






"""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()

lowerCamelCase_							      = logging.get_logger(__name__)


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

def 							snake_case (  A__      ,A__      ,A__      ,A__		):
			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:
						UpperCAmelCase_	:					List[Any]     	=   TOKENIZER_CLASSES
			else:
						UpperCAmelCase_	:					int     	=   {tokenizer_name: getattr(A__      ,tokenizer_name + "Fast"		)}

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

			for tokenizer_name in tokenizer_names:
						UpperCAmelCase_	:					Optional[int]     	=   TOKENIZER_CLASSES[tokenizer_name]

						UpperCAmelCase_	:					Union[str, Any]     	=   True
						if checkpoint_name is None:
									UpperCAmelCase_	:					Union[str, Any]     	=   list(tokenizer_class.max_model_input_sizes.keys()		)
						else:
									UpperCAmelCase_	:					Any     	=   [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
									UpperCAmelCase_	:					Optional[int]     	=   tokenizer_class.from_pretrained(A__      ,force_download=A__		)

									# 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:
												UpperCAmelCase_	,      UpperCAmelCase_	:					List[str]     	=   checkpoint.split("/"		)
												UpperCAmelCase_	:					List[str]     	=   os.path.join(A__      ,A__		)
									elif add_prefix:
												UpperCAmelCase_	:					List[Any]     	=   checkpoint
												UpperCAmelCase_	:					Optional[Any]     	=   dump_path
									else:
												UpperCAmelCase_	:					Union[str, Any]     	=   None
												UpperCAmelCase_	:					List[str]     	=   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]:
												UpperCAmelCase_	:					Optional[Any]     	=   list(tokenizer.pretrained_vocab_files_map.values()		)[0][checkpoint]
												UpperCAmelCase_	:					List[Any]     	=   file_path.split(A__		)[-1][0]
												if next_char == "/":
															UpperCAmelCase_	:					Dict     	=   os.path.join(A__      ,A__		)
															UpperCAmelCase_	:					Dict     	=   None

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

									UpperCAmelCase_	:					Dict     	=   tokenizer.save_pretrained(
									    A__      ,legacy_format=A__      ,filename_prefix=A__		)
									logger.info(F"""=> File names {file_names}"""		)

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


if __name__ == "__main__":
			lowerCamelCase_							      = 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.''',
			)
			lowerCamelCase_							      = parser.parse_args()

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






from __future__ import annotations

from dataclasses import dataclass

@dataclass
class 							UpperCAmelCase_						:
							"""simple docstring"""







							UpperCAmelCase__			:		float
							UpperCAmelCase__			:		TreeNode | None             =       None
							UpperCAmelCase__			:		TreeNode | None             =       None



def   __UpperCAmelCase					(      __a :     TreeNode | None      )     ->	bool:

					"""simple docstring"""

					def is_valid_tree(__a :     TreeNode | None      ) -> bool:
										if node is None:
															return True

										if not isinstance(__a						,__a      ):
															return False

										try:
															float(node.data      )
										except (TypeError, ValueError):
															return False

										return is_valid_tree(node.left      ) and is_valid_tree(node.right      )

					if not is_valid_tree(__a      ):
										raise ValueError(
										    '''Each node should be type of TreeNode and data should be float.'''      )

					def is_binary_search_tree_recursive_check(
					    __a :     TreeNode | None						,__a :     float						,__a :     float      ) -> bool:

										if node is None:
															return True

										return (
										    left_bound < node.data < right_bound
										    and is_binary_search_tree_recursive_check(node.left						,__a						,node.data      )
										    and is_binary_search_tree_recursive_check(
										        node.right						,node.data						,__a      )
										)

					return is_binary_search_tree_recursive_check(__a						,-float('''inf'''      )						,float('''inf'''      )      )


if __name__ == "__main__":
			import doctest

			doctest.testmod()



