






import math
from typing import Optional

import numpy as np

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


A_       :Optional[Any]       =						logging.get_logger(__name__)

A_       :Optional[Any]       =						{
    '''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 				__A     (			lowerCamelCase__ ):





				"""simple docstring"""







				UpperCamelCase__ :      str			 ='encodec'


				def __init__( self							,  lowerCamelCase__=[1.5, 3.0, 6.0, 12.0, 24.0]							,  lowerCamelCase__=24000							,  lowerCamelCase__=1							,  lowerCamelCase__=False							,  lowerCamelCase__=None							,  lowerCamelCase__=None							,  lowerCamelCase__=128							,  lowerCamelCase__=32							,  lowerCamelCase__=1							,  lowerCamelCase__=[8, 5, 4, 2]							,  lowerCamelCase__="weight_norm"							,  lowerCamelCase__=7							,  lowerCamelCase__=7							,  lowerCamelCase__=3							,  lowerCamelCase__=2							,  lowerCamelCase__=True							,  lowerCamelCase__="reflect"							,  lowerCamelCase__=2							,  lowerCamelCase__=2							,  lowerCamelCase__=1.0							,  lowerCamelCase__=1024							,  lowerCamelCase__=None							,  lowerCamelCase__=True							,  **lowerCamelCase__							,  ):




									"""simple docstring"""

									__UpperCamelCase      :					int       		=target_bandwidths
									__UpperCamelCase      :					Optional[int]       		=sampling_rate
									__UpperCamelCase      :					Optional[Any]       		=audio_channels
									__UpperCamelCase      :					List[str]       		=normalize
									__UpperCamelCase      :					Union[str, Any]       		=chunk_length_s
									__UpperCamelCase      :					List[str]       		=overlap
									__UpperCamelCase      :					Optional[Any]       		=hidden_size
									__UpperCamelCase      :					List[Any]       		=num_filters
									__UpperCamelCase      :					Tuple       		=num_residual_layers
									__UpperCamelCase      :					List[Any]       		=upsampling_ratios
									__UpperCamelCase      :					Tuple       		=norm_type
									__UpperCamelCase      :					Optional[int]       		=kernel_size
									__UpperCamelCase      :					str       		=last_kernel_size
									__UpperCamelCase      :					str       		=residual_kernel_size
									__UpperCamelCase      :					List[Any]       		=dilation_growth_rate
									__UpperCamelCase      :					List[Any]       		=use_causal_conv
									__UpperCamelCase      :					Tuple       		=pad_mode
									__UpperCamelCase      :					str       		=compress
									__UpperCamelCase      :					Union[str, Any]       		=num_lstm_layers
									__UpperCamelCase      :					int       		=trim_right_ratio
									__UpperCamelCase      :					str       		=codebook_size
									__UpperCamelCase      :					Any       		=codebook_dim if codebook_dim is not None else hidden_size
									__UpperCamelCase      :					Tuple       		=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__(**lowercase_    )


				@property
				def       __lowercase							( self    ):




									"""simple docstring"""

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


				@property
				def       __lowercase							( self    ):




									"""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       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					List[Any]       		=np.prod(self.upsampling_ratios    )
									return math.ceil(self.sampling_rate / hop_length    )







				@property
				def       __lowercase							( self    ):




									"""simple docstring"""

									return int(1000 * self.target_bandwidths[-1] // (self.frame_rate * 10)    )




from __future__ import annotations




def 			UpperCAmelCase__				(			_A      : float	,      _A      : float	,      _A      : float	,      ):





  '''simple docstring'''







  if (stress, tangential_force, area).count(0							) != 1:
    raise ValueError('''You cannot supply more or less than 2 values'''							)
  elif stress < 0:
    raise ValueError('''Stress cannot be negative'''							)
  elif tangential_force < 0:
    raise ValueError('''Tangential Force cannot be negative'''							)
  elif area < 0:
    raise ValueError('''Area cannot be negative'''							)
  elif stress == 0:
    return (
        "stress",
        tangential_force / area,
    )
  elif tangential_force == 0:
    return (
        "tangential_force",
        stress * area,
    )
  else:
    return (
        "area",
        tangential_force / stress,
    )


if __name__ == "__main__":
       import doctest

       doctest.testmod()
