
class     lowercase		:




							def __init__(    self       ,A__):
												lowercase						     =						len(A__)
												lowercase						     =						[0] * len_array

												if len_array > 0:
																	lowercase						     =						array[0]

												for i in range(1       ,A__):
																	lowercase						     =						self.prefix_sum[i - 1] + array[i]




							def 			A__				(    self       ,A__       ,A__):
												if start == 0:
																	return self.prefix_sum[end]

												return self.prefix_sum[end] - self.prefix_sum[start - 1]





							def 			A__				(    self       ,A__):
												lowercase						     =						{0}
												for sum_item in self.prefix_sum:
																	if sum_item - target_sum in sums:
																						return True

																	sums.add(A__)

												return False


if __name__ == "__main__":
							import doctest

							doctest.testmod()






from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowercase__		:Union[str, Any]			  =   {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:List[Any]			  =   ["DPTFeatureExtractor"]
							lowercase__		:List[Any]			  =   ["DPTImageProcessor"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Optional[int]			  =   [
							    "DPT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "DPTForDepthEstimation",
							    "DPTForSemanticSegmentation",
							    "DPTModel",
							    "DPTPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_dpt import DPTFeatureExtractor
														from .image_processing_dpt import DPTImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_dpt import (
														    DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DPTForDepthEstimation,
														    DPTForSemanticSegmentation,
														    DPTModel,
														    DPTPreTrainedModel,
														)


else:
							import sys

							lowercase__		:List[Any]			  =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




