test 3 version

model.py

@@ -18,39 +18,54 @@ def preprocess(text):
 
 
 def predict(word_before, word_after):
-    prob_list = list(model[(word_before, word_after)].items())
-    print(prob_list)
-    max_prob = max(prob_list, key=lambda pair: pair[1], default=('', 0.0))
-    if max_prob[1] == 0:
-        return 'the'
-    return max_prob[0]
+    prob_list = model[(word_before, word_after)].items()
+    predictions = []
+    total = 0.0
+    for key, value in prob_list:
+        total += value
+        predictions.append(f'{key}:{value}')
+    if total == 0.0:
+        return 'the:1.0'
+    return ' '.join(predictions)
 
 
 with open('train/in.tsv', 'w', encoding='utf-8') as file:
+    print('dekompresja pliku')
     text = lzma.open('train/in.tsv.xz').read().decode('utf-8')
     file.write(text)
 
 with open('train/in.tsv', encoding='utf-8') as file_in, open('train/expected.tsv', encoding='utf-8') as file_expected:
     for index, (line_in, expected) in enumerate(zip(file_in, file_expected)):
         if index % 1000 == 0:
-            print(index)
+            print('zbieranie trigramów', index)
         _, _, _, _, _, _, before, after = line_in.split('\t')
         before, expected, after = preprocess(before), preprocess(expected), preprocess(after)
         words = before + expected + after
         trigrams_list += trigrams(words, pad_right=True, pad_left=True)
 
-for trigram in trigrams_list:
+trigrams_len = len(trigrams_list)
+for index, trigram in enumerate(trigrams_list):
+    if index % 100000 == 0:
+        print('uczenie modelu', index, '/', trigrams_len)
     if not trigram[0] or not trigram[1] or not trigram[2]:
         continue
     model[(trigram[0], trigram[2])][trigram[1]] += 1
+    if index == 999999:
+        break
 
-for words_1_3 in model:
+
+for index, words_1_3 in enumerate(model):
+    if index % 100000 == 0:
+        print('normalizacja', index)
     count = sum(model[words_1_3].values())
     for word_2 in model[words_1_3]:
         model[words_1_3][word_2] /= float(count)
 
 with open('test-A/in.tsv', encoding='utf-8') as file_in, open('test-A/out.tsv', 'w', encoding='utf-8') as file_out:
+    print('zapisywanie wyników')
     for line_in in file_in:
         _, _, _, _, _, _, before, after = line_in.split('\t')
         word_before_in, word_after_in = preprocess(before)[-1], preprocess(after)[0]
         file_out.write(predict(word_before_in, word_after_in) + '\n')
+
+print('koniec')