



'''simple docstring'''



from __future__ import annotations
class 	lowerCamelCase_							:







						def __init__(  self   :      int				,    lowerCAmelCase__   :      int				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			order

													# a_{0} ... a_{k}
													SCREAMING_SNAKE_CASE					:      Any     					=			[1.0] + [0.0] * order
													# b_{0} ... b_{k}
													SCREAMING_SNAKE_CASE					:      str     					=			[1.0] + [0.0] * order

													# x[n-1] ... x[n-k]
													SCREAMING_SNAKE_CASE					:      List[str]     					=			[0.0] * self.order
													# y[n-1] ... y[n-k]
													SCREAMING_SNAKE_CASE					:      Dict     					=			[0.0] * self.order







						def 					__lowercase    (  self   :      Dict				,    lowerCAmelCase__   :      list[float]				,    lowerCAmelCase__   :      list[float]				):

													"""simple docstring"""
													if len(lowerCAmelCase__				) < self.order:
																				SCREAMING_SNAKE_CASE					:      int     					=			[1.0, *a_coeffs]

													if len(lowerCAmelCase__				) != self.order + 1:
																				SCREAMING_SNAKE_CASE					:      str     					=			(
																				    F"""Expected a_coeffs to have {self.order + 1} elements """
																				    F"""for {self.order}-order filter, got {len(lowerCAmelCase__				)}"""
																				)
																				raise ValueError(lowerCAmelCase__				)

													if len(lowerCAmelCase__				) != self.order + 1:
																				SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			(
																				    F"""Expected b_coeffs to have {self.order + 1} elements """
																				    F"""for {self.order}-order filter, got {len(lowerCAmelCase__				)}"""
																				)
																				raise ValueError(lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			a_coeffs
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			b_coeffs







						def 					__lowercase    (  self   :      Any				,    lowerCAmelCase__   :      float				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[str]     					=			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]
																				)

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			(result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

													SCREAMING_SNAKE_CASE					:      Any     					=			self.input_history[:-1]
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.output_history[:-1]

													SCREAMING_SNAKE_CASE					:      Any     					=			sample
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			result

													return result









'''simple docstring'''



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_     :       Optional[int]								=						logging.get_logger(__name__)

lowerCAmelCase_     :       Optional[Any]								=						{
    'microsoft/swinv2-tiny-patch4-window8-256': (
        'https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'
    ),
}
class 	lowerCamelCase_							(					snake_case_			):
						_lowerCAmelCase     :   str	     =				'swinv2'

						_lowerCAmelCase     :   Optional[int]	     =				{
						    'num_attention_heads': 'num_heads',
						    'num_hidden_layers': 'num_layers',
						}







						def __init__(  self   :      Optional[int]				,    lowerCAmelCase__   :      Any=2_24				,    lowerCAmelCase__   :      Optional[Any]=4				,    lowerCAmelCase__   :      Tuple=3				,    lowerCAmelCase__   :      Tuple=96				,    lowerCAmelCase__   :      Optional[int]=[2, 2, 6, 2]				,    lowerCAmelCase__   :      Tuple=[3, 6, 12, 24]				,    lowerCAmelCase__   :      List[str]=7				,    lowerCAmelCase__   :      Tuple=4.0				,    lowerCAmelCase__   :      Dict=True				,    lowerCAmelCase__   :      Any=0.0				,    lowerCAmelCase__   :      Optional[int]=0.0				,    lowerCAmelCase__   :      Optional[Any]=0.1				,    lowerCAmelCase__   :      int="gelu"				,    lowerCAmelCase__   :      Tuple=False				,    lowerCAmelCase__   :      Tuple=0.02				,    lowerCAmelCase__   :      Dict=1e-5				,    lowerCAmelCase__   :      List[str]=32				,    **lowerCAmelCase__   :      Union[str, Any]				,    ):

													"""simple docstring"""
													super().__init__(**lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			image_size
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			patch_size
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			num_channels
													SCREAMING_SNAKE_CASE					:      int     					=			embed_dim
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			depths
													SCREAMING_SNAKE_CASE					:      str     					=			len(lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			num_heads
													SCREAMING_SNAKE_CASE					:      Tuple     					=			window_size
													SCREAMING_SNAKE_CASE					:      Any     					=			mlp_ratio
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			qkv_bias
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			hidden_dropout_prob
													SCREAMING_SNAKE_CASE					:      int     					=			attention_probs_dropout_prob
													SCREAMING_SNAKE_CASE					:      List[str]     					=			drop_path_rate
													SCREAMING_SNAKE_CASE					:      Any     					=			hidden_act
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			use_absolute_embeddings
													SCREAMING_SNAKE_CASE					:      List[str]     					=			layer_norm_eps
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			initializer_range
													SCREAMING_SNAKE_CASE					:      Dict     					=			encoder_stride
													# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
													# this indicates the channel dimension after the last stage of the model
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			int(embed_dim * 2 ** (len(lowerCAmelCase__				) - 1)				)
													SCREAMING_SNAKE_CASE					:      int     					=			(0, 0, 0, 0)




