



'''simple docstring'''







import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


_UpperCamelCase  						=			logging.get_logger(__name__)

class      lowerCamelCase__     (     _A				):






	'''simple docstring'''

	def __init__(  self		:  Union[str, Any]   ,		*__A		:  Union[str, Any]   ,		**__A		:  Optional[int]					)     ->			None:




								'''simple docstring'''





								warnings.warn(
								    """The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
								    """ Please use MobileNetV2ImageProcessor instead."""   ,		__A   ,		)
								super().__init__(*__A   ,		**__A					)










'''simple docstring'''







def 			_lowerCAmelCase(      UpperCAmelCase_      :	str						) ->							str:
							lowerCAmelCase__  =   word.upper()
							lowerCAmelCase__  =   0
							lowerCAmelCase__  =   {}
							lowerCAmelCase__  =   []

							for letter in word:
														if letter not in letter_nums:
																					lowerCAmelCase__  =   str(UpperCAmelCase_						)
																					next_num += 1
														word_pattern.append(letter_nums[letter]						)
							return ".".join(UpperCAmelCase_						)


if __name__ == "__main__":
		import pprint
		import time

		_UpperCamelCase  						=			time.time()
		with open("""dictionary.txt""") as in_file:
				_UpperCamelCase  						=			in_file.read().splitlines()

		_UpperCamelCase  						=			{}
		for word in word_list:
				_UpperCamelCase  						=			get_word_pattern(word)
				if pattern in all_patterns:
						all_patterns[pattern].append(word)
				else:
						_UpperCamelCase  						=			[word]

		with open("""word_patterns.txt""", """w""") as out_file:
				out_file.write(pprint.pformat(all_patterns))

		_UpperCamelCase  						=			round(time.time() - start_time, 2)
		print(f'Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.')
		# Done!  9,581 word patterns found in 0.58 seconds.





