LazilyOuterIndexedArray doesn't support slicing with slice objects

Code Sample, a copy-pastable example if possible

from xarray.core.indexing import LazilyOuterIndexedArray
import numpy as np
x = LazilyOuterIndexedArray(np.ones((5, 5)))
x[:3]

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-4-42bee9beb30a> in <module>
----> 1 x[:3]

~/workspace/xarray/xarray/core/indexing.py in __getitem__(self, indexer)
    518             array = LazilyVectorizedIndexedArray(self.array, self.key)
    519             return array[indexer]
--> 520         return type(self)(self.array, self._updated_key(indexer))
    521
    522     def __setitem__(self, key, value):

~/workspace/xarray/xarray/core/indexing.py in _updated_key(self, new_key)
    483
    484     def _updated_key(self, new_key):
--> 485         iter_new_key = iter(expanded_indexer(new_key.tuple, self.ndim))
    486         full_key = []
    487         for size, k in zip(self.array.shape, self.key.tuple):

AttributeError: 'slice' object has no attribute 'tuple'

Problem description

Dask array meta computations like to run x[:0, :0] on input arrays. This breaks with this class.

This is on master

Start in xarray/core/indexing.py at LazilyOuterIndexedArray._updated_key and getitem, then reproduce the reported x[:3] failure with the provided example. Confirm that slice objects, including the dask-style x[:0, :0] case, are accepted without the AttributeError and preserve lazy indexing behavior.