Update DiaBLa.py

DiaBLa.py

@@ -67,100 +67,7 @@ class Diabla(datasets.GeneratorBasedBuilder):
                     'norm': datasets.Value('string'),
                     'mt': datasets.Value('string'),
                     'ref': datasets.Value('string'),
-                    'utterance_meta': datasets.features.Sequence(
-                        {
-                            'eval-judgment': ClassLabel(num_classes=3, names=['poor', 'medium', 'perfect']),
-                            'eval-verbatim': datasets.Value('string'),
-                            'eval-problems': datasets.features.Sequence(
-                                [
-                                  ClassLabel(num_classes=6, names=['coherence', 'grammar', 'meaning', 'word choice', 'style', 'other'])
-                                ]
-                              ),
-                             'lang': ClassLabel(num_classes=2, names=['english', 'french']),
-                        }
-                    ),
-                    'dialogue_meta': datasets.features.Sequence(
-                        {
-                            'start_time': datasets.Value('string'), 
-                            'end_time' : datasets.Value('string'),
-                            'translation_model': datasets.Value('string'),
-                            'final_evaluation_user1': datasets.features.Sequence(
-                                {
-                                    'style': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'coherence': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'grammaticality': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'meaning': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'word_choice': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent'])
-                                 }
-                             ),
-                            'final_evaluation_user2': datasets.features.Sequence(
-                                {
-                                    'style': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'coherence': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'grammaticality': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'meaning': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent']),
-                                    'word_choice': ClassLabel(num_classes=4, names=['poor', 'average', 'good', 'excellent'])
-                                 }
-                             ),
-                            'scenario': datasets.features.Sequence(
-                                [
-                                  [
-                                     datasets.Value("string")
-                                  ]                                                                            
-                                ]
-                            ),
-                            'user1': datasets.features.Sequence(
-                                {
-                                   'rolenum': datasets.Value('int64'),
-                                   'role': datasets.features.Sequence(
-                                       [ 
-                                           datasets.Value('string')
-                                       ]
-                                   ),
-                                   'initiated_dialogue': datasets.Value('bool'),
-                                   'turn_number': datasets.Value('int64'),
-                                   'lang': ClassLabel(num_classes=2, names=['english', 'french']),
-                                }
-                            ),
-                            'user2': datasets.features.Sequence(
-                                {
-                                   'rolenum': datasets.Value('int64'),
-                                   'role': datasets.features.Sequence(
-                                       [ 
-                                           datasets.Value('string')
-                                       ]
-                                   ),
-                                   'initiated_dialogue': datasets.Value('bool'),
-                                   'turn_number': datasets.Value('int64'),
-                                   'lang': ClassLabel(num_classes=2, names=['english', 'french']),
-                                }
-                            )
-                        }
-                    ),
-                    'dialogue_history': datasets.features.Sequence(
-                        [
-                            datasets.features.Sequence(
-                                {
-                                    'id': datasets.Value('string'),
-                                    'orig': datasets.Value('string'),
-                                    'norm': datasets.Value('string'),
-                                    'mt': datasets.Value('string'),
-                                    'ref': datasets.Value('string'),
-                                    'utterance_meta': datasets.features.Sequence(
-                                        {
-                                            'eval-judgment': ClassLabel(num_classes=3, names=['poor', 'medium', 'perfect']),
-                                             'eval-verbatim': datasets.Value("string"),
-                                             'eval-problems': datasets.features.Sequence(
-                                                 [
-                                                     ClassLabel(num_classes=6, names=['coherence', 'grammar', 'meaning', 'word choice', 'style', 'other'])
-                                                 ]
-                                              ),
-                                             'lang': ClassLabel(num_classes=2, names=['english', 'french']),
-                                        }
-                                    ),
-                             }),
-                        ]
-                    )
+                    
                 }
             ),
             # TODO?
@@ -225,11 +132,11 @@ class Diabla(datasets.GeneratorBasedBuilder):
                         'mt': mt_text,
                         'id': id_,
                         'ref': reference_text,
-                        'utterance_meta': utterance_info
+                        #'utterance_meta': utterance_info
                     }
                     
                     # add to history (without dialogue info and history)
                     dialogue_history.append(utterance_instance.copy()) 
-                    utterance_instance['dialogue_meta'] = dialogue_info
-                    utterance_instance['dialogue_history'] = dialogue_history
+                    #utterance_instance['dialogue_meta'] = dialogue_info
+                    #utterance_instance['dialogue_history'] = dialogue_history
                     yield id_, utterance_instance