




'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowercase      :   Tuple      =       logging.get_logger(__name__)

lowercase      :   Dict      =       {
    """google/bit-50""": """https://huggingface.co/google/bit-50/resolve/main/config.json""",
}







class 					_a (a__,		a__	):





     '''simple docstring'''



     lowerCAmelCase_  :     Optional[int]          =					"""bit"""
     lowerCAmelCase_  :     Tuple          =					["""preactivation""", """bottleneck"""]
     lowerCAmelCase_  :     List[str]          =					["""SAME""", """VALID"""]







     def __init__(				self							,__a=3							,__a=64							,__a=[256, 512, 1_024, 2_048]							,__a=[3, 4, 6, 3]							,__a="preactivation"							,__a="relu"							,__a=None							,__a=32							,__a=0.0							,__a=False							,__a=32							,__a=1							,__a=None							,__a=None							,**__a							,)      ->				List[Any]:
          super().__init__(**__a							)
          if layer_type not in self.layer_types:
               raise ValueError(F'''layer_type={layer_type} is not one of {",".join(self.layer_types							)}'''							)
          if global_padding is not None:
               if global_padding.upper() in self.supported_padding:
                    snake_case			:      str        =			global_padding.upper()
               else:
                    raise ValueError(F'''Padding strategy {global_padding} not supported'''							)
          snake_case			:      str        =			num_channels
          snake_case			:      Optional[int]        =			embedding_size
          snake_case			:      int        =			hidden_sizes
          snake_case			:      List[Any]        =			depths
          snake_case			:      Tuple        =			layer_type
          snake_case			:      int        =			hidden_act
          snake_case			:      Any        =			global_padding
          snake_case			:      List[str]        =			num_groups
          snake_case			:      Optional[int]        =			drop_path_rate
          snake_case			:      str        =			embedding_dynamic_padding
          snake_case			:      Tuple        =			output_stride
          snake_case			:      int        =			width_factor

          snake_case			:      str        =			["""stem"""] + [F'''stage{idx}''' for idx in range(1							,len(__a							) + 1							)]
          snake_case ,		snake_case			:      Tuple        =			get_aligned_output_features_output_indices(
              out_features=__a							,out_indices=__a							,stage_names=self.stage_names							)









'''simple docstring'''







import argparse
import logging
import pickle
from collections import Counter


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

if __name__ == "__main__":
      lowercase      :   List[Any]      =       argparse.ArgumentParser(
          description="""Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)"""
      )
      parser.add_argument(
          """--data_file""", type=str, default="""data/dump.bert-base-uncased.pickle""", help="""The binarized dataset."""
      )
      parser.add_argument(
          """--token_counts_dump""", type=str, default="""data/token_counts.bert-base-uncased.pickle""", help="""The dump file."""
      )
      parser.add_argument("""--vocab_size""", default=3_0522, type=int)
      lowercase      :   str      =       parser.parse_args()

      logger.info(F"""Loading data from {args.data_file}""")
      with open(args.data_file, """rb""") as fp:
            lowercase      :   int      =       pickle.load(fp)

      logger.info("""Counting occurrences for MLM.""")
      lowercase      :   List[Any]      =       Counter()
      for tk_ids in data:
            counter.update(tk_ids)
      lowercase      :   int      =       [0] * args.vocab_size
      for k, v in counter.items():
            lowercase      :   List[Any]      =       v

      logger.info(F"""Dump to {args.token_counts_dump}""")
      with open(args.token_counts_dump, """wb""") as handle:
            pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)



