Remove stale Assert tests

pytensor/link/numba/dispatch/basic.py

@@ -233,37 +233,23 @@ def generate_fallback_impl(op, node, storage_map=None, **kwargs):
         node.dprint(depth=5, print_type=True)
 
     n_outputs = len(node.outputs)
+    single_out = n_outputs == 1
 
-    if n_outputs > 1:
-        ret_sig = numba.types.Tuple([get_numba_type(o.type) for o in node.outputs])
-    else:
+    if single_out:
         ret_sig = get_numba_type(node.outputs[0].type)
-
-    output_types = tuple(out.type for out in node.outputs)
-
-    def py_perform(inputs):
-        outputs = [[None] for i in range(n_outputs)]
-        op.perform(node, inputs, outputs)
-        return outputs
-
-    if n_outputs == 1:
-
-        def py_perform_return(inputs):
-            return output_types[0].filter(py_perform(inputs)[0][0])
-
     else:
+        ret_sig = numba.types.Tuple([get_numba_type(o.type) for o in node.outputs])
 
-        def py_perform_return(inputs):
-            # zip strict not specified because we are in a hot loop
-            return tuple(
-                out_type.filter(out[0])
-                for out_type, out in zip(output_types, py_perform(inputs))
-            )
+    def py_perform(inputs):
+        output_storage = [[None] for _i in range(n_outputs)]
+        op.perform(node, inputs, output_storage)
+        outputs = tuple(o[0] for o in output_storage)
+        return outputs[0] if single_out else outputs
 
     @numba_njit
     def perform(*inputs):
         with numba.objmode(ret=ret_sig):
-            ret = py_perform_return(inputs)
+            ret = py_perform(inputs)
         return ret
 
     return perform

tests/link/numba/test_basic.py

@@ -26,7 +26,6 @@ from pytensor.graph.type import Type
 from pytensor.ifelse import ifelse
 from pytensor.link.numba.dispatch import basic as numba_basic
 from pytensor.link.numba.linker import NumbaLinker
-from pytensor.raise_op import assert_op
 from pytensor.scalar.basic import ScalarOp, as_scalar
 from pytensor.tensor.elemwise import Elemwise
 
@@ -372,32 +371,6 @@ def test_perform(inputs, op, exc):
         )
 
 
-def test_perform_params():
-    """This tests for `Op.perform` implementations that require the `params` arguments."""
-
-    x = pt.vector(shape=(2,))
-    x_test_value = np.array([1.0, 2.0], dtype=config.floatX)
-
-    out = assert_op(x, np.array(True))
-
-    compare_numba_and_py([x], out, [x_test_value])
-
-
-def test_perform_type_convert():
-    """This tests the use of `Type.filter` in `objmode`.
-
-    The `Op.perform` takes a single input that it returns as-is, but it gets a
-    native scalar and it's supposed to return an `np.ndarray`.
-    """
-
-    x = pt.vector()
-    x_test_value = np.array([1.0, 2.0], dtype=config.floatX)
-
-    out = assert_op(x.sum(), np.array(True))
-
-    compare_numba_and_py([x], out, [x_test_value])
-
-
 def test_shared():
     a = shared(np.array([1, 2, 3], dtype=config.floatX))
 

tests/link/numba/test_extra_ops.py

@@ -5,6 +5,7 @@ import pytest
 
 import pytensor.tensor as pt
 from pytensor import config
+from pytensor.raise_op import assert_op
 from pytensor.tensor import extra_ops
 from tests.link.numba.test_basic import compare_numba_and_py
 
@@ -383,3 +384,12 @@ def test_Searchsorted(a, v, side, sorter, exc):
             g,
             [test_a, test_v] if sorter is None else [test_a, test_v, test_sorter],
         )
+
+
+def test_check_and_raise():
+    x = pt.vector()
+    x_test_value = np.array([1.0, 2.0], dtype=config.floatX)
+
+    out = assert_op(x.sum(), np.array(True))
+
+    compare_numba_and_py([x], out, [x_test_value])