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fa437c1f
编写于
11月 04, 2022
作者:
jm_12138
提交者:
GitHub
11月 04, 2022
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电子邮件补丁
差异文件
update porn_detection_gru (#2103)
上级
b2853121
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4
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Showing
4 changed file
with
54 addition
and
112 deletion
+54
-112
modules/text/text_review/porn_detection_gru/README.md
modules/text/text_review/porn_detection_gru/README.md
+18
-14
modules/text/text_review/porn_detection_gru/README_en.md
modules/text/text_review/porn_detection_gru/README_en.md
+18
-14
modules/text/text_review/porn_detection_gru/module.py
modules/text/text_review/porn_detection_gru/module.py
+17
-83
modules/text/text_review/porn_detection_gru/processor.py
modules/text/text_review/porn_detection_gru/processor.py
+1
-1
未找到文件。
modules/text/text_review/porn_detection_gru/README.md
浏览文件 @
fa437c1f
...
@@ -179,7 +179,11 @@
...
@@ -179,7 +179,11 @@
大幅提升预测性能,同时简化接口使用
大幅提升预测性能,同时简化接口使用
*
1.2.0
移除 Fluid API
-
```shell
-
```shell
$ hub install porn_detection_gru==1.
1
.0
$ hub install porn_detection_gru==1.
2
.0
```
```
modules/text/text_review/porn_detection_gru/README_en.md
浏览文件 @
fa437c1f
...
@@ -177,7 +177,11 @@
...
@@ -177,7 +177,11 @@
Improves prediction performance and simplifies interface usage
Improves prediction performance and simplifies interface usage
*
1.2.0
移除 Fluid API
-
```shell
-
```shell
$ hub install porn_detection_gru==1.
1
.0
$ hub install porn_detection_gru==1.
2
.0
```
```
modules/text/text_review/porn_detection_gru/module.py
浏览文件 @
fa437c1f
# -*- coding:utf-8 -*-
from
__future__
import
absolute_import
from
__future__
import
division
from
__future__
import
print_function
import
json
import
math
import
math
import
os
import
os
import
six
import
paddle.fluid
as
fluid
import
paddlehub
as
hub
from
paddlehub.common.paddle_helper
import
get_variable_info
from
paddlehub.module.module
import
moduleinfo
,
serving
from
paddlehub.reader
import
tokenization
from
porn_detection_gru.processor
import
load_vocab
,
preprocess
,
postprocess
import
paddlehub
as
hub
from
.processor
import
load_vocab
from
.processor
import
postprocess
from
.processor
import
preprocess
from
paddlehub.compat.task
import
tokenization
from
paddlehub.module.module
import
moduleinfo
from
paddlehub.module.module
import
serving
@
moduleinfo
(
@
moduleinfo
(
name
=
"porn_detection_gru"
,
name
=
"porn_detection_gru"
,
version
=
"1.2.0"
,
version
=
"1.1.0"
,
summary
=
"Baidu's open-source Porn Detection Model."
,
summary
=
"Baidu's open-source Porn Detection Model."
,
author
=
"baidu-nlp"
,
author
=
"baidu-nlp"
,
author_email
=
""
,
author_email
=
""
,
type
=
"nlp/sentiment_analysis"
)
type
=
"nlp/sentiment_analysis"
)
class
PornDetectionGRU
(
hub
.
NLPPredictionModule
):
class
PornDetectionGRU
(
hub
.
NLPPredictionModule
):
def
_initialize
(
self
):
def
__init__
(
self
):
"""
"""
initialize with the necessary elements
initialize with the necessary elements
"""
"""
...
@@ -42,41 +36,6 @@ class PornDetectionGRU(hub.NLPPredictionModule):
...
@@ -42,41 +36,6 @@ class PornDetectionGRU(hub.NLPPredictionModule):
self
.
_set_config
()
self
.
_set_config
()
def
context
(
self
,
trainable
=
False
):
"""
Get the input ,output and program of the pretrained porn_detection_gru
Args:
trainable(bool): whether fine-tune the pretrained parameters of porn_detection_gru or not
Returns:
inputs(dict): the input variables of porn_detection_gru (words)
outputs(dict): the output variables of porn_detection_gru (the sentiment prediction results)
main_program(Program): the main_program of lac with pretrained prameters
"""
place
=
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
program
,
feed_target_names
,
fetch_targets
=
fluid
.
io
.
load_inference_model
(
dirname
=
self
.
pretrained_model_path
,
executor
=
exe
)
with
open
(
self
.
param_file
,
'r'
)
as
file
:
params_list
=
file
.
readlines
()
for
param
in
params_list
:
param
=
param
.
strip
()
var
=
program
.
global_block
().
var
(
param
)
var_info
=
get_variable_info
(
var
)
program
.
global_block
().
create_parameter
(
shape
=
var_info
[
'shape'
],
dtype
=
var_info
[
'dtype'
],
name
=
var_info
[
'name'
])
for
param
in
program
.
global_block
().
iter_parameters
():
param
.
trainable
=
trainable
for
name
,
var
in
program
.
global_block
().
vars
.
items
():
if
name
==
feed_target_names
[
0
]:
inputs
=
{
"words"
:
var
}
# output of sencond layer from the end prediction layer (fc-softmax)
if
name
==
"@HUB_porn_detection_gru@layer_norm_0.tmp_2"
:
outputs
=
{
"class_probs"
:
fetch_targets
[
0
],
"sentence_feature"
:
var
}
return
inputs
,
outputs
,
program
@
serving
@
serving
def
detection
(
self
,
texts
=
[],
data
=
{},
use_gpu
=
False
,
batch_size
=
1
):
def
detection
(
self
,
texts
=
[],
data
=
{},
use_gpu
=
False
,
batch_size
=
1
):
"""
"""
...
@@ -134,28 +93,3 @@ class PornDetectionGRU(hub.NLPPredictionModule):
...
@@ -134,28 +93,3 @@ class PornDetectionGRU(hub.NLPPredictionModule):
"""
"""
self
.
labels
=
{
"porn"
:
1
,
"not_porn"
:
0
}
self
.
labels
=
{
"porn"
:
1
,
"not_porn"
:
0
}
return
self
.
labels
return
self
.
labels
if
__name__
==
"__main__"
:
porn_detection_gru
=
PornDetectionGRU
()
porn_detection_gru
.
context
()
# porn_detection_gru = hub.Module(name='porn_detection_gru')
test_text
=
[
"黄片下载"
,
"打击黄牛党"
]
results
=
porn_detection_gru
.
detection
(
texts
=
test_text
)
for
index
,
text
in
enumerate
(
test_text
):
results
[
index
][
"text"
]
=
text
for
index
,
result
in
enumerate
(
results
):
if
six
.
PY2
:
print
(
json
.
dumps
(
results
[
index
],
encoding
=
"utf8"
,
ensure_ascii
=
False
))
else
:
print
(
results
[
index
])
input_dict
=
{
"text"
:
test_text
}
results
=
porn_detection_gru
.
detection
(
data
=
input_dict
)
for
index
,
text
in
enumerate
(
test_text
):
results
[
index
][
"text"
]
=
text
for
index
,
result
in
enumerate
(
results
):
if
six
.
PY2
:
print
(
json
.
dumps
(
results
[
index
],
encoding
=
"utf8"
,
ensure_ascii
=
False
))
else
:
print
(
results
[
index
])
modules/text/text_review/porn_detection_gru/processor.py
浏览文件 @
fa437c1f
# -*- coding: utf-8 -*-
import
io
import
io
import
numpy
as
np
import
numpy
as
np
...
...
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