def is_datetimelike_v_object(a, b):
if not hasattr(a, '<STR_LIT>'):<EOL><INDENT>a = np.asarray(a)<EOL><DEDENT>if not hasattr(b, '<STR_LIT>'):<EOL><INDENT>b = np.asarray(b)<EOL><DEDENT>is_datetimelike = needs_i8_conversion<EOL>return ((is_datetimelike(a) and is_object_dtype(b)) or<EOL>(is_datetimelike(b) and is_object_dtype(a)))<EOL>
Check if we are comparing a datetime-like object to an object instance.

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 an object instance.

Examples
--------
>>> obj = object()
>>> dt = np.datetime64(pd.datetime(2017, 1, 1))
>>>
>>> is_datetimelike_v_object(obj, obj)
False
>>> is_datetimelike_v_object(dt, dt)
False
>>> is_datetimelike_v_object(obj, dt)
True
>>> is_datetimelike_v_object(dt, obj)  # symmetric check
True
>>> is_datetimelike_v_object(np.array([dt]), obj)
True
>>> is_datetimelike_v_object(np.array([obj]), dt)
True
>>> is_datetimelike_v_object(np.array([dt]), np.array([obj]))
True
>>> is_datetimelike_v_object(np.array([obj]), np.array([obj]))
False
>>> is_datetimelike_v_object(np.array([dt]), np.array([1]))
False
>>> is_datetimelike_v_object(np.array([dt]), np.array([dt]))
False