"""simple docstring"""







import math
from typing import Optional

import numpy as np

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


_a  :  str=				logging.get_logger(__name__)

_a  :  Union[str, 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 	UpperCamelCase    (					lowercase		):
				UpperCAmelCase       :   Union[str, Any]					=	"""encodec"""



				def __init__(self       :   Tuple			,						_A       :   str=[1.5, 3.0, 6.0, 12.0, 24.0]			,						_A       :   Any=2_40_00			,						_A       :   Union[str, Any]=1			,						_A       :   Optional[Any]=False			,						_A       :   Tuple=None			,						_A       :   int=None			,						_A       :   int=1_28			,						_A       :   List[str]=32			,						_A       :   Tuple=1			,						_A       :   Any=[8, 5, 4, 2]			,						_A       :   int="weight_norm"			,						_A       :   List[Any]=7			,						_A       :   List[str]=7			,						_A       :   str=3			,						_A       :   Tuple=2			,						_A       :   Dict=True			,						_A       :   Optional[int]="reflect"			,						_A       :   Union[str, Any]=2			,						_A       :   str=2			,						_A       :   List[Any]=1.0			,						_A       :   List[Any]=10_24			,						_A       :   Optional[int]=None			,						_A       :   List[Any]=True			,						**_A       :   Union[str, Any]			,						)					->			Union[str, Any]:
					__snake_case    :							Optional[Any]   	=				target_bandwidths
					__snake_case    :							Tuple   	=				sampling_rate
					__snake_case    :							str   	=				audio_channels
					__snake_case    :							Optional[int]   	=				normalize
					__snake_case    :							Optional[Any]   	=				chunk_length_s
					__snake_case    :							int   	=				overlap
					__snake_case    :							Union[str, Any]   	=				hidden_size
					__snake_case    :							int   	=				num_filters
					__snake_case    :							Union[str, Any]   	=				num_residual_layers
					__snake_case    :							int   	=				upsampling_ratios
					__snake_case    :							Optional[Any]   	=				norm_type
					__snake_case    :							Optional[Any]   	=				kernel_size
					__snake_case    :							Tuple   	=				last_kernel_size
					__snake_case    :							Optional[Any]   	=				residual_kernel_size
					__snake_case    :							List[Any]   	=				dilation_growth_rate
					__snake_case    :							Optional[Any]   	=				use_causal_conv
					__snake_case    :							int   	=				pad_mode
					__snake_case    :							List[str]   	=				compress
					__snake_case    :							Tuple   	=				num_lstm_layers
					__snake_case    :							Dict   	=				trim_right_ratio
					__snake_case    :							Dict   	=				codebook_size
					__snake_case    :							List[str]   	=				codebook_dim if codebook_dim is not None else hidden_size
					__snake_case    :							str   	=				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       _lowercase  (self       :   Any)					->			Optional[int]:
					if self.chunk_length_s is None:
						return None
					else:
						return int(self.chunk_length_s * self.sampling_rate)



				@property
				def       _lowercase  (self       :   List[Any])					->			Optional[int]:
					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       :   str)					->			int:
					__snake_case    :							Dict   	=				np.prod(self.upsampling_ratios)
					return math.ceil(self.sampling_rate / hop_length)






				@property
				def       _lowercase  (self       :   List[Any])					->			int:
					return int(10_00 * self.target_bandwidths[-1] // (self.frame_rate * 10))






"""simple docstring"""







from abc import ABC, abstractmethod
from argparse import ArgumentParser

class 	UpperCamelCase    (					lowercase		):



				@staticmethod
				@abstractmethod
				def       _lowercase  (_A       :   ArgumentParser)					->			Tuple:
					raise NotImplementedError()






				@abstractmethod
				def       _lowercase  (self       :   Any)					->			Optional[Any]:
					raise NotImplementedError()





