




import argparse
import logging
import pickle
import random
import time

import numpy as np

from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer


logging.basicConfig(
    format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
)
__A        =    logging.getLogger(__name__)







def 			lowerCamelCase_		(       )     ->       List[str]:





				"""simple docstring"""


				__lowerCamelCase		       =    argparse.ArgumentParser(
				    description='Preprocess the data to avoid re-doing it several times by (tokenization + token_to_ids).'      )
				parser.add_argument('--file_path' ,     type=UpperCamelCase__ ,     default='data/dump.txt' ,     help='The path to the data.'      )
				parser.add_argument('--tokenizer_type' ,     type=UpperCamelCase__ ,     default='bert' ,     choices=['bert', 'roberta', 'gpt2']      )
				parser.add_argument('--tokenizer_name' ,     type=UpperCamelCase__ ,     default='bert-base-uncased' ,     help='The tokenizer to use.'      )
				parser.add_argument('--dump_file' ,     type=UpperCamelCase__ ,     default='data/dump' ,     help='The dump file prefix.'      )
				__lowerCamelCase		       =    parser.parse_args()

				logger.info(F"""Loading Tokenizer ({args.tokenizer_name})"""      )
				if args.tokenizer_type == "bert":
								__lowerCamelCase		       =    BertTokenizer.from_pretrained(args.tokenizer_name      )
								__lowerCamelCase		       =    tokenizer.special_tokens_map['cls_token']  # `[CLS]`
								__lowerCamelCase		       =    tokenizer.special_tokens_map['sep_token']  # `[SEP]`
				elif args.tokenizer_type == "roberta":
								__lowerCamelCase		       =    RobertaTokenizer.from_pretrained(args.tokenizer_name      )
								__lowerCamelCase		       =    tokenizer.special_tokens_map['cls_token']  # `<s>`
								__lowerCamelCase		       =    tokenizer.special_tokens_map['sep_token']  # `</s>`
				elif args.tokenizer_type == "gpt2":
								__lowerCamelCase		       =    GPTaTokenizer.from_pretrained(args.tokenizer_name      )
								__lowerCamelCase		       =    tokenizer.special_tokens_map['bos_token']  # `<|endoftext|>`
								__lowerCamelCase		       =    tokenizer.special_tokens_map['eos_token']  # `<|endoftext|>`

				logger.info(F"""Loading text from {args.file_path}"""      )
				with open(args.file_path ,     'r' ,     encoding='utf8'      ) as fp:
								__lowerCamelCase		       =    fp.readlines()

				logger.info('Start encoding'      )
				logger.info(F"""{len(UpperCamelCase__      )} examples to process."""      )

				__lowerCamelCase		       =    []
				__lowerCamelCase		       =    0
				__lowerCamelCase		       =    1_0000
				__lowerCamelCase		       =    time.time()
				for text in data:
								__lowerCamelCase		       =    F"""{bos} {text.strip()} {sep}"""
								__lowerCamelCase		       =    tokenizer.encode(UpperCamelCase__ ,     add_special_tokens=UpperCamelCase__      )
								rslt.append(UpperCamelCase__      )

								iter += 1
								if iter % interval == 0:
												__lowerCamelCase		       =    time.time()
												logger.info(F"""{iter} examples processed. - {(end-start):.2f}s/{interval}expl"""      )
												__lowerCamelCase		       =    time.time()
				logger.info('Finished binarization'      )
				logger.info(F"""{len(UpperCamelCase__      )} examples processed."""      )

				__lowerCamelCase		       =    F"""{args.dump_file}.{args.tokenizer_name}.pickle"""
				__lowerCamelCase		       =    tokenizer.vocab_size
				if vocab_size < (1 << 16):
								__lowerCamelCase		       =    [np.uintaa(UpperCamelCase__      ) for d in rslt]
				else:
								__lowerCamelCase		       =    [np.intaa(UpperCamelCase__      ) for d in rslt]
				random.shuffle(rslt_      )
				logger.info(F"""Dump to {dp_file}"""      )
				with open(UpperCamelCase__ ,     'wb'      ) as handle:
								pickle.dump(rslt_ ,     UpperCamelCase__ ,     protocol=pickle.HIGHEST_PROTOCOL      )


if __name__ == "__main__":
					main()



'''simple docstring'''

def 			__UpperCamelCase       (   UpperCAmelCase     ):
 lowercase__				:    List[str]  =					0
 while num > 0:
  digit_sum += num % 10
  num //= 10
 return digit_sum
def 			__UpperCamelCase       (   UpperCAmelCase = 100     ):
 lowercase__				:    Dict  =					1
 lowercase__				:    Optional[int]  =					2

 for i in range(2		,     max_n + 1     ):
  lowercase__				:    List[str]  =					pre_numerator
  lowercase__				:    Optional[Any]  =					2 * i // 3 if i % 3 == 0 else 1
  lowercase__				:    Union[str, Any]  =					cur_numerator
  lowercase__				:    int  =					e_cont * pre_numerator + temp

 return sum_digits(UpperCAmelCase     )


if __name__ == "__main__":
  print(F'{solution() = }')

