torch.nn.functional.bilinear
torch.nn.functional.bilinear(input1, input2, weight, bias=None) -> Tensor
Applies a bilinear transformation to the incoming data: y = x_1^T A
   x_2 + b
Shape:
  * input1: (N, *, H_{in1}) where H_{in1}=\text{in1\_features} and
    * means any number of additional dimensions. All but the last
    dimension of the inputs should be the same.

  * input2: (N, *, H_{in2}) where H_{in2}=\text{in2\_features}

  * weight: (\text{out\_features}, \text{in1\_features},
    \text{in2\_features})

  * bias: (\text{out\_features})

  * output: (N, *, H_{out}) where H_{out}=\text{out\_features} and
    all but the last dimension are the same shape as the input.
