


def 						_A						(						_lowercase			,       _lowercase				)			->				int:


     """simple docstring"""


     if len(_lowercase				) < len(_lowercase				):
          return levenshtein_distance(_lowercase			,       _lowercase				)

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

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

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

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

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

          # Store the previous row
          __UpperCamelCase				=	current_row

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


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

    __snake_case     =		levenshtein_distance(first_word, second_word)
    print(f"""Levenshtein distance between {first_word} and {second_word} is {result}""")






# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__snake_case     =		{
    '''configuration_convnextv2''': [
        '''CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConvNextV2Config''',
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case     =		[
        '''CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''ConvNextV2ForImageClassification''',
        '''ConvNextV2Model''',
        '''ConvNextV2PreTrainedModel''',
        '''ConvNextV2Backbone''',
    ]


if TYPE_CHECKING:
    from .configuration_convnextva import (
        CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ConvNextVaConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_convnextva import (
            CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            ConvNextVaBackbone,
            ConvNextVaForImageClassification,
            ConvNextVaModel,
            ConvNextVaPreTrainedModel,
        )

else:
    import sys

    __snake_case     =		_LazyModule(__name__, globals()['''__file__'''], _import_structure)


