2a1bd4c93a998d16516d82893401b346d66a95e9,imgaug/dtypes.py,,get_minimal_dtype,#Any#Any#,58

Before Change

    promoted_dt = np.promote_types(*input_dts)
    if increase_itemsize_factor > 1:
        promoted_dt_highres = "%s%d" % (promoted_dt.kind, promoted_dt.itemsize * increase_itemsize_factor)
        try:
            promoted_dt_highres = np.dtype(promoted_dt_highres)
            return promoted_dt_highres
        except TypeError:
            raise TypeError(
                ("Unable to create a numpy dtype matching the name "%s". "
                 + "This error was caused when trying to find a minimal dtype covering the dtypes "%s" (which was "
                 + "determined to be "%s") and then increasing its resolution (aka itemsize) by a factor of %d. "
                 + "This error can be avoided by choosing arrays with lower resolution dtypes as inputs, e.g. by "
                 + "reducing float32 to float16.") % (
                    promoted_dt_highres,
                    ", ".join([input_dt.name for input_dt in input_dts]),
                    promoted_dt.name,
                    increase_itemsize_factor
                )
            )
    return promoted_dt


def get_minimal_dtype_for_values(values, allowed_kinds, default, allow_bool_as_intlike=True):

After Change

def get_minimal_dtype(arrays, increase_itemsize_factor=1):
    assert isinstance(arrays, list), (
        "Expected a list of arrays or dtypes, got type %s." % (type(arrays),))
    assert len(arrays) > 0, (
        "Cannot estimate minimal dtype of an empty iterable.")

    input_dts = normalize_dtypes(arrays)

Instances