


"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__SCREAMING_SNAKE_CASE					=						logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE					=						{
    """apple/mobilevit-small""": """https://huggingface.co/apple/mobilevit-small/resolve/main/config.json""",
    """apple/mobilevit-x-small""": """https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json""",
    """apple/mobilevit-xx-small""": """https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json""",
    """apple/deeplabv3-mobilevit-small""": (
        """https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json"""
    ),
    """apple/deeplabv3-mobilevit-x-small""": (
        """https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json"""
    ),
    """apple/deeplabv3-mobilevit-xx-small""": (
        """https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json"""
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}





class __snake_case		(					_SCREAMING_SNAKE_CASE      ):







   """simple docstring"""




   lowerCAmelCase_				:   Dict     	=			'mobilevit'




   def __init__(		self							:List[Any]				,  UpperCamelCase__							:Tuple=3				,  UpperCamelCase__							:Optional[int]=256				,  UpperCamelCase__							:Union[str, Any]=2				,  UpperCamelCase__							:List[Any]=[144, 192, 240]				,  UpperCamelCase__							:Optional[Any]=[16, 32, 64, 96, 128, 160, 640]				,  UpperCamelCase__							:Any=4				,  UpperCamelCase__							:int=2.0				,  UpperCamelCase__							:Dict=4.0				,  UpperCamelCase__							:Dict="silu"				,  UpperCamelCase__							:List[Any]=3				,  UpperCamelCase__							:List[str]=32				,  UpperCamelCase__							:Union[str, Any]=0.1				,  UpperCamelCase__							:List[Any]=0.0				,  UpperCamelCase__							:int=0.1				,  UpperCamelCase__							:List[Any]=0.02				,  UpperCamelCase__							:List[str]=1E-5				,  UpperCamelCase__							:List[str]=True				,  UpperCamelCase__							:List[Any]=256				,  UpperCamelCase__							:Optional[int]=[6, 12, 18]				,  UpperCamelCase__							:Any=0.1				,  UpperCamelCase__							:List[str]=255				,  **UpperCamelCase__							:Any				,  ):
          super().__init__(**UpperCamelCase__       )

          _a          =				num_channels
          _a          =				image_size
          _a          =				patch_size
          _a          =				hidden_sizes
          _a          =				neck_hidden_sizes
          _a          =				num_attention_heads
          _a          =				mlp_ratio
          _a          =				expand_ratio
          _a          =				hidden_act
          _a          =				conv_kernel_size
          _a          =				output_stride
          _a          =				hidden_dropout_prob
          _a          =				attention_probs_dropout_prob
          _a          =				classifier_dropout_prob
          _a          =				initializer_range
          _a          =				layer_norm_eps
          _a          =				qkv_bias

          # decode head attributes for semantic segmentation
          _a          =				aspp_out_channels
          _a          =				atrous_rates
          _a          =				aspp_dropout_prob
          _a          =				semantic_loss_ignore_index






class __snake_case		(					_SCREAMING_SNAKE_CASE      ):







   """simple docstring"""




   lowerCAmelCase_				:   int     	=			version.parse('1.11'      )




   @property
   def SCREAMING_SNAKE_CASE_      (		self							:Union[str, Any]       ):
          return OrderedDict([("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"})]       )




   @property
   def SCREAMING_SNAKE_CASE_      (		self							:List[Any]       ):
          if self.task == "image-classification":
                 return OrderedDict([("logits", {0: "batch"})]       )
          else:
                 return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]       )




   @property
   def SCREAMING_SNAKE_CASE_      (		self							:Dict       ):
          return 1E-4




"""simple docstring"""




from __future__ import annotations

__SCREAMING_SNAKE_CASE					=						[2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]





class __snake_case		:







   """simple docstring"""




   def __init__(		self							:Optional[Any]				,  UpperCamelCase__							:int       ):
          _a          =				-1
          _a          =				-1
          _a          =				[-1] * length
          _a          =				None
          _a          =				None




   def __repr__(		self							:Optional[Any]       ):
          return f'Node(min_value={self.minn} max_value={self.maxx})'






def 						__a      (  a					):





       """simple docstring"""







       _a          =				Node(len(a					)					)
       _a   , _a          =				min(a					), max(a					)
       # Leaf node case where the node contains only one unique value
       if root.minn == root.maxx:
              return root
       _a          =				(root.minn + root.maxx) // 2

       _a          =				[]
       _a          =				[]

       for index, num in enumerate(a					):
              if num <= pivot:
                     left_arr.append(a					)
              else:
                     right_arr.append(a					)
              _a          =				len(a					)
       _a          =				build_tree(a					)
       _a          =				build_tree(a					)
       return root



def 						__a      (  a,		a,		a					):





       """simple docstring"""







       if index < 0 or node is None:
              return 0
       # Leaf node cases
       if node.minn == node.maxx:
              return index + 1 if node.minn == num else 0
       _a          =				(node.minn + node.maxx) // 2
       if num <= pivot:
              # go the left subtree and map index to the left subtree
              return rank_till_index(node.left,		a,		node.map_left[index] - 1					)
       else:
              # go to the right subtree and map index to the right subtree
              return rank_till_index(node.right,		a,		index - node.map_left[index]					)



def 						__a      (  a,		a,		a,		a					):





       """simple docstring"""







       if start > end:
              return 0
       _a          =				rank_till_index(a,		a,		a					)
       _a          =				rank_till_index(a,		a,		start - 1					)
       return rank_till_end - rank_before_start



def 						__a      (  a,		a,		a,		a					):





       """simple docstring"""







       if index > (end - start) or start > end or node is None:
              return -1
       # Leaf node case
       if node.minn == node.maxx:
              return node.minn
       # Number of elements in the left subtree in interval [start, end]
       _a          =				node.map_left[end] - (
           node.map_left[start - 1] if start else 0
       )
       if num_elements_in_left_tree > index:
              return quantile(
                  node.left,		a,		(node.map_left[start - 1] if start else 0),		node.map_left[end] - 1,		)
       else:
              return quantile(
                  node.right,		index - num_elements_in_left_tree,		start - (node.map_left[start - 1] if start else 0),		end - node.map_left[end],		)



def 						__a      (  a,		a,		a,		a,		a					):





       """simple docstring"""







       if (
           start > end
           or node is None
           or start_num > end_num
           or node.minn > end_num
           or node.maxx < start_num
       ):
              return 0
       if start_num <= node.minn and node.maxx <= end_num:
              return end - start + 1
       _a          =				range_counting(
           node.left,		(node.map_left[start - 1] if start else 0),		node.map_left[end] - 1,		a,		a,		)
       _a          =				range_counting(
           node.right,		start - (node.map_left[start - 1] if start else 0),		end - node.map_left[end],		a,		a,		)
       return left + right


if __name__ == "__main__":
   import doctest

   doctest.testmod()
