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Add Cholesky decomposition #852
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Hello, can this issue be assigned to me? |
Sure thing! |
Hi @Dbhasin1, The function and tests first need to be added to the various backends, which live in tensornetwork/backends/blah. The first is the AbstractBackend, a base class that just throws NotImplementedError. The others all wrap functions from other numerical packages, the idea being to provide a means to quickly switch between these. Inside the backend files you will see many other functions, such as qr. Our QR differs from e.g. NumPy's by the presence of a pivot argument that matricizes the input. Cholesky should have a similar mechanism. Once added to the backends, the function should also be added to the tn.Tensor interface, which lives in tensornetwork/tensor.py with functions defined in tensornetwork/linalg/blah |
Hello there @alewis I'm interested in working on this issue has a PR been done? If not I would like to work on this. |
Hello, please ignore this PR I made a mistake, the changes implemented for the Cholesky decomposition will be from a different PR. |
Looks good! Just a small fix. |
@alewis Alright I have made the fix, just waiting on the testing. Also, I will start implementing the Cholesky decomposition, quick question, why does Jax not have it's own decompositions file? Oh, could you add me as an assignee for this issue? Thank you |
it uses the numpy decompositions.py file |
Ok, I see, then I will start adding the function to that file and work my way from there, thank you! |
hey is this still open? can I work on this? |
Is this issue still open? Can I work on it? |
Hi, can I work on this? I'm new so can someone guide me? |
Can I work on this issue? |
Hello, Can I use this issue as my first contribution? I'm new so please can someone guide me? |
@prat1999 already opened a PR on this (maybe you guys can work together on this) |
We should support the Cholesky decomposition per https://numpy.org/doc/stable/reference/generated/numpy.linalg.cholesky.html#numpy.linalg.cholesky, adding a pivot argument in the same way as qr and svd.
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