"""simple docstring"""







from collections import Counter
from functools import total_ordering

from data_structures.heap.heap import Heap

@total_ordering
class 						UpperCamelCase     :



				def __init__(self							: List[Any]      ,    _A							: str      ,    _A							: int)       ->      None:
					__snake_case     :				Tuple 						=					word
					__snake_case     :				Optional[Any] 						=					count



				def __eq__(self							: int      ,    _A							: object)       ->      bool:
					if not isinstance(_A      ,    _A):
						return NotImplemented
					return self.count == other.count






				def __lt__(self							: Optional[int]      ,    _A							: object)       ->      bool:
					if not isinstance(_A      ,    _A):
						return NotImplemented
					return self.count < other.count







def     __UpperCAmelCase							(       UpperCAmelCase_       :							list[str]     ,				UpperCAmelCase_       :							int    )				->     list[str]:

	'''simple docstring'''





	__snake_case     :				Heap[WordCount] 						=					Heap()
	__snake_case     :				List[str] 						=					Counter(UpperCAmelCase_    )
	heap.build_max_heap(
	    [WordCount(UpperCAmelCase_     ,				UpperCAmelCase_    ) for word, count in count_by_word.items()]    )
	return [heap.extract_max().word for _ in range(min(UpperCAmelCase_     ,				len(UpperCAmelCase_    )    )    )]


if __name__ == "__main__":
	import doctest

	doctest.testmod()






"""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


_a	:	Union[str, Any]=					"Here is a text containing a lot of information: '''{text}'''.\n\nCan you answer this question about the text: '{question}'"

class 						UpperCamelCase     (       lowercase		):
				UpperCAmelCase							: str       =						"""google/flan-t5-base"""
				UpperCAmelCase							: int       =						(
				    """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							: Dict       =						"""text_qa"""
				UpperCAmelCase							: Dict       =						AutoTokenizer
				UpperCAmelCase							: Optional[Any]       =						AutoModelForSeqaSeqLM

				UpperCAmelCase							: List[str]       =						["""text""", """text"""]
				UpperCAmelCase							: Any       =						["""text"""]



				def    _lowercase	(self							: Tuple      ,    _A							: str      ,    _A							: str)       ->      Tuple:
					__snake_case     :				List[Any] 						=					QA_PROMPT.format(text=_A      ,    question=_A)
					return self.pre_processor(_A      ,    return_tensors='pt')



				def    _lowercase	(self							: Tuple      ,    _A							: Optional[Any])       ->      List[Any]:
					__snake_case     :				List[Any] 						=					self.model.generate(**_A)

					__snake_case						,							__snake_case     :				Any 						=					inputs['input_ids'].shape
					__snake_case     :				Any 						=					output_ids.shape[0]

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






				def    _lowercase	(self							: Optional[int]      ,    _A							: int)       ->      str:
					return self.pre_processor.decode(_A      ,    skip_special_tokens=_A      ,    clean_up_tokenization_spaces=_A)





