from __future__ import annotations

from collections.abc import Callable
from typing import Any, Generic, TypeVar

lowerCAmelCase			:							Optional[int]     =TypeVar("T")




class 	__snake_case	( Generic[T]		):





      '''simple docstring'''






      def __init__(					self     :				Tuple    ,  _UpperCamelCase     :				list[T]    ,  _UpperCamelCase     :				Callable[[T, T], T])				->None:


          """simple docstring"""


          _lowerCamelCase     :		Any | T 						=						None

          _lowerCamelCase     :		int 						=						len(_UpperCamelCase)
          _lowerCamelCase     :		list[T] 						=						[any_type for _ in range(self.N)] + arr
          _lowerCamelCase     :		List[Any] 						=						fnc
          self.build()



      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[int])				->None:


          """simple docstring"""


          for p in range(self.N - 1    ,  0    ,  -1):
              _lowerCamelCase     :		Tuple 						=						self.fn(self.st[p * 2]    ,  self.st[p * 2 + 1])



      def 	_SCREAMING_SNAKE_CASE    (					self     :				List[Any]    ,  _UpperCamelCase     :				int    ,  _UpperCamelCase     :				T)				->None:


          """simple docstring"""


          p += self.N
          _lowerCamelCase     :		List[Any] 						=						v
          while p > 1:
              _lowerCamelCase     :		Union[str, Any] 						=						p // 2
              _lowerCamelCase     :		List[Any] 						=						self.fn(self.st[p * 2]    ,  self.st[p * 2 + 1])




      def 	_SCREAMING_SNAKE_CASE    (					self     :				Optional[int]    ,  _UpperCamelCase     :				int    ,  _UpperCamelCase     :				int)				->T | None:  # noqa: E741


          """simple docstring"""


          _lowerCamelCase						,							_lowerCamelCase     :		List[str] 						=						l + self.N, r + self.N

          _lowerCamelCase     :		T | None 						=						None
          while l <= r:
              if l % 2 == 1:
                  _lowerCamelCase     :		int 						=						self.st[l] if res is None else self.fn(_UpperCamelCase    ,  self.st[l])
              if r % 2 == 0:
                  _lowerCamelCase     :		List[Any] 						=						self.st[r] if res is None else self.fn(_UpperCamelCase    ,  self.st[r])
              _lowerCamelCase						,							_lowerCamelCase     :		Tuple 						=						(l + 1) // 2, (r - 1) // 2
          return res


if __name__ == "__main__":
    from functools import reduce

    lowerCAmelCase			:							Optional[int]     =[1, 10, -2, 9, -3, 8, 4, -7, 5, 6, 11, -12]

    lowerCAmelCase			:							str     ={
        0: 7,
        1: 2,
        2: 6,
        3: -14,
        4: 5,
        5: 4,
        6: 7,
        7: -10,
        8: 9,
        9: 10,
        10: 12,
        11: 1,
    }

    lowerCAmelCase			:							Union[str, Any]     =SegmentTree(test_array, min)
    lowerCAmelCase			:							Any     =SegmentTree(test_array, max)
    lowerCAmelCase			:							Any     =SegmentTree(test_array, lambda a, b: a + b)







    def 						A__  (					):







        '''simple docstring'''
        for i in range(len(__A	)	):
            for j in range(__A   , len(__A	)	):
                _lowerCamelCase     :		Optional[int] 						=						reduce(__A   , test_array[i : j + 1]	)
                _lowerCamelCase     :		Union[str, Any] 						=						reduce(__A   , test_array[i : j + 1]	)
                _lowerCamelCase     :		Union[str, Any] 						=						reduce(lambda __A   , __A	: a + b   , test_array[i : j + 1]	)
                assert min_range == min_segment_tree.query(__A   , __A	)
                assert max_range == max_segment_tree.query(__A   , __A	)
                assert sum_range == sum_segment_tree.query(__A   , __A	)

    test_all_segments()

    for index, value in test_updates.items():
        lowerCAmelCase			:							Union[str, Any]     =value
        min_segment_tree.update(index, value)
        max_segment_tree.update(index, value)
        sum_segment_tree.update(index, value)
        test_all_segments()





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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowerCAmelCase			:							Any     =logging.get_logger(__name__)

lowerCAmelCase			:							List[Any]     ={
    "microsoft/swin-tiny-patch4-window7-224": (
        "https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json"
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}




class 	__snake_case	( __lowerCAmelCase ,  __lowerCAmelCase		):





      '''simple docstring'''






      _snake_case    		=       'swin'

      _snake_case    		=       {
          'num_attention_heads': 'num_heads',
          'num_hidden_layers': 'num_layers',
      }



      def __init__(					self     :				Optional[int]    ,  _UpperCamelCase     :				List[str]=224    ,  _UpperCamelCase     :				List[str]=4    ,  _UpperCamelCase     :				List[Any]=3    ,  _UpperCamelCase     :				Dict=96    ,  _UpperCamelCase     :				Any=[2, 2, 6, 2]    ,  _UpperCamelCase     :				Any=[3, 6, 12, 24]    ,  _UpperCamelCase     :				Tuple=7    ,  _UpperCamelCase     :				Tuple=4.0    ,  _UpperCamelCase     :				Dict=True    ,  _UpperCamelCase     :				Tuple=0.0    ,  _UpperCamelCase     :				Any=0.0    ,  _UpperCamelCase     :				Optional[int]=0.1    ,  _UpperCamelCase     :				Any="gelu"    ,  _UpperCamelCase     :				str=False    ,  _UpperCamelCase     :				str=0.0_2    ,  _UpperCamelCase     :				Dict=1E-5    ,  _UpperCamelCase     :				List[str]=32    ,  _UpperCamelCase     :				Optional[Any]=None    ,  _UpperCamelCase     :				List[Any]=None    ,  **_UpperCamelCase     :				List[Any]    ,  )				->Tuple:


          """simple docstring"""


          super().__init__(**_UpperCamelCase)

          _lowerCamelCase     :		List[str] 						=						image_size
          _lowerCamelCase     :		Tuple 						=						patch_size
          _lowerCamelCase     :		Dict 						=						num_channels
          _lowerCamelCase     :		Union[str, Any] 						=						embed_dim
          _lowerCamelCase     :		str 						=						depths
          _lowerCamelCase     :		str 						=						len(_UpperCamelCase)
          _lowerCamelCase     :		Optional[Any] 						=						num_heads
          _lowerCamelCase     :		Tuple 						=						window_size
          _lowerCamelCase     :		int 						=						mlp_ratio
          _lowerCamelCase     :		Optional[int] 						=						qkv_bias
          _lowerCamelCase     :		List[str] 						=						hidden_dropout_prob
          _lowerCamelCase     :		str 						=						attention_probs_dropout_prob
          _lowerCamelCase     :		Tuple 						=						drop_path_rate
          _lowerCamelCase     :		List[str] 						=						hidden_act
          _lowerCamelCase     :		Dict 						=						use_absolute_embeddings
          _lowerCamelCase     :		int 						=						layer_norm_eps
          _lowerCamelCase     :		str 						=						initializer_range
          _lowerCamelCase     :		Dict 						=						encoder_stride
          # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
          # this indicates the channel dimension after the last stage of the model
          _lowerCamelCase     :		int 						=						int(embed_dim * 2 ** (len(_UpperCamelCase) - 1))
          _lowerCamelCase     :		Dict 						=						["""stem"""] + [F"""stage{idx}""" for idx in range(1    ,  len(_UpperCamelCase) + 1)]
          _lowerCamelCase						,							_lowerCamelCase     :		List[str] 						=						get_aligned_output_features_output_indices(
              out_features=_UpperCamelCase    ,  out_indices=_UpperCamelCase    ,  stage_names=self.stage_names)





class 	__snake_case	( __lowerCAmelCase		):





      '''simple docstring'''






      _snake_case    		=       version.parse('1.11'		)



      @property
      def 	_SCREAMING_SNAKE_CASE    (					self     :				Tuple)				->Mapping[str, Mapping[int, str]]:


          """simple docstring"""


          return OrderedDict(
              [
                  ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
              ])




      @property
      def 	_SCREAMING_SNAKE_CASE    (					self     :				Union[str, Any])				->float:


          """simple docstring"""


          return 1E-4




