






def 		_UpperCamelCase      (			UpperCamelCase_				:    list			,				UpperCamelCase_				:    int			,				UpperCamelCase_				:    int			,				UpperCamelCase_				:    int						)     ->      int:

						"""simple docstring"""



						lowerCAmelCase__			  =  int((lower_bound + upper_bound) // 2						)
						if array[r] == value:
												return r
						if lower_bound >= upper_bound:
												return -1
						if array[r] < value:
												return binary_search(UpperCamelCase_			,				r + 1			,				UpperCamelCase_			,				UpperCamelCase_						)
						else:
												return binary_search(UpperCamelCase_			,				UpperCamelCase_			,				r - 1			,				UpperCamelCase_						)







def 		_UpperCamelCase      (			UpperCamelCase_				:    int			,				UpperCamelCase_				:    list						)     ->      list:

						"""simple docstring"""



						lowerCAmelCase__			  =  0
						if matrix[index][0] == value:
												return [index, 0]
						while index < len(UpperCamelCase_						) and matrix[index][0] < value:
												lowerCAmelCase__			  =  binary_search(matrix[index]			,				0			,				len(matrix[index]						) - 1			,				UpperCamelCase_						)
												if r != -1:
																		return [index, r]
												index += 1
						return [-1, -1]


if __name__ == "__main__":
					import doctest

					doctest.testmod()













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case			:			Optional[int]			   =   {"""configuration_sew_d""": ["""SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWDConfig"""]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case			:			List[Any]			   =   [
					    """SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """SEWDForCTC""",
					    """SEWDForSequenceClassification""",
					    """SEWDModel""",
					    """SEWDPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sew_d import (
										    SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SEWDForCTC,
										    SEWDForSequenceClassification,
										    SEWDModel,
										    SEWDPreTrainedModel,
										)


else:
					import sys

					__snake_case			:			Dict			   =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





