update

Author: bob7783

nlp_class3/cnn_toxic.py

@@ -56,12 +56,6 @@
 possible_labels = ["toxic", "severe_toxic", "obscene", "threat", "insult", "identity_hate"]
 targets = train[possible_labels].values
 
-print("max sequence length:", max(len(s) for s in sentences))
-print("min sequence length:", min(len(s) for s in sentences))
-s = sorted(len(s) for s in sentences)
-print("median sequence length:", s[len(s) // 2])
-
-
 
 
 # convert the sentences (strings) into integers
@@ -71,6 +65,12 @@
 # print("sequences:", sequences); exit()
 
 
+print("max sequence length:", max(len(s) for s in sequences))
+print("min sequence length:", min(len(s) for s in sequences))
+s = sorted(len(s) for s in sequences)
+print("median sequence length:", s[len(s) // 2])
+
+
 # get word -> integer mapping
 word2idx = tokenizer.word_index
 print('Found %s unique tokens.' % len(word2idx))