def 	__lowerCamelCase							(				__a    : str      ,							__a    : str		)      ->       int:
	# The longer word should come first
	if len(__a		) < len(__a		):
		return levenshtein_distance(__a      ,							__a		)

	if len(__a		) == 0:
		return len(__a		)

	_lowercase   =list(range(len(__a		) + 1		)		)

	for i, ca in enumerate(__a		):
		_lowercase   =[i + 1]

		for j, ca in enumerate(__a		):
			# Calculate insertions, deletions and substitutions
			_lowercase   =previous_row[j + 1] + 1
			_lowercase   =current_row[j] + 1
			_lowercase   =previous_row[j] + (ca != ca)

			# Get the minimum to append to the current row
			current_row.append(min(__a      ,							__a      ,							__a		)		)

		# Store the previous row
		_lowercase   =current_row

	# Returns the last element (distance)
	return previous_row[-1]


if __name__ == "__main__":
						lowerCAmelCase__  	=      input("Enter the first word:\n").strip()
						lowerCAmelCase__  	=      input("Enter the second word:\n").strip()

						lowerCAmelCase__  	=      levenshtein_distance(first_word, second_word)
						print(F'''Levenshtein distance between {first_word} and {second_word} is {result}''')









import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


__SCREAMING_SNAKE_CASE     =	logging.get_logger(__name__)

class 						lowerCamelCase_     (			_A    ):






						'''simple docstring'''







						def __init__(						self   :      Dict						,						*__lowerCamelCase   :      Tuple						,						**__lowerCamelCase   :      Dict			)   ->					None:
									warnings.warn(
									    "The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
									    " Please use DetrImageProcessor instead."						,						__lowerCamelCase						,						)
									super().__init__(*__lowerCamelCase						,						**__lowerCamelCase			)