attend_preliminary.py

class AttendDiagnose(nn.Module):
  def __init__(self, number_measurements, filter_number):
    super().__init__()
    self.d_model = filter_number*number_measurements
    self.embedding_conv = nn.Conv1d(number_measurements, filter_number*number_measurements, 1) 
    self.pe = PositionalEncoding(filter_number*number_measurements)
    # embed_dim and attention_heads  
    self.masked_attn = nn.modules.activation.MultiheadAttention(filter_number*number_measurements, 8)
    self.norm = nn.modules.normalization.LayerNorm(self.d_model)
    self.final_layer = nn.Linear(self.d_model, 1)
  def forward(self, X):
    x = self.embedding_conv(X)
    x= x.transpose(1,2)
    x = self.pe(x)
    x = self.masked_attn(x, x, x)[0]
    x = self.norm(x)
    x = self.final_layer(x)
    print(x.shape)
  def positional_encoding(X):
    # TODO implement
    pass