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}''')





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCAmelCase__  	=      {
    "configuration_imagegpt": ["IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ImageGPTConfig", "ImageGPTOnnxConfig"]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  	=      ["ImageGPTFeatureExtractor"]
						lowerCAmelCase__  	=      ["ImageGPTImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  	=      [
						    "IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "ImageGPTForCausalImageModeling",
						    "ImageGPTForImageClassification",
						    "ImageGPTModel",
						    "ImageGPTPreTrainedModel",
						    "load_tf_weights_in_imagegpt",
						]


if TYPE_CHECKING:
						from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
												from .image_processing_imagegpt import ImageGPTImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_imagegpt import (
												    IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    ImageGPTForCausalImageModeling,
												    ImageGPTForImageClassification,
												    ImageGPTModel,
												    ImageGPTPreTrainedModel,
												    load_tf_weights_in_imagegpt,
												)

else:
						import sys

						lowerCAmelCase__  	=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




