wehub-resource-sync
41 lines
1.3 KiB
Python
41 lines
1.3 KiB
Python
import warnings
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from contextlib import contextmanager
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from unittest.mock import patch
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import pandas as pd
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import pytest
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import mlflow
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_TEST_DATA = pd.DataFrame({"x": [1, 2, 3], "y": [4, 5, 6]})
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@pytest.mark.parametrize("tracking_uri", ["databricks", "http://localhost:5000"])
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def test_global_evaluate_warn_in_tracking_uri(tracking_uri):
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with patch("mlflow.get_tracking_uri", return_value=tracking_uri):
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with pytest.warns(FutureWarning, match="The `mlflow.evaluate` API has been deprecated"):
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mlflow.evaluate(
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data=_TEST_DATA,
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model=lambda x: x["x"] * 2,
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extra_metrics=[mlflow.metrics.latency()],
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)
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@contextmanager
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def no_future_warning():
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with warnings.catch_warnings():
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# Translate future warning into an exception
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warnings.simplefilter("error", FutureWarning)
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yield
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@pytest.mark.parametrize("tracking_uri", ["databricks", "sqlite://"])
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def test_models_evaluate_does_not_warn(tracking_uri):
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with patch("mlflow.get_tracking_uri", return_value=tracking_uri):
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with no_future_warning():
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mlflow.models.evaluate(
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data=_TEST_DATA,
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model=lambda x: x["x"] * 2,
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extra_metrics=[mlflow.metrics.mse()],
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)
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