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体验新版 GitCode,发现更多精彩内容 >>
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6361a38f
编写于
6月 03, 2021
作者:
littletomatodonkey
浏览文件
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电子邮件补丁
差异文件
fix export model for distillation model
上级
ab4db2ac
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
62 addition
and
40 deletion
+62
-40
ppocr/losses/distillation_loss.py
ppocr/losses/distillation_loss.py
+1
-1
ppocr/modeling/architectures/distillation_model.py
ppocr/modeling/architectures/distillation_model.py
+7
-7
tools/export_model.py
tools/export_model.py
+54
-32
未找到文件。
ppocr/losses/distillation_loss.py
浏览文件 @
6361a38f
...
@@ -82,7 +82,7 @@ class DistillationDistanceLoss(DistanceLoss):
...
@@ -82,7 +82,7 @@ class DistillationDistanceLoss(DistanceLoss):
key
=
None
,
key
=
None
,
name
=
"loss_distance"
,
name
=
"loss_distance"
,
**
kargs
):
**
kargs
):
super
().
__init__
(
mode
=
mode
,
name
=
name
)
super
().
__init__
(
mode
=
mode
,
name
=
name
,
**
kargs
)
assert
isinstance
(
model_name_pairs
,
list
)
assert
isinstance
(
model_name_pairs
,
list
)
self
.
key
=
key
self
.
key
=
key
self
.
model_name_pairs
=
model_name_pairs
self
.
model_name_pairs
=
model_name_pairs
...
...
ppocr/modeling/architectures/distillation_model.py
浏览文件 @
6361a38f
...
@@ -34,8 +34,8 @@ class DistillationModel(nn.Layer):
...
@@ -34,8 +34,8 @@ class DistillationModel(nn.Layer):
config (dict): the super parameters for module.
config (dict): the super parameters for module.
"""
"""
super
().
__init__
()
super
().
__init__
()
self
.
model_
dict
=
dict
()
self
.
model_
list
=
[]
index
=
0
self
.
model_name_list
=
[]
for
key
in
config
[
"Models"
]:
for
key
in
config
[
"Models"
]:
model_config
=
config
[
"Models"
][
key
]
model_config
=
config
[
"Models"
][
key
]
freeze_params
=
False
freeze_params
=
False
...
@@ -46,15 +46,15 @@ class DistillationModel(nn.Layer):
...
@@ -46,15 +46,15 @@ class DistillationModel(nn.Layer):
pretrained
=
model_config
.
pop
(
"pretrained"
)
pretrained
=
model_config
.
pop
(
"pretrained"
)
model
=
BaseModel
(
model_config
)
model
=
BaseModel
(
model_config
)
if
pretrained
is
not
None
:
if
pretrained
is
not
None
:
load_dygraph_pretrain
(
model
,
path
=
pretrained
[
index
]
)
load_dygraph_pretrain
(
model
,
path
=
pretrained
)
if
freeze_params
:
if
freeze_params
:
for
param
in
model
.
parameters
():
for
param
in
model
.
parameters
():
param
.
trainable
=
False
param
.
trainable
=
False
self
.
model_
dict
[
key
]
=
self
.
add_sublayer
(
key
,
model
)
self
.
model_
list
.
append
(
self
.
add_sublayer
(
key
,
model
)
)
index
+=
1
self
.
model_name_list
.
append
(
key
)
def
forward
(
self
,
x
):
def
forward
(
self
,
x
):
result_dict
=
dict
()
result_dict
=
dict
()
for
key
in
self
.
model_dict
:
for
idx
,
model_name
in
enumerate
(
self
.
model_name_list
)
:
result_dict
[
key
]
=
self
.
model_dict
[
key
](
x
)
result_dict
[
model_name
]
=
self
.
model_list
[
idx
](
x
)
return
result_dict
return
result_dict
tools/export_model.py
浏览文件 @
6361a38f
...
@@ -17,7 +17,7 @@ import sys
...
@@ -17,7 +17,7 @@ import sys
__dir__
=
os
.
path
.
dirname
(
os
.
path
.
abspath
(
__file__
))
__dir__
=
os
.
path
.
dirname
(
os
.
path
.
abspath
(
__file__
))
sys
.
path
.
append
(
__dir__
)
sys
.
path
.
append
(
__dir__
)
sys
.
path
.
append
(
os
.
path
.
abspath
(
os
.
path
.
join
(
__dir__
,
'..'
)))
sys
.
path
.
append
(
os
.
path
.
abspath
(
os
.
path
.
join
(
__dir__
,
".."
)))
import
argparse
import
argparse
...
@@ -31,32 +31,12 @@ from ppocr.utils.logging import get_logger
...
@@ -31,32 +31,12 @@ from ppocr.utils.logging import get_logger
from
tools.program
import
load_config
,
merge_config
,
ArgsParser
from
tools.program
import
load_config
,
merge_config
,
ArgsParser
def
main
():
def
export_single_model
(
model
,
arch_config
,
save_path
,
logger
):
FLAGS
=
ArgsParser
().
parse_args
()
if
arch_config
[
"algorithm"
]
==
"SRN"
:
config
=
load_config
(
FLAGS
.
config
)
max_text_length
=
arch_config
[
"Head"
][
"max_text_length"
]
merge_config
(
FLAGS
.
opt
)
logger
=
get_logger
()
# build post process
post_process_class
=
build_post_process
(
config
[
'PostProcess'
],
config
[
'Global'
])
# build model
# for rec algorithm
if
hasattr
(
post_process_class
,
'character'
):
char_num
=
len
(
getattr
(
post_process_class
,
'character'
))
config
[
'Architecture'
][
"Head"
][
'out_channels'
]
=
char_num
model
=
build_model
(
config
[
'Architecture'
])
init_model
(
config
,
model
,
logger
)
model
.
eval
()
save_path
=
'{}/inference'
.
format
(
config
[
'Global'
][
'save_inference_dir'
])
if
config
[
'Architecture'
][
'algorithm'
]
==
"SRN"
:
max_text_length
=
config
[
'Architecture'
][
'Head'
][
'max_text_length'
]
other_shape
=
[
other_shape
=
[
paddle
.
static
.
InputSpec
(
paddle
.
static
.
InputSpec
(
shape
=
[
None
,
1
,
64
,
256
],
dtype
=
'float32'
),
[
shape
=
[
None
,
1
,
64
,
256
],
dtype
=
"float32"
),
[
paddle
.
static
.
InputSpec
(
paddle
.
static
.
InputSpec
(
shape
=
[
None
,
256
,
1
],
shape
=
[
None
,
256
,
1
],
dtype
=
"int64"
),
paddle
.
static
.
InputSpec
(
dtype
=
"int64"
),
paddle
.
static
.
InputSpec
(
...
@@ -71,24 +51,66 @@ def main():
...
@@ -71,24 +51,66 @@ def main():
model
=
to_static
(
model
,
input_spec
=
other_shape
)
model
=
to_static
(
model
,
input_spec
=
other_shape
)
else
:
else
:
infer_shape
=
[
3
,
-
1
,
-
1
]
infer_shape
=
[
3
,
-
1
,
-
1
]
if
config
[
'Architecture'
][
'model_type'
]
==
"rec"
:
if
arch_config
[
"model_type"
]
==
"rec"
:
infer_shape
=
[
3
,
32
,
-
1
]
# for rec model, H must be 32
infer_shape
=
[
3
,
32
,
-
1
]
# for rec model, H must be 32
if
'Transform'
in
config
[
'Architecture'
]
and
config
[
'Architecture'
]
[
if
"Transform"
in
arch_config
and
arch_config
[
'Transform'
]
is
not
None
and
config
[
'Architecture'
][
"Transform"
]
is
not
None
and
arch_config
[
"Transform"
][
'Transform'
][
'name'
]
==
'TPS'
:
"name"
]
==
"TPS"
:
logger
.
info
(
logger
.
info
(
'When there is tps in the network, variable length input is not supported, and the input size needs to be the same as during training'
"When there is tps in the network, variable length input is not supported, and the input size needs to be the same as during training"
)
)
infer_shape
[
-
1
]
=
100
infer_shape
[
-
1
]
=
100
model
=
to_static
(
model
=
to_static
(
model
,
model
,
input_spec
=
[
input_spec
=
[
paddle
.
static
.
InputSpec
(
paddle
.
static
.
InputSpec
(
shape
=
[
None
]
+
infer_shape
,
dtype
=
'float32'
)
shape
=
[
None
]
+
infer_shape
,
dtype
=
"float32"
)
])
])
paddle
.
jit
.
save
(
model
,
save_path
)
paddle
.
jit
.
save
(
model
,
save_path
)
logger
.
info
(
'inference model is saved to {}'
.
format
(
save_path
))
logger
.
info
(
"inference model is saved to {}"
.
format
(
save_path
))
return
def
main
():
FLAGS
=
ArgsParser
().
parse_args
()
config
=
load_config
(
FLAGS
.
config
)
merge_config
(
FLAGS
.
opt
)
logger
=
get_logger
()
# build post process
post_process_class
=
build_post_process
(
config
[
"PostProcess"
],
config
[
"Global"
])
# build model
# for rec algorithm
if
hasattr
(
post_process_class
,
"character"
):
char_num
=
len
(
getattr
(
post_process_class
,
"character"
))
if
config
[
"Architecture"
][
"algorithm"
]
in
[
"Distillation"
,
]:
# distillation model
for
key
in
config
[
"Architecture"
][
"Models"
]:
config
[
"Architecture"
][
"Models"
][
key
][
"Head"
][
"out_channels"
]
=
char_num
else
:
# base rec model
config
[
"Architecture"
][
"Head"
][
"out_channels"
]
=
char_num
model
=
build_model
(
config
[
"Architecture"
])
init_model
(
config
,
model
,
logger
)
model
.
eval
()
save_path
=
config
[
"Global"
][
"save_inference_dir"
]
arch_config
=
config
[
"Architecture"
]
if
arch_config
[
"algorithm"
]
in
[
"Distillation"
,
]:
# distillation model
archs
=
list
(
arch_config
[
"Models"
].
values
())
for
idx
,
name
in
enumerate
(
model
.
model_name_list
):
sub_model_save_path
=
os
.
path
.
join
(
save_path
,
name
,
"inference"
)
export_single_model
(
model
.
model_list
[
idx
],
archs
[
idx
],
sub_model_save_path
,
logger
)
else
:
save_path
=
os
.
path
.
join
(
save_path
,
"inference"
)
export_single_model
(
model
,
arch_config
,
save_path
,
logger
)
if
__name__
==
"__main__"
:
if
__name__
==
"__main__"
:
...
...
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