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问题:
I have two arrays A=[1,2,3] and B=[[1],[0],[1],[0]]. The question how to perform their tensor dot product in python. I am expecting to get:
C=[[1,2,3], [0,0,0], [1,2,3], [0,0,0]]
The function np.tensordot() returns an error concerning shapes of arrays.
A little addition to this question. How to do such operation if matrix are totally different in shape, like:
A=[[1,1,1,1], [1,1,1,1], [2,2,2,2], [3,3,3,3]] B=[2,1] C=[[[2,1],[2,1],[2,1],[2,1]], [[2,1],[2,1],[2,1],[2,1]], [[4,2],[4,2],[4,2],[4,2]], [[6,3],[6,3],[6,3],[6,3]]]
回答1:
Try using correct numpy arrays:
>>> array([[1],[2],[3]]).dot(array([[1,0,1,0]])) array([[1, 0, 1, 0], [2, 0, 2, 0], [3, 0, 3, 0]])
If your alignment is different, using a.transpose() can flip it:
>>> array([[1],[2],[3]]).dot(array([[1,0,1,0]])).transpose() array([[1, 2, 3], [0, 0, 0], [1, 2, 3], [0, 0, 0]])
If you (for whatever reason) have to use tensordot(), try this:
>>> numpy.tensordot([1,2,3], [1,0,1,0], axes=0) array([[1, 0, 1, 0], [2, 0, 2, 0], [3, 0, 3, 0]])
回答2:
I'm not so expert with this argument but if you try to change axes in numpy it works:
A=[1,2,3] B=[[1],[0],[1],[0]] np.tensordot(B, A, axes=0) array([[[1, 2, 3]], [[0, 0, 0]], [[1, 2, 3]], [[0, 0, 0]]])
