
'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCamelCase__ :						Tuple    							=					logging.get_logger(__name__)

UpperCamelCase__ :						Optional[Any]    							=					{
    "flaubert/flaubert_small_cased": "https://huggingface.co/flaubert/flaubert_small_cased/resolve/main/config.json",
    "flaubert/flaubert_base_uncased": "https://huggingface.co/flaubert/flaubert_base_uncased/resolve/main/config.json",
    "flaubert/flaubert_base_cased": "https://huggingface.co/flaubert/flaubert_base_cased/resolve/main/config.json",
    "flaubert/flaubert_large_cased": "https://huggingface.co/flaubert/flaubert_large_cased/resolve/main/config.json",
}

class 				_a			(_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE =					'flaubert'
       SCREAMING_SNAKE_CASE =					{
           'hidden_size': 'emb_dim',
           'num_attention_heads': 'n_heads',
           'num_hidden_layers': 'n_layers',
           'n_words': 'vocab_size',  # For backward compatibility
       }






       def __init__(							self    ,							A__=False    ,							A__=0.0    ,							A__=3_01_45    ,							A__=20_48    ,							A__=12    ,							A__=16    ,							A__=0.1    ,							A__=0.1    ,							A__=True    ,							A__=False    ,							A__=False    ,							A__=False    ,							A__=1    ,							A__=True    ,							A__=5_12    ,							A__=20_48**-0.5    ,							A__=1E-12    ,							A__=0.02    ,							A__=0    ,							A__=1    ,							A__=2    ,							A__=3    ,							A__=5    ,							A__=True    ,							A__="first"    ,							A__=True    ,							A__=None    ,							A__=True    ,							A__=0.1    ,							A__=5    ,							A__=5    ,							A__=0    ,							A__=0    ,							A__=2    ,							A__=0    ,							**A__    ,							)      ->     Optional[int]:
          _SCREAMING_SNAKE_CASE       	=			pre_norm
          _SCREAMING_SNAKE_CASE       	=			layerdrop
          _SCREAMING_SNAKE_CASE       	=			vocab_size
          _SCREAMING_SNAKE_CASE       	=			emb_dim
          _SCREAMING_SNAKE_CASE       	=			n_layers
          _SCREAMING_SNAKE_CASE       	=			n_heads
          _SCREAMING_SNAKE_CASE       	=			dropout
          _SCREAMING_SNAKE_CASE       	=			attention_dropout
          _SCREAMING_SNAKE_CASE       	=			gelu_activation
          _SCREAMING_SNAKE_CASE       	=			sinusoidal_embeddings
          _SCREAMING_SNAKE_CASE       	=			causal
          _SCREAMING_SNAKE_CASE       	=			asm
          _SCREAMING_SNAKE_CASE       	=			n_langs
          _SCREAMING_SNAKE_CASE       	=			use_lang_emb
          _SCREAMING_SNAKE_CASE       	=			layer_norm_eps
          _SCREAMING_SNAKE_CASE       	=			bos_index
          _SCREAMING_SNAKE_CASE       	=			eos_index
          _SCREAMING_SNAKE_CASE       	=			pad_index
          _SCREAMING_SNAKE_CASE       	=			unk_index
          _SCREAMING_SNAKE_CASE       	=			mask_index
          _SCREAMING_SNAKE_CASE       	=			is_encoder
          _SCREAMING_SNAKE_CASE       	=			max_position_embeddings
          _SCREAMING_SNAKE_CASE       	=			embed_init_std
          _SCREAMING_SNAKE_CASE       	=			init_std
          _SCREAMING_SNAKE_CASE       	=			summary_type
          _SCREAMING_SNAKE_CASE       	=			summary_use_proj
          _SCREAMING_SNAKE_CASE       	=			summary_activation
          _SCREAMING_SNAKE_CASE       	=			summary_proj_to_labels
          _SCREAMING_SNAKE_CASE       	=			summary_first_dropout
          _SCREAMING_SNAKE_CASE       	=			start_n_top
          _SCREAMING_SNAKE_CASE       	=			end_n_top
          _SCREAMING_SNAKE_CASE       	=			mask_token_id
          _SCREAMING_SNAKE_CASE       	=			lang_id

          if "n_words" in kwargs:
             _SCREAMING_SNAKE_CASE       	=			kwargs["""n_words"""]

          super().__init__(pad_token_id=A__    ,							bos_token_id=A__    ,							**A__ )






class 				_a			(_lowerCamelCase):





       """simple docstring"""




       @property
       def     UpperCamelCase			(							self )      ->     Mapping[str, Mapping[int, str]]:
          if self.task == "multiple-choice":
             _SCREAMING_SNAKE_CASE       	=			{0: """batch""", 1: """choice""", 2: """sequence"""}
          else:
             _SCREAMING_SNAKE_CASE       	=			{0: """batch""", 1: """sequence"""}
          return OrderedDict(
              [
                  ("""input_ids""", dynamic_axis),
                  ("""attention_mask""", dynamic_axis),
              ] )








'''simple docstring'''



#
# Sort large text files in a minimum amount of memory
#
import argparse
import os

class 				_a			:





       """simple docstring"""




       SCREAMING_SNAKE_CASE =					'block_{0}.dat'






       def __init__(							self    ,							A__ )      ->     Union[str, Any]:
          _SCREAMING_SNAKE_CASE       	=			filename
          _SCREAMING_SNAKE_CASE       	=			[]






       def     UpperCamelCase			(							self    ,							A__    ,							A__ )      ->     Optional[Any]:
          _SCREAMING_SNAKE_CASE       	=			self.BLOCK_FILENAME_FORMAT.format(A__ )
          with open(A__    ,							"""w""" ) as file:
             file.write(A__ )
          self.block_filenames.append(A__ )






       def     UpperCamelCase			(							self )      ->     Tuple:
          return self.block_filenames






       def     UpperCamelCase			(							self    ,							A__    ,							A__=None )      ->     Any:
          _SCREAMING_SNAKE_CASE       	=			0
          with open(self.filename ) as file:
             while True:
                _SCREAMING_SNAKE_CASE       	=			file.readlines(A__ )

                if lines == []:
                   break

                if sort_key is None:
                   lines.sort()
                else:
                   lines.sort(key=A__ )

                self.write_block("""""".join(A__ )    ,							A__ )
                i += 1






       def     UpperCamelCase			(							self )      ->     List[Any]:
          map(os.remove    ,							self.block_filenames )






class 				_a			:





       """simple docstring"""




       def     UpperCamelCase			(							self    ,							A__ )      ->     str:
          _SCREAMING_SNAKE_CASE       	=			-1
          _SCREAMING_SNAKE_CASE       	=			None

          for i in range(len(A__ ) ):
             if min_str is None or choices[i] < min_str:
                _SCREAMING_SNAKE_CASE       	=			i

          return min_index






class 				_a			:





       """simple docstring"""




       def __init__(							self    ,							A__ )      ->     Dict:
          _SCREAMING_SNAKE_CASE       	=			files
          _SCREAMING_SNAKE_CASE       	=			set()
          _SCREAMING_SNAKE_CASE       	=			len(A__ )
          _SCREAMING_SNAKE_CASE       	=			{i: None for i in range(self.num_buffers )}






       def     UpperCamelCase			(							self )      ->     Dict:
          return {
              i: self.buffers[i] for i in range(self.num_buffers ) if i not in self.empty
          }






       def     UpperCamelCase			(							self )      ->     Tuple:
          for i in range(self.num_buffers ):
             if self.buffers[i] is None and i not in self.empty:
                _SCREAMING_SNAKE_CASE       	=			self.files[i].readline()

                if self.buffers[i] == "":
                   self.empty.add(A__ )
                   self.files[i].close()

          if len(self.empty ) == self.num_buffers:
             return False

          return True






       def     UpperCamelCase			(							self    ,							A__ )      ->     List[str]:
          _SCREAMING_SNAKE_CASE       	=			self.buffers[index]
          _SCREAMING_SNAKE_CASE       	=			None

          return value






class 				_a			:





       """simple docstring"""




       def __init__(							self    ,							A__ )      ->     str:
          _SCREAMING_SNAKE_CASE       	=			merge_strategy






       def     UpperCamelCase			(							self    ,							A__    ,							A__    ,							A__ )      ->     Union[str, Any]:
          _SCREAMING_SNAKE_CASE       	=			FilesArray(self.get_file_handles(A__    ,							A__ ) )
          with open(A__    ,							"""w"""    ,							A__ ) as outfile:
             while buffers.refresh():
                _SCREAMING_SNAKE_CASE       	=			self.merge_strategy.select(buffers.get_dict() )
                outfile.write(buffers.unshift(A__ ) )






       def     UpperCamelCase			(							self    ,							A__    ,							A__ )      ->     str:
          _SCREAMING_SNAKE_CASE       	=			{}

          for i in range(len(A__ ) ):
             _SCREAMING_SNAKE_CASE       	=			open(filenames[i]    ,							"""r"""    ,							A__ )  # noqa: UP015

          return files






class 				_a			:





       """simple docstring"""




       def __init__(							self    ,							A__ )      ->     Union[str, Any]:
          _SCREAMING_SNAKE_CASE       	=			block_size






       def     UpperCamelCase			(							self    ,							A__    ,							A__=None )      ->     Optional[Any]:
          _SCREAMING_SNAKE_CASE       	=			self.get_number_blocks(A__    ,							self.block_size )
          _SCREAMING_SNAKE_CASE       	=			FileSplitter(A__ )
          splitter.split(self.block_size    ,							A__ )

          _SCREAMING_SNAKE_CASE       	=			FileMerger(NWayMerge() )
          _SCREAMING_SNAKE_CASE       	=			self.block_size / (num_blocks + 1)
          merger.merge(splitter.get_block_filenames()    ,							filename + """.out"""    ,							A__ )

          splitter.cleanup()






       def     UpperCamelCase			(							self    ,							A__    ,							A__ )      ->     Any:
          return (os.stat(A__ ).st_size / block_size) + 1






def 				lowerCAmelCase_		(			SCREAMING_SNAKE_CASE_  )       ->       str:




   """simple docstring"""
   if string[-1].lower() == "k":
      return int(string[:-1]  ) * 10_24
   elif string[-1].lower() == "m":
      return int(string[:-1]  ) * 10_24 * 10_24
   elif string[-1].lower() == "g":
      return int(string[:-1]  ) * 10_24 * 10_24 * 10_24
   else:
      return int(SCREAMING_SNAKE_CASE_  )
def 				lowerCAmelCase_		(			)       ->       List[str]:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE       	=			argparse.ArgumentParser()
   parser.add_argument(
       """-m"""      , """--mem"""      , help="""amount of memory to use for sorting"""      , default="""100M"""  )
   parser.add_argument(
       """filename"""      , metavar="""<filename>"""      , nargs=1      , help="""name of file to sort"""  )
   _SCREAMING_SNAKE_CASE       	=			parser.parse_args()

   _SCREAMING_SNAKE_CASE       	=			ExternalSort(parse_memory(args.mem  )  )
   sorter.sort(args.filename[0]  )


if __name__ == "__main__":
     main()






