You can check the mean distance between the points via:
print(torch.mean((r1[:,:,:30]-r2[:,:,:30])**2)**0.5)

It’s fairly small. Something like e-06 to e-08.
The actual algorithm used to calculate convolutions is not from Pytorch but from 3rd party libraries, depending on cpu or gpu, etc.
Keep in mind that torch.float32 has only 5 points of precision. (i.e. 0.4322). So the mean difference falls below the rounding error threshold.
Additionally, in Machine Learning applications, you generally do not need such high precision. Even half precision is sufficient.