





import mpmath  # for roots of unity
import numpy as np




class        _a    :

      """simple docstring"""


      def __init__(		self:			List[Any]	,    __lowerCamelCase:			List[str]=None	,    __lowerCamelCase:			str=None					):
          '''simple docstring'''


          UpperCamelCase__:	Tuple					=     list(poly_a or [0]					)[:]
          UpperCamelCase__:	int					=     list(poly_b or [0]					)[:]

          # Remove leading zero coefficients
          while self.polyA[-1] == 0:
              self.polyA.pop()
          UpperCamelCase__:	Union[str, Any]					=     len(self.polyA					)

          while self.polyB[-1] == 0:
              self.polyB.pop()
          UpperCamelCase__:	Optional[int]					=     len(self.polyB					)

          # Add 0 to make lengths equal a power of 2
          UpperCamelCase__:	Optional[Any]					=     int(
              2 ** np.ceil(np.loga(len(self.polyA					) + len(self.polyB					) - 1					)					)					)

          while len(self.polyA					) < self.c_max_length:
              self.polyA.append(0					)
          while len(self.polyB					) < self.c_max_length:
              self.polyB.append(0					)
          # A complex root used for the fourier transform
          UpperCamelCase__:	Tuple					=     complex(mpmath.root(x=1	,    n=self.c_max_length	,    k=1					)					)

          # The product
          UpperCamelCase__:	Union[str, Any]					=     self.__multiply()






      def 			UpperCAmelCase_       (		self:			Tuple	,    __lowerCamelCase:			Any					):
          '''simple docstring'''


          UpperCamelCase__:	List[str]					=     [[x] for x in self.polyA] if which == "A" else [[x] for x in self.polyB]
          # Corner case
          if len(__lowerCamelCase					) <= 1:
              return dft[0]
          #
          UpperCamelCase__:	Union[str, Any]					=     self.c_max_length // 2
          while next_ncol > 0:
              UpperCamelCase__:	List[str]					=     [[] for i in range(__lowerCamelCase					)]
              UpperCamelCase__:	str					=     self.root**next_ncol

              # First half of next step
              UpperCamelCase__:	List[str]					=     1
              for j in range(self.c_max_length // (next_ncol * 2)					):
                  for i in range(__lowerCamelCase					):
                      new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j]					)
                  current_root *= root
              # Second half of next step
              UpperCamelCase__:	List[str]					=     1
              for j in range(self.c_max_length // (next_ncol * 2)					):
                  for i in range(__lowerCamelCase					):
                      new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j]					)
                  current_root *= root
              # Update
              UpperCamelCase__:	Tuple					=     new_dft
              UpperCamelCase__:	Union[str, Any]					=     next_ncol // 2
          return dft[0]






      def 			UpperCAmelCase_       (		self:			List[Any]					):
          '''simple docstring'''


          UpperCamelCase__:	List[str]					=     self.__dft("A"					)
          UpperCamelCase__:	int					=     self.__dft("B"					)
          UpperCamelCase__:	Tuple					=     [[dft_a[i] * dft_b[i] for i in range(self.c_max_length					)]]
          del dft_a
          del dft_b

          # Corner Case
          if len(inverce_c[0]					) <= 1:
              return inverce_c[0]
          # Inverse DFT
          UpperCamelCase__:	Optional[int]					=     2
          while next_ncol <= self.c_max_length:
              UpperCamelCase__:	int					=     [[] for i in range(__lowerCamelCase					)]
              UpperCamelCase__:	Any					=     self.root ** (next_ncol // 2)
              UpperCamelCase__:	Dict					=     1
              # First half of next step
              for j in range(self.c_max_length // next_ncol					):
                  for i in range(next_ncol // 2					):
                      # Even positions
                      new_inverse_c[i].append(
                          (
                              inverce_c[i][j]
                              + inverce_c[i][j + self.c_max_length // next_ncol]
                          )
                          / 2					)
                      # Odd positions
                      new_inverse_c[i + next_ncol // 2].append(
                          (
                              inverce_c[i][j]
                              - inverce_c[i][j + self.c_max_length // next_ncol]
                          )
                          / (2 * current_root)					)
                  current_root *= root
              # Update
              UpperCamelCase__:	List[str]					=     new_inverse_c
              next_ncol *= 2
          # Unpack
          UpperCamelCase__:	Optional[Any]					=     [round(x[0].real	,    8					) + round(x[0].imag	,    8					) * 1J for x in inverce_c]

          # Remove leading 0's
          while inverce_c[-1] == 0:
              inverce_c.pop()
          return inverce_c






      def __str__(		self:			List[str]					):
          '''simple docstring'''


          UpperCamelCase__:	int					=     "A = " + " + ".join(
              F"{coef}*x^{i}" for coef, i in enumerate(self.polyA[: self.len_A]					)					)
          UpperCamelCase__:	Union[str, Any]					=     "B = " + " + ".join(
              F"{coef}*x^{i}" for coef, i in enumerate(self.polyB[: self.len_B]					)					)
          UpperCamelCase__:	Any					=     "A*B = " + " + ".join(
              F"{coef}*x^{i}" for coef, i in enumerate(self.product					)					)

          return F"{a}\n{b}\n{c}"


# Unit tests
if __name__ == "__main__":
   import doctest

   doctest.testmod()








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


A__:    Tuple  	=	logging.get_logger(__name__)

A__:    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        _a    (    UpperCamelCase__						,			UpperCamelCase__):

      """simple docstring"""


      UpperCamelCase__  		=       """swin"""

      UpperCamelCase__  		=       {
          """num_attention_heads""": """num_heads""",
          """num_hidden_layers""": """num_layers""",
      }






      def __init__(		self:			Any	,    __lowerCamelCase:			Optional[Any]=224	,    __lowerCamelCase:			List[Any]=4	,    __lowerCamelCase:			Any=3	,    __lowerCamelCase:			Dict=96	,    __lowerCamelCase:			List[str]=[2, 2, 6, 2]	,    __lowerCamelCase:			int=[3, 6, 12, 24]	,    __lowerCamelCase:			str=7	,    __lowerCamelCase:			Union[str, Any]=4.0	,    __lowerCamelCase:			Union[str, Any]=True	,    __lowerCamelCase:			List[str]=0.0	,    __lowerCamelCase:			Union[str, Any]=0.0	,    __lowerCamelCase:			List[str]=0.1	,    __lowerCamelCase:			Union[str, Any]="gelu"	,    __lowerCamelCase:			List[str]=False	,    __lowerCamelCase:			Any=0.02	,    __lowerCamelCase:			Any=1e-5	,    __lowerCamelCase:			Optional[Any]=32	,    __lowerCamelCase:			Tuple=None	,    __lowerCamelCase:			int=None	,    **__lowerCamelCase:			int	,    ):
          '''simple docstring'''


          super().__init__(**__lowerCamelCase					)

          UpperCamelCase__:	List[Any]					=     image_size
          UpperCamelCase__:	str					=     patch_size
          UpperCamelCase__:	Optional[int]					=     num_channels
          UpperCamelCase__:	Dict					=     embed_dim
          UpperCamelCase__:	int					=     depths
          UpperCamelCase__:	List[str]					=     len(__lowerCamelCase					)
          UpperCamelCase__:	List[Any]					=     num_heads
          UpperCamelCase__:	Union[str, Any]					=     window_size
          UpperCamelCase__:	Dict					=     mlp_ratio
          UpperCamelCase__:	List[Any]					=     qkv_bias
          UpperCamelCase__:	Union[str, Any]					=     hidden_dropout_prob
          UpperCamelCase__:	int					=     attention_probs_dropout_prob
          UpperCamelCase__:	str					=     drop_path_rate
          UpperCamelCase__:	str					=     hidden_act
          UpperCamelCase__:	Any					=     use_absolute_embeddings
          UpperCamelCase__:	Union[str, Any]					=     layer_norm_eps
          UpperCamelCase__:	Tuple					=     initializer_range
          UpperCamelCase__:	Tuple					=     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
          UpperCamelCase__:	Any					=     int(embed_dim * 2 ** (len(__lowerCamelCase					) - 1)					)
          UpperCamelCase__:	str					=     ["stem"] + [F"stage{idx}" for idx in range(1	,    len(__lowerCamelCase					) + 1					)]
          UpperCamelCase__				, UpperCamelCase__:	List[str]					=     get_aligned_output_features_output_indices(
              out_features=__lowerCamelCase	,    out_indices=__lowerCamelCase	,    stage_names=self.stage_names					)




class        _a    (    UpperCamelCase__):

      """simple docstring"""


      UpperCamelCase__  		=       version.parse("""1.11""")






      @property
      def 			UpperCAmelCase_       (		self:			List[Any]					):
          '''simple docstring'''


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






      @property
      def 			UpperCAmelCase_       (		self:			Union[str, Any]					):
          '''simple docstring'''


          return 1e-4

