






"""simple docstring"""



from __future__ import annotations



def 						lowercase    (				__snake_case				: str		,					__snake_case				: list[str] | None = None	):
		lowercase_ : Dict							       =   word_bank or []
		# create a table
		lowercase_ : int							       =   len(__snake_case	) + 1

		lowercase_ : list[list[list[str]]]							       =   []
		for _ in range(__snake_case	):
				table.append([]	)
		# seed value
		lowercase_ : str							       =   [[]]  # because empty string has empty combination

		# iterate through the indices
		for i in range(__snake_case	):
				# condition
				if table[i] != []:
						for word in word_bank:
								# slice condition
								if target[i : i + len(__snake_case	)] == word:
										lowercase_ : list[list[str]]							       =   [
										    [word, *way] for way in table[i]
										]
										# adds the word to every combination the current position holds
										# now,push that combination to the table[i+len(word)]
										table[i + len(__snake_case	)] += new_combinations

    # combinations are in reverse order so reverse for better output
		for combination in table[len(__snake_case	)]:
				combination.reverse()

		return table[len(__snake_case	)]


if __name__ == "__main__":
						print(all_construct('''jwajalapa''', ['''jwa''', '''j''', '''w''', '''a''', '''la''', '''lapa''']))
						print(all_construct('''rajamati''', ['''s''', '''raj''', '''amat''', '''raja''', '''ma''', '''i''', '''t''']))
						print(
						    all_construct(
						        '''hexagonosaurus''',
						        ['''h''', '''ex''', '''hex''', '''ag''', '''ago''', '''ru''', '''auru''', '''rus''', '''go''', '''no''', '''o''', '''s'''],
						    )
						)











"""simple docstring"""



import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


__A		:       Dict  				=		'''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
'''





class 					_UpperCAmelCase       ( unittest.TestCase   ,						_A							):




					def   A  (				self     :						List[Any]   )  ->  Dict:
							lowercase_ : Optional[int]							       =   load_tool('''text-question-answering'''   )
							self.tool.setup()
							lowercase_ : Union[str, Any]							       =   load_tool('''text-question-answering'''    ,						remote=A   )




					def   A  (				self     :						Any   )  ->  List[str]:
							lowercase_ : Union[str, Any]							       =   self.tool(A    ,						'''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )




					def   A  (				self     :						str   )  ->  List[str]:
							lowercase_ : int							       =   self.remote_tool(A    ,						'''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )




					def   A  (				self     :						List[Any]   )  ->  int:
							lowercase_ : Optional[Any]							       =   self.tool(text=A    ,						question='''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )






					def   A  (				self     :						List[str]   )  ->  Optional[int]:
							lowercase_ : int							       =   self.remote_tool(text=A    ,						question='''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )



