wehub-resource-sync
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
import numpy as np
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import pytest
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import mlflow
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from mlflow import tracking
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from mlflow.exceptions import INVALID_PARAMETER_VALUE, ErrorCode, MlflowException
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from mlflow.tracking.fluent import start_run
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from mlflow.tracking.metric_value_conversion_utils import convert_metric_value_to_float_if_possible
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from tests.helper_functions import random_int
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def test_reraised_value_errors():
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multi_item_array = np.random.rand(2, 2)
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with pytest.raises(MlflowException, match=r"Failed to convert metric value to float") as e:
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convert_metric_value_to_float_if_possible(multi_item_array)
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assert e.value.error_code == ErrorCode.Name(INVALID_PARAMETER_VALUE)
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def test_convert_metric_value_to_float():
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float_metric_val = float(random_int(10, 50))
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assert convert_metric_value_to_float_if_possible(float_metric_val) == float_metric_val
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ndarray_val = np.random.rand(1)
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assert convert_metric_value_to_float_if_possible(ndarray_val) == float(ndarray_val[0])
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def test_log_np_array_as_metric():
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ndarray_val = np.random.rand(1)
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ndarray_float_val = float(ndarray_val[0])
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with start_run() as run:
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mlflow.log_metric("name_numpy", ndarray_val)
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finished_run = tracking.MlflowClient().get_run(run.info.run_id)
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assert finished_run.data.metrics == {"name_numpy": ndarray_float_val}
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