TransposeMatMul

 Graphs in : cluster, ONNX model architecture.

A (heterogeneous) – T : object, N-dimensional matrix A.
B (heterogeneous) – T : object, N-dimensional matrix B.

 Parameters : cluster,

alpha : float, scalar multiplier for the product of the input tensors.
Default value “1”.
transA : boolean, whether A should be transposed on the last two dimensions before doing multiplication.
Default value “False”.
transB : boolean, whether B should be transposed on the last two dimensions before doing multiplication.
Default value “False”.
 training? : boolean, whether the layer is in training mode (can store data for backward).
Default value “True”.
 lda coeff : float, defines the coefficient by which the loss derivative will be multiplied before being sent to the previous layer (since during the backward run we go backwards).
Default value “1”.

 name (optional) : string, name of the node.