Remove redundant add_mul_fusion

The same job is done by canonicalize before this rewrite is ever called.

aesara/tensor/rewriting/math.py

@@ -82,7 +82,6 @@
     register_uncanonicalize,
     register_useless,
 )
-from aesara.tensor.rewriting.elemwise import FusionOptimizer, fuse_seqopt
 from aesara.tensor.shape import Shape, Shape_i
 from aesara.tensor.subtensor import Subtensor
 from aesara.tensor.type import (
@@ -2843,66 +2842,6 @@ def check_input(inputs):
     return [ret]
 
 
-def local_add_mul_fusion(fgraph, node):
-    """Fuse consecutive add or mul in one such node with more inputs.
-
-    It is better to fuse add/mul that way then in a Composite node as
-    this make the inner graph of the Composite smaller. This allow to
-    put more computation in a Composite before hitting the max
-    recursion limit when pickling Composite.
-
-    """
-    if not isinstance(node.op, Elemwise) or not isinstance(
-        node.op.scalar_op, (aes.Add, aes.Mul)
-    ):
-        return False
-
-    s_op = node.op.scalar_op.__class__
-    new_inp = []
-    fused = False
-    nb_inputs = len(node.inputs)
-    max_inputs = float("inf")
-    if hasattr(node.op, "max_inputs"):
-        max_inputs = node.op.max_inputs(node)
-    for inp in node.inputs:
-        if (
-            inp.owner
-            and isinstance(inp.owner.op, Elemwise)
-            and isinstance(inp.owner.op.scalar_op, s_op)
-            and
-            # Do not duplicate the operation.
-            len(fgraph.clients[inp]) == 1
-            and (nb_inputs + len(inp.owner.inputs) - 1) <= max_inputs
-        ):
-            new_inp.extend(inp.owner.inputs)
-            fused = True
-        else:
-            new_inp.append(inp)
-
-    # We can not compare the number of inputs as Mul and Add could have
-    # 0 or 1 inputs in some corner cases.
-    if fused:
-        output = node.op(*new_inp)
-        copy_stack_trace(node.outputs[0], output)
-
-        # Do the recursion here to help lower the number of
-        # FusionOptimizer iteration.
-        if output.owner:
-            output2 = local_add_mul_fusion(fgraph, output.owner)
-            if output2:
-                return output2
-        return [output]
-
-
-fuse_seqopt.register(
-    "local_add_mul_fusion",
-    FusionOptimizer(local_add_mul_fusion),
-    "fast_run",
-    "fusion",
-    position=0,
-)
-
-
 def _skip_mul_1(r):
     if r.owner and r.owner.op == mul:
         not_is_1 = [i for i in r.owner.inputs if not _is_1(i)]

tests/tensor/rewriting/test_elemwise.py

@@ -998,23 +998,35 @@ def test_big_fusion(self):
             for node in dlogp.maker.fgraph.toposort()
         )
 
-    def test_add_mul_fusion_inplace(self):
-
-        rewrites = RewriteDatabaseQuery(
-            include=[
-                "local_elemwise_fusion",
-                "composite_elemwise_fusion",
-                "canonicalize",
-                "inplace",
-            ],
-            exclude=["cxx_only", "BlasOpt"],
-        )
-
-        mode = Mode(self.mode.linker, rewrites)
+    def test_add_mul_fusion_precedence(self):
+        """Test that additions and multiplications are "fused together" before
+        a `Composite` `Op` is introduced. This fusion is done by canonicalization
+        """
+        x, y, z = vectors("x", "y", "z")
+        out = log((x + y + z) / (x * y * z))
+        f = aesara.function([x, y, z], out, mode=self.mode)
+        # There should be a single Composite Op
+        nodes = f.maker.fgraph.apply_nodes
+        assert len(nodes) == 1
+        (node,) = nodes
+        assert isinstance(node.op, Elemwise)
+        scalar_op = node.op.scalar_op
+        assert isinstance(scalar_op, Composite)
+        assert [node.op for node in scalar_op.fgraph.toposort()] == [
+            # There should be a single mul
+            aes.mul,
+            # There should be a single add
+            aes.add,
+            aes.true_div,
+            aes.log,
+        ]
 
+    def test_add_mul_fusion_inplace(self):
+        # Note: This has nothing to do with the FusionOptimizer, as the "fusion"
+        # is done by canonicalize
         x, y, z = dmatrices("xyz")
         out = dot(x, y) + x + y + z
-        f = function([x, y, z], out, mode=mode)
+        f = function([x, y, z], out, mode=self.mode)
         topo = [n for n in f.maker.fgraph.toposort()]
         assert len(topo) == 2
         assert topo[-1].op.inplace_pattern
@@ -1026,7 +1038,9 @@ def test_add_mul_fusion_inplace(self):
 
         # TODO: Do we really need to do this?
         _ = f(
-            np.random.random((5, 5)), np.random.random((5, 5)), np.random.random((5, 5))
+            np.random.random((5, 5)),
+            np.random.random((5, 5)),
+            np.random.random((5, 5)),
         )
 
     @pytest.mark.skipif(not config.cxx, reason="No cxx compiler")