




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


_snake_case										=       logging.get_logger(__name__)

_snake_case										=       {
    "facebook/levit-128S": "https://huggingface.co/facebook/levit-128S/resolve/main/config.json",
    # See all LeViT models at https://huggingface.co/models?filter=levit
}







class 						lowercase							(   UpperCamelCase__		):
     _a							 =						"levit"

     def __init__(  self		,     _a=224		,     _a=3		,     _a=3		,     _a=2		,     _a=1		,     _a=16		,     _a=[128, 256, 384]		,     _a=[4, 8, 12]		,     _a=[4, 4, 4]		,     _a=[16, 16, 16]		,     _a=0		,     _a=[2, 2, 2]		,     _a=[2, 2, 2]		,     _a=0.02		,     **_a		,     )						->							Any:
           super().__init__(**_a				)
           _A							:     List[Any]			=						image_size
           _A							:     Union[str, Any]			=						num_channels
           _A							:     Optional[Any]			=						kernel_size
           _A							:     Optional[int]			=						stride
           _A							:     int			=						padding
           _A							:     Optional[int]			=						hidden_sizes
           _A							:     List[str]			=						num_attention_heads
           _A							:     Tuple			=						depths
           _A							:     Any			=						key_dim
           _A							:     Optional[Any]			=						drop_path_rate
           _A							:     Tuple			=						patch_size
           _A							:     Tuple			=						attention_ratio
           _A							:     int			=						mlp_ratio
           _A							:     Any			=						initializer_range
           _A							:     Tuple			=						[
               ["""Subsample""", key_dim[0], hidden_sizes[0] // key_dim[0], 4, 2, 2],
               ["""Subsample""", key_dim[0], hidden_sizes[1] // key_dim[0], 4, 2, 2],
           ]







class 						lowercase							(   UpperCamelCase__		):
     _a							 =						version.parse("1.11"		)

     @property
     def 					a__	(  self				)						->							Mapping[str, Mapping[int, str]]:
           return OrderedDict(
               [
                   ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
               ]				)



     @property
     def 					a__	(  self				)						->							float:
           return 1e-4







def 				lowerCAmelCase_	(     snake_case_,snake_case_     ):
      _enforce_args(snake_case_,snake_case_     )
      if n == 0:
            return 0
      _A							:     Tuple			=						float("""-inf"""     )
      for i in range(1,n + 1     ):
            _A							:     str			=						max(
                snake_case_,prices[i - 1] + naive_cut_rod_recursive(n - i,snake_case_     )     )

      return max_revue







def 				lowerCAmelCase_	(     snake_case_,snake_case_     ):
      _enforce_args(snake_case_,snake_case_     )
      _A							:     Dict			=						[float("""-inf"""     ) for _ in range(n + 1     )]
      return _top_down_cut_rod_recursive(snake_case_,snake_case_,snake_case_     )







def 				lowerCAmelCase_	(     snake_case_,snake_case_,snake_case_     ):
      if max_rev[n] >= 0:
            return max_rev[n]
      elif n == 0:
            return 0
      else:
            _A							:     List[str]			=						float("""-inf"""     )
            for i in range(1,n + 1     ):
                  _A							:     Optional[Any]			=						max(
                      snake_case_,prices[i - 1] + _top_down_cut_rod_recursive(n - i,snake_case_,snake_case_     ),)

            _A							:     Tuple			=						max_revenue

      return max_rev[n]







def 				lowerCAmelCase_	(     snake_case_,snake_case_     ):
      _enforce_args(snake_case_,snake_case_     )

      # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
      # length 0.
      _A							:     List[Any]			=						[float("""-inf"""     ) for _ in range(n + 1     )]
      _A							:     Any			=						0

      for i in range(1,n + 1     ):
            _A							:     Optional[Any]			=						max_rev[i]
            for j in range(1,i + 1     ):
                  _A							:     int			=						max(snake_case_,prices[j - 1] + max_rev[i - j]     )

            _A							:     int			=						max_revenue_i

      return max_rev[n]







def 				lowerCAmelCase_	(     snake_case_,snake_case_     ):
      if n < 0:
            _A							:     Optional[Any]			=						f'''n must be greater than or equal to 0. Got n = {n}'''
            raise ValueError(snake_case_     )

      if n > len(snake_case_     ):
            _A							:     Any			=						(
                """Each integral piece of rod must have a corresponding price. """
                f'''Got n = {n} but length of prices = {len(snake_case_     )}'''
            )
            raise ValueError(snake_case_     )







def 				lowerCAmelCase_	(     ):
      _A							:     Tuple			=						[6, 10, 12, 15, 20, 23]
      _A							:     List[Any]			=						len(snake_case_     )

      # the best revenue comes from cutting the rod into 6 pieces, each
      # of length 1 resulting in a revenue of 6 * 6 = 36.
      _A							:     Any			=						36

      _A							:     List[Any]			=						top_down_cut_rod(snake_case_,snake_case_     )
      _A							:     List[Any]			=						bottom_up_cut_rod(snake_case_,snake_case_     )
      _A							:     Dict			=						naive_cut_rod_recursive(snake_case_,snake_case_     )

      assert expected_max_revenue == max_rev_top_down
      assert max_rev_top_down == max_rev_bottom_up
      assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
  main()

