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a981af15
编写于
3月 10, 2020
作者:
Z
zhupengyang
提交者:
GitHub
3月 10, 2020
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
[NPU] support more elementwise cases (#3133)
* [NPU] revert shape check for input&output * [NPU] reshape elt input&output
上级
66f0b25b
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
93 addition
and
92 deletion
+93
-92
lite/kernels/npu/bridges/elementwise_ops.cc
lite/kernels/npu/bridges/elementwise_ops.cc
+87
-52
lite/kernels/npu/bridges/utility.cc
lite/kernels/npu/bridges/utility.cc
+0
-9
lite/kernels/npu/bridges/utility.h
lite/kernels/npu/bridges/utility.h
+0
-3
lite/kernels/npu/subgraph_compute.cc
lite/kernels/npu/subgraph_compute.cc
+6
-28
未找到文件。
lite/kernels/npu/bridges/elementwise_ops.cc
浏览文件 @
a981af15
...
...
@@ -21,42 +21,78 @@ namespace lite {
namespace
subgraph
{
namespace
npu
{
void
CvtYShape
(
std
::
vector
<
int64_t
>*
x_shape
,
std
::
vector
<
int64_t
>*
y_shape
,
int
axis
)
{
CHECK_GE
(
x_shape
->
size
(),
y_shape
->
size
());
void
CvtXYShape
(
std
::
vector
<
int64_t
>*
x_shape
,
std
::
vector
<
int64_t
>*
y_shape
,
int
axis
)
{
int
x_shape_size
=
x_shape
->
size
();
int
y_shape_size
=
y_shape
->
size
();
CHECK_GE
(
x_shape_size
,
y_shape_size
);
if
(
axis
<
0
)
{
axis
=
x_shape
->
size
()
-
y_shape
->
size
();
// only support:
// 1. same shape
// 2. (n,c,h,w) * (1,c,1,1)
// 3. (n,c,h,w) * (n,c,1,1)
// 4. (n,c,h,w) * (1,c,h,1)
// 5. (n,c,h,w) * (1,c,h,w)
// 6. (n,c,h,w) * (n,c,1,w)
if
(
*
x_shape
==
*
y_shape
)
{
*
x_shape
=
CvtShape
(
*
x_shape
);
*
y_shape
=
CvtShape
(
*
y_shape
);
return
;
}
// only support:
// (n,c,h,w) * (n,c,h,w)
// (n,c,h,w) * (1,c,1,1)
// (n,c,h,w) * (1,c,h,1)
// (n,c,h,w) * (1,c,h,w)
int
y_shape_size
=
y_shape
->
size
();
if
(
y_shape_size
==
1
)
{
y_shape
->
insert
(
y_shape
->
begin
(),
1
);
y_shape
->
insert
(
y_shape
->
end
(),
2
,
1
);
}
else
if
(
y_shape_size
==
2
)
{
y_shape
->
insert
(
y_shape
->
begin
(),
1
);
y_shape
->
insert
(
y_shape
->
end
(),
1
);
}
else
if
(
y_shape_size
==
3
)
{
y_shape
->
insert
(
y_shape
->
begin
(),
1
);
for
(
int
i
=
0
;
i
<
4
-
x_shape_size
;
i
++
)
{
x_shape
->
push_back
(
1
);
}
int64_t
n
=
x_shape
->
at
(
0
);
int64_t
c
=
x_shape
->
at
(
1
);
int64_t
h
=
x_shape
->
at
(
2
);
int64_t
w
=
x_shape
->
at
(
3
);
if
(
axis
==
0
)
{
*
x_shape
=
std
::
vector
<
int64_t
>
{
1
,
n
,
c
*
h
*
w
,
1
};
}
else
if
(
axis
==
2
)
{
*
x_shape
=
std
::
vector
<
int64_t
>
{
n
*
c
,
h
,
w
,
1
};
}
else
if
(
axis
==
3
)
{
*
x_shape
=
std
::
vector
<
int64_t
>
{
n
*
c
*
h
,
w
,
1
,
1
};
}
*
y_shape
=
std
::
vector
<
int64_t
>
{
1
,
y_shape
->
at
(
0
),
1
,
1
};
return
;
}
if
(
y_shape_size
<
4
)
{
int
n
=
1
;
for
(
int
i
=
0
;
i
<
axis
;
i
++
)
{
n
*=
x_shape
->
at
(
i
);
if
(
y_shape_size
==
2
)
{
for
(
int
i
=
0
;
i
<
4
-
x_shape_size
;
i
++
)
{
x_shape
->
push_back
(
1
);
}
int64_t
n
=
x_shape
->
at
(
0
);
int64_t
c
=
x_shape
->
at
(
1
);
int64_t
h
=
x_shape
->
at
(
2
);
int64_t
w
=
x_shape
->
at
(
3
);
if
(
axis
==
0
)
{
y_shape
->
insert
(
y_shape
->
end
(),
2
,
1
);
}
else
if
(
axis
==
1
)
{
y_shape
->
insert
(
y_shape
->
begin
(),
1
);
y_shape
->
insert
(
y_shape
->
end
(),
1
);
}
else
if
(
axis
==
2
)
{
*
x_shape
=
std
::
vector
<
int64_t
>
{
n
*
c
,
h
,
w
,
1
};
y_shape
->
insert
(
y_shape
->
begin
(),
1
);
y_shape
->
insert
(
y_shape
->
end
(),
1
);
}
x_shape
->
erase
(
x_shape
->
begin
(),
x_shape
->
begin
()
+
axis
);
x_shape
->
insert
(
x_shape
->
begin
(),
n
);
x_shape
->
insert
(
x_shape
->
end
(),
4
-
x_shape
->
size
(),
1
);
return
;
}
CHECK_EQ
(
x_shape
->
size
(),
4UL
);
CHECK_EQ
(
y_shape
->
size
(),
4UL
);
if
(
y_shape_size
==
3
)
{
y_shape
->
insert
(
y_shape
->
begin
(),
1
);
int64_t
n
=
x_shape
->
at
(
0
);
int64_t
c
=
x_shape
->
at
(
1
);
int64_t
h
=
x_shape
->
at
(
2
);
int64_t
w
=
x_shape
->
at
(
3
);
if
(
axis
==
0
)
{
*
x_shape
=
std
::
vector
<
int64_t
>
{
1
,
n
*
c
*
h
,
w
,
1
};
*
y_shape
=
std
::
vector
<
int64_t
>
{
1
,
n
*
c
*
h
,
1
,
1
};
}
return
;
}
}
int
ElementwiseConverter
(
void
*
ctx
,
OpLite
*
op
,
KernelBase
*
kernel
)
{
...
...
@@ -70,36 +106,37 @@ int ElementwiseConverter(void* ctx, OpLite* op, KernelBase* kernel) {
// Get input and output vars and op attributes
auto
x_name
=
op_info
->
Input
(
"X"
).
front
();
auto
x
=
scope
->
Find
Mutable
Tensor
(
x_name
);
auto
x
=
scope
->
FindTensor
(
x_name
);
auto
x_dims
=
x
->
dims
();
auto
y_name
=
op_info
->
Input
(
"Y"
).
front
();
auto
y
=
scope
->
Find
Mutable
Tensor
(
y_name
);
auto
y
=
scope
->
FindTensor
(
y_name
);
auto
y_dims
=
y
->
dims
();
auto
out_name
=
op_info
->
Output
(
"Out"
).
front
();
auto
out
=
scope
->
Find
Mutable
Tensor
(
out_name
);
auto
out
=
scope
->
FindTensor
(
out_name
);
auto
out_dims
=
out
->
dims
();
auto
axis
=
op_info
->
GetAttr
<
int
>
(
"axis"
);
if
(
axis
<
0
)
{
axis
=
x_dims
.
size
()
-
y_dims
.
size
();
}
auto
x_new_shape
=
x_dims
.
Vectorize
();
auto
y_new_shape
=
y_dims
.
Vectorize
();
CvtYShape
(
&
x_new_shape
,
&
y_new_shape
,
axis
);
Cvt
X
YShape
(
&
x_new_shape
,
&
y_new_shape
,
axis
);
// X node
std
::
shared_ptr
<
Node
>
x_node
=
nullptr
;
if
(
graph
->
Has
(
x_name
))
{
x_node
=
graph
->
Get
(
x_name
);
if
(
x_dims
.
Vectorize
()
!=
x_new_shape
)
{
auto
reshaped_x_node
=
graph
->
Add
<
ge
::
op
::
Reshape
>
(
x_name
+
"/reshape"
);
auto
reshaped_x_op
=
reshaped_x_node
->
data
<
ge
::
op
::
Reshape
>
();
reshaped_x_op
->
set_input_tensor
(
*
x_node
->
data
());
reshaped_x_op
->
set_attr_shape
(
ge
::
AttrValue
::
LIST_INT
(
x_new_shape
.
begin
(),
x_new_shape
.
end
()));
reshaped_x_op
->
set_attr_axis
(
0
);
x_node
=
reshaped_x_node
;
}
auto
reshaped_x_node
=
graph
->
Add
<
ge
::
op
::
Reshape
>
(
x_name
+
"/reshape"
);
auto
reshaped_x_op
=
reshaped_x_node
->
data
<
ge
::
op
::
Reshape
>
();
reshaped_x_op
->
set_input_tensor
(
*
x_node
->
data
());
reshaped_x_op
->
set_attr_shape
(
ge
::
AttrValue
::
LIST_INT
(
x_new_shape
.
begin
(),
x_new_shape
.
end
()));
reshaped_x_op
->
set_attr_axis
(
0
);
x_node
=
reshaped_x_node
;
}
else
{
x_node
=
graph
->
Add
(
x_name
,
*
x
,
x_new_shape
);
}
...
...
@@ -108,15 +145,13 @@ int ElementwiseConverter(void* ctx, OpLite* op, KernelBase* kernel) {
std
::
shared_ptr
<
Node
>
y_node
=
nullptr
;
if
(
graph
->
Has
(
y_name
))
{
y_node
=
graph
->
Get
(
y_name
);
if
(
y_dims
.
Vectorize
()
!=
y_new_shape
)
{
auto
reshaped_y_node
=
graph
->
Add
<
ge
::
op
::
Reshape
>
(
y_name
+
"/reshape"
);
auto
reshaped_y_op
=
reshaped_y_node
->
data
<
ge
::
op
::
Reshape
>
();
reshaped_y_op
->
set_input_tensor
(
*
y_node
->
data
());
reshaped_y_op
->
set_attr_shape
(
ge
::
AttrValue
::
LIST_INT
(
y_new_shape
.
begin
(),
y_new_shape
.
end
()));
reshaped_y_op
->
set_attr_axis
(
0
);
y_node
=
reshaped_y_node
;
}
auto
reshaped_y_node
=
graph
->
Add
<
ge
::
op
::
Reshape
>
(
y_name
+
"/reshape"
);
auto
reshaped_y_op
=
reshaped_y_node
->
data
<
ge
::
op
::
Reshape
>
();
reshaped_y_op
->
set_input_tensor
(
*
y_node
->
data
());
reshaped_y_op
->
set_attr_shape
(
ge
::
AttrValue
::
LIST_INT
(
y_new_shape
.
begin
(),
y_new_shape
.
end
()));
reshaped_y_op
->
set_attr_axis
(
0
);
y_node
=
reshaped_y_node
;
}
else
{
y_node
=
graph
->
Add
(
y_name
,
*
y
,
y_new_shape
);
}
...
...
@@ -152,11 +187,11 @@ int ElementwiseConverter(void* ctx, OpLite* op, KernelBase* kernel) {
return
FAILED
;
}
if
(
out_dims
.
Vectorize
()
!=
x_new_shape
)
{
auto
out_shape
=
out_dims
.
Vectorize
();
if
(
out_shape
!=
x_new_shape
)
{
auto
reshaped_elt_node
=
graph
->
Add
<
ge
::
op
::
Reshape
>
(
out_name
);
auto
reshaped_elt_op
=
reshaped_elt_node
->
data
<
ge
::
op
::
Reshape
>
();
reshaped_elt_op
->
set_input_tensor
(
*
elt_node
->
data
());
auto
out_shape
=
out_dims
.
Vectorize
();
reshaped_elt_op
->
set_attr_shape
(
ge
::
AttrValue
::
LIST_INT
(
out_shape
.
begin
(),
out_shape
.
end
()));
reshaped_elt_op
->
set_attr_axis
(
0
);
...
...
lite/kernels/npu/bridges/utility.cc
浏览文件 @
a981af15
...
...
@@ -151,15 +151,6 @@ int CvtActMode(std::string act_type) {
return
act_mode
;
}
bool
CheckShape
(
DDim
origin_dims
,
hiai
::
TensorDimension
device_dims
)
{
auto
origin_shape
=
CvtShape
(
origin_dims
);
CHECK_EQ
(
origin_shape
.
size
(),
4
);
return
origin_shape
[
0
]
==
device_dims
.
GetNumber
()
&&
origin_shape
[
1
]
==
device_dims
.
GetChannel
()
&&
origin_shape
[
2
]
==
device_dims
.
GetHeight
()
&&
origin_shape
[
3
]
==
device_dims
.
GetWidth
();
}
}
// namespace npu
}
// namespace subgraph
}
// namespace lite
...
...
lite/kernels/npu/bridges/utility.h
浏览文件 @
a981af15
...
...
@@ -19,7 +19,6 @@
#include <string>
#include <unordered_map>
#include <vector>
#include "HiAiModelManagerService.h"
#include "graph/buffer.h"
#include "graph/graph.h"
#include "graph/model.h"
...
...
@@ -146,8 +145,6 @@ ge::TensorPtr CvtTensor(const Tensor& in_tensor,
int
CvtActMode
(
std
::
string
act_type
);
bool
CheckShape
(
DDim
origin_dims
,
hiai
::
TensorDimension
device_dims
);
}
// namespace npu
}
// namespace subgraph
}
// namespace lite
...
...
lite/kernels/npu/subgraph_compute.cc
浏览文件 @
a981af15
...
...
@@ -124,19 +124,9 @@ int SubgraphEngine::BuildDeviceProgram() {
<<
device_idims
[
i
].
GetHeight
()
<<
","
<<
device_idims
[
i
].
GetWidth
()
<<
"}"
;
// Prepare the device input tensors
if
(
!
subgraph
::
npu
::
CheckShape
(
origin_idims_
[
i
],
device_idims
[
i
]))
{
LOG
(
WARNING
)
<<
"origin and device input's dims are mismatched."
;
for
(
int
j
=
0
;
j
<
origin_idims_
[
i
].
size
();
j
++
)
{
LOG
(
WARNING
)
<<
"origin_idims_["
<<
i
<<
"]["
<<
j
<<
"]: "
<<
origin_idims_
[
i
][
j
];
}
LOG
(
WARNING
)
<<
"device_idims["
<<
i
<<
"]: {"
<<
device_idims
[
i
].
GetNumber
()
<<
", "
<<
device_idims
[
i
].
GetChannel
()
<<
", "
<<
device_idims
[
i
].
GetHeight
()
<<
", "
<<
device_idims
[
i
].
GetWidth
()
<<
"}"
;
return
subgraph
::
FAILED
;
}
CHECK_EQ
(
origin_idims_
[
i
].
production
(),
device_idims
[
i
].
GetNumber
()
*
device_idims
[
i
].
GetChannel
()
*
device_idims
[
i
].
GetHeight
()
*
device_idims
[
i
].
GetWidth
());
device_itensors_
[
i
].
reset
(
new
hiai
::
AiTensor
);
device_itensors_
[
i
]
->
Init
(
&
(
device_idims
[
i
]));
}
...
...
@@ -177,21 +167,9 @@ int SubgraphEngine::BuildDeviceProgram() {
<<
PrecisionToStr
(
precision
);
break
;
}
/*
if (!subgraph::npu::CheckShape(origin_odims_[i], device_odims[i])) {
LOG(WARNING) << "origin and device output's dims are mismatched.";
for (int j = 0; j < origin_odims_[i].size(); j++) {
LOG(WARNING) << "origin_odims_[" << i << "][" << j
<< "]: " << origin_odims_[i][j];
}
LOG(WARNING) << "device_odims[" << i << "]: {"
<< device_odims[i].GetNumber() << ", "
<< device_odims[i].GetChannel() << ", "
<< device_odims[i].GetHeight() << ", "
<< device_odims[i].GetWidth() << "}";
return subgraph::FAILED;
}
*/
CHECK_EQ
(
origin_odims_
[
i
].
production
(),
device_odims
[
i
].
GetNumber
()
*
device_odims
[
i
].
GetChannel
()
*
device_odims
[
i
].
GetHeight
()
*
device_odims
[
i
].
GetWidth
());
device_otensors_
[
i
].
reset
(
new
hiai
::
AiTensor
);
device_otensors_
[
i
]
->
Init
(
&
(
device_odims
[
i
]));
}
...
...
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