



import math
from typing import Optional

import numpy as np

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


__UpperCAmelCase          =       logging.get_logger(__name__)

__UpperCAmelCase          =       {
    '''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__							):
       UpperCAmelCase__				:					Union[str, Any]        =  "encodec"
       def __init__(			self,			SCREAMING_SNAKE_CASE_=[1.5, 3.0, 6.0, 12.0, 24.0],			SCREAMING_SNAKE_CASE_=2_4000,			SCREAMING_SNAKE_CASE_=1,			SCREAMING_SNAKE_CASE_=False,			SCREAMING_SNAKE_CASE_=None,			SCREAMING_SNAKE_CASE_=None,			SCREAMING_SNAKE_CASE_=128,			SCREAMING_SNAKE_CASE_=32,			SCREAMING_SNAKE_CASE_=1,			SCREAMING_SNAKE_CASE_=[8, 5, 4, 2],			SCREAMING_SNAKE_CASE_="weight_norm",			SCREAMING_SNAKE_CASE_=7,			SCREAMING_SNAKE_CASE_=7,			SCREAMING_SNAKE_CASE_=3,			SCREAMING_SNAKE_CASE_=2,			SCREAMING_SNAKE_CASE_=True,			SCREAMING_SNAKE_CASE_="reflect",			SCREAMING_SNAKE_CASE_=2,			SCREAMING_SNAKE_CASE_=2,			SCREAMING_SNAKE_CASE_=1.0,			SCREAMING_SNAKE_CASE_=1024,			SCREAMING_SNAKE_CASE_=None,			SCREAMING_SNAKE_CASE_=True,			**SCREAMING_SNAKE_CASE_,			)     ->		Tuple:
          UpperCamelCase    :  Optional[Any]							=	target_bandwidths
          UpperCamelCase    :  Optional[int]							=	sampling_rate
          UpperCamelCase    :  int							=	audio_channels
          UpperCamelCase    :  List[Any]							=	normalize
          UpperCamelCase    :  Dict							=	chunk_length_s
          UpperCamelCase    :  Union[str, Any]							=	overlap
          UpperCamelCase    :  Any							=	hidden_size
          UpperCamelCase    :  Tuple							=	num_filters
          UpperCamelCase    :  Union[str, Any]							=	num_residual_layers
          UpperCamelCase    :  str							=	upsampling_ratios
          UpperCamelCase    :  Optional[int]							=	norm_type
          UpperCamelCase    :  Union[str, Any]							=	kernel_size
          UpperCamelCase    :  str							=	last_kernel_size
          UpperCamelCase    :  Tuple							=	residual_kernel_size
          UpperCamelCase    :  Tuple							=	dilation_growth_rate
          UpperCamelCase    :  Any							=	use_causal_conv
          UpperCamelCase    :  str							=	pad_mode
          UpperCamelCase    :  Optional[int]							=	compress
          UpperCamelCase    :  Optional[Any]							=	num_lstm_layers
          UpperCamelCase    :  Optional[Any]							=	trim_right_ratio
          UpperCamelCase    :  List[str]							=	codebook_size
          UpperCamelCase    :  Dict							=	codebook_dim if codebook_dim is not None else hidden_size
          UpperCamelCase    :  Any							=	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__(**SCREAMING_SNAKE_CASE_       )
       @property
       def 					snake_case_       (			self       )     ->		Optional[int]:
          if self.chunk_length_s is None:
             return None
          else:
             return int(self.chunk_length_s * self.sampling_rate       )
       @property
       def 					snake_case_       (			self       )     ->		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 					snake_case_       (			self       )     ->		int:
          UpperCamelCase    :  Any							=	np.prod(self.upsampling_ratios       )
          return math.ceil(self.sampling_rate / hop_length       )






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








from __future__ import annotations

from typing import Any



class 				lowerCAmelCase_		:
       def __init__(			self,			SCREAMING_SNAKE_CASE_       )     ->		None:
          UpperCamelCase    :  Any							=	num_of_nodes
          UpperCamelCase    :  list[list[int]]							=	[]
          UpperCamelCase    :  dict[int, int]							=	{}
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )     ->		None:
          self.m_edges.append([u_node, v_node, weight]       )
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_       )     ->		int:

          if self.m_component[u_node] == u_node:
             return u_node
          return self.find_component(self.m_component[u_node]       )
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_       )     ->		None:

          if self.m_component[u_node] != u_node:
             for k in self.m_component:
                UpperCamelCase    :  Dict							=	self.find_component(SCREAMING_SNAKE_CASE_       )
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )     ->		None:

          if component_size[u_node] <= component_size[v_node]:
             UpperCamelCase    :  Tuple							=	v_node
             component_size[v_node] += component_size[u_node]
             self.set_component(SCREAMING_SNAKE_CASE_       )

          elif component_size[u_node] >= component_size[v_node]:
             UpperCamelCase    :  Union[str, Any]							=	self.find_component(SCREAMING_SNAKE_CASE_       )
             component_size[u_node] += component_size[v_node]
             self.set_component(SCREAMING_SNAKE_CASE_       )






       def 					snake_case_       (			self       )     ->		None:
          UpperCamelCase    :  int							=	[]
          UpperCamelCase    :  int							=	0

          UpperCamelCase    :  list[Any]							=	[-1] * self.m_num_of_nodes

          # A list of components (initialized to all of the nodes)
          for node in range(self.m_num_of_nodes       ):
             self.m_component.update({node: node}       )
             component_size.append(1       )

          UpperCamelCase    :  List[str]							=	self.m_num_of_nodes

          while num_of_components > 1:
             for edge in self.m_edges:
                UpperCamelCase	,     UpperCamelCase	,     UpperCamelCase    :  List[Any]							=	edge

                UpperCamelCase    :  str							=	self.m_component[u]
                UpperCamelCase    :  Any							=	self.m_component[v]

                if u_component != v_component:

                   for component in (u_component, v_component):
                      if (
                          minimum_weight_edge[component] == -1
                          or minimum_weight_edge[component][2] > w
                      ):
                         UpperCamelCase    :  Any							=	[u, v, w]

             for edge in minimum_weight_edge:
                if isinstance(SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       ):
                   UpperCamelCase	,     UpperCamelCase	,     UpperCamelCase    :  int							=	edge

                   UpperCamelCase    :  List[Any]							=	self.m_component[u]
                   UpperCamelCase    :  Tuple							=	self.m_component[v]

                   if u_component != v_component:
                      mst_weight += w
                      self.union(SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )
                      print(F"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""       )
                      num_of_components -= 1

             UpperCamelCase    :  Optional[Any]							=	[-1] * self.m_num_of_nodes
          print(F"""The total weight of the minimal spanning tree is: {mst_weight}"""       )






def 		UpperCamelCase	(   )	->     None:
   pass


if __name__ == "__main__":
    import doctest

    doctest.testmod()



