Remove `warn__reduce_join` flag

aesara/configdefaults.py

@@ -1454,23 +1454,6 @@ def add_deprecated_configvars():
         in_c_key=False,
     )
 
-    config.add(
-        "warn__reduce_join",
-        (
-            "Your current code is fine, but Aesara versions "
-            "prior to 0.7 (or this development version) "
-            "might have given an incorrect result. "
-            "To disable this warning, set the Aesara flag "
-            "warn__reduce_join to False. The problem was an "
-            "optimization, that modified the pattern "
-            '"Reduce{scalar.op}(Join(axis=0, a, b), axis=0)", '
-            "did not check the reduction axis. So if the "
-            "reduction axis was not 0, you got a wrong answer."
-        ),
-        BoolParam(_warn_default("0.7")),
-        in_c_key=False,
-    )
-
     config.add(
         "warn__inc_set_subtensor1",
         (

aesara/tensor/math_opt.py

@@ -5,7 +5,6 @@
 import itertools
 import logging
 import operator
-import warnings
 from functools import partial, reduce
 
 import numpy as np
@@ -13,7 +12,6 @@ import numpy as np
 import aesara.scalar.basic as aes
 import aesara.scalar.math as aes_math
 from aesara.assert_op import assert_op
-from aesara.configdefaults import config
 from aesara.graph.basic import Constant, Variable
 from aesara.graph.opt import (
     LocalOptGroup,
@@ -1609,20 +1607,7 @@ def local_reduce_join(fgraph, node):
         if reduce_axis is None:
             reduce_axis = tuple(range(node.inputs[0].ndim))
 
-        # I put this warning late to don't add extra warning.
         if len(reduce_axis) != 1 or 0 not in reduce_axis:
-            if config.warn__reduce_join:
-                warnings.warning(
-                    "Your current code is fine, but Aesara versions "
-                    "prior to 0.7 (or this development version Sept 2014) "
-                    "might have given an incorrect result for this code. "
-                    "To disable this warning, set the Aesara flag "
-                    "warn__reduce_join to False. The problem was an "
-                    "optimization, that modified the pattern "
-                    '"Reduce{scalar.op}(Join(axis=0, a, b), axis=0)", '
-                    "did not check the reduction axis. So if the "
-                    "reduction axis was not 0, you got a wrong answer."
-                )
             return
 
         # We add the new check late to don't add extra warning.

tests/tensor/test_math_opt.py

@@ -3567,8 +3567,7 @@ class TestLocalReduce:
         assert isinstance(topo[-1].op, Elemwise)
 
         # Test a case that was bugged in a old Aesara bug
-        with config.change_flags(warn__reduce_join=False):
-            f = function([], aet_sum(aet.stack([A, A]), axis=1), mode=self.mode)
+        f = function([], aet_sum(aet.stack([A, A]), axis=1), mode=self.mode)
 
         utt.assert_allclose(f(), [15, 15])
         topo = f.maker.fgraph.toposort()
@@ -3594,9 +3593,8 @@ class TestLocalReduce:
         # Test that the optimization does not crash in one case where it
         # is not applied.  Reported at
         # https://groups.google.com/d/topic/theano-users/EDgyCU00fFA/discussion
-        with config.change_flags(warn__reduce_join=False):
-            out = aet_sum([vx, vy, vz], axis=None)
-            f = function([vx, vy, vz], out)
+        out = aet_sum([vx, vy, vz], axis=None)
+        f = function([vx, vy, vz], out)
 
 
 class TestLocalSumProdDimshuffle: