





"""simple docstring"""






import math
from typing import Optional

import numpy as np

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


A	     =					logging.get_logger(__name__)

A	     =					{
    '''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 			__lowercase     (     _UpperCamelCase							):







     '''simple docstring'''




     __lowerCAmelCase					=					'''encodec'''







     def __init__(  self		,     _UpperCAmelCase=[1.5, 3.0, 6.0, 12.0, 24.0]		,     _UpperCAmelCase=24000		,     _UpperCAmelCase=1		,     _UpperCAmelCase=False		,     _UpperCAmelCase=None		,     _UpperCAmelCase=None		,     _UpperCAmelCase=128		,     _UpperCAmelCase=32		,     _UpperCAmelCase=1		,     _UpperCAmelCase=[8, 5, 4, 2]		,     _UpperCAmelCase="weight_norm"		,     _UpperCAmelCase=7		,     _UpperCAmelCase=7		,     _UpperCAmelCase=3		,     _UpperCAmelCase=2		,     _UpperCAmelCase=True		,     _UpperCAmelCase="reflect"		,     _UpperCAmelCase=2		,     _UpperCAmelCase=2		,     _UpperCAmelCase=1.0		,     _UpperCAmelCase=1024		,     _UpperCAmelCase=None		,     _UpperCAmelCase=True		,     **_UpperCAmelCase		,     ):
         __a	:  List[str]         =					target_bandwidths
         __a	:  List[Any]         =					sampling_rate
         __a	:  Union[str, Any]         =					audio_channels
         __a	:  Tuple         =					normalize
         __a	:  str         =					chunk_length_s
         __a	:  Optional[Any]         =					overlap
         __a	:  Tuple         =					hidden_size
         __a	:  List[Any]         =					num_filters
         __a	:  str         =					num_residual_layers
         __a	:  Optional[Any]         =					upsampling_ratios
         __a	:  List[str]         =					norm_type
         __a	:  List[Any]         =					kernel_size
         __a	:  int         =					last_kernel_size
         __a	:  Tuple         =					residual_kernel_size
         __a	:  Dict         =					dilation_growth_rate
         __a	:  Any         =					use_causal_conv
         __a	:  List[Any]         =					pad_mode
         __a	:  List[Any]         =					compress
         __a	:  Any         =					num_lstm_layers
         __a	:  Optional[int]         =					trim_right_ratio
         __a	:  Tuple         =					codebook_size
         __a	:  str         =					codebook_dim if codebook_dim is not None else hidden_size
         __a	:  Optional[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       ):
         if self.chunk_length_s is None:
             return None
         else:
             return int(self.chunk_length_s * self.sampling_rate       )







     @property
     def 	_lowerCamelCase						(  self       ):
         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       ):
         __a	:  Tuple         =					np.prod(self.upsampling_ratios       )
         return math.ceil(self.sampling_rate / hop_length       )







     @property
     def 	_lowerCamelCase						(  self       ):
         return int(1000 * self.target_bandwidths[-1] // (self.frame_rate * 10)       )






"""simple docstring"""






def       __A (     a_  :int = 1_00_00_00)						->						int:
				__a	:  Tuple         =					[i - 1 for i in range(limit + 1)]

				for i in range(2				,    limit + 1):
								if phi[i] == i - 1:
												for j in range(2 * i				,    limit + 1				,    a_):
																phi[j] -= phi[j] // i

				return sum(phi[2 : limit + 1])


if __name__ == "__main__":
		print(solution())