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ca35fa969f
* refactoring TransformersEstimator to support default and custom_hp * handling starting_points not in search space * addressing starting point more than max_iter * fixing upper < lower bug
37 lines
1007 B
Python
37 lines
1007 B
Python
import sys
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import pytest
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from utils import get_toy_data_seqclassification, get_automl_settings
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@pytest.mark.skipif(sys.platform == "darwin", reason="do not run on mac os")
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def test_custom_hp_nlp():
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from flaml import AutoML
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import flaml
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X_train, y_train, X_val, y_val, X_test = get_toy_data_seqclassification()
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automl = AutoML()
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automl_settings = get_automl_settings()
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automl_settings["custom_hp"] = None
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automl_settings["custom_hp"] = {
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"transformer": {
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"model_path": {
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"domain": flaml.tune.choice(["google/electra-small-discriminator"]),
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},
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"num_train_epochs": {"domain": 3},
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}
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}
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automl_settings["fit_kwargs_by_estimator"] = {
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"transformer": {
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"output_dir": "test/data/output/",
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"ckpt_per_epoch": 1,
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"fp16": False,
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}
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}
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automl.fit(X_train=X_train, y_train=y_train, **automl_settings)
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if __name__ == "__main__":
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test_custom_hp_nlp()
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