human
Complete this python program:
def is_datetimelike_v_numeric(a, b):
assistant
#Here is the Python program you requested.

    """Check if we are comparing a datetime-like object to a numeric object.
    By "numeric," we mean an object that is either of an int or float dtype.
    Parameters
    a : array-like, scalar
    The first object to check.
    b : array-like, scalar
    The second object to check.
    Returns
    boolean : Whether we return a comparing a datetime-like
    to a numeric object.
    Examples
    >>> dt = np.datetime64(pd.datetime(2017, 1, 1))
    >>> is_datetimelike_v_numeric(1, 1)
    False
    >>> is_datetimelike_v_numeric(dt, dt)
    False
    >>> is_datetimelike_v_numeric(1, dt)
    True
    >>> is_datetimelike_v_numeric(dt, 1)  # symmetric check
    True
    >>> is_datetimelike_v_numeric(np.array([dt]), 1)
    True
    >>> is_datetimelike_v_numeric(np.array([1]), dt)
    True
    >>> is_datetimelike_v_numeric(np.array([dt]), np.array([1]))
    True
    >>> is_datetimelike_v_numeric(np.array([1]), np.array([2]))
    False
    >>> is_datetimelike_v_numeric(np.array([dt]), np.array([dt]))
    False
    """
    if (not hasattr(a, 'dtype')):
        a = np.asarray(a)
    if (not hasattr(b, 'dtype')):
        b = np.asarray(b)
    def is_numeric(x):
        '\n                                Check    if    an    object    has    a    numeric    dtype    (i.e.    integer    or    float).\n                                '
        return (is_integer_dtype(x) or is_float_dtype(x))
    is_datetimelike = needs_i8_conversion
    return ((is_datetimelike(a) and is_numeric(b)) or (is_datetimelike(b) and is_numeric(a)))