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Essentially, when saving an empty torch tensor of some dimension, that dimensionality information is lost when converting that tensor into json. This should be an easy fix: detect if the tensor is empty, and if so, explicitly save the dimension instead of the data.
Where the dimension of the empty tensor has been lost.
I'd be happy to take a shot at fixing if you'd like.
By the way, why is this important (i.e., why on earth would we care about the dimension of an empty tensor)? Turns out when sampling from the dataless "uninformative" prior using gpytorch, we need to feed it an empty tensor of the correct dimension. I'd like to be able to save this data along with my model!
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v2024.4.17
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Essentially, when saving an empty torch tensor of some dimension, that dimensionality information is lost when converting that tensor into json. This should be an easy fix: detect if the tensor is empty, and if so, explicitly save the dimension instead of the data.
Results in
Where the dimension of the empty tensor has been lost.
I'd be happy to take a shot at fixing if you'd like.
By the way, why is this important (i.e., why on earth would we care about the dimension of an empty tensor)? Turns out when sampling from the dataless "uninformative" prior using gpytorch, we need to feed it an empty tensor of the correct dimension. I'd like to be able to save this data along with my model!
Code snippet
Log output
No response
Code of Conduct
The text was updated successfully, but these errors were encountered: