code: def __init__(
      self,
      enc_dim,
      feature_dim,
      hidden_dim,
      layer,
      segment_size=24,
      nspk=2,
      win_len=16,
      context_len=16,
      dropout=0.0,
      sr=16000,
  ):
      super(FaSNet_base, self).__init__()
  
      # parameters
      self.win_len = win_len
      self.window = max(int(sr * win_len / 1000), 2)
      self.stride = self.window // 2
      self.sr = sr
      self.context_len = context_len
      self.dropout = dropout
  
      self.enc_dim = enc_dim
      self.feature_dim = feature_dim
      self.hidden_dim = hidden_dim
      self.segment_size = segment_size
  
      self.layer = layer
      self.num_spk = nspk
      self.eps = 1e-8
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from espnet2.enh.layers import dprnn
label_desc: Use image node_id 1 to create a new FaSNet_base object from inherited base classes: nn with example: obj = FaSNet_base(enc_dim, feature_dim, hidden_dim, layer, segment_size, nspk, win_len, context_len, dropout, sr)