






"""simple docstring"""



import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

A__       :				Any 					=					logging.get_logger(__name__)


A__       :				Dict 					=					{name: getattr(transformers, name + 'Fast') for name in SLOW_TO_FAST_CONVERTERS}

def  _snake_case				(     lowerCamelCase__	:    List[Any]				,						lowerCamelCase__	:    Tuple				,						lowerCamelCase__	:    Union[str, Any]				,						lowerCamelCase__	:    Dict  )				->	Optional[Any]:





							if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
														raise ValueError(F"""Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys()  )}."""  )

							if tokenizer_name is None:
														lowerCamelCase_       :							Any									=TOKENIZER_CLASSES
							else:
														lowerCamelCase_       :							Any									={tokenizer_name: getattr(lowerCamelCase__				,						tokenizer_name + "Fast"  )}

							logger.info(F"""Loading tokenizer classes: {tokenizer_names}"""  )

							for tokenizer_name in tokenizer_names:
														lowerCamelCase_       :							List[Any]									=TOKENIZER_CLASSES[tokenizer_name]

														lowerCamelCase_       :							Any									=True
														if checkpoint_name is None:
																					lowerCamelCase_       :							Optional[int]									=list(tokenizer_class.max_model_input_sizes.keys()  )
														else:
																					lowerCamelCase_       :							int									=[checkpoint_name]

														logger.info(F"""For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}"""  )

														for checkpoint in checkpoint_names:
																					logger.info(F"""Loading {tokenizer_class.__class__.__name__} {checkpoint}"""  )

																					# Load tokenizer
																					lowerCamelCase_       :							Union[str, Any]									=tokenizer_class.from_pretrained(lowerCamelCase__				,						force_download=lowerCamelCase__  )

																					# Save fast tokenizer
																					logger.info(F"""Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}"""  )

																					# For organization names we create sub-directories
																					if "/" in checkpoint:
																												lowerCamelCase_							,						lowerCamelCase_       :							List[str]									=checkpoint.split("/"  )
																												lowerCamelCase_       :							Optional[int]									=os.path.join(lowerCamelCase__				,						lowerCamelCase__  )
																					elif add_prefix:
																												lowerCamelCase_       :							int									=checkpoint
																												lowerCamelCase_       :							List[Any]									=dump_path
																					else:
																												lowerCamelCase_       :							Optional[Any]									=None
																												lowerCamelCase_       :							Tuple									=dump_path

																					logger.info(F"""=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}"""  )

																					if checkpoint in list(tokenizer.pretrained_vocab_files_map.values()  )[0]:
																												lowerCamelCase_       :							Tuple									=list(tokenizer.pretrained_vocab_files_map.values()  )[0][checkpoint]
																												lowerCamelCase_       :							Union[str, Any]									=file_path.split(lowerCamelCase__  )[-1][0]
																												if next_char == "/":
																																			lowerCamelCase_       :							Tuple									=os.path.join(lowerCamelCase__				,						lowerCamelCase__  )
																																			lowerCamelCase_       :							Tuple									=None

																												logger.info(F"""=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}"""  )

																					lowerCamelCase_       :							List[str]									=tokenizer.save_pretrained(
																					    lowerCamelCase__				,						legacy_format=lowerCamelCase__				,						filename_prefix=lowerCamelCase__  )
																					logger.info(F"""=> File names {file_names}"""  )

																					for file_name in file_names:
																												if not file_name.endswith("tokenizer.json"  ):
																																			os.remove(lowerCamelCase__  )
																																			logger.info(F"""=> removing {file_name}"""  )


if __name__ == "__main__":
						A__       :				Optional[int] 					=					argparse.ArgumentParser()
						# Required parameters
						parser.add_argument(
						    '--dump_path', default=None, type=str, required=True, help='Path to output generated fast tokenizer files.'
						)
						parser.add_argument(
						    '--tokenizer_name',
						    default=None,
						    type=str,
						    help=(
						        f'Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will '
						        'download and convert all the checkpoints from AWS.'
						    ),
						)
						parser.add_argument(
						    '--checkpoint_name',
						    default=None,
						    type=str,
						    help='Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.',
						)
						parser.add_argument(
						    '--force_download',
						    action='store_true',
						    help='Re-download checkpoints.',
						)
						A__       :				Any 					=					parser.parse_args()

						convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)








import random






def     a(      A       :    Optional[Any] ,     A       :    Optional[Any] ,     A       :    str       )		->       List[Any]:
					"""simple docstring"""





					a					     =   a[left_index]
					a					     =   left_index + 1
					for j in range(left_index + 1 ,     A       ):
										if a[j] < pivot:
															a     ,				a					     =   a[i], a[j]
															i += 1
					a     ,				a					     =   a[i - 1], a[left_index]
					return i - 1






def     a(      A       :    List[Any] ,     A       :    List[Any] ,     A       :    Union[str, Any]       )		->       List[Any]:
					"""simple docstring"""





					if left < right:
										a					     =   random.randint(A ,     right - 1       )
										a     ,				a					     =   (
										    a[left],
										    a[pivot],
										)  # switches the pivot with the left most bound
										a					     =   partition(A ,     A ,     A       )
										quick_sort_random(
										    A ,     A ,     A       )  # recursive quicksort to the left of the pivot point
										quick_sort_random(
										    A ,     pivot_index + 1 ,     A       )  # recursive quicksort to the right of the pivot point






def     a(      )		->       Any:
					"""simple docstring"""





					a					     =   input("Enter numbers separated by a comma:\n"       ).strip()
					a					     =   [int(A       ) for item in user_input.split(","       )]

					quick_sort_random(A ,     0 ,     len(A       )       )

					print(A       )


if __name__ == "__main__":
				main()
