


"""simple docstring"""






def 			A__		(					_UpperCAmelCase    :      str	)							->	str:

	'''simple docstring'''


	snake_case__  :						str		=      word.upper()
	snake_case__  :						List[Any]		=      0
	snake_case__  :						Union[str, Any]		=      {}
	snake_case__  :						int		=      []

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


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

					lowercase  		=			time.time()
					with open("""dictionary.txt""") as in_file:
										lowercase  		=			in_file.read().splitlines()

					lowercase  		=			{}
					for word in word_list:
										lowercase  		=			get_word_pattern(word)
										if pattern in all_patterns:
															all_patterns[pattern].append(word)
										else:
															lowercase  		=			[word]

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

					lowercase  		=			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.









"""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


lowercase  		=			"""Here is a text containing a lot of information: '''{text}'''.

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


class 			SCREAMING_SNAKE_CASE_  (   _lowercase):




							'''simple docstring'''





							__magic_name__					:     List[Any]				  =  '''google/flan-t5-base'''
							__magic_name__					:     Dict				  =  (
							    '''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.'''
							)
							__magic_name__					:     Union[str, Any]				  =  '''text_qa'''
							__magic_name__					:     Union[str, Any]				  =  AutoTokenizer
							__magic_name__					:     List[Any]				  =  AutoModelForSeqaSeqLM

							__magic_name__					:     Tuple				  =  ['''text''', '''text''']
							__magic_name__					:     Tuple				  =  ['''text''']




							def        UpperCAmelCase (						self	,					lowerCamelCase__	,					lowerCamelCase__)   ->	Optional[int]:







								'''simple docstring'''




								snake_case__  :						str		=      QA_PROMPT.format(text=lowerCamelCase__	,					question=lowerCamelCase__)
								return self.pre_processor(lowerCamelCase__	,					return_tensors="pt")




							def        UpperCAmelCase (						self	,					lowerCamelCase__)   ->	Optional[int]:







								'''simple docstring'''




								snake_case__  :						Tuple		=      self.model.generate(**lowerCamelCase__)

								snake_case__,					snake_case__  :						Dict		=      inputs["input_ids"].shape
								snake_case__  :						List[Any]		=      output_ids.shape[0]

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







							def        UpperCAmelCase (						self	,					lowerCamelCase__)   ->	List[Any]:







								'''simple docstring'''




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





