





'''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
)
__lowerCAmelCase							:	Union[str, Any]			=logging.getLogger(__name__)





def 						UpperCamelCase				(							):
    A__				=			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."       )
    A__				=			parser.parse_args()

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

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

    A__				=			[]
    A__				=			0
    A__				=			1_00_00
    A__				=			time.time()
    for text in data:
        A__				=			F"{bos} {text.strip()} {sep}"
        A__				=			tokenizer.encode(_lowerCamelCase						,       add_special_tokens=_lowerCamelCase       )
        rslt.append(_lowerCamelCase       )

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

    A__				=			F"{args.dump_file}.{args.tokenizer_name}.pickle"
    A__				=			tokenizer.vocab_size
    if vocab_size < (1 << 16):
        A__				=			[np.uintaa(_lowerCamelCase       ) for d in rslt]
    else:
        A__				=			[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()










'''simple docstring'''

from ..utils import DummyObject, requires_backends






class    UpperCAmelCase	(       metaclass=UpperCamelCase__				):
 __lowercase   		=				["""note_seq"""]
 def __init__(				self      :Optional[Any]						,       *lowercase_      :List[Any]						,       **lowercase_      :List[str]							)->							int:
     requires_backends(self						,       ["note_seq"]							)
 @classmethod
 def      UpperCAmelCase_							(				cls      :str						,       *lowercase_      :Union[str, Any]						,       **lowercase_      :Any							)->							Optional[int]:
     requires_backends(cls						,       ["note_seq"]							)



 @classmethod
 def      UpperCAmelCase_							(				cls      :Dict						,       *lowercase_      :Tuple						,       **lowercase_      :List[Any]							)->							Optional[Any]:
     requires_backends(cls						,       ["note_seq"]							)



