

import mpmath  # for roots of unity
import numpy as np






class _UpperCamelCase				:
			'''simple docstring'''







			def __init__(      self				:			Any   ,   a				:			Any=None   ,   a				:			List[Any]=None						)				->							int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Optional[int]					  =							list(poly_a or [0]						)[:]
				SCREAMING_SNAKE_CASE :   str					  =							list(poly_b or [0]						)[:]

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

				while self.polyB[-1] == 0:
					self.polyB.pop()
				SCREAMING_SNAKE_CASE :   Dict					  =							len(self.polyB						)

				# Add 0 to make lengths equal a power of 2
				SCREAMING_SNAKE_CASE :   str					  =							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
				SCREAMING_SNAKE_CASE :   Any					  =							complex(mpmath.root(x=1   ,   n=self.c_max_length   ,   k=1						)						)

				# The product
				SCREAMING_SNAKE_CASE :   Any					  =							self.__multiply()
			def 				__UpperCamelCase			(      self				:			int   ,   a				:			List[Any]						)				->							int:

				"""simple docstring"""

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

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

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Tuple					  =							self.__dft("A"						)
				SCREAMING_SNAKE_CASE :   int					  =							self.__dft("B"						)
				SCREAMING_SNAKE_CASE :   Optional[Any]					  =							[[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
				SCREAMING_SNAKE_CASE :   List[str]					  =							2
				while next_ncol <= self.c_max_length:
					SCREAMING_SNAKE_CASE :   Any					  =							[[] for i in range(a						)]
					SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							self.root ** (next_ncol // 2)
					SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							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
					SCREAMING_SNAKE_CASE :   List[str]					  =							new_inverse_c
					next_ncol *= 2
				# Unpack
				SCREAMING_SNAKE_CASE :   List[str]					  =							[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				:			int						)				->							Dict:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							"A = " + " + ".join(
				    F"{coef}*x^{i}" for coef, i in enumerate(self.polyA[: self.len_A]						)						)
				SCREAMING_SNAKE_CASE :   Tuple					  =							"B = " + " + ".join(
				    F"{coef}*x^{i}" for coef, i in enumerate(self.polyB[: self.len_B]						)						)
				SCREAMING_SNAKE_CASE :   List[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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_      =     {
    'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_      =     [
			    'SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'Swinv2ForImageClassification',
			    'Swinv2ForMaskedImageModeling',
			    'Swinv2Model',
			    'Swinv2PreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_swinva import (
						    SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
						    SwinvaForImageClassification,
						    SwinvaForMaskedImageModeling,
						    SwinvaModel,
						    SwinvaPreTrainedModel,
						)


else:
			import sys

			a_      =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)