Numba sparse: Remove codebase xfails

Author: ricardoV94

pytensor/link/numba/dispatch/typed_list.py

@@ -9,6 +9,7 @@
     register_funcify_default_op_cache_key,
 )
 from pytensor.link.numba.dispatch.compile_ops import numba_deepcopy
+from pytensor.link.numba.dispatch.sparse.basic import CSCMatrixType, CSRMatrixType
 from pytensor.tensor.type_other import SliceType
 from pytensor.typed_list import (
     Append,
@@ -64,6 +65,18 @@ def all_equal(x, y):
         def all_equal(x, y):
             return x == y
 
+    if (isinstance(x, CSRMatrixType) and isinstance(y, CSRMatrixType)) or (
+        isinstance(x, CSCMatrixType) and isinstance(y, CSCMatrixType)
+    ):
+
+        def all_equal(x, y):
+            return (
+                x.shape == y.shape
+                and (x.data == y.data).all()
+                and (x.indptr == y.indptr).all()
+                and (x.indices == y.indices).all()
+            )
+
     return all_equal
 
 

tests/compile/function/test_pfunc.py

@@ -3,14 +3,13 @@
 import scipy as sp
 
 import pytensor.tensor as pt
-from pytensor.compile import UnusedInputError, get_default_mode, get_mode
+from pytensor.compile import UnusedInputError, get_mode
 from pytensor.compile.function import function, pfunc
 from pytensor.compile.function.pfunc import rebuild_collect_shared
 from pytensor.compile.io import In
 from pytensor.compile.sharedvalue import shared
 from pytensor.configdefaults import config
 from pytensor.graph.utils import MissingInputError
-from pytensor.link.numba import NumbaLinker
 from pytensor.sparse import SparseTensorType
 from pytensor.tensor.math import sum as pt_sum
 from pytensor.tensor.type import (
@@ -766,10 +765,6 @@ def test_shared_constructor_copies(self):
         # rule #2 reading back from pytensor-managed memory
         assert not np.may_share_memory(A.get_value(borrow=False), data_of(A))
 
-    @pytest.mark.xfail(
-        condition=isinstance(get_default_mode().linker, NumbaLinker),
-        reason="Numba does not support Sparse Ops yet",
-    )
     def test_sparse_input_aliasing_affecting_inplace_operations(self):
         # Note: to trigger this bug with pytensor rev 4586:2bc6fc7f218b,
         #        you need to make in inputs mutable (so that inplace

tests/typed_list/test_basic.py

@@ -7,8 +7,6 @@
 import pytensor
 import pytensor.typed_list
 from pytensor import sparse
-from pytensor.compile import get_default_mode
-from pytensor.link.numba import NumbaLinker
 from pytensor.tensor.type import (
     TensorType,
     integer_dtypes,
@@ -454,10 +452,6 @@ def test_non_tensor_type(self):
 
         assert f([[x, y], [x, y, y]], [x, y]) == 0
 
-    @pytest.mark.xfail(
-        condition=isinstance(get_default_mode().linker, NumbaLinker),
-        reason="Numba does not support Sparse Ops yet",
-    )
     def test_sparse(self):
         mySymbolicSparseList = TypedListType(
             sparse.SparseTensorType("csr", pytensor.config.floatX)
@@ -525,10 +519,6 @@ def test_non_tensor_type(self):
 
         assert f([[x, y], [x, y, y]], [x, y]) == 1
 
-    @pytest.mark.xfail(
-        condition=isinstance(get_default_mode().linker, NumbaLinker),
-        reason="Numba does not support Sparse Ops yet",
-    )
     def test_sparse(self):
         mySymbolicSparseList = TypedListType(
             sparse.SparseTensorType("csr", pytensor.config.floatX)