✏️ Fixing typos.

BrikerMan · May 22, 2019 · 8b38efb · 8b38efb
1 parent dce5719
commit 8b38efb
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Showing 2 changed files with 6 additions and 6 deletions.
diff --git a/kashgari/pre_processors/classification_processor.py b/kashgari/pre_processors/classification_processor.py
@@ -39,9 +39,9 @@ def process_x_dataset(self,
                 target = utils.get_list_subset(dataset, subset)
             else:
                 target = dataset
-            numezied_target = self.numerize_token_sequences(target)
+            numerized_samples = self.numerize_token_sequences(target)
             target_maxlen = utils.get_tuple_item(maxlens, index)
-            padded_target = pad_sequences(numezied_target, target_maxlen)
+            padded_target = pad_sequences(numerized_samples, target_maxlen)
             result.append(padded_target)
         if len(result) == 1:
             return result[0]
@@ -58,8 +58,8 @@ def process_y_dataset(self,
                 target = utils.get_list_subset(dataset, subset)
             else:
                 target = dataset
-            numezied_target = self.numerize_label_sequences(target)
-            one_hot_result = to_categorical(numezied_target, len(self.label2idx))
+            numerized_samples = self.numerize_label_sequences(target)
+            one_hot_result = to_categorical(numerized_samples, len(self.label2idx))
             result.append(one_hot_result)
         if len(result) == 1:
             return result[0]

diff --git a/kashgari/pre_processors/labeling_processor.py b/kashgari/pre_processors/labeling_processor.py
@@ -132,9 +132,9 @@ def _process_sequence(self,
                 target = utils.get_list_subset(dataset, subset)
             else:
                 target = dataset
-            numezied_target = numerize_function(target)
+            numerized_samples = numerize_function(target)
             target_maxlen = utils.get_tuple_item(maxlens, index)
-            padded_target = pad_sequences(numezied_target, target_maxlen)
+            padded_target = pad_sequences(numerized_samples, target_maxlen)
             result.append(padded_target)
         if len(result) == 1:
             return result[0]