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I'm playing around with PyTorch with the aim of learning it, and I have a very dumb question: how can I multiply a matrix by a single vector?

Here's what I've tried:

>>> import torch >>> a = torch.rand(4,4) >>> a 0.3162 0.4434 0.9318 0.8752 0.0129 0.8609 0.6402 0.2396 0.5720 0.7262 0.7443 0.0425 0.4561 0.1725 0.4390 0.8770 [torch.FloatTensor of size 4x4] >>> b = torch.rand(4) >>> b 0.1813 0.7090 0.0329 0.7591 [torch.FloatTensor of size 4] >>> a.mm(b) Traceback (most recent call last): File "<stdin>", line 1, in <module> RuntimeError: invalid argument 2: dimension 1 out of range of 1D tensor at /Users/soumith/code/builder/wheel/pytorch-src/torch/lib/TH/generic/THTensor.c:24 >>> a.mm(b.t()) Traceback (most recent call last): File "<stdin>", line 1, in <module> RuntimeError: t() expects a 2D tensor, but self is 1D >>> b.mm(a) Traceback (most recent call last): File "<stdin>", line 1, in <module> RuntimeError: matrices expected, got 1D, 2D tensors at /Users/soumith/code/builder/wheel/pytorch-src/torch/lib/TH/generic/THTensorMath.c:1288 >>> b.t().mm(a) Traceback (most recent call last): File "<stdin>", line 1, in <module> RuntimeError: t() expects a 2D tensor, but self is 1D

On the other hand, if I do

>>> b = torch.rand(4,2)

then my first attempt, a.mm(b), works fine. So the problem is just that I'm multiplying a vector rather than a matrix --- but how can I do this?

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2 Answers 2

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37

You're looking for 

torch.mv(a,b)

Note that for the future, you may also find torch.matmul() useful. torch.matmul() infers the dimensionality of your arguments and accordingly performs either dot products between vectors, matrix-vector or vector-matrix multiplication, matrix multiplication or batch matrix multiplication for higher order tensors.

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1 Comment

Thanks! I wrote a self-answer with some supplementary information, for the sake of future visitors.
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This is a self-answer to supplement @mexmex's correct and useful answer.

In PyTorch, unlike numpy, 1D Tensors are not interchangeable with 1xN or Nx1 tensors. If I replace

>>> b = torch.rand(4)

with

>>> b = torch.rand((4,1))

then I will have a column vector, and matrix multiplication with mm will work as expected.

But this is not necessary, because as @mexmex points out there is an mv function for matrix-vector multiplication, as well as a matmul function that dispatches the appropriate function depending on the dimensions of its input.

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