XFAIL Sparse operations

Author: ricardoV94

tests/compile/function/test_pfunc.py

@@ -1,5 +1,6 @@
 import numpy as np
 import pytest
+import scipy as sp
 
 import pytensor.tensor as pt
 from pytensor.compile import UnusedInputError, get_mode
@@ -9,6 +10,7 @@
 from pytensor.compile.sharedvalue import shared
 from pytensor.configdefaults import config
 from pytensor.graph.utils import MissingInputError
+from pytensor.sparse import SparseTensorType
 from pytensor.tensor.math import sum as pt_sum
 from pytensor.tensor.type import (
     bscalar,
@@ -763,18 +765,15 @@ 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(reason="Numba does not support Sparse Ops yet")
     def test_sparse_input_aliasing_affecting_inplace_operations(self):
-        sp = pytest.importorskip("scipy", minversion="0.7.0")
-
-        from pytensor import sparse
-
         # Note: to trigger this bug with pytensor rev 4586:2bc6fc7f218b,
         #        you need to make in inputs mutable (so that inplace
         #        operations are used) and to break the elemwise composition
         #        with some non-elemwise op (here dot)
 
-        x = sparse.SparseTensorType("csc", dtype="float64")()
-        y = sparse.SparseTensorType("csc", dtype="float64")()
+        x = SparseTensorType("csc", dtype="float64")()
+        y = SparseTensorType("csc", dtype="float64")()
         f = function([In(x, mutable=True), In(y, mutable=True)], (x + y) + (x + y))
         # Test 1. If the same variable is given twice
 

tests/test_raise_op.py

@@ -181,6 +181,7 @@ def test_infer_shape_scalar(self):
         )
 
 
+@pytest.mark.xfail(reason="Numba does not support Sparse Ops yet")
 def test_CheckAndRaise_sparse_variable():
     check_and_raise = CheckAndRaise(ValueError, "sparse_check")
 

tests/typed_list/test_basic.py

@@ -452,6 +452,7 @@ def test_non_tensor_type(self):
 
         assert f([[x, y], [x, y, y]], [x, y]) == 0
 
+    @pytest.mark.xfail(reason="Numba does not support Sparse Ops yet")
     def test_sparse(self):
         mySymbolicSparseList = TypedListType(
             sparse.SparseTensorType("csr", pytensor.config.floatX)
@@ -519,6 +520,7 @@ def test_non_tensor_type(self):
 
         assert f([[x, y], [x, y, y]], [x, y]) == 1
 
+    @pytest.mark.xfail(reason="Numba does not support Sparse Ops yet")
     def test_sparse(self):
         mySymbolicSparseList = TypedListType(
             sparse.SparseTensorType("csr", pytensor.config.floatX)