from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCamelCase__											=					logging.get_logger(__name__)

UpperCamelCase__											=					{
    'shi-labs/nat-mini-in1k-224': 'https://huggingface.co/shi-labs/nat-mini-in1k-224/resolve/main/config.json',
    # See all Nat models at https://huggingface.co/models?filter=nat
}





class      A							(				UpperCAmelCase_		,				UpperCAmelCase_     ):
   __UpperCAmelCase : str      =			'nat'

   __UpperCAmelCase : Tuple      =			{
       'num_attention_heads': 'num_heads',
       'num_hidden_layers': 'num_layers',
   }


   def __init__(self     :						List[str]       ,  __UpperCAmelCase     :						int=4       ,  __UpperCAmelCase     :						List[str]=3       ,  __UpperCAmelCase     :						str=6_4       ,  __UpperCAmelCase     :						Optional[int]=[3, 4, 6, 5]       ,  __UpperCAmelCase     :						List[Any]=[2, 4, 8, 1_6]       ,  __UpperCAmelCase     :						str=7       ,  __UpperCAmelCase     :						int=3.0       ,  __UpperCAmelCase     :						int=True       ,  __UpperCAmelCase     :						int=0.0       ,  __UpperCAmelCase     :						Optional[Any]=0.0       ,  __UpperCAmelCase     :						Dict=0.1       ,  __UpperCAmelCase     :						int="gelu"       ,  __UpperCAmelCase     :						Dict=0.02       ,  __UpperCAmelCase     :						str=1E-5       ,  __UpperCAmelCase     :						str=0.0       ,  __UpperCAmelCase     :						int=None       ,  __UpperCAmelCase     :						Union[str, Any]=None       ,  **__UpperCAmelCase     :						str       ,  )						->				Union[str, Any]:
         """simple docstring"""



         super().__init__(**__UpperCAmelCase		)

         UpperCAmelCase__								=  patch_size
         UpperCAmelCase__								=  num_channels
         UpperCAmelCase__								=  embed_dim
         UpperCAmelCase__								=  depths
         UpperCAmelCase__								=  len(__UpperCAmelCase		)
         UpperCAmelCase__								=  num_heads
         UpperCAmelCase__								=  kernel_size
         UpperCAmelCase__								=  mlp_ratio
         UpperCAmelCase__								=  qkv_bias
         UpperCAmelCase__								=  hidden_dropout_prob
         UpperCAmelCase__								=  attention_probs_dropout_prob
         UpperCAmelCase__								=  drop_path_rate
         UpperCAmelCase__								=  hidden_act
         UpperCAmelCase__								=  layer_norm_eps
         UpperCAmelCase__								=  initializer_range
         # we set the hidden_size attribute in order to make Nat work with VisionEncoderDecoderModel
         # this indicates the channel dimension after the last stage of the model
         UpperCAmelCase__								=  int(embed_dim * 2 ** (len(__UpperCAmelCase		) - 1)		)
         UpperCAmelCase__								=  layer_scale_init_value
         UpperCAmelCase__								=  ["stem"] + [f"""stage{idx}""" for idx in range(1       ,  len(__UpperCAmelCase		) + 1		)]
         UpperCAmelCase__		,      UpperCAmelCase__								=  get_aligned_output_features_output_indices(
             out_features=__UpperCAmelCase       ,  out_indices=__UpperCAmelCase       ,  stage_names=self.stage_names		)




from __future__ import annotations

from scipy.special import comb  # type: ignore





class      A							:


   def __init__(self     :						List[Any]       ,  __UpperCAmelCase     :						list[tuple[float, float]]		)						->				List[str]:
         """simple docstring"""



         UpperCAmelCase__								=  list_of_points
         # Degree determines the flexibility of the curve.
         # Degree = 1 will produce a straight line.
         UpperCAmelCase__								=  len(__UpperCAmelCase		) - 1


   def 			lowercase_      (self     :						int       ,  __UpperCAmelCase     :						float		)						->				list[float]:
         """simple docstring"""



         assert 0 <= t <= 1, "Time t must be between 0 and 1."
         UpperCAmelCase__								=  []
         for i in range(len(self.list_of_points		)		):
               # basis function for each i
               output_values.append(
                   comb(self.degree       ,  __UpperCAmelCase		) * ((1 - t) ** (self.degree - i)) * (t**i)		)
         # the basis must sum up to 1 for it to produce a valid Bezier curve.
         assert round(sum(__UpperCAmelCase		)       ,  5		) == 1
         return output_values


   def 			lowercase_      (self     :						Dict       ,  __UpperCAmelCase     :						float		)						->				tuple[float, float]:
         """simple docstring"""



         assert 0 <= t <= 1, "Time t must be between 0 and 1."

         UpperCAmelCase__								=  self.basis_function(__UpperCAmelCase		)
         UpperCAmelCase__								=  0.0
         UpperCAmelCase__								=  0.0
         for i in range(len(self.list_of_points		)		):
               # For all points, sum up the product of i-th basis function and i-th point.
               x += basis_function[i] * self.list_of_points[i][0]
               y += basis_function[i] * self.list_of_points[i][1]
         return (x, y)





   def 			lowercase_      (self     :						Optional[int]       ,  __UpperCAmelCase     :						float = 0.01		)						->				Optional[int]:
         """simple docstring"""



         from matplotlib import pyplot as plt  # type: ignore

         UpperCAmelCase__								=  []  # x coordinates of points to plot
         UpperCAmelCase__								=  []  # y coordinates of points to plot

         UpperCAmelCase__								=  0.0
         while t <= 1:
               UpperCAmelCase__								=  self.bezier_curve_function(__UpperCAmelCase		)
               to_plot_x.append(value[0]		)
               to_plot_y.append(value[1]		)
               t += step_size

         UpperCAmelCase__								=  [i[0] for i in self.list_of_points]
         UpperCAmelCase__								=  [i[1] for i in self.list_of_points]

         plt.plot(
             __UpperCAmelCase       ,  __UpperCAmelCase       ,  color="blue"       ,  label="Curve of Degree " + str(self.degree		)       ,  )
         plt.scatter(__UpperCAmelCase       ,  __UpperCAmelCase       ,  color="red"       ,  label="Control Points"		)
         plt.legend()
         plt.show()


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      BezierCurve([(1, 2), (3, 5)]).plot_curve()  # degree 1
      BezierCurve([(0, 0), (5, 5), (5, 0)]).plot_curve()  # degree 2
      BezierCurve([(0, 0), (5, 5), (5, 0), (2.5, -2.5)]).plot_curve()  # degree 3



