

'''simple docstring'''

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

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

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

  SCREAMING_SNAKE_CASE:List[Any]						      =					[]
  SCREAMING_SNAKE_CASE:int						      =					0
  SCREAMING_SNAKE_CASE:int						      =					10000
  SCREAMING_SNAKE_CASE:int						      =					time.time()
  for text in data:
    SCREAMING_SNAKE_CASE:List[str]						      =					F'''{bos} {text.strip()} {sep}'''
    SCREAMING_SNAKE_CASE:Tuple						      =					tokenizer.encode(snake_case      ,       add_special_tokens=snake_case )
    rslt.append(snake_case )

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

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


if __name__ == "__main__":
    main()









'''simple docstring'''

from ..utils import DummyObject, requires_backends





class 							_snake_case (       metaclass=_a						):
   _A       :     Any       =					['''torch''', '''torchsde''']
   def __init__( self			:      Any     ,*SCREAMING_SNAKE_CASE__			:      int     ,**SCREAMING_SNAKE_CASE__			:      Tuple							):
     requires_backends(self     ,["torch", "torchsde"]							)
   @classmethod
   def     __UpperCamelCase						( cls			:      Dict     ,*SCREAMING_SNAKE_CASE__			:      Dict     ,**SCREAMING_SNAKE_CASE__			:      Optional[Any]							):
     requires_backends(cls     ,["torch", "torchsde"]							)







   @classmethod
   def     __UpperCamelCase						( cls			:      List[str]     ,*SCREAMING_SNAKE_CASE__			:      int     ,**SCREAMING_SNAKE_CASE__			:      Optional[Any]							):
     requires_backends(cls     ,["torch", "torchsde"]							)






