"""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()

UpperCAmelCase__  		=						logging.get_logger(__name__)


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






def     __UpperCAmelCase					(			lowercase   ,lowercase   ,lowercase   ,lowercase		):







		"""simple docstring"""
		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						 =      TOKENIZER_CLASSES
		else:
				_UpperCAmelCase						 =      {tokenizer_name: getattr(lowercase   ,tokenizer_name + """Fast"""		)}

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

		for tokenizer_name in tokenizer_names:
				_UpperCAmelCase						 =      TOKENIZER_CLASSES[tokenizer_name]

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

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

						_UpperCAmelCase						 =      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__":
				UpperCAmelCase__  		=						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.""",
				)
				UpperCAmelCase__  		=						parser.parse_args()

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

"""simple docstring"""


import random






def     __UpperCAmelCase					(			lowercase   ,lowercase   ,lowercase = False		):







  """simple docstring"""
  _UpperCAmelCase						 =      {i: [] for i in range(lowercase		)}

  # if probability is greater or equal than 1, then generate a complete graph
  if probability >= 1:
    return complete_graph(lowercase		)
  # if probability is lower or equal than 0, then return a graph without edges
  if probability <= 0:
    return graph

  # for each couple of nodes, add an edge from u to v
  # if the number randomly generated is greater than probability probability
  for i in range(lowercase		):
    for j in range(i + 1   ,lowercase		):
      if random.random() < probability:
        graph[i].append(lowercase		)
        if not directed:
          # if the graph is undirected, add an edge in from j to i, either
          graph[j].append(lowercase		)
  return graph






def     __UpperCAmelCase					(			lowercase		):







  """simple docstring"""
  return {
      i: [j for j in range(lowercase		) if i != j] for i in range(lowercase		)
  }


if __name__ == "__main__":
    import doctest

    doctest.testmod()
