Replace more not x.owner by x.owner is None

pytensor/compile/function/__init__.py

@@ -221,7 +221,7 @@ def function(
                     if not isinstance(node.op.scalar_op, log):
                        return
                     inp = node.inputs[0]
-                    if not inp.owner:
+                    if inp.owner is None:
                        return
                     if not isinstance(inp.owner.op, add):
                        return

pytensor/graph/basic.py

@@ -1896,11 +1896,10 @@ def equal_computations(
             if isinstance(x, Constant):
                 return np.array_equal(x.data, y)
             return False
-        if x.owner and not y.owner:
+        x_is_owned, y_is_owned = (x.owner is not None, y.owner is not None)
+        if x_is_owned != y_is_owned:
             return False
-        if y.owner and not x.owner:
-            return False
-        if x.owner and y.owner:
+        if x_is_owned and y_is_owned:
             if x.owner.outputs.index(x) != y.owner.outputs.index(y):
                 return False
         if x not in in_xs and not (y.type.in_same_class(x.type)):
@@ -1918,7 +1917,7 @@ def equal_computations(
     for dx, dy in zip(xs, ys):
         assert isinstance(dx, Variable)
         # We checked above that both dx and dy have an owner or not
-        if not dx.owner:
+        if dx.owner is None:
             if isinstance(dx, Constant) and isinstance(dy, Constant):
                 if not dx.equals(dy):
                     return False

pytensor/graph/fg.py

@@ -252,7 +252,7 @@ class FunctionGraph(MetaObject):
 
             # Now, `var` has no more clients, so check if we need to remove it
             # and its `Apply` node
-            if not var.owner:
+            if var.owner is None:
                 self.variables.remove(var)
             else:
                 apply_node = var.owner

pytensor/graph/rewriting/basic.py

@@ -1321,7 +1321,7 @@ class SequentialNodeRewriter(NodeRewriter):
             # only 1 iteration
             if not self.apply_all_rewrites:
                 return new_repl
-            if not new_vars[0].owner:
+            if new_vars[0].owner is None:
                 # We are at the start of the graph.
                 return new_repl
             if len(new_repl) > 1:

pytensor/tensor/rewriting/basic.py

@@ -662,7 +662,7 @@ def local_cast_cast(fgraph, node):
         return
     x = node.inputs[0]
     if (
-        not x.owner
+        x.owner is None
         or not isinstance(x.owner.op, Elemwise)
         or not isinstance(x.owner.op.scalar_op, ps.Cast)
     ):
@@ -1189,7 +1189,7 @@ def local_merge_alloc(fgraph, node):
     """
     if not isinstance(node.op, Alloc):
         return False
-    if not node.inputs[0].owner or not isinstance(node.inputs[0].owner.op, Alloc):
+    if not (node.inputs[0].owner and isinstance(node.inputs[0].owner.op, Alloc)):
         return False
     inputs_outer = node.inputs
     inputs_inner = node.inputs[0].owner.inputs

pytensor/tensor/rewriting/elemwise.py

@@ -370,7 +370,7 @@ def apply_local_dimshuffle_lift(fgraph, var):
     """
     lift recursively
     """
-    if not var.owner:
+    if var.owner is None:
         return var
     new = local_dimshuffle_lift.transform(fgraph, var.owner)
     if new:

pytensor/tensor/rewriting/math.py

@@ -1248,7 +1248,7 @@ def local_sum_prod_of_mul_or_div(fgraph, node):
     """
 
     [node_inps] = node.inputs
-    if not node_inps.owner:
+    if node_inps.owner is None:
         return None
 
     inner_op = node_inps.owner.op
@@ -2711,13 +2711,13 @@ def local_grad_log_erfc_neg(fgraph, node):
     Make it so that the test does not generate an error in that case!
 
     """
-    if not node.inputs[1].owner or node.inputs[1].owner.op != erfc:
+    if not (node.inputs[1].owner and node.inputs[1].owner.op == erfc):
         return False
 
     erfc_in = node.inputs[1]
     erfc_x = erfc_in.owner.inputs[0]
 
-    if not node.inputs[0].owner:
+    if node.inputs[0].owner is None:
         return False
 
     # TODO: All of this should be replaced with a single, simple unification
@@ -2744,7 +2744,7 @@ def local_grad_log_erfc_neg(fgraph, node):
             y = mul_in.owner.inputs[:]
             del y[idx]
 
-    if not exp_in.owner.inputs[0].owner:
+    if exp_in.owner.inputs[0].owner is None:
         return False
 
     if exp_in.owner.inputs[0].owner.op == neg:

pytensor/tensor/rewriting/subtensor.py

@@ -286,7 +286,7 @@ def local_subtensor_of_dot(fgraph, node):
     """
     if not isinstance(node.op, Subtensor):
         return
-    if not node.inputs[0].owner or not isinstance(node.inputs[0].owner.op, Dot):
+    if not (node.inputs[0].owner and isinstance(node.inputs[0].owner.op, Dot)):
         return
     # If there is other node that use the outputs of the dot
     # We don't want to compute twice the sub part.
@@ -1445,7 +1445,7 @@ def local_adv_sub1_adv_inc_sub1(fgraph, node):
     if not isinstance(node.op, AdvancedSubtensor1):
         return
     inp = node.inputs[0]
-    if not inp.owner or not isinstance(inp.owner.op, AdvancedIncSubtensor1):
+    if not (inp.owner and isinstance(inp.owner.op, AdvancedIncSubtensor1)):
         return
     idx = node.inputs[1]
     idx2 = inp.owner.inputs[2]