| | import argparse |
| | import os |
| | import shutil |
| | from transformers import T5Tokenizer |
| | from tqdm import tqdm |
| |
|
| |
|
| | def parse(): |
| | parser = argparse.ArgumentParser() |
| |
|
| | parser.add_argument("--input-dir", type=str) |
| | parser.add_argument("--output-dir", type=str) |
| | parser.add_argument("--max-src-length", type=int, default=512) |
| | parser.add_argument("--max-dialogue-history-len", type=int, default=256) |
| | parser.add_argument("--tokenizer-path", type=str) |
| | parser.add_argument("--special-tokens-file", type=str, default=None) |
| | parser.add_argument( |
| | "--truncate-side", type=str, default="left", choices=["left", "right"] |
| | ) |
| |
|
| | return parser.parse_args() |
| |
|
| |
|
| | def truncate(args): |
| | left_tokenizer = T5Tokenizer.from_pretrained( |
| | args.tokenizer_path, truncate_side="left" |
| | ) |
| | right_tokenizer = T5Tokenizer.from_pretrained( |
| | args.tokenizer_path, truncate_side="right" |
| | ) |
| | tokenizer = T5Tokenizer.from_pretrained(args.tokenizer_path) |
| |
|
| | if args.special_tokens_file is not None: |
| | with open(args.special_tokens_file, "r") as reader: |
| | special_tokens_dict = { |
| | "additional_special_tokens": [ |
| | token.strip() for token in reader.readlines() |
| | ] |
| | } |
| |
|
| | left_tokenizer.add_special_tokens(special_tokens_dict) |
| | right_tokenizer.add_special_tokens(special_tokens_dict) |
| | tokenizer.add_special_tokens(special_tokens_dict) |
| |
|
| | def normalize(x): |
| | return tokenizer.decode(tokenizer(x).input_ids[:-1]) |
| |
|
| | def divide_chunks(src): |
| | prefix, postfix = src.split("]", 1) |
| | prefix = prefix + "]" |
| |
|
| | knowledge_start_index = postfix.index("[EK]") |
| | dialogue = postfix[: knowledge_start_index - 1] |
| | knowledge_and_instruction = postfix[knowledge_start_index - 1 :] |
| |
|
| | instruction_start_index = knowledge_and_instruction.rfind("[C]") |
| | knowledge = knowledge_and_instruction[: instruction_start_index - 1] |
| | instruction = knowledge_and_instruction[instruction_start_index - 1 :] |
| |
|
| | return prefix, dialogue, knowledge, instruction |
| |
|
| | def token_num(x): |
| | return len(tokenizer.tokenize(x)) |
| |
|
| | min_knowledge_len = token_num(" [EK] None") |
| |
|
| | if not os.path.exists(args.output_dir): |
| | os.makedirs(args.output_dir) |
| |
|
| | print(f" {os.path.basename(args.input_dir)} ".center(70, "=")) |
| |
|
| | for filename in os.listdir(args.input_dir): |
| | if not filename.endswith(".src"): |
| | filepath = os.path.join(args.input_dir, filename) |
| | if not os.path.exists(os.path.join(args.output_dir, filename)): |
| | if os.path.isfile(filepath): |
| | shutil.copyfile( |
| | os.path.join(args.input_dir, filename), |
| | os.path.join(args.output_dir, filename), |
| | ) |
| | else: |
| | shutil.copytree( |
| | os.path.join(args.input_dir, filename), |
| | os.path.join(args.output_dir, filename), |
| | ) |
| | else: |
| | dialogue_cut_num = 0 |
| | knowledge_cut_num = 0 |
| | cut_token_num = 0 |
| | |
| | with open(os.path.join(args.input_dir, filename), "r") as reader, open( |
| | os.path.join(args.output_dir, filename), "w" |
| | ) as writer: |
| | for line in tqdm(reader.readlines()): |
| | src = line.strip() |
| | src = normalize(src) |
| |
|
| | prefix, dialogue, knowledge, instruction = divide_chunks(src) |
| |
|
| | prefix_token_num = token_num(prefix) |
| | dialogue_token_num = token_num(dialogue) |
| | knowledge_token_num = token_num(knowledge) |
| | instruction_token_num = token_num(instruction) |
| |
|
| | assert ( |
| | args.max_src_length >= prefix_token_num + instruction_token_num |
| | ) |
| |
|
| | origin_src_token_num = ( |
| | prefix_token_num |
| | + dialogue_token_num |
| | + knowledge_token_num |
| | + instruction_token_num |
| | ) |
| | |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| |
|
| | if origin_src_token_num > args.max_src_length: |
| | left_token_num = ( |
| | args.max_src_length |
| | - prefix_token_num |
| | - instruction_token_num |
| | ) |
| | max_dialogue_token_num = min( |
| | max( |
| | args.max_dialogue_history_len, |
| | left_token_num - knowledge_token_num, |
| | ), |
| | left_token_num - min_knowledge_len, |
| | ) |
| |
|
| | |
| | if dialogue_token_num > max_dialogue_token_num: |
| | |
| | truncate_tokenizer = ( |
| | left_tokenizer |
| | if args.truncate_side == "left" |
| | else right_tokenizer |
| | ) |
| | dialogue_ids = truncate_tokenizer( |
| | dialogue, |
| | max_length=max_dialogue_token_num |
| | + 1, |
| | truncation=True, |
| | ).input_ids |
| |
|
| | dialogue = tokenizer.decode(dialogue_ids[:-1]) |
| | dialogue_token_num = max_dialogue_token_num |
| | dialogue_cut_num += 1 |
| |
|
| | |
| |
|
| | if knowledge_token_num > left_token_num - dialogue_token_num: |
| | |
| | knowledge_ids = right_tokenizer( |
| | knowledge, |
| | max_length=left_token_num - dialogue_token_num + 1, |
| | truncation=True, |
| | ).input_ids |
| |
|
| | knowledge = tokenizer.decode(knowledge_ids[:-1]) |
| |
|
| | knowledge = " " + knowledge |
| |
|
| | knowledge_token_num = left_token_num - dialogue_token_num |
| | knowledge_cut_num += 1 |
| |
|
| | |
| | |
| | |
| |
|
| | src = ( |
| | prefix.strip() |
| | + " " |
| | + dialogue.strip() |
| | + " " |
| | + knowledge.strip() |
| | + " " |
| | + instruction.strip() |
| | ) |
| |
|
| | src_token_num = token_num(src) |
| |
|
| | |
| |
|
| | cut_token_num += origin_src_token_num - src_token_num |
| |
|
| | prefix, dialogue, knowledge, instruction = divide_chunks(src) |
| |
|
| | prefix_token_num = token_num(prefix) |
| | dialogue_token_num = token_num(dialogue) |
| | knowledge_token_num = token_num(knowledge) |
| | instruction_token_num = token_num(instruction) |
| |
|
| | writer.write(src + "\n") |
| |
|
| | print(f" {filename} ".center(40, "-")) |
| | print(f"dialogue cut num: {dialogue_cut_num}") |
| | print(f"knowledge cut num: {knowledge_cut_num}") |
| | print(f"token cut num: {cut_token_num}") |
| |
|
| |
|
| | if __name__ == "__main__": |
| | truncate(parse()) |
| |
|