
();
i
++
)
{
paddings
[
i
]
=
0
;
}
}
// TODO(zhangjun): nhwc support
bool
channel_last
=
false
;
// conv_fusion: input, filter, bias
const
nvinfer1
::
DimsExprs
input_dims
=
inputs
[
0
];
const
nvinfer1
::
DimsExprs
filter_dims
=
inputs
[
1
];
auto
input_dims_wrap
=
DimsExprs2VecExprWrapper
(
input_dims
,
expr_builder
);
auto
filter_dims_wrap
=
DimsExprs2VecExprWrapper
(
filter_dims
,
expr_builder
);
std
::
vector
<
ExprWrapper
>
hw_dims_wrap
;
// d, h, w
if
(
channel_last
)
{
for
(
int
i
=
1
;
i
<
input_dims
.
nbDims
-
1
;
++
i
)
{
hw_dims_wrap
.
emplace_back
(
input_dims_wrap
[
i
]);
}
}
else
{
for
(
int
i
=
2
;
i
<
input_dims
.
nbDims
;
++
i
)
{
hw_dims_wrap
.
emplace_back
(
input_dims_wrap
[
i
]);
}
}
std
::
vector
<
ExprWrapper
>
filter_hw_dims_wrap
;
// filter_h, filter_w
if
(
channel_last
)
{
for
(
int
i
=
1
;
i
<
filter_dims
.
nbDims
-
1
;
++
i
)
{
filter_hw_dims_wrap
.
emplace_back
(
filter_dims_wrap
[
i
]);
}
}
else
{
for
(
int
i
=
2
;
i
<
filter_dims
.
nbDims
;
++
i
)
{
filter_hw_dims_wrap
.
emplace_back
(
filter_dims_wrap
[
i
]);
}
}
std
::
vector
<
ExprWrapper
>
paddings_wrap
;
for
(
size_t
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
paddings_wrap
.
emplace_back
(
ExprWrapper
(
paddings
[
i
],
&
expr_builder
));
}
UpdatePaddingAndDilation
(
&
paddings_wrap
,
&
dilations
,
padding_algorithm
,
hw_dims_wrap
,
strides
,
filter_hw_dims_wrap
,
expr_builder
);
std
::
vector
<
ExprWrapper
>
output_dims_wrap
(
input_dims
.
nbDims
);
int
out_idx
=
0
;
output_dims_wrap
[
out_idx
++
]
=
input_dims_wrap
[
0
];
if
(
!
channel_last
)
{
output_dims_wrap
[
out_idx
++
]
=
filter_dims_wrap
[
0
];
}
for
(
size_t
i
=
0
;
i
<
hw_dims_wrap
.
size
();
++
i
)
{
output_dims_wrap
[
out_idx
++
]
=
ConvOutputSize
(
hw_dims_wrap
[
i
],
filter_hw_dims_wrap
[
i
],
dilations
[
i
],
paddings_wrap
[
2
*
i
],
paddings_wrap
[
2
*
i
+
1
],
strides
[
i
]);
}
if
(
channel_last
)
{
output_dims_wrap
[
out_idx
++
]
=
filter_dims_wrap
[
0
];
}
return
VecExprWrapper2DimsExprs
(
output_dims_wrap
);
}
nvinfer1
::
DimsExprs
LookupTableV2InferMeta
(
nvinfer1
::
DimsExprs
LookupTableV2InferMeta
(
int
output_index
,
int
output_index
,
const
nvinfer1
::
DimsExprs
*
inputs
,
const
nvinfer1
::
DimsExprs
*
inputs
,
...
@@ -435,6 +693,85 @@ nvinfer1::DimsExprs LookupTableV2InferMeta(
...
@@ -435,6 +693,85 @@ nvinfer1::DimsExprs LookupTableV2InferMeta(
return
output
;
return
output
;
}
}
nvinfer1
::
DimsExprs
Conv2dTransposeInferMeta
(
int
output_index
,
const
nvinfer1
::
DimsExprs
*
inputs
,
int
nb_inputs
,
nvinfer1
::
IExprBuilder
&
expr_builder
,
// NOLINT
const
framework
::
OpDesc
&
op_desc
)
{
auto
x_dims
=
inputs
[
0
];
auto
filter_dims
=
inputs
[
1
];
std
::
vector
<
ExprWrapper
>
x_dims_wrap
=
DimsExprs2VecExprWrapper
(
x_dims
,
expr_builder
);
std
::
vector
<
ExprWrapper
>
filter_dims_wrap
=
DimsExprs2VecExprWrapper
(
filter_dims
,
expr_builder
);
const
std
::
vector
<
int
>
dilations
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"dilations"
));
const
std
::
vector
<
int
>
strides
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"strides"
));
std
::
vector
<
int
>
paddings
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"paddings"
));
std
::
vector
<
int
>
output_size
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"output_size"
));
std
::
vector
<
int
>
output_padding
=
PADDLE_GET_CONST
(
std
::
vector
<
int
>
,
op_desc
.
GetAttr
(
"output_padding"
));
auto
data_format
=
PADDLE_GET_CONST
(
std
::
string
,
op_desc
.
GetAttr
(
"data_format"
));
int
groups
=
PADDLE_GET_CONST
(
int
,
op_desc
.
GetAttr
(
"groups"
));
std
::
string
padding_algorithm
=
"EXPLICIT"
;
if
(
op_desc
.
HasAttr
(
"padding_algorithm"
))
{
padding_algorithm
=
PADDLE_GET_CONST
(
std
::
string
,
op_desc
.
GetAttr
(
"padding_algorithm"
));
}
CHECK_EQ
(
padding_algorithm
==
"EXPLICIT"
,
true
);
CHECK_EQ
(
data_format
==
"NCHW"
,
true
);
CHECK_EQ
(
output_size
.
size
()
==
0
,
true
);
CHECK_EQ
(
paddings
.
size
()
==
2
,
true
);
CHECK_EQ
(
x_dims
.
nbDims
==
4
,
true
);
CHECK_EQ
(
x_dims
.
nbDims
==
filter_dims
.
nbDims
,
true
);
CHECK_EQ
(
output_padding
.
size
()
==
0
,
true
);
int
stride_size
=
strides
.
size
();
for
(
int
i
=
0
;
i
<
stride_size
;
++
i
)
{
CHECK_EQ
(
strides
[
i
]
>
0
,
true
);
}
int
in_sub_stride_size
=
x_dims
.
nbDims
-
stride_size
;
CHECK_EQ
(
in_sub_stride_size
==
2
,
true
);
if
(
output_size
.
size
())
{
CHECK_EQ
(
output_size
.
size
()
==
strides
.
size
(),
true
);
}
if
(
output_padding
.
size
())
{
CHECK_EQ
(
strides
.
size
()
==
output_padding
.
size
(),
true
);
}
std
::
vector
<
ExprWrapper
>
output_dims_wrap
(
x_dims
.
nbDims
);
output_dims_wrap
[
0
]
=
x_dims_wrap
[
0
];
output_dims_wrap
[
1
]
=
filter_dims_wrap
[
1
]
*
groups
;
auto
ih
=
x_dims_wrap
[
2
];
auto
iw
=
x_dims_wrap
[
3
];
auto
kh
=
filter_dims_wrap
[
2
];
auto
kw
=
filter_dims_wrap
[
3
];
int
pad_h0
=
paddings
[
0
];
int
pad_h1
=
paddings
[
0
];
int
pad_w0
=
paddings
[
1
];
int
pad_w1
=
paddings
[
1
];
output_dims_wrap
[
2
]
=
(
ih
-
1
)
*
strides
[
0
]
-
pad_h0
-
pad_h1
+
(
kh
-
1
)
*
dilations
[
0
]
+
1
;
output_dims_wrap
[
3
]
=
(
iw
-
1
)
*
strides
[
1
]
-
pad_w0
-
pad_w1
+
(
kw
-
1
)
*
dilations
[
1
]
+
1
;
return
VecExprWrapper2DimsExprs
(
output_dims_wrap
);
}
PD_REGISTER_DYNAMIC_INFER_META_FN
(
gather_nd
,
GatherNdInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
gather_nd
,
GatherNdInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
yolo_box
,
YoloBoxInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
yolo_box
,
YoloBoxInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
instance_norm
,
InstanceNormInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
instance_norm
,
InstanceNormInferMeta
);
...
@@ -444,6 +781,9 @@ PD_REGISTER_DYNAMIC_INFER_META_FN(inverse, UnchangedInferMeta);
...
@@ -444,6 +781,9 @@ PD_REGISTER_DYNAMIC_INFER_META_FN(inverse, UnchangedInferMeta);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
moe
,
MoeInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
moe
,
MoeInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
pad3d
,
Pad3dInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
pad3d
,
Pad3dInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
grid_sampler
,
GridSamplerInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
grid_sampler
,
GridSamplerInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
conv2d_fusion
,
Conv2dFusionInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
conv2d
,
Conv2dFusionInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
conv2d_transpose
,
Conv2dTransposeInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
p_norm
,
PNormInferMeta
);
PD_REGISTER_DYNAMIC_INFER_META_FN
(
p_norm
,
PNormInferMeta
);
}
// namespace tensorrt
}
// namespace tensorrt
...
...
paddle/fluid/inference/tensorrt/dynamic_shape_infermeta_registry.h
浏览文件 @
c15e53d6
...
@@ -28,6 +28,9 @@ USE_TRT_DYNAMIC_INFER_META_FN(scatter_nd_add);
...
@@ -28,6 +28,9 @@ USE_TRT_DYNAMIC_INFER_META_FN(scatter_nd_add);
USE_TRT_DYNAMIC_INFER_META_FN
(
pad3d
);
USE_TRT_DYNAMIC_INFER_META_FN
(
pad3d
);
USE_TRT_DYNAMIC_INFER_META_FN
(
inverse
);
USE_TRT_DYNAMIC_INFER_META_FN
(
inverse
);
USE_TRT_DYNAMIC_INFER_META_FN
(
grid_sampler
);
USE_TRT_DYNAMIC_INFER_META_FN
(
grid_sampler
);
USE_TRT_DYNAMIC_INFER_META_FN
(
conv2d_fusion
);
USE_TRT_DYNAMIC_INFER_META_FN
(
conv2d
);
USE_TRT_DYNAMIC_INFER_META_FN
(
conv2d_transpose
);
USE_TRT_DYNAMIC_INFER_META_FN
(
p_norm
);
USE_TRT_DYNAMIC_INFER_META_FN
(
p_norm
);
}
// namespace tensorrt
}
// namespace tensorrt
}
// namespace inference
}
// namespace inference
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录