Upload preprocess.py

preprocess.py

@@ -0,0 +1,276 @@
+import zipfile
+import json
+import os
+import copy
+from shutil import copy2, rmtree
+from zipfile import ZipFile, ZIP_DEFLATED
+
+ontology = {
+    'domains': {
+        'restaurant': {
+            'description': 'find a restaurant to eat',
+            'slots': {
+                'area': {
+                    'description': 'area where the restaurant is located',
+                    'is_categorical': True,
+                    'possible_values': ["centre","north","west","south","east"]
+                },
+                'price range': {
+                    'description': 'price range of the restaurant',
+                    'is_categorical': True,
+                    'possible_values': ["cheap","moderate","expensive"]
+                },
+                'food': {
+                    'description': 'the cuisine of the restaurant',
+                    'is_categorical': False,
+                    'possible_values': ["afghan","african","afternoon tea","asian oriental","australasian","australian","austrian","barbeque","basque","belgian","bistro","brazilian","british","canapes","cantonese","caribbean","catalan","chinese","christmas","corsica","creative","crossover","cuban","danish","eastern european","english","eritrean","european","french","fusion","gastropub","german","greek","halal","hungarian","indian","indonesian","international","irish","italian","jamaican","japanese","korean","kosher","latin american","lebanese","light bites","malaysian","mediterranean","mexican","middle eastern","modern american","modern eclectic","modern european","modern global","molecular gastronomy","moroccan","new zealand","north african","north american","north indian","northern european","panasian","persian","polish","polynesian","portuguese","romanian","russian","scandinavian","scottish","seafood","singaporean","south african","south indian","spanish","sri lankan","steakhouse","swedish","swiss","thai","the americas","traditional","turkish","tuscan","unusual","vegetarian","venetian","vietnamese","welsh","world"]
+                },
+                'name': {
+                    'description': 'name of the restaurant',
+                    'is_categorical': False,
+                    'possible_values': []
+                },
+                'phone': {
+                    'description': 'phone number of the restaurant',
+                    'is_categorical': False,
+                    'possible_values': []
+                },
+                'address': {
+                    'description': 'exact location of the restaurant',
+                    'is_categorical': False,
+                    'possible_values': []
+                },
+                'postcode': {
+                    'description': 'postcode of the restaurant',
+                    'is_categorical': False,
+                    'possible_values': []
+                }
+            }
+        }
+    },
+    'intents': {
+        'inform': {
+            'description': 'inform the value of a slot'
+        },
+        'request': {
+            'description': 'ask for the value of a slot'
+        },
+        'nooffer': {
+            'description': 'inform the user that there is no result satisfies user requirements'
+        }
+    },
+    'state': {
+        'restaurant': {
+            'price range': '',
+            'area': '',
+            'food': ''
+        }
+    },
+    'dialogue_acts': {
+        "categorical": {},
+        "non-categorical": {},
+        "binary": {}
+    }
+}
+
+
+def convert_da(utt, da):
+    global ontology
+    converted_da = {
+        'binary': [],
+        'categorical': [],
+        'non-categorical': []
+    }
+
+    for intent, svs in da.items():
+        assert intent in ontology['intents']
+        if intent == 'nooffer':
+            assert svs == [['none', 'none']]
+            converted_da['binary'].append({
+                'intent': intent,
+                'domain': 'restaurant',
+                'slot': '',
+            })
+            continue
+
+        for s, v in svs:
+            if 'care' in v:
+                assert v == 'dontcare', print(v)
+            assert s == s.lower()
+            if s == 'pricerange':
+                s = 'price range'
+            v = v
+            if intent == 'request':
+                assert v == '?'
+                converted_da['binary'].append({
+                    'intent': intent,
+                    'domain': 'restaurant',
+                    'slot': s
+                })
+                continue
+
+            if s in ['price range', 'area']:
+                assert v.lower() in ontology['domains']['restaurant']['slots'][s]['possible_values'] + ['dontcare'], print(s, v)
+                converted_da['categorical'].append({
+                    'intent': intent,
+                    'domain': 'restaurant',
+                    'slot': s,
+                    'value': v
+                })
+
+            else:
+                # non-categorical
+                start_ch = utt.lower().find(v.lower())
+
+                if start_ch == -1:
+                    if not v == 'dontcare':
+                        print('non-categorical slot value not found')
+                        print('value: {}'.format(v))
+                        print('sentence: {}'.format(utt))
+                        print()
+
+                    converted_da['non-categorical'].append({
+                        'intent': intent,
+                        'domain': 'restaurant',
+                        'slot': s,
+                        'value': v,
+                    })
+                else:
+                    converted_da['non-categorical'].append({
+                        'intent': intent,
+                        'domain': 'restaurant',
+                        'slot': s,
+                        'value': utt[start_ch: start_ch + len(v)],
+                        'start': start_ch,
+                        'end': start_ch + len(v)
+                    })
+                    assert utt[start_ch: start_ch + len(v)].lower() == v.lower()
+
+    return converted_da
+
+
+def convert_state(slu):
+    global ontology
+    ret_state = copy.deepcopy(ontology['state'])
+    for da in slu:
+        if da['act'] != 'inform':
+            continue
+
+        for s, v in da['slots']:
+            s = s if s != 'pricerange' else 'price range'
+            if s not in ret_state['restaurant']:
+                print('slot not in state')
+                print(da)
+                print()
+                continue
+            ret_state['restaurant'][s] = v
+
+    return ret_state
+
+
+def preprocess():
+    # use convlab-2 version camrest which already has dialog act annotation
+    original_data_dir = '../../camrest/'
+    new_data_dir = 'data'
+    
+    os.makedirs(new_data_dir, exist_ok=True)
+
+    copy2(f'{original_data_dir}/db/CamRestDB.json', new_data_dir)
+    
+    dataset = 'camrest'
+    domain = 'restaurant'
+    splits = ['train', 'validation', 'test']
+    dialogues_by_split = {split:[] for split in splits}
+    
+    for split in ['train', 'val', 'test']:
+        data = json.load(zipfile.ZipFile(os.path.join(original_data_dir, f'{split}.json.zip'), 'r').open(f'{split}.json'))
+        if split == 'val':
+            split = 'validation'
+
+        cur_domains = [domain]
+
+        for ori_dialog in data:
+            dialogue_id = f'{dataset}-{split}-{len(dialogues_by_split[split])}'
+
+            goal = {
+                'description': ori_dialog['goal']['text'],
+                'inform': {'restaurant': {}},
+                'request': {'restaurant': {}}
+            }
+            for slot, value in ori_dialog['goal']['info'].items():
+                if slot == 'pricerange':
+                    slot = 'price range'
+                goal['inform'][domain][slot] = value
+            for slot in ori_dialog['goal']['reqt']:
+                if slot == 'pricerange':
+                    slot = 'price range'
+                goal['request'][domain][slot] = ''
+
+            dialogue = {
+                'dataset': dataset,
+                'data_split': split,
+                'dialogue_id': dialogue_id,
+                'original_id': ori_dialog['dialogue_id'],
+                'domains': cur_domains,
+                'goal': goal,
+                'finished': ori_dialog['finished'],
+                'turns': []
+            }
+
+            for turn in ori_dialog['dial']:
+                usr_text = turn['usr']['transcript']
+                usr_da = turn['usr']['dialog_act']
+
+                sys_text = turn['sys']['sent']
+                sys_da = turn['sys']['dialog_act']
+
+                cur_state = convert_state(turn['usr']['slu'])
+                cur_user_da = convert_da(usr_text, usr_da)
+
+                usr_turn = {
+                    'speaker': 'user',
+                    'utterance': usr_text,
+                    'utt_idx': len(dialogue['turns']),
+                    'dialogue_acts': cur_user_da,
+                    'state': cur_state,
+                }
+
+                sys_turn = {
+                    'speaker': 'system',
+                    'utterance': sys_text,
+                    'utt_idx': len(dialogue['turns'])+1,
+                    'dialogue_acts': convert_da(sys_text, sys_da),
+                }
+
+                dialogue['turns'].append(usr_turn)
+                dialogue['turns'].append(sys_turn)
+
+            for turn in dialogue['turns']:
+                speaker = turn['speaker']
+                dialogue_acts = turn['dialogue_acts']
+
+                # add to dialogue_acts dictionary in the ontology
+                for da_type in dialogue_acts:
+                    das = dialogue_acts[da_type]
+                    for da in das:
+                        ontology["dialogue_acts"][da_type].setdefault((da['intent'], da['domain'], da['slot']), {})
+                        ontology["dialogue_acts"][da_type][(da['intent'], da['domain'], da['slot'])][speaker] = True
+            dialogues_by_split[split].append(dialogue)
+
+    dialogues = []
+    for split in splits:
+        dialogues += dialogues_by_split[split]
+    for da_type in ontology['dialogue_acts']:
+        ontology["dialogue_acts"][da_type] = sorted([str({'user': speakers.get('user', False), 'system': speakers.get('system', False), 'intent':da[0],'domain':da[1], 'slot':da[2]}) for da, speakers in ontology["dialogue_acts"][da_type].items()])
+    json.dump(dialogues[:10], open(f'dummy_data.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
+    json.dump(ontology, open(f'{new_data_dir}/ontology.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
+    json.dump(dialogues, open(f'{new_data_dir}/dialogues.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False)
+    with ZipFile('data.zip', 'w', ZIP_DEFLATED) as zf:
+        for filename in os.listdir(new_data_dir):
+            zf.write(f'{new_data_dir}/{filename}')
+    rmtree(new_data_dir)
+    return dialogues, ontology
+
+
+if __name__ == '__main__':
+    preprocess()