def _maybe_write_metric(self, metric_key: str, metric_val: Any,
step: int) -> None:
# For now, we only log scalar metrics.
if not util.is_numerical_scalar(metric_val):
return
self.writer.add_scalar("Determined/" + metric_key, metric_val, step)
def test_is_numerical_scalar() -> None:
assert metric_writers_util.is_numerical_scalar(1)
assert metric_writers_util.is_numerical_scalar(1.0)
assert metric_writers_util.is_numerical_scalar(-3.14)
assert metric_writers_util.is_numerical_scalar(np.ones(shape=()))
assert metric_writers_util.is_numerical_scalar(np.array(1))
assert metric_writers_util.is_numerical_scalar(np.array(-3.14))
assert metric_writers_util.is_numerical_scalar(np.array([1.0])[0])
def test_is_not_numerical_scalar() -> None:
# Invalid types
assert not metric_writers_util.is_numerical_scalar("foo")
assert not metric_writers_util.is_numerical_scalar(np.array("foo"))
assert not metric_writers_util.is_numerical_scalar(object())
# Invalid shapes
assert not metric_writers_util.is_numerical_scalar([1])
assert not metric_writers_util.is_numerical_scalar(np.array([3.14]))
assert not metric_writers_util.is_numerical_scalar(np.ones(shape=(5, 5)))
