





'''simple docstring'''




import math



def 		__A		(  lowerCamelCase_			,			lowerCamelCase_	):


		"""simple docstring"""



		SCREAMING_SNAKE_CASE :				List[str]		=			len(lowerCamelCase_	)
		SCREAMING_SNAKE_CASE :				Tuple		=			int(math.floor(math.sqrt(lowerCamelCase_	)	)	)
		SCREAMING_SNAKE_CASE :				int		=			0
		while arr[min(lowerCamelCase_			,			lowerCamelCase_	) - 1] < x:
				SCREAMING_SNAKE_CASE :				int		=			step
				step += int(math.floor(math.sqrt(lowerCamelCase_	)	)	)
				if prev >= n:
						return -1

		while arr[prev] < x:
				SCREAMING_SNAKE_CASE :				Any		=			prev + 1
				if prev == min(lowerCamelCase_			,			lowerCamelCase_	):
						return -1
		if arr[prev] == x:
				return prev
		return -1


if __name__ == "__main__":
							__UpperCAmelCase            =       input("""Enter numbers separated by a comma:\n""").strip()
							__UpperCAmelCase            =       [int(item) for item in user_input.split(""",""")]
							__UpperCAmelCase            =       int(input("""Enter the number to be searched:\n"""))
							__UpperCAmelCase            =       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 ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


__UpperCAmelCase            =       {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCAmelCase            =       ["""GPTNeoXTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCAmelCase            =       [
							    """GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """GPTNeoXForCausalLM""",
							    """GPTNeoXForQuestionAnswering""",
							    """GPTNeoXForSequenceClassification""",
							    """GPTNeoXForTokenClassification""",
							    """GPTNeoXLayer""",
							    """GPTNeoXModel""",
							    """GPTNeoXPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_gpt_neox import (
														    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
														    GPTNeoXForCausalLM,
														    GPTNeoXForQuestionAnswering,
														    GPTNeoXForSequenceClassification,
														    GPTNeoXForTokenClassification,
														    GPTNeoXLayer,
														    GPTNeoXModel,
														    GPTNeoXPreTrainedModel,
														)


else:
							import sys

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



