class_docstr: Graves Attention as is ref1 with updates from ref2.
  ref1: https://arxiv.org/abs/1910.10288
  ref2: https://arxiv.org/pdf/1906.01083.pdf
  
  Args:
      query_dim (int): number of channels in query tensor.
      K (int): number of Gaussian heads to be used for computing attention.
code: def init_layers(self):
      torch.nn.init.constant_(
          self.N_a[2].bias[(2 * self.K) : (3 * self.K)], 1.0
      )  # bias mean
      torch.nn.init.constant_(
          self.N_a[2].bias[self.K : (2 * self.K)], 10
      )
  
imports: import torch
  from scipy.stats import betabinom
  from torch import nn
  from torch.nn import functional
  from TTS.tts.layers.tacotron.common_layers import Linear
label_desc: Use image node_id 2 for calling the GravesAttention obj's underlying member method code with example usage: obj.init_layers() without return types