code: def __init__(
      self, attention, d_model, n_heads, d_keys=None, d_values=None
  ):
      super(AttentionLayer, self).__init__()
  
      d_keys = d_keys or (d_model // n_heads)
      d_values = d_values or (d_model // n_heads)
  
      self.inner_attention = attention
      self.query_projection = nn.Linear(d_model, d_keys * n_heads)
      self.key_projection = nn.Linear(d_model, d_keys * n_heads)
      self.value_projection = nn.Linear(d_model, d_values * n_heads)
      self.out_projection = nn.Linear(d_values * n_heads, d_model)
      self.n_heads = n_heads
  
imports: import numpy
  import math
  from math import sqrt
  import os
  from scipy.fftpack import next_fast_len
  from merlion.models.utils.nn_modules.blocks import ExponentialSmoothing, conv1d_fft
label_desc: Use image node_id 1 to create a new AttentionLayer object from inherited base classes: nn with example: obj = AttentionLayer(attention, d_model, n_heads, d_keys, d_values)