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体验新版 GitCode,发现更多精彩内容 >>
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4350bd05
编写于
6月 16, 2020
作者:
J
Jason
提交者:
GitHub
6月 16, 2020
浏览文件
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差异文件
Merge pull request #274 from PaddlePaddle/2onnx
2onnx
上级
279253e2
2b30df83
变更
1
隐藏空白更改
内联
并排
Showing
1 changed file
with
208 addition
and
37 deletion
+208
-37
x2paddle/op_mapper/paddle_op_mapper.py
x2paddle/op_mapper/paddle_op_mapper.py
+208
-37
未找到文件。
x2paddle/op_mapper/paddle_op_mapper.py
浏览文件 @
4350bd05
...
...
@@ -13,6 +13,7 @@
# limitations under the License.
import
math
import
sys
import
x2paddle
import
os
import
numpy
as
np
...
...
@@ -77,6 +78,11 @@ class PaddleOpMapper(object):
'Relu'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
))
return
node
def
sigmoid
(
self
,
op
,
block
):
node
=
helper
.
make_node
(
'Sigmoid'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
))
return
node
def
elementwise_add
(
self
,
op
,
block
):
axis
=
op
.
attr
(
'axis'
)
x_shape
=
block
.
var
(
op
.
input
(
'X'
)[
0
]).
shape
...
...
@@ -128,12 +134,40 @@ class PaddleOpMapper(object):
return
node
def
softmax
(
self
,
op
,
block
):
node
=
helper
.
make_node
(
'Softmax'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
),
axis
=
op
.
attr
(
'axis'
))
return
node
axis
=
op
.
attr
(
'axis'
)
shape
=
block
.
var
(
op
.
output
(
'Out'
)[
0
]).
shape
if
axis
<
0
:
axis
+=
len
(
shape
)
if
axis
==
len
(
shape
)
-
1
:
node
=
helper
.
make_node
(
'Softmax'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
),
axis
=
op
.
attr
(
'axis'
))
return
node
else
:
perm
=
[
i
for
i
in
range
(
len
(
shape
))]
perm
[
-
1
]
=
axis
perm
[
axis
]
=
len
(
shape
)
-
1
transpose_name0
=
self
.
get_name
(
op
.
type
,
'transpose'
)
transpose_node0
=
helper
.
make_node
(
'Transpose'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
[
transpose_name0
],
perm
=
perm
)
softmax_name
=
self
.
get_name
(
op
.
type
,
'softmax'
)
softmax_node
=
helper
.
make_node
(
'Softmax'
,
inputs
=
[
transpose_name0
],
outputs
=
[
softmax_name
],
axis
=-
1
)
transpose_name1
=
self
.
get_name
(
op
.
type
,
'transpose'
)
transpose_node1
=
helper
.
make_node
(
'Transpose'
,
inputs
=
[
softmax_name
],
outputs
=
op
.
output
(
'Out'
),
perm
=
perm
)
return
[
transpose_node0
,
softmax_node
,
transpose_node1
]
def
scale
(
self
,
op
,
block
):
scale
=
op
.
attr
(
'scale'
)
...
...
@@ -261,21 +295,22 @@ class PaddleOpMapper(object):
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
),
axis
=
op
.
attr
(
'axis'
))
return
node
def
slice
(
self
,
op
,
block
):
axes
=
op
.
attr
(
'axes'
)
starts
=
op
.
attr
(
'starts'
)
ends
=
op
.
attr
(
'ends'
)
axes_name
=
get_name
(
op
.
type
,
'axes'
)
starts_name
=
get_name
(
op
.
type
,
'starts'
)
ends_name
=
get_name
(
op
.
type
,
'ends'
)
axes_node
=
make_constant_node
(
axes_name
,
onnx_pb
.
TensorProto
.
INT64
,
axes
)
starts_node
=
make_constant_node
(
starts_name
,
onnx_pb
.
TensorProto
.
INT64
,
starts
)
ends_node
=
make_constant_node
(
ends_name
,
onnx_pb
.
TensorProto
.
INT64
,
ends
)
axes_name
=
self
.
get_name
(
op
.
type
,
'axes'
)
starts_name
=
self
.
get_name
(
op
.
type
,
'starts'
)
ends_name
=
self
.
get_name
(
op
.
type
,
'ends'
)
axes_node
=
self
.
make_constant_node
(
axes_name
,
onnx_pb
.
TensorProto
.
INT64
,
axes
)
starts_node
=
self
.
make_constant_node
(
starts_name
,
onnx_pb
.
TensorProto
.
INT64
,
starts
)
ends_node
=
self
.
make_constant_node
(
ends_name
,
onnx_pb
.
TensorProto
.
INT64
,
ends
)
node
=
helper
.
make_node
(
"Slice"
,
inputs
=
[
op
.
input
(
'Input'
)[
0
],
starts_name
,
ends_name
,
axes_name
],
...
...
@@ -288,12 +323,14 @@ class PaddleOpMapper(object):
dtype
=
op
.
attr
(
'dtype'
)
shape
=
op
.
attr
(
'shape'
)
value
=
np
.
ones
(
shape
)
*
value
if
dtype
==
2
:
value
=
value
.
astype
(
'int32'
)
node
=
helper
.
make_node
(
'Constant'
,
inputs
=
[],
outputs
=
op
.
attr
(
'Out'
),
outputs
=
op
.
output
(
'Out'
),
value
=
helper
.
make_tensor
(
name
=
op
.
attr
(
'Out'
)
,
name
=
op
.
output
(
'Out'
)[
0
]
,
data_type
=
self
.
paddle_onnx_dtype_map
[
dtype
],
dims
=
shape
,
vals
=
value
.
tolist
()))
...
...
@@ -304,28 +341,45 @@ class PaddleOpMapper(object):
'Transpose'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
),
perm
=
op
.
attr
(
'
perm
'
))
perm
=
op
.
attr
(
'
axis
'
))
return
node
def
reshape2
(
self
,
op
,
block
):
input_names
=
op
.
input_names
if
'Shape'
in
input_names
and
len
(
op
.
input
(
'Shape'
))
>
0
:
if
len
(
op
.
input
(
'ShapeTensor'
))
>
1
:
cast_shape_nodes
=
list
()
cast_shape_names
=
list
()
for
i
in
range
(
len
(
op
.
input
(
'ShapeTensor'
))):
dim
=
op
.
input
(
'ShapeTensor'
)[
i
]
temp_name
=
self
.
get_name
(
op
.
type
,
'shape.cast'
)
node
=
helper
.
make_node
(
'Cast'
,
inputs
=
[
dim
],
outputs
=
[
temp_name
],
to
=
onnx_pb
.
TensorProto
.
INT64
)
cast_shape_nodes
.
append
(
node
)
cast_shape_names
.
append
(
temp_name
)
temp_name
=
self
.
get_name
(
op
.
type
,
'shape.concat'
)
shape_node
=
helper
.
make_node
(
'Concat'
,
inputs
=
cast_shape_names
,
outputs
=
[
temp_name
],
axis
=-
1
)
node
=
helper
.
make_node
(
'Reshape'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
op
.
input
(
'Shape'
)[
0
]],
inputs
=
[
op
.
input
(
'X'
)[
0
],
temp_name
],
outputs
=
op
.
output
(
'Out'
))
return
cast_shape_nodes
+
[
shape_node
,
node
]
else
:
shape
=
op
.
attr
(
'shape'
)
shape_name
=
get_name
(
op
.
type
,
'shape'
)
shape_node
=
make_constant_node
(
shape_name
,
onnxpb
.
TensorProto
.
INT64
,
shape
)
temp_name
=
self
.
get_name
(
op
.
type
,
'shape.cast'
)
cast_shape_node
=
helper
.
make_node
(
'Cast'
,
inputs
=
op
.
input
(
'ShapeTensor'
),
outputs
=
[
temp_name
],
to
=
onnx_pb
.
TensorProto
.
INT64
)
node
=
helper
.
make_node
(
'Reshape'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
shape
_name
],
inputs
=
[
op
.
input
(
'X'
)[
0
],
temp
_name
],
outputs
=
op
.
output
(
'Out'
))
return
[
shape_node
,
node
]
return
node
return
[
cast_shape_node
,
node
]
def
dropout
(
self
,
op
,
block
):
dropout_mode
=
op
.
attr
(
'dropout_implementation'
)
...
...
@@ -351,24 +405,119 @@ class PaddleOpMapper(object):
'ReduceMean'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
),
axes
=
op
.
attr
(
'
axes
'
),
axes
=
op
.
attr
(
'
dim
'
),
keepdims
=
op
.
attr
(
'keep_dim'
))
return
node
def
bilinear_interp
(
self
,
op
,
block
):
input_names
=
op
.
input_names
coordinate_transformation_mode
=
'half_pixel'
shape_dtype
=
block
.
var
(
op
.
input
(
'OutSize'
)[
0
]).
dtype
if
op
.
attr
(
'align_corners'
):
coordinate_transformation_mode
=
'align_corners'
if
'OutSize'
in
input_names
and
len
(
op
.
input
(
'OutSize'
))
>
0
:
roi_node
=
self
.
make_constant_node
(
self
.
get_name
(
op
.
type
,
'roi'
),
onnx_pb
.
TensorProto
.
FLOAT
,
[
1
,
1
,
1
,
1
,
1
,
1
,
1
,
1
])
roi_name
=
self
.
get_name
(
op
.
type
,
'roi'
)
roi_node
=
self
.
make_constant_node
(
roi_name
,
onnx_pb
.
TensorProto
.
FLOAT
,
[
1
,
1
,
1
,
1
,
1
,
1
,
1
,
1
])
empty_name
=
self
.
get_name
(
op
.
type
,
'empty'
)
empty_tensor
=
helper
.
make_tensor
(
empty_name
,
onnx_pb
.
TensorProto
.
FLOAT
,
(
0
,
),
np
.
array
([]).
astype
(
'float32'
),
raw
=
False
)
empty_node
=
helper
.
make_node
(
'Constant'
,
[],
outputs
=
[
empty_name
],
value
=
empty_tensor
)
shape_name0
=
self
.
get_name
(
op
.
type
,
'shape'
)
shape_node0
=
helper
.
make_node
(
'Shape'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
[
shape_name0
])
starts_name
=
self
.
get_name
(
op
.
type
,
'slice.starts'
)
starts_node
=
self
.
make_constant_node
(
starts_name
,
onnx_pb
.
TensorProto
.
INT64
,
[
0
])
ends_name
=
self
.
get_name
(
op
.
type
,
'slice.ends'
)
ends_node
=
self
.
make_constant_node
(
ends_name
,
onnx_pb
.
TensorProto
.
INT64
,
[
2
])
shape_name1
=
self
.
get_name
(
op
.
type
,
'shape'
)
shape_node1
=
helper
.
make_node
(
'Slice'
,
inputs
=
[
shape_name0
,
starts_name
,
ends_name
],
outputs
=
[
shape_name1
])
shape_name2
=
self
.
get_name
(
op
.
type
,
"shape.cast"
)
shape_node2
=
helper
.
make_node
(
'Cast'
,
inputs
=
op
.
input
(
'OutSize'
),
outputs
=
[
shape_name2
],
to
=
onnx_pb
.
TensorProto
.
INT64
)
shape_name3
=
self
.
get_name
(
op
.
type
,
"shape.concat"
)
shape_node3
=
helper
.
make_node
(
'Concat'
,
inputs
=
[
shape_name1
,
shape_name2
],
outputs
=
[
shape_name3
],
axis
=
0
)
result_node
=
helper
.
make_node
(
'Resize'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
roi_name
,
empty_name
,
shape_name3
],
outputs
=
op
.
output
(
'Out'
),
mode
=
'linear'
,
coordinate_transformation_mode
=
coordinate_transformation_mode
)
return
[
roi_node
,
empty_node
,
shape_node0
,
starts_node
,
ends_node
,
shape_node1
,
shape_node2
,
shape_node3
,
result_node
]
elif
'Scale'
in
input_names
and
len
(
op
.
input
(
'Scale'
))
>
0
:
node
=
helper
.
make_node
(
'Resize'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
op
.
input
(
'Scale'
)[
0
]],
outputs
=
op
.
output
(
'Out'
),
mode
=
'linear'
,
coordinate_transformation_mode
=
coordinate_transformation_mode
)
else
:
out_shape
=
[
op
.
attr
(
'out_h'
),
op
.
attr
(
'out_w'
)]
scale
=
op
.
attr
(
'scale'
)
if
out_shape
.
count
(
-
1
)
>
0
:
scale_name
=
self
.
get_name
(
op
.
type
,
'scale'
)
scale_node
=
self
.
make_constant_node
(
scale_name
,
onnx_pb
.
TensorProto
.
FLOAT
,
[
1
,
1
,
scale
,
scale
])
roi_name
=
self
.
get_name
(
op
.
type
,
'roi'
)
roi_node
=
self
.
make_constant_node
(
roi_name
,
onnx_pb
.
TensorProto
.
FLOAT
,
[
1
,
1
,
1
,
1
,
1
,
1
,
1
,
1
])
node
=
helper
.
make_node
(
'Resize'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
roi_name
,
scale_name
],
outputs
=
op
.
output
(
'Out'
),
mode
=
'nearest'
,
coordinate_transformation_mode
=
coordinate_transformation_mode
)
return
[
scale_node
,
roi_node
,
node
]
else
:
raise
Exception
(
"Unexpected situation happend"
)
return
node
def
nearest_interp
(
self
,
op
,
block
):
input_names
=
op
.
input_names
coordinate_transformation_mode
=
'half_pixel'
if
op
.
attr
(
'align_corners'
):
coordinate_transformation_mode
=
'align_corners'
if
'OutSize'
in
input_names
and
len
(
op
.
input
(
'OutSize'
))
>
0
:
node
=
helper
.
make_node
(
'Resize'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
''
,
op
.
input
(
'OutSize'
)[
0
]],
outputs
=
op
.
output
(
'Out'
))
outputs
=
op
.
output
(
'Out'
),
mode
=
'nearest'
,
coordinate_transformation_mode
=
coordinate_transformation_mode
)
elif
'Scale'
in
input_names
and
len
(
op
.
input
(
'Scale'
))
>
0
:
node
=
helper
.
make_node
(
'Resize'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
op
.
input
(
'Scale'
)[
0
]],
outputs
=
op
.
output
(
'Out'
))
outputs
=
op
.
output
(
'Out'
),
mode
=
'nearest'
,
coordinate_transformation_mode
=
coordinate_transformation_mode
)
else
:
out_shape
=
[
op
.
attr
(
'out_h'
),
op
.
attr
(
'out_w'
)]
scale
=
op
.
attr
(
'scale'
)
...
...
@@ -384,7 +533,9 @@ class PaddleOpMapper(object):
'Resize'
,
inputs
=
[
op
.
input
(
'X'
)[
0
],
roi_name
,
scale_name
],
outputs
=
op
.
output
(
'Out'
),
mode
=
'nearest'
)
mode
=
'nearest'
,
coordinate_transformation_mode
=
coordinate_transformation_mode
)
return
[
scale_node
,
roi_node
,
node
]
else
:
raise
Exception
(
"Unexpected situation happend"
)
...
...
@@ -449,6 +600,23 @@ class PaddleOpMapper(object):
elem_type
=
self
.
paddle_onnx_dtype_map
[
var
.
dtype
])
return
tensor_info
def
unsqueeze2
(
self
,
op
,
block
):
node
=
helper
.
make_node
(
'Unsqueeze'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
),
axes
=
op
.
attr
(
'axes'
))
return
node
def
arg_max
(
self
,
op
,
block
):
node
=
helper
.
make_node
(
'ArgMax'
,
inputs
=
op
.
input
(
'X'
),
outputs
=
op
.
output
(
'Out'
),
axis
=
op
.
attr
(
'axis'
),
keepdims
=
0
)
return
node
def
convert_weights
(
self
,
program
):
var_names
=
program
.
global_block
().
vars
nodes
=
list
()
...
...
@@ -477,9 +645,12 @@ class PaddleOpMapper(object):
unsupported_ops
=
set
()
print
(
"Translating PaddlePaddle to ONNX...
\n
"
)
for
block
in
program
.
blocks
:
for
op
in
block
.
ops
:
print
(
'Translating op: {}'
.
format
(
op
.
type
))
for
i
,
op
in
enumerate
(
block
.
ops
):
sys
.
stdout
.
write
(
"
\r
Total:{}, Current:{} : {} "
.
format
(
len
(
block
.
ops
),
i
+
1
,
op
.
type
))
if
not
hasattr
(
self
,
op
.
type
):
unsupported_ops
.
add
(
op
.
type
)
continue
...
...
@@ -497,7 +668,7 @@ class PaddleOpMapper(object):
op_nodes
.
append
(
node
)
if
len
(
unsupported_ops
)
>
0
:
print
(
"There's {} ops are not supported yet"
.
format
(
print
(
"
\n
There's {} ops are not supported yet"
.
format
(
len
(
unsupported_ops
)))
for
op
in
unsupported_ops
:
print
(
"=========== {} ==========="
.
format
(
op
))
...
...
@@ -516,5 +687,5 @@ class PaddleOpMapper(object):
os
.
makedirs
(
save_dir
)
with
open
(
os
.
path
.
join
(
save_dir
,
'x2paddle_model.onnx'
),
'wb'
)
as
f
:
f
.
write
(
model
.
SerializeToString
())
print
(
"Translated model saved in {}"
.
format
(
print
(
"
\n
Translated model saved in {}"
.
format
(
os
.
path
.
join
(
save_dir
,
'x2paddle_model.onnx'
)))
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