





# 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 					__lowerCAmelCase       (			_a     ):
			lowerCamelCase_     :     int       			=      '''philschmid/bart-large-cnn-samsum'''
			lowerCamelCase_     :     List[str]       			=      (
			    '''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.'''
			)
			lowerCamelCase_     :     Optional[Any]       			=      '''summarizer'''
			lowerCamelCase_     :     str       			=      AutoTokenizer
			lowerCamelCase_     :     Any       			=      AutoModelForSeqaSeqLM

			lowerCamelCase_     :     Optional[int]       			=      ['''text''']
			lowerCamelCase_     :     Dict       			=      ['''text''']






			def 			lowerCamelCase  (self					,							__magic_name__    )     ->   Any:


							'''simple docstring'''



							return self.pre_processor(__magic_name__					,							return_tensors='''pt'''					,							truncation=__magic_name__    )






			def 			lowerCamelCase  (self					,							__magic_name__    )     ->   Any:


							'''simple docstring'''



							return self.model.generate(**__magic_name__    )[0]






			def 			lowerCamelCase  (self					,							__magic_name__    )     ->   Union[str, Any]:


							'''simple docstring'''



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







from math import factorial

lowerCAmelCase_    =				{str(digit): factorial(digit) for digit in range(1_0)}






def      lowerCamelCase_						(				_UpperCamelCase )		->						int:






				"""simple docstring"""


				if not isinstance(_UpperCamelCase ,				_UpperCamelCase ):
								raise TypeError('''Parameter number must be int''' )

				if number < 0:
								raise ValueError('''Parameter number must be greater than or equal to 0''' )

				# Converts number in string to iterate on its digits and adds its factorial.
				return sum(DIGIT_FACTORIAL[digit] for digit in str(_UpperCamelCase ) )






def      lowerCamelCase_						(				_UpperCamelCase = 60 ,				_UpperCamelCase = 1_000_000 )		->						int:






				"""simple docstring"""


				if not isinstance(_UpperCamelCase ,				_UpperCamelCase ) or not isinstance(_UpperCamelCase ,				_UpperCamelCase ):
								raise TypeError('''Parameters chain_length and number_limit must be int''' )

				if chain_length <= 0 or number_limit <= 0:
								raise ValueError(
								    '''Parameters chain_length and number_limit must be greater than 0''' )

				# the counter for the chains with the exact desired length
				snake_case_						:    Optional[Any]				=  0
				# the cached sizes of the previous chains
				snake_case_						:    dict[int, int]				=  {}

				for start_chain_element in range(1 ,				_UpperCamelCase ):
								# The temporary set will contain the elements of the chain
								snake_case_						:    List[str]				=  set()
								snake_case_						:    List[Any]				=  0

								# Stop computing the chain when you find a cached size, a repeating item or the
								# length is greater then the desired one.
								snake_case_						:    Any				=  start_chain_element
								while (
								    chain_element not in chain_sets_lengths
								    and chain_element not in chain_set
								    and chain_set_length <= chain_length
								):
												chain_set.add(_UpperCamelCase )
												chain_set_length += 1
												snake_case_						:    List[Any]				=  digit_factorial_sum(_UpperCamelCase )

								if chain_element in chain_sets_lengths:
												chain_set_length += chain_sets_lengths[chain_element]

								snake_case_						:    List[str]				=  chain_set_length

								# If chain contains the exact amount of elements increase the counter
								if chain_set_length == chain_length:
												chains_counter += 1

				return chains_counter


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	print(F'''{solution()}''')
