def soft_convert_objects(values, datetime=True, numeric=True, timedelta=True,
                         coerce=False, copy=True):
    """ if we have an object dtype, try to coerce dates and/or numbers """

    conversion_count = sum((datetime, numeric, timedelta))
    if conversion_count == 0:
        raise ValueError('At least one of datetime, numeric or timedelta must '
                         'be True.')
    elif conversion_count > 1 and coerce:
        raise ValueError("Only one of 'datetime', 'numeric' or "
                         "'timedelta' can be True when when coerce=True.")

    if isinstance(values, (list, tuple)):
        # List or scalar
        values = np.array(values, dtype=np.object_)
    elif not hasattr(values, 'dtype'):
        values = np.array([values], dtype=np.object_)
    elif not is_object_dtype(values.dtype):
        # If not object, do not attempt conversion
        values = values.copy() if copy else values
        return values

    # If 1 flag is coerce, ensure 2 others are False
    if coerce:
        # Immediate return if coerce
        if datetime:
            from pandas import to_datetime
            return to_datetime(values, errors='coerce').to_numpy()
        elif timedelta:
            from pandas import to_timedelta
            return to_timedelta(values, errors='coerce').to_numpy()
        elif numeric:
            from pandas import to_numeric
            return to_numeric(values, errors='coerce')

    # Soft conversions
    if datetime:
        # GH 20380, when datetime is beyond year 2262, hence outside
        # bound of nanosecond-resolution 64-bit integers.
        try:
            values = lib.maybe_convert_objects(values,
                                               convert_datetime=datetime)
        except OutOfBoundsDatetime:
            pass

    if timedelta and is_object_dtype(values.dtype):
        # Object check to ensure only run if previous did not convert
        values = lib.maybe_convert_objects(values, convert_timedelta=timedelta)

    if numeric and is_object_dtype(values.dtype):
        try:
            converted = lib.maybe_convert_numeric(values, set(),
                                                  coerce_numeric=True)
            # If all NaNs, then do not-alter
            values = converted if not isna(converted).all() else values
            values = values.copy() if copy else values
        except Exception:
            pass

    return values