some tiny fix

demo/seqToseq/dataprovider.py

@@ -24,21 +24,20 @@ def hook(settings, src_dict_path, trg_dict_path, is_generating, file_list,
     # job_mode = 1: training mode
     # job_mode = 0: generating mode
     settings.job_mode = not is_generating
-    settings.src_dict = dict()
-    with open(src_dict_path, "r") as fin:
-        settings.src_dict = {
-            line.strip(): line_count
-            for line_count, line in enumerate(fin)
-        }
-    settings.trg_dict = dict()
-    with open(trg_dict_path, "r") as fin:
-        settings.trg_dict = {
-            line.strip(): line_count
-            for line_count, line in enumerate(fin)
-        }
+
+    def fun(dict_path):
+        out_dict = dict()
+        with open(dict_path, "r") as fin:
+            out_dict = {
+                line.strip(): line_count
+                for line_count, line in enumerate(fin)
+            }
+        return out_dict
+
+    settings.src_dict = fun(src_dict_path)
+    settings.trg_dict = fun(trg_dict_path)
 
     settings.logger.info("src dict len : %d" % (len(settings.src_dict)))
-    settings.sample_count = 0
 
     if settings.job_mode:
         settings.slots = {

doc_theme/static/css/override.css

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 body {
     padding-top: 80px;
     background-image: none !important;
@@ -922,4 +503,4 @@ a, a:focus, a:hover, a:visited {
     background-color: transparent;
     color: #ff9711;
     padding: 0;
-}
\ No newline at end of file
+}

python/paddle/trainer/config_parser.py

@@ -1872,7 +1872,7 @@ class BatchNormLayer(LayerBase):
         image_conf = self.config.inputs[0].image_conf
         parse_image(self.inputs[0].image, input_layer.name, image_conf)
         self.set_cnn_layer(name, image_conf.img_size_y, image_conf.img_size,
-                           image_conf.channels)
+                           image_conf.channels, False)
 
         psize = self.calc_parameter_size(image_conf)
         dims = [1, psize]
@@ -3387,10 +3387,11 @@ def parse_config(config_file, config_arg_str):
     # config = parse_config(configs, "is_predict=1")
     # # then you get config proto object.
     if hasattr(config_file, '__call__'):
-      config_file.func_globals.update(make_config_environment("", config_args))
-      config_file()
+        config_file.func_globals.update(
+            make_config_environment("", config_args))
+        config_file()
     else:
-      execfile(config_file, make_config_environment(config_file, config_args))
+        execfile(config_file, make_config_environment(config_file, config_args))
     for k, v in settings.iteritems():
         if v is None:
             continue