mlx - implement segment_sum and segment_max

[lkarthee]

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 0% with 22 lines in your changes are missing coverage. Please review.

:exclamation: No coverage uploaded for pull request base (mlx@4c90dfb). Click here to learn what that means.

Files	Patch %	Lines
keras/src/backend/mlx/math.py	0.00%	22 Missing :warning:

Additional details and impacted files

@@          Coverage Diff           @@
##             mlx   #19652   +/-   ##
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  Coverage       ?   68.43%           
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  Files          ?      506           
  Lines          ?    45959           
  Branches       ?     8496           
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  Hits           ?    31451           
  Misses         ?    12857           
  Partials       ?     1651           

Flag	Coverage Δ
keras	68.35% <0.00%> (?)
keras-jax	58.82% <0.00%> (?)
keras-numpy	53.16% <0.00%> (?)
keras-tensorflow	59.97% <0.00%> (?)

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[Faisal-Alsrheed]

Hi @lkarthee,

I have noticed the same issue: there are missing and needed functions in MLX.

What is the best strategy here? Should we use NumPy temporarily and add a TODO comment?

I have decided to start with core files and functions. https://github.com/keras-team/keras/pull/19619

I suggest creating a roadmap where we start with fundamental functions and then move up.

best

[lkarthee]

@Faisal-Alsrheed My thoughts regarding missing functions which can't be added due to design decisions/limitations of mlx:

• we have to check if there is a workaround.
• if there is no workaround, may be we have to fallback to using numpy or jax adding a TODO?

Regarding fixing core first, I have been doing that in my PRs. I tried to implement Pooling and CNN related funcs, realised many tests are failing and started fixing test cases.

@fchollet any thoughts on what to use as fallback - numpy or jax.

[gbaned]

Hi @fchollet Any update on this PR? Please. Thank you!

[fchollet]

@fchollet any thoughts on what to use as fallback - numpy or jax.

Sorry, just checking this now. I would say that JAX is preferable as fallback since numpy would not be sufficiently performant.

[gbaned]

Hi @lkarthee Any update on this PR? Please. Thank you!

[github-actions[bot]]

This PR is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.

[github-actions[bot]]

This PR was closed because it has been inactive for 28 days. Please reopen if you'd like to work on this further.