






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        __UpperCamelCase    (     unittest.TestCase   ):







	@require_torch
	def  _a   (  self      :							Any			)		-> Optional[Any]:
					"""simple docstring"""







					__lowercase             =  pipeline(
					    task="""zero-shot-audio-classification"""       ,				model="""hf-internal-testing/tiny-clap-htsat-unfused"""			)
					__lowercase             =  load_dataset("""ashraq/esc50"""			)
					__lowercase             =  dataset["""train"""]["""audio"""][-1]["""array"""]
					__lowercase             =  audio_classifier(_lowerCAmelCase       ,				candidate_labels=["""Sound of a dog""", """Sound of vaccum cleaner"""]			)
					self.assertEqual(
					    nested_simplify(_lowerCAmelCase			)       ,				[{"""score""": 0.501, """label""": """Sound of a dog"""}, {"""score""": 0.499, """label""": """Sound of vaccum cleaner"""}]       ,				)







	@unittest.skip("""No models are available in TF"""			)
	def  _a   (  self      :							Any			)		-> int:
					"""simple docstring"""







					pass







	@slow
	@require_torch
	def  _a   (  self      :							Tuple			)		-> Tuple:
					"""simple docstring"""







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

					self.assertEqual(
					    nested_simplify(_lowerCAmelCase			)       ,				[
					        {"""score""": 0.999, """label""": """Sound of a dog"""},
					        {"""score""": 0.001, """label""": """Sound of vaccum cleaner"""},
					    ]       ,				)

					__lowercase             =  audio_classifier([audio] * 5       ,				candidate_labels=["""Sound of a dog""", """Sound of vaccum cleaner"""]			)
					self.assertEqual(
					    nested_simplify(_lowerCAmelCase			)       ,				[
					        [
					            {"""score""": 0.999, """label""": """Sound of a dog"""},
					            {"""score""": 0.001, """label""": """Sound of vaccum cleaner"""},
					        ],
					    ]
					    * 5       ,				)
					__lowercase             =  audio_classifier(
					    [audio] * 5       ,				candidate_labels=["""Sound of a dog""", """Sound of vaccum cleaner"""]       ,				batch_size=5			)
					self.assertEqual(
					    nested_simplify(_lowerCAmelCase			)       ,				[
					        [
					            {"""score""": 0.999, """label""": """Sound of a dog"""},
					            {"""score""": 0.001, """label""": """Sound of vaccum cleaner"""},
					        ],
					    ]
					    * 5       ,				)







	@unittest.skip("""No models are available in TF"""			)
	def  _a   (  self      :							Union[str, Any]			)		-> int:
					"""simple docstring"""







					pass









from math import sqrt





def 				snake_case  (     lowerCamelCase					):




	'''simple docstring'''







	if 1 < number < 4:
		# 2 and 3 are primes
		return True
	elif number < 2 or number % 2 == 0 or number % 3 == 0:
		# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
		return False

	# All primes number are in format of 6k +/- 1
	for i in range(5				,  int(sqrt(lowerCamelCase					) + 1					)				,  6					):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True





def 				snake_case  (     lowerCamelCase = 10_001					):




	'''simple docstring'''







	__lowercase             =  0
	__lowercase             =  1
	while count != nth and number < 3:
		number += 1
		if is_prime(lowerCamelCase					):
			count += 1
	while count != nth:
		number += 2
		if is_prime(lowerCamelCase					):
			count += 1
	return number


if __name__ == "__main__":
						print(F'''{solution() = }''')

