


'''simple docstring'''



import math
from typing import Optional

import numpy as np

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


__lowercase     :						List[str]	=     logging.get_logger(__name__)

__lowercase     :						Optional[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 							__UpperCamelCase    (		lowerCAmelCase_ ):
	A_           =   "encodec"




	def __init__(       self						,    __a=[1.5, 3.0, 6.0, 12.0, 24.0]						,    __a=2_4000						,    __a=1						,    __a=False						,    __a=None						,    __a=None						,    __a=128						,    __a=32						,    __a=1						,    __a=[8, 5, 4, 2]						,    __a="weight_norm"						,    __a=7						,    __a=7						,    __a=3						,    __a=2						,    __a=True						,    __a="reflect"						,    __a=2						,    __a=2						,    __a=1.0						,    __a=1024						,    __a=None						,    __a=True						,    **__a						,    ):

						'''simple docstring'''





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




	@property
	def 				__UpperCAmelCase							(       self							):

						'''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							):

						'''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							):

						'''simple docstring'''





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





	@property
	def 				__UpperCAmelCase							(       self							):

						'''simple docstring'''





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







'''simple docstring'''



def   lowerCamelCase							(_SCREAMING_SNAKE_CASE				:       int						,				_SCREAMING_SNAKE_CASE				:       int       ):
					if not isinstance(_SCREAMING_SNAKE_CASE						,				_SCREAMING_SNAKE_CASE       ):
										raise ValueError('iterations must be defined as integers'       )
					if not isinstance(_SCREAMING_SNAKE_CASE						,				_SCREAMING_SNAKE_CASE       ) or not number >= 1:
										raise ValueError(
										    'starting number must be\n                         and integer and be more than 0'       )
					if not iterations >= 1:
										raise ValueError('Iterations must be done more than 0 times to play FizzBuzz'       )

					__a      :	Dict    =  ''
					while number <= iterations:
										if number % 3 == 0:
															out += "Fizz"
										if number % 5 == 0:
															out += "Buzz"
										if 0 not in (number % 3, number % 5):
															out += str(_SCREAMING_SNAKE_CASE       )

										# print(out)
										number += 1
										out += " "
					return out


if __name__ == "__main__":
	import doctest

	doctest.testmod()



