






"""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            =	logging.getLogger(__name__)


def      UpperCamelCase       ( )     ->       Optional[int]:
				lowercase    :      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=_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.""" )
				lowercase    :      Dict       = parser.parse_args()

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

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

				lowercase    :      Any       = []
				lowercase    :      Dict       = 0
				lowercase    :      Any       = 10_000
				lowercase    :      Union[str, Any]       = time.time()
				for text in data:
								lowercase    :      List[Any]       = F"""{bos} {text.strip()} {sep}"""
								lowercase    :      str       = tokenizer.encode(_lowerCAmelCase  ,				add_special_tokens=_lowerCAmelCase )
								rslt.append(_lowerCAmelCase )

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

				lowercase    :      List[Any]       = F"""{args.dump_file}.{args.tokenizer_name}.pickle"""
				lowercase    :      List[str]       = tokenizer.vocab_size
				if vocab_size < (1 << 16):
								lowercase    :      Optional[int]       = [np.uintaa(_lowerCAmelCase ) for d in rslt]
				else:
								lowercase    :      List[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()


"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_					     =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_					     =	{
    '''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}
class       lowerCAmelCase_		(				A__ ):



							'''simple docstring'''





							_snake_case						      =		'''mgp-str'''




							def __init__( self    ,				snake_case_=[32, 128]    ,				snake_case_=4    ,				snake_case_=3    ,				snake_case_=27    ,				snake_case_=38    ,				snake_case_=50_257    ,				snake_case_=30_522    ,				snake_case_=768    ,				snake_case_=12    ,				snake_case_=12    ,				snake_case_=4.0    ,				snake_case_=True    ,				snake_case_=False    ,				snake_case_=1e-5    ,				snake_case_=0.0    ,				snake_case_=0.0    ,				snake_case_=0.0    ,				snake_case_=False    ,				snake_case_=0.02    ,				**snake_case_    ,				)       ->  List[Any]:
													super().__init__(**snake_case_				)

													__lowerCAmelCase     =  image_size
													__lowerCAmelCase     =  patch_size
													__lowerCAmelCase     =  num_channels
													__lowerCAmelCase     =  max_token_length
													__lowerCAmelCase     =  num_character_labels
													__lowerCAmelCase     =  num_bpe_labels
													__lowerCAmelCase     =  num_wordpiece_labels
													__lowerCAmelCase     =  hidden_size
													__lowerCAmelCase     =  num_hidden_layers
													__lowerCAmelCase     =  num_attention_heads
													__lowerCAmelCase     =  mlp_ratio
													__lowerCAmelCase     =  distilled
													__lowerCAmelCase     =  layer_norm_eps
													__lowerCAmelCase     =  drop_rate
													__lowerCAmelCase     =  qkv_bias
													__lowerCAmelCase     =  attn_drop_rate
													__lowerCAmelCase     =  drop_path_rate
													__lowerCAmelCase     =  output_aa_attentions
													__lowerCAmelCase     =  initializer_range
