
"""simple docstring"""

import unittest

from datasets import load_dataset

from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow

@is_pipeline_test
@require_torch
class __lowerCAmelCase		(				unittest.TestCase      ):





     @require_torch
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	pipeline(
          task='zero-shot-audio-classification'     ,					model='hf-internal-testing/tiny-clap-htsat-unfused'				)
      __UpperCamelCase      =	load_dataset('ashraq/esc50'				)
      __UpperCamelCase      =	dataset['train']['audio'][-1]['array']
      __UpperCamelCase      =	audio_classifier(__UpperCAmelCase     ,					candidate_labels=['Sound of a dog', 'Sound of vaccum cleaner']				)
      self.assertEqual(
          nested_simplify(__UpperCAmelCase				)     ,					[{'score': 0.5_0_1, 'label': 'Sound of a dog'}, {'score': 0.4_9_9, 'label': 'Sound of vaccum cleaner'}]     ,					)





     @unittest.skip('No models are available in TF'				)
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      pass





     @slow
     @require_torch
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	pipeline(
          task='zero-shot-audio-classification'     ,					model='laion/clap-htsat-unfused'     ,					)
      # This is an audio of a dog
      __UpperCamelCase      =	load_dataset('ashraq/esc50'				)
      __UpperCamelCase      =	dataset['train']['audio'][-1]['array']
      __UpperCamelCase      =	audio_classifier(__UpperCAmelCase     ,					candidate_labels=['Sound of a dog', 'Sound of vaccum cleaner']				)

      self.assertEqual(
          nested_simplify(__UpperCAmelCase				)     ,					[
              {'score': 0.9_9_9, 'label': 'Sound of a dog'},
              {'score': 0.0_0_1, 'label': 'Sound of vaccum cleaner'},
          ]     ,					)

      __UpperCamelCase      =	audio_classifier([audio] * 5     ,					candidate_labels=['Sound of a dog', 'Sound of vaccum cleaner']				)
      self.assertEqual(
          nested_simplify(__UpperCAmelCase				)     ,					[
              [
                  {'score': 0.9_9_9, 'label': 'Sound of a dog'},
                  {'score': 0.0_0_1, 'label': 'Sound of vaccum cleaner'},
              ],
          ]
          * 5     ,					)
      __UpperCamelCase      =	audio_classifier(
          [audio] * 5     ,					candidate_labels=['Sound of a dog', 'Sound of vaccum cleaner']     ,					batch_size=5				)
      self.assertEqual(
          nested_simplify(__UpperCAmelCase				)     ,					[
              [
                  {'score': 0.9_9_9, 'label': 'Sound of a dog'},
                  {'score': 0.0_0_1, 'label': 'Sound of vaccum cleaner'},
              ],
          ]
          * 5     ,					)







     @unittest.skip('No models are available in TF'				)
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      pass





"""simple docstring"""

def 							A						(    snake_case				:list[list[int]]    , snake_case				:int    , snake_case				:int    , snake_case				:list[int]		)				->     bool:

 # 1. Validate that path exists between current and next vertices
 if graph[path[curr_ind - 1]][next_ver] == 0:
  return False

 # 2. Validate that next vertex is not already in path
 return not any(vertex == next_ver for vertex in path		)






def 							A						(    snake_case				:list[list[int]]    , snake_case				:list[int]    , snake_case				:int		)				->     bool:

 # Base Case
 if curr_ind == len(snake_case		):
  # return whether path exists between current and starting vertices
  return graph[path[curr_ind - 1]][path[0]] == 1

 # Recursive Step
 for next_ver in range(0    , len(snake_case		)		):
  if valid_connection(snake_case    , snake_case    , snake_case    , snake_case		):
   # Insert current vertex  into path as next transition
   __UpperCamelCase      =	next_ver
   # Validate created path
   if util_hamilton_cycle(snake_case    , snake_case    , curr_ind + 1		):
    return True
   # Backtrack
   __UpperCamelCase      =	-1
 return False






def 							A						(    snake_case				:list[list[int]]    , snake_case				:int = 0		)				->     list[int]:
 __UpperCamelCase      =	[-1] * (len(snake_case		) + 1)
 # initialize start and end of path with starting index
 __UpperCamelCase      =	__UpperCamelCase      =	start_index
 # evaluate and if we find answer return path either return empty array
 return path if util_hamilton_cycle(snake_case    , snake_case    , 1		) else []



