
import math
from typing import Optional

import numpy as np

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


__lowerCAmelCase					   =       logging.get_logger(__name__)

__lowerCAmelCase					   =       {
    "facebook/encodec_24khz": "https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json",
    "facebook/encodec_48khz": "https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json",
}





class     lowerCamelCase      (       __a					):
	UpperCamelCase_  :					int    		=	'''encodec'''







	def __init__(     self      :List[str]   ,     lowercase      :Optional[Any]=[1.5, 3.0, 6.0, 12.0, 24.0]   ,     lowercase      :Union[str, Any]=2_4_0_0_0   ,     lowercase      :Optional[int]=1   ,     lowercase      :str=False   ,     lowercase      :Optional[Any]=None   ,     lowercase      :str=None   ,     lowercase      :Dict=1_2_8   ,     lowercase      :List[str]=3_2   ,     lowercase      :Tuple=1   ,     lowercase      :Optional[Any]=[8, 5, 4, 2]   ,     lowercase      :List[str]="weight_norm"   ,     lowercase      :Tuple=7   ,     lowercase      :Optional[Any]=7   ,     lowercase      :Any=3   ,     lowercase      :Union[str, Any]=2   ,     lowercase      :List[Any]=True   ,     lowercase      :str="reflect"   ,     lowercase      :Dict=2   ,     lowercase      :int=2   ,     lowercase      :Any=1.0   ,     lowercase      :Any=1_0_2_4   ,     lowercase      :int=None   ,     lowercase      :int=True   ,     **lowercase      :int   ,     )		->      Dict:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= target_bandwidths
				SCREAMING_SNAKE_CASE     						= sampling_rate
				SCREAMING_SNAKE_CASE     						= audio_channels
				SCREAMING_SNAKE_CASE     						= normalize
				SCREAMING_SNAKE_CASE     						= chunk_length_s
				SCREAMING_SNAKE_CASE     						= overlap
				SCREAMING_SNAKE_CASE     						= hidden_size
				SCREAMING_SNAKE_CASE     						= num_filters
				SCREAMING_SNAKE_CASE     						= num_residual_layers
				SCREAMING_SNAKE_CASE     						= upsampling_ratios
				SCREAMING_SNAKE_CASE     						= norm_type
				SCREAMING_SNAKE_CASE     						= kernel_size
				SCREAMING_SNAKE_CASE     						= last_kernel_size
				SCREAMING_SNAKE_CASE     						= residual_kernel_size
				SCREAMING_SNAKE_CASE     						= dilation_growth_rate
				SCREAMING_SNAKE_CASE     						= use_causal_conv
				SCREAMING_SNAKE_CASE     						= pad_mode
				SCREAMING_SNAKE_CASE     						= compress
				SCREAMING_SNAKE_CASE     						= num_lstm_layers
				SCREAMING_SNAKE_CASE     						= trim_right_ratio
				SCREAMING_SNAKE_CASE     						= codebook_size
				SCREAMING_SNAKE_CASE     						= codebook_dim if codebook_dim is not None else hidden_size
				SCREAMING_SNAKE_CASE     						= use_conv_shortcut

				if self.norm_type not in ["weight_norm", "time_group_norm"]:
							raise ValueError(
							    f"""self.norm_type must be one of `\"weight_norm\"`, `\"time_group_norm\"`), got {self.norm_type}"""			)

				super().__init__(**__UpperCamelCase			)







	@property
	def  snake_case__     (     self      :Union[str, Any]			)		->      Optional[int]:







				"""simple docstring"""






				if self.chunk_length_s is None:
							return None
				else:
							return int(self.chunk_length_s * self.sampling_rate			)







	@property
	def  snake_case__     (     self      :Tuple			)		->      Optional[int]:







				"""simple docstring"""






				if self.chunk_length_s is None or self.overlap is None:
							return None
				else:
							return max(1   ,     int((1.0 - self.overlap) * self.chunk_length			)			)







	@property
	def  snake_case__     (     self      :str			)		->      int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= np.prod(self.upsampling_ratios			)
				return math.ceil(self.sampling_rate / hop_length			)







	@property
	def  snake_case__     (     self      :Optional[int]			)		->      int:







				"""simple docstring"""






				return int(1_0_0_0 * self.target_bandwidths[-1] // (self.frame_rate * 1_0)			)
import numpy as np






def     lowerCAmelCase_			(   _SCREAMING_SNAKE_CASE     :				np.array			):
						return (2 / (1 + np.exp(-2 * vector			))) - 1


if __name__ == "__main__":
	import doctest

	doctest.testmod()






