



# 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				:					Union[str, Any]     					="""Here is a text containing a lot of information: '''{text}'''.

Can you answer this question about the text: '{question}'"""
class lowerCAmelCase_       (   A_			):







	'''simple docstring'''




	A_       :     Optional[Any]									=		'google/flan-t5-base'
	A_       :     Union[str, Any]									=		(
	    '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_       :     Any									=		'text_qa'
	A_       :     str									=		AutoTokenizer
	A_       :     Optional[int]									=		AutoModelForSeqaSeqLM

	A_       :     List[Any]									=		['text', 'text']
	A_       :     List[Any]									=		['text']

	def 				_A			(	self   ,       lowerCamelCase   ,       lowerCamelCase       ):



				'''simple docstring'''


				a__					=  QA_PROMPT.format(text=lowerCamelCase   ,       question=lowerCamelCase       )
				return self.pre_processor(lowerCamelCase   ,       return_tensors="""pt"""       )

	def 				_A			(	self   ,       lowerCamelCase       ):



				'''simple docstring'''


				a__					=  self.model.generate(**lowerCamelCase       )

				a__				,       a__					=  inputs["""input_ids"""].shape
				a__					=  output_ids.shape[0]

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







	def 				_A			(	self   ,       lowerCamelCase       ):



				'''simple docstring'''


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






def    UpperCAmelCase					(  lowercase__						:					List[Any]				,					lowercase__						:					Optional[int]	):



			'''simple docstring'''





			print("""\nVertex Distance"""	)
			for i in range(lowercase__	):
						if dist[i] != float("""inf"""	):
									print(lowercase__				,					"""\t"""				,					int(dist[i]	)				,					end="""\t"""	)
						else:
									print(lowercase__				,					"""\t"""				,					"""INF"""				,					end="""\t"""	)
						print()




def    UpperCAmelCase					(  lowercase__						:					Optional[int]				,					lowercase__						:					Any				,					lowercase__						:					Tuple	):



			'''simple docstring'''





			a__					=  float("""inf"""	)
			a__					=  -1
			for i in range(lowercase__	):
						if (not vset[i]) and mdist[i] < min_val:
									a__					=  i
									a__					=  mdist[i]
			return min_ind




def    UpperCAmelCase					(  lowercase__						:					Optional[Any]				,					lowercase__						:					Tuple				,					lowercase__						:					List[Any]	):



			'''simple docstring'''





			a__					=  [float("""inf"""	) for _ in range(lowercase__	)]
			a__					=  [False for _ in range(lowercase__	)]
			a__					=  0.0

			for _ in range(v - 1	):
						a__					=  min_dist(lowercase__				,					lowercase__				,					lowercase__	)
						a__					=  True

						for i in range(lowercase__	):
									if (
									    (not vset[i])
									    and graph[u][i] != float("""inf"""	)
									    and mdist[u] + graph[u][i] < mdist[i]
									):
												a__					=  mdist[u] + graph[u][i]

			print_dist(lowercase__				,					lowercase__	)


if __name__ == "__main__":
	_lowercase				:					Any     					=int(input("""Enter number of vertices: """).strip())
	_lowercase				:					List[str]     					=int(input("""Enter number of edges: """).strip())

	_lowercase				:					List[str]     					=[[float("""inf""") for i in range(V)] for j in range(V)]

	for i in range(V):
		_lowercase				:					Dict     					=0.0

	for i in range(E):
		print("""\nEdge """, i + 1)
		_lowercase				:					Dict     					=int(input("""Enter source:""").strip())
		_lowercase				:					Optional[Any]     					=int(input("""Enter destination:""").strip())
		_lowercase				:					List[Any]     					=float(input("""Enter weight:""").strip())
		_lowercase				:					List[str]     					=weight

	_lowercase				:					List[Any]     					=int(input("""\nEnter shortest path source:""").strip())
	dijkstra(graph, V, gsrc)

