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Applies a bilinear transformation to the incoming data: \(y = x_1 A x_2 + b\)

Usage

nnf_bilinear(input1, input2, weight, bias = NULL)

Arguments

input1

\((N, *, H_{in1})\) where \(H_{in1}=\mbox{in1\_features}\) and \(*\) means any number of additional dimensions. All but the last dimension of the inputs should be the same.

input2

\((N, *, H_{in2})\) where \(H_{in2}=\mbox{in2\_features}\)

weight

\((\mbox{out\_features}, \mbox{in1\_features}, \mbox{in2\_features})\)

bias

\((\mbox{out\_features})\)

Value

output \((N, *, H_{out})\) where \(H_{out}=\mbox{out\_features}\)

and all but the last dimension are the same shape as the input.