


import math
from typing import Optional

import numpy as np

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


SCREAMING_SNAKE_CASE       :      Union[str, Any]												= logging.get_logger(__name__)

SCREAMING_SNAKE_CASE       :      int												= {
    "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   ):
       lowercase_ :	int     =			"""encodec"""
       def __init__(					self,      lowerCamelCase=[1.5, 3.0, 6.0, 1_2.0, 2_4.0],      lowerCamelCase=2_40_00,      lowerCamelCase=1,      lowerCamelCase=False,      lowerCamelCase=None,      lowerCamelCase=None,      lowerCamelCase=1_28,      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=10_24,      lowerCamelCase=None,      lowerCamelCase=True,      **lowerCamelCase,      )       ->   Optional[int]:




           """simple docstring"""

           _lowercase       :							List[Any]      		=		target_bandwidths
           _lowercase       :							Dict      		=		sampling_rate
           _lowercase       :							List[Any]      		=		audio_channels
           _lowercase       :							Any      		=		normalize
           _lowercase       :							str      		=		chunk_length_s
           _lowercase       :							Tuple      		=		overlap
           _lowercase       :							str      		=		hidden_size
           _lowercase       :							List[Any]      		=		num_filters
           _lowercase       :							Tuple      		=		num_residual_layers
           _lowercase       :							Union[str, Any]      		=		upsampling_ratios
           _lowercase       :							Union[str, Any]      		=		norm_type
           _lowercase       :							Optional[int]      		=		kernel_size
           _lowercase       :							List[str]      		=		last_kernel_size
           _lowercase       :							Optional[Any]      		=		residual_kernel_size
           _lowercase       :							Union[str, Any]      		=		dilation_growth_rate
           _lowercase       :							Tuple      		=		use_causal_conv
           _lowercase       :							Tuple      		=		pad_mode
           _lowercase       :							str      		=		compress
           _lowercase       :							List[str]      		=		num_lstm_layers
           _lowercase       :							Optional[Any]      		=		trim_right_ratio
           _lowercase       :							List[Any]      		=		codebook_size
           _lowercase       :							Dict      		=		codebook_dim if codebook_dim is not None else hidden_size
           _lowercase       :							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__(**lowerCamelCase)
       @property
       def 			UpperCamelCase     (					self)       ->   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 			UpperCamelCase     (					self)       ->   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 			UpperCamelCase     (					self)       ->   int:




           """simple docstring"""

           _lowercase       :							Optional[int]      		=		np.prod(self.upsampling_ratios)
           return math.ceil(self.sampling_rate / hop_length)




       @property
       def 			UpperCamelCase     (					self)       ->   int:




           """simple docstring"""

           return int(10_00 * self.target_bandwidths[-1] // (self.frame_rate * 10))






from __future__ import annotations



def 				UpperCamelCase_(      lowerCamelCase_ )    ->						bool:
    if len(lowerCamelCase_ ) < 2:
        raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
    if any(i <= 0 for i in nums ):
        raise ValueError('All values must be greater than 0' )
    _lowercase       :							Tuple      		=		nums.copy()
    copy_nums.sort()
    return copy_nums[-1] < sum(copy_nums[:-1] )


if __name__ == "__main__":
 import doctest

 doctest.testmod()


