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Implementing grad and shape transformations as a follow up to pytensor_from_scratch would highlight different approaches to graph transformation: eager (grad) and lazy via rewrites (shape).
This has links to vectorization, scalarization, logprob transformation/inference, marginalization...
The text was updated successfully, but these errors were encountered:
Implementing grad and shape transformations as a follow up to
pytensor_from_scratch
would highlight different approaches to graph transformation: eager (grad) and lazy via rewrites (shape).This has links to
vectorization
,scalarization
,logprob transformation/inference
,marginalization
...The text was updated successfully, but these errors were encountered: