




"""simple docstring"""






import numpy as np

lowercase__     						=						[
    ["""a""", """b""", """c""", """d""", """e"""],
    ["""f""", """g""", """h""", """i""", """k"""],
    ["""l""", """m""", """n""", """o""", """p"""],
    ["""q""", """r""", """s""", """t""", """u"""],
    ["""v""", """w""", """x""", """y""", """z"""],
]






class lowerCAmelCase__	:






			'''simple docstring'''



			def __init__(  self  ):
							_lowerCamelCase     :			Dict    =    np.array(lowercase  )
			def 					A_    (  self  ,      lowercase  ):
							_lowerCamelCase, _lowerCamelCase     :			Any    =    np.where(letter == self.SQUARE  )
							_lowerCamelCase     :			Tuple    =    np.concatenate([indexa + 1, indexa + 1]  )
							return indexes
			def 					A_    (  self  ,      lowercase  ,      lowercase  ):
							_lowerCamelCase     :			Tuple    =    self.SQUARE[indexa - 1, indexa - 1]
							return letter
			def 					A_    (  self  ,      lowercase  ):
							_lowerCamelCase     :			int    =    message.lower()
							_lowerCamelCase     :			Optional[int]    =    message.replace(' '  ,      ''  )
							_lowerCamelCase     :			List[str]    =    message.replace('j'  ,      'i'  )

							_lowerCamelCase     :			Any    =    np.empty((2, len(lowercase  ))  )
							for letter_index in range(len(lowercase  )  ):
											_lowerCamelCase     :			Dict    =    self.letter_to_numbers(message[letter_index]  )

											_lowerCamelCase     :			str    =    numbers[0]
											_lowerCamelCase     :			Union[str, Any]    =    numbers[1]

							_lowerCamelCase     :			str    =    first_step.reshape(2 * len(lowercase  )  )
							_lowerCamelCase     :			Dict    =    ''
							for numbers_index in range(len(lowercase  )  ):
											_lowerCamelCase     :			str    =    int(second_step[numbers_index * 2]  )
											_lowerCamelCase     :			List[Any]    =    int(second_step[(numbers_index * 2) + 1]  )
											_lowerCamelCase     :			List[Any]    =    self.numbers_to_letter(lowercase  ,      lowercase  )
											_lowerCamelCase     :			Any    =    encoded_message + letter

							return encoded_message






			def 					A_    (  self  ,      lowercase  ):
							_lowerCamelCase     :			Tuple    =    message.lower()
							message.replace(' '  ,      ''  )
							_lowerCamelCase     :			List[str]    =    np.empty(2 * len(lowercase  )  )
							for letter_index in range(len(lowercase  )  ):
											_lowerCamelCase     :			str    =    self.letter_to_numbers(message[letter_index]  )
											_lowerCamelCase     :			Tuple    =    numbers[0]
											_lowerCamelCase     :			int    =    numbers[1]

							_lowerCamelCase     :			Union[str, Any]    =    first_step.reshape((2, len(lowercase  ))  )
							_lowerCamelCase     :			List[str]    =    ''
							for numbers_index in range(len(lowercase  )  ):
											_lowerCamelCase     :			Tuple    =    int(second_step[0, numbers_index]  )
											_lowerCamelCase     :			Any    =    int(second_step[1, numbers_index]  )
											_lowerCamelCase     :			Optional[Any]    =    self.numbers_to_letter(lowercase  ,      lowercase  )
											_lowerCamelCase     :			List[str]    =    decoded_message + letter

							return decoded_message



'''simple docstring'''






# Copyright 2023 The HuggingFace Inc. 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 ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool






class    __snake_case       (   _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase    =					'philschmid/bart-large-cnn-samsum'
    lowercase    =					(
        'This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '
        'and returns a summary of the text.'
    )
    lowercase    =					'summarizer'
    lowercase    =					AutoTokenizer
    lowercase    =					AutoModelForSeqaSeqLM

    lowercase    =					['text']
    lowercase    =					['text']

    def __lowercase   (   self    :  Dict    ,						lowerCamelCase    :  Dict		)   ->  Any:
      return self.pre_processor(lowerCamelCase    ,						return_tensors="""pt"""    ,						truncation=lowerCamelCase		)

    def __lowercase   (   self    :  Optional[Any]    ,						lowerCamelCase    :  Tuple		)   ->  List[str]:
      return self.model.generate(**lowerCamelCase		)[0]





    def __lowercase   (   self    :  str    ,						lowerCamelCase    :  Dict		)   ->  List[Any]:
      return self.pre_processor.decode(lowerCamelCase    ,						skip_special_tokens=lowerCamelCase    ,						clean_up_tokenization_spaces=lowerCamelCase		)



