
import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

__A							=logging.get_logger(__name__)


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





def      lowerCamelCase_					(							lowerCamelCase__      ,					lowerCamelCase__      ,					lowerCamelCase__      ,					lowerCamelCase__       ):
				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_         =     TOKENIZER_CLASSES
				else:
								lowerCamelCase_         =     {tokenizer_name: getattr(lowerCamelCase__      ,					tokenizer_name + "Fast"       )}

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

				for tokenizer_name in tokenizer_names:
								lowerCamelCase_         =     TOKENIZER_CLASSES[tokenizer_name]

								lowerCamelCase_         =     True
								if checkpoint_name is None:
												lowerCamelCase_         =     list(tokenizer_class.max_model_input_sizes.keys()       )
								else:
												lowerCamelCase_         =     [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_         =     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_         =     checkpoint.split("/"       )
																lowerCamelCase_         =     os.path.join(lowerCamelCase__      ,					lowerCamelCase__       )
												elif add_prefix:
																lowerCamelCase_         =     checkpoint
																lowerCamelCase_         =     dump_path
												else:
																lowerCamelCase_         =     None
																lowerCamelCase_         =     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_         =     list(tokenizer.pretrained_vocab_files_map.values()       )[0][checkpoint]
																lowerCamelCase_         =     file_path.split(lowerCamelCase__       )[-1][0]
																if next_char == "/":
																				lowerCamelCase_         =     os.path.join(lowerCamelCase__      ,					lowerCamelCase__       )
																				lowerCamelCase_         =     None

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

												lowerCamelCase_         =     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							=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							=parser.parse_args()

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




from math import isqrt





def      lowerCamelCase_					(							lowerCamelCase__       ):
				lowerCamelCase_         =     [True] * max_number
				for i in range(2      ,					isqrt(max_number - 1       ) + 1       ):
								if is_prime[i]:
												for j in range(i**2      ,					lowerCamelCase__      ,					lowerCamelCase__       ):
																lowerCamelCase_         =     False

				return [i for i in range(2      ,					lowerCamelCase__       ) if is_prime[i]]





def      lowerCamelCase_					(							lowerCamelCase__ = 1_0**8       ):
				lowerCamelCase_         =     calculate_prime_numbers(max_number // 2       )

				lowerCamelCase_         =     0
				lowerCamelCase_         =     0
				lowerCamelCase_         =     len(lowerCamelCase__       ) - 1
				while left <= right:
								while prime_numbers[left] * prime_numbers[right] >= max_number:
												right -= 1
								semiprimes_count += right - left + 1
								left += 1

				return semiprimes_count


if __name__ == "__main__":
			print(F"""{solution() = }""")


