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When I have a tensor m of shape [12, 10] and a vector s of scalars with shape [12], how can I multiply each row of m with the corresponding scalar in s?
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To perform element-wise subtraction on tensors, we can use the torch. sub() method of PyTorch. The corresponding elements of the tensors are subtracted. We can subtract a scalar or tensor from another tensor.
. item() ensures that you append only the float values to the list rather the tensor itself. You are basically converting a single element tensor value to a python number. This should not affect the performance in any way.
You need to add a corresponding singleton dimension:
m * s[:, None]
s[:, None] has size of (12, 1) when multiplying a (12, 10) tensor by a (12, 1) tensor pytoch knows to broadcast s along the second singleton dimension and perform the "element-wise" product correctly.
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