


from __future__ import annotations






class      UpperCamelCase:


					def __init__(    self						:		Union[str, Any]  ,     SCREAMING_SNAKE_CASE						:		int    )      ->						None:




											'''simple docstring'''

											__snake_case				=		order

											# a_{0} ... a_{k}
											__snake_case				=		[1.0] + [0.0] * order
											# b_{0} ... b_{k}
											__snake_case				=		[1.0] + [0.0] * order

											# x[n-1] ... x[n-k]
											__snake_case				=		[0.0] * self.order
											# y[n-1] ... y[n-k]
											__snake_case				=		[0.0] * self.order


					def 				SCREAMING_SNAKE_CASE_	(    self						:		str  ,     SCREAMING_SNAKE_CASE						:		list[float]  ,     SCREAMING_SNAKE_CASE						:		list[float]    )      ->						None:




											'''simple docstring'''

											if len(SCREAMING_SNAKE_CASE    ) < self.order:
																	__snake_case				=		[1.0, *a_coeffs]

											if len(SCREAMING_SNAKE_CASE    ) != self.order + 1:
																	__snake_case				=		(
																	    f'''Expected a_coeffs to have {self.order + 1} elements '''
																	    f'''for {self.order}-order filter, got {len(SCREAMING_SNAKE_CASE    )}'''
																	)
																	raise ValueError(SCREAMING_SNAKE_CASE    )

											if len(SCREAMING_SNAKE_CASE    ) != self.order + 1:
																	__snake_case				=		(
																	    f'''Expected b_coeffs to have {self.order + 1} elements '''
																	    f'''for {self.order}-order filter, got {len(SCREAMING_SNAKE_CASE    )}'''
																	)
																	raise ValueError(SCREAMING_SNAKE_CASE    )

											__snake_case				=		a_coeffs
											__snake_case				=		b_coeffs






					def 				SCREAMING_SNAKE_CASE_	(    self						:		Any  ,     SCREAMING_SNAKE_CASE						:		float    )      ->						float:




											'''simple docstring'''

											__snake_case				=		0.0

											# Start at index 1 and do index 0 at the end.
											for i in range(1  ,     self.order + 1    ):
																	result += (
																	    self.b_coeffs[i] * self.input_history[i - 1]
																	    - self.a_coeffs[i] * self.output_history[i - 1]
																	)

											__snake_case				=		(result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

											__snake_case				=		self.input_history[:-1]
											__snake_case				=		self.output_history[:-1]

											__snake_case				=		sample
											__snake_case				=		result

											return result









from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A				:       Optional[Any]      =  {'configuration_van': ['VAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VanConfig']}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A				:       Optional[Any]      =  [
	    'VAN_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'VanForImageClassification',
	    'VanModel',
	    'VanPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_van import (
		    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    VanForImageClassification,
		    VanModel,
		    VanPreTrainedModel,
		)

else:
	import sys

	A				:       Union[str, Any]      =  _LazyModule(__name__, globals()['__file__'], _import_structure)





