Implementation of np.linalg.eig #61
Merged
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR will allow users to compute np.linalg.eig on accelerator devices. We enable this support throught dpnp.
According to https://numpy.org/doc/stable/reference/generated/numpy.linalg.eig.html, NumPy does not order the eigen values. Dpnp provides support of np.linalg.eig through MKL which returns the eigen values in order. To check the correctness of our implementation we have borrowed the check from dpnp, where we sort the eigen values for both our implementation and NumPy's. The eigen vectors are corresponding to each eigen value and we swap the vectors accordingly when we sort the eigen values. The eigen vectors could be in different directions which we correct in our test as well.
@diptorupd @oleksandr-pavlyk Please let me know if the explanation makes sense.