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import sys |
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import time |
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import inspect |
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from transformers import AutoTokenizer |
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from typing import Any |
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import numpy as np |
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from tqdm import tqdm |
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import json |
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import argparse |
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import os |
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def parse_args(): |
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parser = argparse.ArgumentParser(description="Finetune a transformers model on a causal language modeling task") |
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parser.add_argument( |
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"--source_file", |
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type=str, |
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) |
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parser.add_argument( |
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"--max_length", |
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type=int, |
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default=512, |
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) |
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parser.add_argument( |
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"--chunk_size", |
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type=int, |
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default=1024, |
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) |
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parser.add_argument( |
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"--tokenizer_path", |
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type=str, |
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) |
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args = parser.parse_args() |
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return args |
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def get_tokenizer(tokenizer_path): |
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tokenizer = tokenizer = AutoTokenizer.from_pretrained( |
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tokenizer_path, use_fast=not False, trust_remote_code=False |
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) |
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return tokenizer |
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def convert_data_to_id(tokenizer: AutoTokenizer, data: Any): |
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input_ids = tokenizer.encode(data) |
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ids = input_ids |
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ids = np.array(ids, dtype=np.int32) |
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return ids |
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args = parse_args() |
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tokenizer = get_tokenizer(args.tokenizer_path) |
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infile = open(args.source_file, 'r', encoding='utf-8') |
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file_name, _ = os.path.splitext(os.path.basename(args.source_file)) |
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print("source file - ", args.source_file) |
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print('############ Start data reading ###########') |
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idx = 0 |
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max_length = args.max_length |
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chunk_size = args.chunk_size |
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token_ids = np.array([], dtype=np.int32) |
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with open(file_name+'_streaming_'+str(max_length)+'.jsonl', 'w') as f: |
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for line in infile: |
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idx += 1 |
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if idx % 10000 == 0: |
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print('Cur idx - ', idx) |
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try: |
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line = json.loads(line) |
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cur_texts = [] |
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if 'text' in line: |
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temp = line['text'] + "\n" |
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elif 'raw_content_lines' in line: |
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temp = "\n".join(line['raw_content_lines']) + "\n" |
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else: |
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print("error") |
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exit() |
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try: |
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token_id = convert_data_to_id(tokenizer, temp) |
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token_ids = np.concatenate((token_ids, token_id), dtype=np.int32) |
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except UnicodeDecodeError: |
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print('Error line - encoding: ', idx) |
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if len(token_ids) > max_length*chunk_size: |
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while len(token_ids) > max_length: |
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try: |
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temp_text = tokenizer.decode(token_ids[: max_length]) |
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temp_dic = {'text': temp_text} |
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f.write(json.dumps(temp_dic) + "\n") |
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token_ids = token_ids[max_length:] |
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except UnicodeDecodeError: |
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print('Error line - decoding: ', idx) |
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token_ids = token_ids[max_length:] |
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except: |
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print("error source file - ", args.source_file) |
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print('Error line: ', idx) |
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continue |
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infile.close() |
