



'''simple docstring'''







from __future__ import annotations







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     ):
		SCREAMING_SNAKE_CASE_						:str										=      [None] * (len(SCREAMING_SNAKE_CASE     ) + len(SCREAMING_SNAKE_CASE     ))

		SCREAMING_SNAKE_CASE_						:str										=      0  # pointer to current index for left Half
		SCREAMING_SNAKE_CASE_						:Any										=      0  # pointer to current index for the right Half
		SCREAMING_SNAKE_CASE_						:Any										=      0  # pointer to current index for the sorted array Half

		while pointera < len(SCREAMING_SNAKE_CASE     ) and pointera < len(SCREAMING_SNAKE_CASE     ):
				if left_half[pointera] < right_half[pointera]:
						SCREAMING_SNAKE_CASE_						:Any										=      left_half[pointera]
						pointera += 1
						index += 1
				else:
						SCREAMING_SNAKE_CASE_						:Optional[Any]										=      right_half[pointera]
						pointera += 1
						index += 1
		while pointera < len(SCREAMING_SNAKE_CASE     ):
				SCREAMING_SNAKE_CASE_						:int										=      left_half[pointera]
				pointera += 1
				index += 1

		while pointera < len(SCREAMING_SNAKE_CASE     ):
				SCREAMING_SNAKE_CASE_						:Optional[Any]										=      right_half[pointera]
				pointera += 1
				index += 1

		return sorted_array







def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE     ):
		if len(SCREAMING_SNAKE_CASE     ) <= 1:
				return array
		# the actual formula to calculate the middle element = left + (right - left) // 2
		# this avoids integer overflow in case of large N
		SCREAMING_SNAKE_CASE_						:Optional[Any]										=      0 + (len(SCREAMING_SNAKE_CASE     ) - 0) // 2

		# Split the array into halves till the array length becomes equal to One
		# merge the arrays of single length returned by mergeSort function and
		# pass them into the merge arrays function which merges the array
		SCREAMING_SNAKE_CASE_						:List[str]										=      array[:middle]
		SCREAMING_SNAKE_CASE_						:List[Any]										=      array[middle:]

		return merge(merge_sort(SCREAMING_SNAKE_CASE     ) ,		merge_sort(SCREAMING_SNAKE_CASE     )     )


if __name__ == "__main__":
							import doctest

							doctest.testmod()





'''simple docstring'''







from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__     : Dict				=   {"""configuration_detr""": ["""DETR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DetrConfig""", """DetrOnnxConfig"""]}

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : List[Any]				=   ["""DetrFeatureExtractor"""]
							SCREAMING_SNAKE_CASE__     : str				=   ["""DetrImageProcessor"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : Optional[Any]				=   [
							    """DETR_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """DetrForObjectDetection""",
							    """DetrForSegmentation""",
							    """DetrModel""",
							    """DetrPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_detr import DetrFeatureExtractor
														from .image_processing_detr import DetrImageProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_detr import (
														    DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DetrForObjectDetection,
														    DetrForSegmentation,
														    DetrModel,
														    DetrPreTrainedModel,
														)

else:
							import sys

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