





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
)
__lowerCamelCase			:	List[Any]					    =	logging.getLogger(__name__)



def 						A_							(	)		->					List[str]:
 UpperCamelCase      :   List[str]			      =  argparse.ArgumentParser(
     description="Preprocess the data to avoid re-doing it several times by (tokenization + token_to_ids)."	)
 parser.add_argument("--file_path"				,  type=_lowerCAmelCase				,  default="data/dump.txt"				,  help="The path to the data."	)
 parser.add_argument("--tokenizer_type"				,  type=_lowerCAmelCase				,  default="bert"				,  choices=["bert", "roberta", "gpt2"]	)
 parser.add_argument("--tokenizer_name"				,  type=_lowerCAmelCase				,  default="bert-base-uncased"				,  help="The tokenizer to use."	)
 parser.add_argument("--dump_file"				,  type=_lowerCAmelCase				,  default="data/dump"				,  help="The dump file prefix."	)
 UpperCamelCase      :   Any			      =  parser.parse_args()

 logger.info(F"""Loading Tokenizer ({args.tokenizer_name})"""	)
 if args.tokenizer_type == "bert":
  UpperCamelCase      :   int			      =  BertTokenizer.from_pretrained(args.tokenizer_name	)
  UpperCamelCase      :   List[str]			      =  tokenizer.special_tokens_map["cls_token"]  # `[CLS]`
  UpperCamelCase      :   str			      =  tokenizer.special_tokens_map["sep_token"]  # `[SEP]`
 elif args.tokenizer_type == "roberta":
  UpperCamelCase      :   List[str]			      =  RobertaTokenizer.from_pretrained(args.tokenizer_name	)
  UpperCamelCase      :   Any			      =  tokenizer.special_tokens_map["cls_token"]  # `<s>`
  UpperCamelCase      :   List[Any]			      =  tokenizer.special_tokens_map["sep_token"]  # `</s>`
 elif args.tokenizer_type == "gpt2":
  UpperCamelCase      :   Optional[int]			      =  GPTaTokenizer.from_pretrained(args.tokenizer_name	)
  UpperCamelCase      :   Optional[int]			      =  tokenizer.special_tokens_map["bos_token"]  # `<|endoftext|>`
  UpperCamelCase      :   int			      =  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:
  UpperCamelCase      :   Tuple			      =  fp.readlines()

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

 UpperCamelCase      :   Dict			      =  []
 UpperCamelCase      :   str			      =  0
 UpperCamelCase      :   Optional[Any]			      =  1_0000
 UpperCamelCase      :   str			      =  time.time()
 for text in data:
  UpperCamelCase      :   Tuple			      =  F"""{bos} {text.strip()} {sep}"""
  UpperCamelCase      :   str			      =  tokenizer.encode(_lowerCAmelCase				,  add_special_tokens=_lowerCAmelCase	)
  rslt.append(_lowerCAmelCase	)

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

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


if __name__ == "__main__":
    main()







def 						A_							(	_lowerCAmelCase				,  _lowerCAmelCase	)		->					Optional[int]:
 UpperCamelCase      :   List[Any]			      =  [1]
 for i in range(2				,  _lowerCAmelCase	):
  factorials.append(factorials[-1] * i	)
 assert 0 <= k < factorials[-1] * n, "k out of bounds"

 UpperCamelCase      :   Tuple			      =  []
 UpperCamelCase      :   str			      =  list(range(_lowerCAmelCase	)	)

 # Find permutation
 while factorials:
  UpperCamelCase      :   int			      =  factorials.pop()
  UpperCamelCase      ,       UpperCamelCase      :   int			      =  divmod(_lowerCAmelCase				,  _lowerCAmelCase	)
  permutation.append(elements[number]	)
  elements.remove(elements[number]	)
 permutation.append(elements[0]	)

 return permutation


if __name__ == "__main__":
    import doctest

    doctest.testmod()
