ENH: support datetime64[ns] dtype

Before

index = array(['2017-06-02T00:00:00.000000000', '2017-06-03T00:00:00.000000000',
       '2017-06-04T00:00:00.000000000', ...,
       '2021-06-28T00:00:00.000000000', '2021-06-29T00:00:00.000000000',
       '2021-06-30T00:00:00.000000000'], dtype='datetime64[ns]')

pt.as_tensor(index)

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
File .venv/lib/python3.10/site-packages/pytensor/tensor/type.py:287, in TensorType.dtype_specs(self)
    286 try:
--> 287     return self.dtype_specs_map[self.dtype]
    288 except KeyError:

KeyError: 'datetime64[ns]'

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
Cell In[12], line 1
----> 1 pt.as_tensor(index)

File .venv/lib/python3.10/site-packages/pytensor/tensor/__init__.py:49, in as_tensor_variable(x, name, ndim, **kwargs)
     17 def as_tensor_variable(
     18     x: TensorLike, name: Optional[str] = None, ndim: Optional[int] = None, **kwargs
     19 ) -> "TensorVariable":
     20     """Convert `x` into an equivalent `TensorVariable`.
     21 
     22     This function can be used to turn ndarrays, numbers, `ScalarType` instances,
   (...)
     47 
     48     """
---> 49     return _as_tensor_variable(x, name, ndim, **kwargs)

File /usr/lib/python3.10/functools.py:889, in singledispatch.<locals>.wrapper(*args, **kw)
    885 if not args:
    886     raise TypeError(f'{funcname} requires at least '
    887                     '1 positional argument')
--> 889 return dispatch(args[0].__class__)(*args, **kw)

File .venv/lib/python3.10/site-packages/pytensor/tensor/basic.py:176, in _as_tensor_numbers(x, name, ndim, dtype, **kwargs)
    171 @_as_tensor_variable.register(np.bool_)
    172 @_as_tensor_variable.register(np.number)
    173 @_as_tensor_variable.register(Number)
    174 @_as_tensor_variable.register(np.ndarray)
    175 def _as_tensor_numbers(x, name, ndim, dtype=None, **kwargs):
--> 176     return constant(x, name=name, ndim=ndim, dtype=dtype)

File venv/lib/python3.10/site-packages/pytensor/tensor/basic.py:229, in constant(x, name, ndim, dtype)
    223             raise ValueError(
    224                 f"ndarray could not be cast to constant with {int(ndim)} dimensions"
    225             )
    227     assert x_.ndim == ndim
--> 229 ttype = TensorType(dtype=x_.dtype, shape=x_.shape)
    231 return TensorConstant(ttype, x_, name=name)

File .venv/lib/python3.10/site-packages/pytensor/tensor/type.py:116, in TensorType.__init__(self, dtype, shape, name, broadcastable)
    113         return s
    115 self.shape = tuple(parse_bcast_and_shape(s) for s in shape)
--> 116 self.dtype_specs()  # error checking is done there
    117 self.name = name
    118 self.numpy_dtype = np.dtype(self.dtype)

File .venv/lib/python3.10/site-packages/pytensor/tensor/type.py:289, in TensorType.dtype_specs(self)
    287     return self.dtype_specs_map[self.dtype]
    288 except KeyError:
--> 289     raise TypeError(
    290         f"Unsupported dtype for {self.__class__.__name__}: {self.dtype}"
    291     )

TypeError: Unsupported dtype for TensorType: datetime64[ns]

After

No error

Context for the issue:

Would be nice to have native support for datetimes in pytensor

Start with the dtype handling shown in pytensor/tensor/type.py and the conversion path in pytensor/tensor/init.py and pytensor/tensor/basic.py. Trace how pt.as_tensor receives the datetime64[ns] array, then verify that the example completes without the unsupported-dtype error.