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import json
import os
import random
from clean_diag import *
file_name = "modernfamily"
def get_concat_diags(root="diags_raw"):
diags = []
for d in os.listdir(root):
for file in os.listdir(os.path.join(root, d)):
if file.endswith(".json"):
for item in json.load(open(os.path.join(root, d, file), encoding='utf-8')):
diags.append({"id": "episode_{}_chunk_{}".format(item['episode_idx'], item['chunk_idx']),
"conversations": item['diag']})
print(f"[Whole diags length]: {len(diags)}")
return diags
def get_role_list(diags):
role_dict = {}
for diag in diags:
for conv in diag['conversations']:
role = conv['from']
if role not in role_dict:
role_dict[role] = 1
else:
role_dict[role] += 1
sorted_role_dict = {}
for k, v in sorted(role_dict.items(), key=lambda x: (-x[1], x[0])):
sorted_role_dict[k] = v
# filter out roles whose conversation is less than 50
role_list = []
for role in role_dict:
if role_dict[role] >= 40:
role_list.append(role)
role_pinyin = {role: "".join(role) for role in role_list}
return role_pinyin, sorted_role_dict
def extract_conversations_between_two_role(conversations, role1, role2):
def maybe_append_conversation(conv, role1, role2):
roles = set([item['from'] for item in conv])
if role1 in roles and role2 in roles and len(roles) == 2:
return True
return False
new_conversations = []
start_flag = False
start_idx = 0
end_idx = 0
for i, conversation in enumerate(conversations):
if not start_flag and (conversation['from'] == role1 or conversation['from'] == role2):
start_flag = True
start_idx = i
end_idx = i
continue
if start_flag:
if conversation['from'] == role1 or conversation['from'] == role2:
end_idx = i
continue
elif maybe_append_conversation(conversations[start_idx:end_idx+1], role1, role2):
new_conversations.append(conversations[start_idx:end_idx+1])
start_flag = False
return new_conversations
def extract_diag_between_two_role(diags, role1, role2):
new_diags = []
for item in diags:
new_conversations = extract_conversations_between_two_role(item['conversations'], role1, role2)
if len(new_conversations) > 0:
for i, conversation in enumerate(new_conversations):
new_diags.append({"id": "{}_index_{}".format(item["id"], i), "conversations": conversation})
return new_diags
def split_train_and_dev(data, prob=0.8):
random.shuffle(data)
index = max(int(len(data)*prob), 1)
train_data = data[:index]
dev_data = data[index:]
return train_data, dev_data
def split_diag(data, max_length=2048):
new_data = []
for item in data:
id = item["id"]
conversations = item['conversations']
count_len = [0 for _ in range(len(conversations) + 1)] # [0, len(1st conv), len(1st + 2nd conv), ...]
count = 0 # the number of final parts
conversations = remove_blank_value_for_conv(conversations)
for i, conv in enumerate(conversations):
if i == 0:
count_len[i + 1] = len("{}\n{}".format(conv['from'], conv['value']))
continue
count_len[i + 1] = count_len[i] + len("{}\n{}".format(conv['from'], conv['value']))
flag = False
for start_id in range(0, i + 1):
if count_len[i + 1] - count_len[start_id] < max_length:
flag = True
break
if flag:
new_conv = conversations[start_id:i + 1]
new_id = id + f"_part{count}"
count += 1
new_data.append({"id": new_id, "conversations": new_conv})
return new_data
def extract_diag_for_target_from_role_conv(diags, role_pair_id, target_role, target_role_pinyin, input_role, input_role_pinyin):
new_diags = []
for item in diags:
if item['conversations'][-1]['from'] == target_role:
new_diags.append(item)
item['target_role'] = target_role
item['target_role_short'] = target_role_pinyin
item['input_role'] = input_role
item['input_role_short'] = input_role_pinyin
item['role_pair_id'] = role_pair_id[target_role][input_role]
return new_diags
if __name__ == "__main__":
# Step2-0: concat all diags
diags = get_concat_diags(root='diags_raw')
diags = clean_diag(diags)
json.dump(diags, open(f"{file_name}_diags.json", 'w', encoding='utf-8'), ensure_ascii=False, indent=4)
# Step2-1: get filtered role list and its pinyin
role_pinyin, sorted_role_dict = get_role_list(diags)
role1 = "Phil"
role1_pinyin = role_pinyin[role1]
role_pinyin.pop(role1)
print(f"[Role list length]: {len(role_pinyin)}")
os.makedirs("diags_two_role_phil/configs", exist_ok=True)
json.dump(role_pinyin, open("diags_two_role_phil/configs/role_list.json", 'w', encoding='utf-8'), ensure_ascii=False, indent=4)
json.dump(sorted_role_dict, open("diags_two_role_phil/configs/role_dict.json", 'w', encoding='utf-8'), ensure_ascii=False, indent=4)
# Step2-2 ~ 4
removed_role = []
for role2 in role_pinyin:
# Step 2-2: extract diag between two role
role2_pinyin = role_pinyin[role2]
new_diags = extract_diag_between_two_role(diags, role1, role2)
new_diags = clean_diag(new_diags)
if len(new_diags) < 20:
removed_role.append(role2)
continue
output_dir = f'diags_two_role_phil/{role1_pinyin}_{role2_pinyin}'
os.makedirs(output_dir, exist_ok=True)
json.dump(new_diags, open(os.path.join(output_dir, f'{file_name}_diags_{role1_pinyin}_{role2_pinyin}.json'), 'w', encoding='utf-8'), ensure_ascii=False, indent=4)
print(f"[Diags between {output_dir}]:", len(new_diags))
# Step 2-3: split training set and validation set
train_data, dev_data = split_train_and_dev(new_diags, prob=0.8)
json.dump(train_data, open(os.path.join(output_dir, f'{file_name}_diags_{role1_pinyin}_{role2_pinyin}_train.json'), "w", encoding="utf-8"), ensure_ascii=False, indent=4)
json.dump(dev_data, open(os.path.join(output_dir, f'{file_name}_diags_{role1_pinyin}_{role2_pinyin}_dev.json'), "w", encoding="utf-8"), ensure_ascii=False, indent=4)
print("[Split train and dev] {} - {}: {}".format(role1, role2, len(new_diags)), '->', len(train_data), len(dev_data))
# Step 2-4: split diags with sliding window
new_train_data = split_diag(train_data, max_length=512)
new_train_data = clean_diag_with_repeated(new_train_data)
new_dev_data = split_diag(dev_data, max_length=512)
new_dev_data = clean_diag_with_repeated(new_dev_data)
json.dump(new_train_data, open(os.path.join(output_dir, f"{file_name}_diags_{role1_pinyin}_{role2_pinyin}_L512_train.json"), "w", encoding='utf-8'), ensure_ascii=False, indent=4)
json.dump(new_dev_data, open(os.path.join(output_dir, f"{file_name}_diags_{role1_pinyin}_{role2_pinyin}_L512_dev.json"), "w", encoding='utf-8'), ensure_ascii=False, indent=4)
print("[Split diag with sliding window] {}, {}".format(len(new_train_data), len(new_dev_data)))
for role in removed_role: role_pinyin.pop(role)
# Step 2-5: extract diag for target role
role_pair_id = {role1: {role2: i+1 for i, role2 in enumerate(role_pinyin)}}
json.dump(role_pair_id, open("diags_two_role_phil/configs/role_pair_id.json", 'w', encoding='utf-8'), ensure_ascii=False, indent=4)
for role2 in role_pinyin:
role2_pinyin = role_pinyin[role2]
input_dir = f'diags_two_role_phil/{role1_pinyin}_{role2_pinyin}'
input_file = f"{file_name}_diags_{role1_pinyin}_{role2_pinyin}_L512_train.json"
output_file = f"{file_name}_diags_{role1_pinyin}_{role2_pinyin}_{role1_pinyin}_response_L512_train.json"
diags = json.load(open(os.path.join(input_dir, input_file), encoding='utf-8'))
new_diags = extract_diag_for_target_from_role_conv(diags, role_pair_id, role1, role1_pinyin, role2, role2_pinyin)
new_diags = clean_diag(new_diags)
new_diags = remove_diags_without_target_role_and_input_role(new_diags)
new_diags = re_id_to_avoid_repeat(new_diags)
json.dump(new_diags, open(os.path.join(input_dir, output_file), 'w', encoding='utf-8'), ensure_ascii=False, indent=4)
input_file = f"{file_name}_diags_{role1_pinyin}_{role2_pinyin}_L512_dev.json"
output_file = f"{file_name}_diags_{role1_pinyin}_{role2_pinyin}_{role1_pinyin}_response_L512_dev.json"
diags = json.load(open(os.path.join(input_dir, input_file), encoding='utf-8'))
new_diags = extract_diag_for_target_from_role_conv(diags, role_pair_id, role1, role1_pinyin, role2, role2_pinyin)
new_diags = clean_diag_with_repeated(new_diags)
new_diags = remove_diags_without_target_role_and_input_role(new_diags)
new_diags = re_id_to_avoid_repeat(new_diags)
json.dump(new_diags, open(os.path.join(input_dir, output_file), 'w', encoding='utf-8'), ensure_ascii=False, indent=4) |