Remove tensor.ScalarSharedVariable

[ricardoV94]

pytensor/pytensor/tensor/sharedvar.py

Lines 97 to 142 in 673c1ac

	class ScalarSharedVariable(TensorSharedVariable):
	pass
	@shared_constructor.register(np.number)
	@shared_constructor.register(float)
	@shared_constructor.register(int)
	@shared_constructor.register(complex)
	def scalar_constructor(
	value, name=None, strict=False, allow_downcast=None, borrow=False, target="cpu"
	):
	"""`SharedVariable` constructor for scalar values.
	Default: int64 or float64.
	Notes
	-----
	We implement this using 0-d tensors for now.
	We ignore the borrow parameter as we convert ``value`` to an
	ndarray (this is a new object). This respects the semantic of
	borrow, as it is a hint to PyTensor that we can reuse it.
	"""
	if target != "cpu":
	raise TypeError("not for cpu")
	try:
	dtype = value.dtype
	except AttributeError:
	dtype = np.asarray(value).dtype
	dtype = str(dtype)
	value = _asarray(value, dtype=dtype)
	tensor_type = TensorType(dtype=str(value.dtype), shape=())
	# Do not pass the dtype to asarray because we want this to fail if
	# strict is True and the types do not match.
	rval = ScalarSharedVariable(
	type=tensor_type,
	value=np.array(value, copy=True),
	name=name,
	strict=strict,
	allow_downcast=allow_downcast,
	)
	return rval

This is an empty subclass created when doing shared(5). Internally, it behaves exactly like a shared 0d tensor variable shared(np.array(5)). In fact calling shared(shared(5).get_value()) will return a TensorSharedVariable from the original ScalarSharedVariable.

There exists a true ScalarSharedVariable with scalar operators in

pytensor/pytensor/scalar/sharedvar.py

Lines 25 to 61 in 673c1ac

	class ScalarSharedVariable(_scalar_py_operators, SharedVariable):
	pass
	# this is not installed in the default shared variable registry so that
	# scalars are typically 0-d tensors.
	# still, in case you need a shared variable scalar, you can get one
	# by calling this function directly.
	def shared(value, name=None, strict=False, allow_downcast=None):
	"""
	SharedVariable constructor for scalar values. Default: int64 or float64.
	Notes
	-----
	We implement this using 0-d tensors for now.
	"""
	if not isinstance(value, (np.number, float, int, complex)):
	raise TypeError()
	try:
	dtype = value.dtype
	except AttributeError:
	dtype = np.asarray(value).dtype
	dtype = str(dtype)
	value = getattr(np, dtype)(value)
	scalar_type = ScalarType(dtype=dtype)
	rval = ScalarSharedVariable(
	type=scalar_type,
	value=value,
	name=name,
	strict=strict,
	allow_downcast=allow_downcast,
	)
	return rval

We should probably not use that when a user calls shared(5), but I don't see any reason for the tensor.ScalarSharedVariable either. Just do the same checks as we have now but return the same type as shared(np.array(5)).

This would be as if type(pytensor.tensor.scalar()) returned a dummy subclass of TensorVariable confusingly called ScalarVariable (it does not).