Method forward

model.py:68–94

(self, x1, x2, x3)

            self.linear_h3, self.linear_o3 = nn.Identity(), nn.Identity()  

    def forward(self, x1, x2, x3):

        if self.gate_h1:
            h1 = self.linear_h1(x1) #breaks colli of h1
            z1 = self.linear_z1(x1, torch.cat([x2,x3], dim=-1)) if self.use_bilinear[0] else self.linear_z1(torch.cat((x1, x2, x3), dim=-1)) #creates a vector combining both modalities
            o1 = self.linear_o1(nn.Sigmoid()(z1)*h1) #update modality input
        else:
            h1 = self.linear_h1(x1)
            o1 = self.linear_o1(h1)

        if self.gate_h2:
            h2 = self.linear_h2(x2)
            z2 = self.linear_z2(x2, torch.cat([x1,x3], dim=-1)) if self.use_bilinear[1] else self.linear_z2(torch.cat((x1, x2, x3), dim=-1))
            o2 = self.linear_o2(nn.Sigmoid()(z2)*h2)
        else:
            h2 = self.linear_h2(x2)
            o2 = self.linear_o2(h2)
        
        if self.gate_h3:
            h3 = self.linear_h3(x3)
            z3 = self.linear_z3(x3, torch.cat([x1,x2], dim=-1)) if self.use_bilinear[2] else self.linear_z3(torch.cat((x1, x2, x3), dim=-1))
            o3 = self.linear_o3(nn.Sigmoid()(z3)*h3)
        else:
            h3 = self.linear_h3(x3)
            o3 = self.linear_o3(h3)

        return o1, o2, o3

class FC_block(nn.Module):
    def __init__(self, dim_in, dim_out, act_layer=nn.ReLU, dropout=True, p_dropout_fc=0.25):