XFAIL conv tests of Ops without Python implementation

tests/tensor/conv/test_abstract_conv.py

@@ -3,9 +3,11 @@ import pytest
 
 import pytensor
 import pytensor.tensor as pt
+from pytensor.compile import get_default_mode
 from pytensor.compile.mode import Mode
 from pytensor.configdefaults import config
 from pytensor.graph.rewriting.basic import check_stack_trace
+from pytensor.link.numba import NumbaLinker
 from pytensor.tensor.conv import abstract_conv
 from pytensor.tensor.conv.abstract_conv import (
     AbstractConv2d,
@@ -757,6 +759,10 @@ class BaseTestConv:
     def run_test_case(self, *args, **kargs):
         raise NotImplementedError()
 
+    @pytest.mark.xfail(
+        condition=isinstance(get_default_mode().linker, NumbaLinker),
+        reason="Involves Ops with no Python implementation for numba to use as fallback",
+    )
     def test_all(self):
         ds = self.default_subsamples
         db = self.default_border_mode
@@ -815,6 +821,10 @@ class BaseTestConv2d(BaseTestConv):
     def run_test_case_gi(self, *args, **kwargs):
         raise NotImplementedError()
 
+    @pytest.mark.xfail(
+        condition=isinstance(get_default_mode().linker, NumbaLinker),
+        reason="Involves Ops with no Python implementation for numba to use as fallback",
+    )
     def test_gradinput_arbitrary_output_shapes(self):
         # this computes the grad wrt inputs for an output shape
         # that the forward convolution would not produce
@@ -948,10 +958,7 @@ class BaseTestConv2d(BaseTestConv):
         )
 
 
-@pytest.mark.skipif(
-    config.cxx == "",
-    reason="SciPy and cxx needed",
-)
+@pytest.mark.skipif(config.cxx == "", reason="cxx needed")
 class TestAbstractConvNoOptim(BaseTestConv2d):
     @classmethod
     def setup_class(cls):
@@ -1884,9 +1891,10 @@ class TestConv2dGrads:
                         )
 
 
-@pytest.mark.skipif(
-    config.cxx == "",
-    reason="SciPy and cxx needed",
+@pytest.mark.skipif(config.cxx == "", reason="cxx needed")
+@pytest.mark.xfail(
+    condition=isinstance(get_default_mode().linker, NumbaLinker),
+    reason="Involves Ops with no Python implementation for numba to use as fallback",
 )
 class TestGroupedConvNoOptim:
     conv = abstract_conv.AbstractConv2d
@@ -2096,9 +2104,10 @@ class TestGroupedConvNoOptim:
             utt.verify_grad(conv_gradinputs, [kern, top], mode=self.mode, eps=1)
 
 
-@pytest.mark.skipif(
-    config.cxx == "",
-    reason="SciPy and cxx needed",
+@pytest.mark.skipif(config.cxx == "", reason="cxx needed")
+@pytest.mark.xfail(
+    condition=isinstance(get_default_mode().linker, NumbaLinker),
+    reason="Involves Ops with no Python implementation for numba to use as fallback",
 )
 class TestGroupedConv3dNoOptim(TestGroupedConvNoOptim):
     conv = abstract_conv.AbstractConv3d