Make Sparse tensor Types extend TensorType

aesara/__init__.py

@@ -167,7 +167,7 @@ def get_scalar_constant_value(v):
     """
     # Is it necessary to test for presence of aesara.sparse at runtime?
     sparse = globals().get("sparse")
-    if sparse and isinstance(v.type, sparse.SparseType):
+    if sparse and isinstance(v.type, sparse.SparseTensorType):
         if v.owner is not None and isinstance(v.owner.op, sparse.CSM):
             data = v.owner.inputs[0]
             return tensor.get_scalar_constant_value(data)

aesara/link/c/type.py

@@ -17,7 +17,7 @@ class CType(Type, CLinkerType):
 
     - `TensorType`: for numpy.ndarray
 
-    - `SparseType`: for scipy.sparse
+    - `SparseTensorType`: for scipy.sparse
 
     But you are encouraged to write your own, as described in WRITEME.
 

aesara/misc/may_share_memory.py

@@ -12,7 +12,7 @@
 try:
     import scipy.sparse
 
-    from aesara.sparse.basic import SparseType
+    from aesara.sparse.basic import SparseTensorType
 
     def _is_sparse(a):
         return scipy.sparse.issparse(a)
@@ -64,4 +64,4 @@ def may_share_memory(a, b, raise_other_type=True):
 
     if a_gpua or b_gpua:
         return False
-    return SparseType.may_share_memory(a, b)
+    return SparseTensorType.may_share_memory(a, b)

aesara/sparse/__init__.py

@@ -9,7 +9,7 @@
     enable_sparse = False
     warn("SciPy can't be imported.  Sparse matrix support is disabled.")
 
-from aesara.sparse.type import SparseType, _is_sparse
+from aesara.sparse.type import SparseTensorType, _is_sparse
 
 
 if enable_sparse: