autogen/test/nlp/test_autohf_regression.py

import sys
import pytest


@pytest.mark.skipif(sys.platform == "darwin", reason="do not run on mac os")
def test_regression():
    try:
        import ray
    except ImportError:
        return
    from flaml import AutoML
    import requests
    from datasets import load_dataset

    try:
        train_dataset = load_dataset("glue", "stsb", split="train[:2%]").to_pandas()
        dev_dataset = (
            load_dataset("glue", "stsb", split="train[2%:3%]").to_pandas().iloc[:32]
        )
    except requests.exceptions.ConnectionError:
        return

    custom_sent_keys = ["sentence1", "sentence2"]
    label_key = "label"

    X_train = train_dataset[custom_sent_keys]
    y_train = train_dataset[label_key]

    X_val = dev_dataset[custom_sent_keys]
    y_val = dev_dataset[label_key]

    automl = AutoML()

    automl_settings = {
        "gpu_per_trial": 0,
        "max_iter": 2,
        "time_budget": 5,
        "task": "seq-regression",
        "metric": "pearsonr",
        "starting_points": {"transformer": {"num_train_epochs": 1}},
        "use_ray": True,
    }

    automl_settings["custom_hpo_args"] = {
        "model_path": "google/electra-small-discriminator",
        "output_dir": "test/data/output/",
        "ckpt_per_epoch": 5,
        "fp16": False,
    }

    ray.shutdown()
    ray.init()
    automl.fit(
        X_train=X_train, y_train=y_train, X_val=X_val, y_val=y_val, **automl_settings
    )
    automl.predict(X_val)


if __name__ == "__main__":
    test_regression()