Hi, I’d like to broadcast dimensions across aesara tensors. As an example, I can do this with numpy inputs as follows: r, c = at.row(), at.col() f_subtract = aesara.function([c,r], [r-c]) c_ = np.array([1,2]).reshape(2,1) r_ = np.array([2,3,4]).reshape(1,3) f_subtract(c_,r_) which gives: [arr…

You don’t need to ever compile an aesara function to do computation with symbolic tensors. Your code already contains the answer to your question: it’s just r-c.

Broadcast dimensions across aesara/theano tensors

Questions version agnostic

HarryS December 21, 2022, 9:19pm 3

AHH thanks!

I realised I hadn’t reshaped my tensors when working with them so it was giving my shape errors. You’re right, once I’ve reshaped them then everything works as expected!

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Broadcast dimensions across aesara/theano tensors

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