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Adding get_device_count function to the distribution_lib #21791
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Adding get_device_count function to the distribution_lib #21791
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Summary of ChangesHello @buildwithsuhana, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request enhances Keras's device management capabilities by introducing a new "get_device_count" utility function within the "keras.distribution" module. This function provides a standardized and convenient way for users to programmatically determine the number of available computational devices, such as GPUs, TPUs, or CPUs, that Keras can leverage, thereby simplifying device configuration and resource allocation for distributed training. Highlights
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Code Review
This pull request introduces a new utility function get_device_count to the distribution API. The implementation looks good, but I've identified a couple of areas for improvement. The public API docstring for the new function is misleading regarding its behavior when no device type is specified, which could confuse users. I've suggested a clarification. Additionally, the new function lacks unit tests, which are essential for ensuring its correctness and preventing future regressions. I've recommended adding a test case.
Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #21791 +/- ##
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+ Coverage 82.59% 82.63% +0.04%
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Files 572 577 +5
Lines 58535 59329 +794
Branches 9158 9300 +142
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+ Hits 48345 49026 +681
- Misses 7853 7915 +62
- Partials 2337 2388 +51
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@buildwithsuhana |
| device_type: Optional device type to count (e.g., "cpu", | ||
| "gpu", "tpu"). If `None`, it counts all available | ||
| devices. |
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Oh, copy the one from the jax implementation. This one is incorrect.
This PR introduces a new utility function, keras.distribution.get_device_count, to the Keras distribution API.
This function allows a user to query the total number of available devices (like GPUs, TPUs, or CPUs) that Keras can see.