





"""simple docstring"""
import math

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    list  ,     _UpperCAmelCase					:    int			):
 lowerCAmelCase    				= len(_UpperCAmelCase			)
 lowerCAmelCase    				= int(math.floor(math.sqrt(_UpperCAmelCase			)			)			)
 lowerCAmelCase    				= 0
 while arr[min(_UpperCAmelCase  ,     _UpperCAmelCase			) - 1] < x:
  lowerCAmelCase    				= step
  step += int(math.floor(math.sqrt(_UpperCAmelCase			)			)			)
  if prev >= n:
   return -1

 while arr[prev] < x:
  lowerCAmelCase    				= prev + 1
  if prev == min(_UpperCAmelCase  ,     _UpperCAmelCase			):
   return -1
 if arr[prev] == x:
  return prev
 return -1


if __name__ == "__main__":
       __UpperCamelCase     :						str						       =  input('''Enter numbers separated by a comma:\n''').strip()
       __UpperCamelCase     :						Any						       =  [int(item) for item in user_input.split(''',''')]
       __UpperCamelCase     :						Dict						       =  int(input('''Enter the number to be searched:\n'''))
       __UpperCamelCase     :						List[str]						       =  jump_search(arr, x)
       if res == -1:
              print('''Number not found!''')
       else:
              print(f'''Number {x} is at index {res}''')










"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase     =							{"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase     =							[
			    """WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """WavLMForAudioFrameClassification""",
			    """WavLMForCTC""",
			    """WavLMForSequenceClassification""",
			    """WavLMForXVector""",
			    """WavLMModel""",
			    """WavLMPreTrainedModel""",
			]

if TYPE_CHECKING:
			from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_wavlm import (
						    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
						    WavLMForAudioFrameClassification,
						    WavLMForCTC,
						    WavLMForSequenceClassification,
						    WavLMForXVector,
						    WavLMModel,
						    WavLMPreTrainedModel,
						)

else:
			import sys

			UpperCamelCase     =							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




