CI - Add kaggle creds to pull model #1459
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mattdangerw
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We can skip these by default, for users who have not yet set them up. We will need to set them up for CI, see keras-team#1459
mattdangerw
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We can skip these by default, for users who have not yet set them up. We will need to set them up for CI, see #1459
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mattdangerw
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| def test_smallest_preset(self): | ||
| # TODO: Fails with OOM on current GPU CI |
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Another option would be to take in a dtype to run_preset_test and pass is it as kwarg to from_preset. Then we could try bfloat16 precision, which might avoid the oom?
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I tried keras.config.set_floatx("float16"), but that didn't help. So going to land this PR now. We can address it in another PR
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We can skip these by default, for users who have not yet set them up. We will need to set them up for CI, see keras-team#1459
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* CI - Add kaggle creds to pull model * add kaggle env variables * Kaggle env: * Kaggle env: * Kaggle env: * Kaggle env: * Update Build script for Kokoro * Add Kaggle env var * set gemma preset to extra_large * Change Gemma small preset to bfloat16 * Change Gemma small preset to xlarge
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We can skip these by default, for users who have not yet set them up. We will need to set them up for CI, see keras-team/keras-hub#1459
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We can skip these by default, for users who have not yet set them up. We will need to set them up for CI, see keras-team/keras-hub#1459
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keras_nlp/models/gemma/gemma_backbone_test.py::GemmaBackboneTest::test_smallest_preset- Failing on OOM.Marked the test as
extra_largeso GPU CI passes.