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Matmul rework

Houssem ROUIS requested to merge hrouis/aidge_core:matmul_rework into dev

[ADD] support for Multi-dimensional Matrix Multiplication, following numpy MatMul operation specificities.

In the context of Multi-dimensional MatMul, we consider an N-Dim Tensor as a stack of 2-D matrices having as shape the last two dimensions of the Tensor.

From Numpy documentation:

The behavior depends on the arguments in the following way.

  • If both arguments are 2-D they are multiplied like conventional matrices.
  • If either argument is N-D, N > 2, it is treated as a stack of matrices residing in the last two indexes and broadcast accordingly.
  • If the first argument is 1-D, it is promoted to a matrix by prepending a 1 to its dimensions. After matrix multiplication the prepended 1 is removed.
  • If the second argument is 1-D, it is promoted to a matrix by appending a 1 to its dimensions. After matrix multiplication the appended 1 is removed.
Edited by Maxence Naud

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