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#
# 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


snake_case_					:					Optional[int]       						=			"Here is a text containing a lot of information: '''{text}'''.\n\nCan you answer this question about the text: '{question}'"







class __snake_case     (     a						):
   UpperCAmelCase__    :       int		=    '''google/flan-t5-base'''
   UpperCAmelCase__    :       Optional[Any]		=    (
       '''This is a tool that answers questions related to a text. It takes two arguments named `text`, which is the '''
       '''text where to find the answer, and `question`, which is the question, and returns the answer to the question.'''
   )
   UpperCAmelCase__    :       Union[str, Any]		=    '''text_qa'''
   UpperCAmelCase__    :       List[str]		=    AutoTokenizer
   UpperCAmelCase__    :       str		=    AutoModelForSeqaSeqLM

   UpperCAmelCase__    :       List[Any]		=    ['''text''', '''text''']
   UpperCAmelCase__    :       str		=    ['''text''']







   def lowerCamelCase		( self						:		Optional[Any]   ,		_snake_case						:		str   ,		_snake_case						:		str):

        """simple docstring"""


        UpperCAmelCase_		=				QA_PROMPT.format(text=_snake_case   ,		question=_snake_case)
        return self.pre_processor(_snake_case   ,		return_tensors='''pt''')







   def lowerCamelCase		( self						:		Dict   ,		_snake_case						:		Union[str, Any]):

        """simple docstring"""


        UpperCAmelCase_		=				self.model.generate(**_snake_case)

        UpperCAmelCase_	,			UpperCAmelCase_		=				inputs['''input_ids'''].shape
        UpperCAmelCase_		=				output_ids.shape[0]

        return output_ids.reshape(_snake_case   ,		out_b // in_b   ,		*output_ids.shape[1:])[0][0]







   def lowerCamelCase		( self						:		Union[str, Any]   ,		_snake_case						:		Dict):

        """simple docstring"""


        return self.pre_processor.decode(_snake_case   ,		skip_special_tokens=_snake_case   ,		clean_up_tokenization_spaces=_snake_case)












from .stack import Stack


def   A		(__A  :       str			)  -> bool:







     """simple docstring"""


     UpperCAmelCase_		=				Stack()
     UpperCAmelCase_		=				{'''(''': ''')''', '''[''': ''']''', '''{''': '''}'''}
     for bracket in parentheses:
          if bracket in bracket_pairs:
               stack.push(__A			)
          elif bracket in (")", "]", "}"):
               if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
                    return False
     return stack.is_empty()


if __name__ == "__main__":
    from doctest import testmod

    testmod()

    snake_case_					:					Dict       						=			["((()))", "((())", "(()))"]
    print("Balanced parentheses demonstration:\n")
    for example in examples:
        snake_case_					:					Optional[int]       						=			"" if balanced_parentheses(example) else "not "
        print(f"{example} is {not_str}balanced")






