AutoYAHP Part 1: Cleanup the Algorithms for AutoYAHP #1056
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- Treat all python warnings as errors in tests. Existing tests that were throwing warnings were either fixed (yay!) or modified with `@pytest.mark.filterwarnings` - In BlurPool, throwing an error if both `replace_maxpools` and `replace_convs` are False, as that results in the algorithm being a no-op. - Made the default optimizer warning in the trainer less verbose. - Converted the bert yaml to have duration specified in terms of samples, to fix an issue where the warmup period, combine with max duration, was a noop. - Moved `TestMetricSetter` to `tests/common` and renamed as `MetricSetterCallback`. Tests should not be importing from other test files (tests/common is OK) - Removed TestWandBLogger, since the trainer tests do the same thing
Fix progressive resizing
This PR refactors the algorithms and tests as will be required by AutoYAHP. It does not depend on AutoYAHP itself (a future PR will remove the underlying hparam classes). - Refactored algorithm tests to not depend on hparams - Reformatted the factorize and selective backprop docstrings so they would be correctly parsed by auto-yahp - Refactor `algorithm_settings.py` to not depend on hparams and to return a list of `pytest.param` objects for a `pytest.mark.parametrize`. This change makes it more re-usable since it now includes information about markers required for each algorithm. - Moved the `TestTrainerAlgorithms` into `tests/algorithms/test_algorithms_train.py`, since it tests the individual algorithms, not the trainer, and thus should live in `tests/algorithms`. - Add helper methods for scanning a module to discover subclass implementations, check that the registry contains an entry, and test that a class is constructable from yaml
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Silencing deepspeed deprecation warnings
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Similar to #1056, this PR cleans up the callbacks and loggers for AutoYAHP. It does not depend on AutoYAHP itself (a future PR will remove the underlying hparam classes). - Refactored callback and logger tests to not depend on hparams - Reformatted the docstrings so they would be correctly parsed by auto-yahp - Added `callback_settings.py`, similar to `algorithm_settings.py`, to return a list of pytest param objects for parameterization across callback tests. These param objects include appropriate markers (e.g. conditional skipping for wandb and mlperf; requiring that the memory monitor runs on GPU, ...) - Moved the `TestTrainerAssets` into `tests/callbacks/test_callbacks.py`, since it tests the individual callbacks and loggers, not the trainer, and thus should live in `tests/callbacks`. - Cleaned up the `MemoryMonitor` warnings when cuda is not available. Now, it warns when the model is not on cuda, to catch the edge case where one does CPU training when GPUs are available.
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This PR refactors the algorithms and tests as will be required by AutoYAHP. It does not depend on AutoYAHP itself (a future PR will remove the underlying hparam classes).