


"""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


UpperCamelCase__							:Optional[int]       =  """Here is a text containing a lot of information: '''{text}'''.

Can you answer this question about the text: '{question}'"""






class     A(     lowerCamelCase__		):

		"""simple docstring"""





		A         =       "google/flan-t5-base"
		A         =       (
		    "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."
		)
		A         =       "text_qa"
		A         =       AutoTokenizer
		A         =       AutoModelForSeqaSeqLM

		A         =       ["text", "text"]
		A         =       ["text"]
		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__      )			->  int:

					"""simple docstring"""



					_UpperCamelCase				:str				    =  QA_PROMPT.format(text=SCREAMING_SNAKE_CASE__				,							question=SCREAMING_SNAKE_CASE__      )
					return self.pre_processor(SCREAMING_SNAKE_CASE__				,							return_tensors='''pt'''      )
		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  Any:

					"""simple docstring"""



					_UpperCamelCase				:List[str]				    =  self.model.generate(**SCREAMING_SNAKE_CASE__      )

					_UpperCamelCase    ,			_UpperCamelCase				:int				    =  inputs['''input_ids'''].shape
					_UpperCamelCase				:Optional[int]				    =  output_ids.shape[0]

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





		def      _UpperCamelCase(   self				,							SCREAMING_SNAKE_CASE__      )			->  List[Any]:

					"""simple docstring"""



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





"""simple docstring"""






def 							A_					(   snake_case__		)				->     str:
			_UpperCamelCase				:Tuple				    =  word.upper()
			_UpperCamelCase				:Dict				    =  0
			_UpperCamelCase				:Union[str, Any]				    =  {}
			_UpperCamelCase				:Optional[int]				    =  []

			for letter in word:
						if letter not in letter_nums:
									_UpperCamelCase				:Dict				    =  str(snake_case__		)
									next_num += 1
						word_pattern.append(letter_nums[letter]		)
			return ".".join(snake_case__		)


if __name__ == "__main__":
					import pprint
					import time

					UpperCamelCase__							:Dict       =  time.time()
					with open("""dictionary.txt""") as in_file:
										UpperCamelCase__							:str       =  in_file.read().splitlines()

					UpperCamelCase__							:dict       =  {}
					for word in word_list:
										UpperCamelCase__							:List[Any]       =  get_word_pattern(word)
										if pattern in all_patterns:
															all_patterns[pattern].append(word)
										else:
															UpperCamelCase__							:Tuple       =  [word]

					with open("""word_patterns.txt""", """w""") as out_file:
										out_file.write(pprint.pformat(all_patterns))

					UpperCamelCase__							:Dict       =  round(time.time() - start_time, 2)
					print(F"""Done!  {len(all_patterns):,} word patterns found in {total_time} seconds.""")
					# Done!  9,581 word patterns found in 0.58 seconds.

