Improve error handling for non-keras model loading attempts #1577
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fchollet
approved these changes
Apr 17, 2024
keras_nlp/models/task_test.py
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| @@ -69,6 +69,9 @@ def test_from_preset_errors(self): | |||
| with self.assertRaises(ValueError): | |||
| # No loading on an incorrect class. | |||
| BertClassifier.from_preset("gpt2_base_en", load_weights=False) | |||
| with self.assertRaises(FileNotFoundError): | |||
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In general as a best practice unit tests should use assertRaisesRegex, because sometimes a different exception with the same type can be raised (not the one you expect). In this case it doesn't matter because the exception class is fairly specific.
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Make sense! I updated these unit tests to use assertRaisesRegex.
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This PR addresses #1574. At the moment,
from_presetcan only load Keras models so if a user attempts to load a non-Keras model, we should inform them that only Keras models are valid.