


"""simple docstring"""





import math
from typing import Optional

import numpy as np

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


snake_case__						:   Any			 = logging.get_logger(__name__)

snake_case__						:   Dict			 = {
    '''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 						snake_case_(				_a	):
     __UpperCamelCase     =    """encodec"""






     def __init__(		self     :    Any    , UpperCamelCase_     :    List[Any]=[1.5, 3.0, 6.0, 12.0, 24.0]    , UpperCamelCase_     :    str=2_4_0_0_0    , UpperCamelCase_     :    List[Any]=1    , UpperCamelCase_     :    Union[str, Any]=False    , UpperCamelCase_     :    List[str]=None    , UpperCamelCase_     :    Dict=None    , UpperCamelCase_     :    Optional[Any]=1_2_8    , UpperCamelCase_     :    Any=3_2    , UpperCamelCase_     :    str=1    , UpperCamelCase_     :    str=[8, 5, 4, 2]    , UpperCamelCase_     :    Union[str, Any]="weight_norm"    , UpperCamelCase_     :    Tuple=7    , UpperCamelCase_     :    Tuple=7    , UpperCamelCase_     :    Tuple=3    , UpperCamelCase_     :    Optional[int]=2    , UpperCamelCase_     :    Any=True    , UpperCamelCase_     :    str="reflect"    , UpperCamelCase_     :    Any=2    , UpperCamelCase_     :    int=2    , UpperCamelCase_     :    str=1.0    , UpperCamelCase_     :    str=1_0_2_4    , UpperCamelCase_     :    Any=None    , UpperCamelCase_     :    Union[str, Any]=True    , **UpperCamelCase_     :    Dict    , ):
           lowerCAmelCase    :		Any				=      target_bandwidths
           lowerCAmelCase    :		str				=      sampling_rate
           lowerCAmelCase    :		Union[str, Any]				=      audio_channels
           lowerCAmelCase    :		Optional[int]				=      normalize
           lowerCAmelCase    :		Optional[Any]				=      chunk_length_s
           lowerCAmelCase    :		str				=      overlap
           lowerCAmelCase    :		List[str]				=      hidden_size
           lowerCAmelCase    :		List[str]				=      num_filters
           lowerCAmelCase    :		Union[str, Any]				=      num_residual_layers
           lowerCAmelCase    :		Tuple				=      upsampling_ratios
           lowerCAmelCase    :		Tuple				=      norm_type
           lowerCAmelCase    :		List[str]				=      kernel_size
           lowerCAmelCase    :		Tuple				=      last_kernel_size
           lowerCAmelCase    :		Union[str, Any]				=      residual_kernel_size
           lowerCAmelCase    :		Union[str, Any]				=      dilation_growth_rate
           lowerCAmelCase    :		Any				=      use_causal_conv
           lowerCAmelCase    :		str				=      pad_mode
           lowerCAmelCase    :		Dict				=      compress
           lowerCAmelCase    :		Union[str, Any]				=      num_lstm_layers
           lowerCAmelCase    :		List[Any]				=      trim_right_ratio
           lowerCAmelCase    :		str				=      codebook_size
           lowerCAmelCase    :		Optional[int]				=      codebook_dim if codebook_dim is not None else hidden_size
           lowerCAmelCase    :		int				=      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    lowerCamelCase__   (		self     :    Union[str, Any] ):
           if self.chunk_length_s is None:
                 return None
           else:
                 return int(self.chunk_length_s * self.sampling_rate )






     @property
     def    lowerCamelCase__   (		self     :    Union[str, Any] ):
           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    lowerCamelCase__   (		self     :    List[str] ):
           lowerCAmelCase    :		Optional[int]				=      np.prod(self.upsampling_ratios )
           return math.ceil(self.sampling_rate / hop_length )






     @property
     def    lowerCamelCase__   (		self     :    List[str] ):
           return int(1_0_0_0 * self.target_bandwidths[-1] // (self.frame_rate * 1_0) )






"""simple docstring"""







def      lowercase			(				A_       )->      str:
  '''simple docstring'''







  if isinstance(A_  ,   A_       ):
    raise TypeError("'float' object cannot be interpreted as an integer"       )
  if isinstance(A_  ,   A_       ):
    raise TypeError("'str' object cannot be interpreted as an integer"       )

  if num == 0:
    return "0b0"

  a						:		Optional[Any]      							=			False

  if num < 0:
    a						:		Tuple      							=			True
    a						:		str      							=			-num

  a						:		list[int]      							=			[]
  while num > 0:
    binary.insert(0  ,   num % 2       )
    num >>= 1

  if negative:
    return "-0b" + "".join(str(A_       ) for e in binary       )

  return "0b" + "".join(str(A_       ) for e in binary       )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






