update porn_detection_cnn (#2102)

modules/text/text_review/porn_detection_cnn/README.md

@@ -177,8 +177,10 @@
 
   大幅提升预测性能，同时简化接口使用
 
-  - ```shell
-    $ hub install porn_detection_cnn==1.1.0
-    ```
+* 1.2.0
 
+  移除 fluid api
 
+  - ```shell
+    $ hub install porn_detection_cnn==1.2.0
+    ```

modules/text/text_review/porn_detection_cnn/module.py

-# -*- coding:utf-8 -*-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import json
 import math
 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_cnn.processor import load_vocab, preprocess, postprocess
+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(
-    name="porn_detection_cnn",
-    version="1.1.0",
+@moduleinfo(name="porn_detection_cnn",
+            version="1.2.0",
             summary="Baidu's open-source Porn Detection Model.",
             author="baidu-nlp",
             author_email="",
             type="nlp/sentiment_analysis")
 class PornDetectionCNN(hub.NLPPredictionModule):
-    def _initialize(self):
+
+    def __init__(self):
         """
         initialize with the necessary elements
         """
@@ -42,42 +35,6 @@ class PornDetectionCNN(hub.NLPPredictionModule):
 
         self._set_config()
 
-    def context(self, trainable=False):
-        """
-        Get the input ,output and program of the pretrained porn_detection_cnn
-        Args:
-             trainable(bool): whether fine-tune the pretrained parameters of porn_detection_cnn or not
-        Returns:
-             inputs(dict): the input variables of porn_detection_cnn (words)
-             outputs(dict): the output variables of porn_detection_cnn (the sentiment prediction results)
-             main_program(Program): the main_program of porn_detection_cnn 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_cnn@layer_norm_1.tmp_2":
-                outputs = {"class_probs": fetch_targets[0], "sentence_feature": var}
-        return inputs, outputs, program
-
     @serving
     def detection(self, texts=[], data={}, use_gpu=False, batch_size=1):
         """
@@ -135,26 +92,3 @@ class PornDetectionCNN(hub.NLPPredictionModule):
         """
         self.labels = {"porn": 1, "not_porn": 0}
         return self.labels
-
-
-if __name__ == "__main__":
-    porn_detection_cnn = PornDetectionCNN()
-    test_text = ["黄片下载", "打击黄牛党"]
-
-    results = porn_detection_cnn.detection(texts=test_text, batch_size=9)
-    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_cnn.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_cnn/processor.py

-# -*- coding: utf-8 -*-
 import io
+
 import numpy as np