




"""simple docstring"""



from __future__ import annotations







def   _SCREAMING_SNAKE_CASE       (							lowercase_ = 4						)						->		list[list[int]]:
 A__	=    abs(lowercase_						) or 4
 return [[1 + x + y * row_size for x in range(lowercase_						)] for y in range(lowercase_						)]







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		list[list[int]]:
 return reverse_row(transpose(lowercase_						)						)
 # OR.. transpose(reverse_column(matrix))







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		list[list[int]]:
 return reverse_row(reverse_column(lowercase_						)						)
 # OR.. reverse_column(reverse_row(matrix))







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		list[list[int]]:
 return reverse_column(transpose(lowercase_						)						)
 # OR.. transpose(reverse_row(matrix))







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		list[list[int]]:
 A__	=    [list(lowercase_						) for x in zip(*lowercase_						)]
 return matrix







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		list[list[int]]:
 A__	=    matrix[::-1]
 return matrix







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		list[list[int]]:
 A__	=    [x[::-1] for x in matrix]
 return matrix







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		None:
 for i in matrix:
  print(*lowercase_						)


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE    =	make_matrix()
      print("\norigin:\n")
      print_matrix(matrix)
      print("\nrotate 90 counterclockwise:\n")
      print_matrix(rotate_aa(matrix))

      SCREAMING_SNAKE_CASE    =	make_matrix()
      print("\norigin:\n")
      print_matrix(matrix)
      print("\nrotate 180:\n")
      print_matrix(rotate_aaa(matrix))

      SCREAMING_SNAKE_CASE    =	make_matrix()
      print("\norigin:\n")
      print_matrix(matrix)
      print("\nrotate 270 counterclockwise:\n")
      print_matrix(rotate_aaa(matrix))











"""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()

SCREAMING_SNAKE_CASE    =	logging.get_logger(__name__)


SCREAMING_SNAKE_CASE    =	{name: getattr(transformers, name + "Fast") for name in SLOW_TO_FAST_CONVERTERS}







def   _SCREAMING_SNAKE_CASE       (							lowercase_      ,			lowercase_      ,			lowercase_      ,			lowercase_						)						->		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:
  A__	=    TOKENIZER_CLASSES
 else:
  A__	=    {tokenizer_name: getattr(lowercase_      ,			tokenizer_name + "Fast"						)}

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

 for tokenizer_name in tokenizer_names:
  A__	=    TOKENIZER_CLASSES[tokenizer_name]

  A__	=    True
  if checkpoint_name is None:
   A__	=    list(tokenizer_class.max_model_input_sizes.keys()						)
  else:
   A__	=    [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
   A__	=    tokenizer_class.from_pretrained(lowercase_      ,			force_download=lowercase_						)

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

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

   A__	=    tokenizer.save_pretrained(
       lowercase_      ,			legacy_format=lowercase_      ,			filename_prefix=lowercase_						)
   logger.info(f"""=> File names {file_names}"""						)

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


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

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





