Remove numba__vectorize_target config

pytensor/configdefaults.py

@@ -1099,12 +1099,6 @@ def add_scan_configvars():
 
 
 def add_numba_configvars():
-    config.add(
-        "numba__vectorize_target",
-        ("Default target for numba.vectorize."),
-        EnumStr("cpu", ["parallel", "cuda"], mutable=True),
-        in_c_key=False,
-    )
     config.add(
         "numba__fastmath",
         ("If True, use Numba's fastmath mode."),

pytensor/configparser.py

@@ -157,7 +157,6 @@ class PyTensorConfigParser:
     scan__allow_gc: bool
     scan__allow_output_prealloc: bool
     # add_numba_configvars
-    numba__vectorize_target: str
     numba__fastmath: bool
     numba__cache: bool
     # add_caching_dir_configvars

tests/link/numba/test_basic.py

@@ -769,16 +769,6 @@ def test_IfElse(inputs, cond_fn, true_vals, false_vals):
     compare_numba_and_py(inputs, out, test_values)
 
 
-@pytest.mark.xfail(reason="https://github.com/numba/numba/issues/7409")
-def test_config_options_parallel():
-    x = pt.dvector()
-
-    with config.change_flags(numba__vectorize_target="parallel"):
-        pytensor_numba_fn = function([x], pt.sum(x), mode=numba_mode)
-        numba_mul_fn = pytensor_numba_fn.vm.jit_fn.py_func.__globals__["impl_sum"]
-        assert numba_mul_fn.targetoptions["parallel"] is True
-
-
 def test_config_options_fastmath():
     x = pt.dvector()