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you have to remember to set properties in the correct dimension even if you are not using multiple dimensions or only a single value for that property
elemt3=Drift(length=torch.tensor([0.3142])
By introducing automatic broadcasting (in a similar way to how PyTorch does it), we want to be able to use either one of the examples in the first code block while tracking, for example, a beam with 1000 different properties.
The text was updated successfully, but these errors were encountered:
In #116, we added a vectorised way of using Cheetah. This means that instead of either one of these
you have to remember to set properties in the correct dimension even if you are not using multiple dimensions or only a single value for that property
By introducing automatic broadcasting (in a similar way to how PyTorch does it), we want to be able to use either one of the examples in the first code block while tracking, for example, a beam with 1000 different properties.
The text was updated successfully, but these errors were encountered: