Remove internal get_constant helper

Fixes bug in `local_add_neg_to_sub` reported in pymc-devs#584

pytensor/tensor/rewriting/math.py

@@ -126,24 +126,6 @@ def scalarconsts_rest(inputs, elemwise=True, only_process_constants=False):
     return consts, origconsts, nonconsts
 
 
-def get_constant(v):
-    """
-
-    Returns
-    -------
-    object
-        A numeric constant if v is a Constant or, well, a
-        numeric constant. If v is a plain Variable, returns None.
-
-    """
-    if isinstance(v, TensorConstant):
-        return v.unique_value
-    elif isinstance(v, Variable):
-        return None
-    else:
-        return v
-
-
 @register_canonicalize
 @register_stabilize
 @node_rewriter([Dot])
@@ -994,8 +976,8 @@ def simplify_constants(self, orig_num, orig_denum, out_type=None):
         """
         Find all constants and put them together into a single constant.
 
-        Finds all constants in orig_num and orig_denum (using
-        get_constant) and puts them together into a single
+        Finds all constants in orig_num and orig_denum
+        and puts them together into a single
         constant. The constant is inserted as the first element of the
         numerator. If the constant is the neutral element, it is
         removed from the numerator.
@@ -1016,17 +998,15 @@ def simplify_constants(self, orig_num, orig_denum, out_type=None):
         numct, denumct = [], []
 
         for v in orig_num:
-            ct = get_constant(v)
-            if ct is not None:
+            if isinstance(v, TensorConstant) and v.unique_value is not None:
                 # We found a constant in the numerator!
                 # We add it to numct
-                numct.append(ct)
+                numct.append(v.unique_value)
             else:
                 num.append(v)
         for v in orig_denum:
-            ct = get_constant(v)
-            if ct is not None:
-                denumct.append(ct)
+            if isinstance(v, TensorConstant) and v.unique_value is not None:
+                denumct.append(v.unique_value)
             else:
                 denum.append(v)
 
@@ -1050,10 +1030,15 @@ def simplify_constants(self, orig_num, orig_denum, out_type=None):
 
         if orig_num and len(numct) == 1 and len(denumct) == 0 and ct:
             # In that case we should only have one constant in `ct`.
-            assert len(ct) == 1
-            first_num_ct = get_constant(orig_num[0])
-            if first_num_ct is not None and ct[0].type.values_eq(
-                ct[0].data, first_num_ct
+            [var_ct] = ct
+            first_num_var = orig_num[0]
+            first_num_ct = (
+                first_num_var.unique_value
+                if isinstance(first_num_var, TensorConstant)
+                else None
+            )
+            if first_num_ct is not None and var_ct.type.values_eq(
+                var_ct.data, first_num_ct
             ):
                 # This is an important trick :( if it so happens that:
                 # * there's exactly one constant on the numerator and none on
@@ -1840,9 +1825,12 @@ def local_add_neg_to_sub(fgraph, node):
                     return [new_out]
 
             # Check if it is a negative constant
-            const = get_constant(second)
-            if const is not None and const < 0:
-                new_out = sub(first, np.abs(const))
+            if (
+                isinstance(second, TensorConstant)
+                and second.unique_value is not None
+                and second.unique_value < 0
+            ):
+                new_out = sub(first, np.abs(second.data))
                 return [new_out]
 
 
@@ -1871,7 +1859,12 @@ def local_mul_zero(fgraph, node):
 @register_specialize
 @node_rewriter([true_div])
 def local_div_to_reciprocal(fgraph, node):
-    if np.all(get_constant(node.inputs[0]) == 1.0):
+    if (
+        get_underlying_scalar_constant_value(
+            node.inputs[0], only_process_constants=True, raise_not_constant=False
+        )
+        == 1.0
+    ):
         out = node.outputs[0]
         new_out = reciprocal(local_mul_canonizer.merge_num_denum(node.inputs[1:], []))
         # The ones could have forced upcasting
@@ -1892,7 +1885,9 @@ def local_reciprocal_canon(fgraph, node):
 @register_canonicalize
 @node_rewriter([pt_pow])
 def local_pow_canonicalize(fgraph, node):
-    cst = get_constant(node.inputs[1])
+    cst = get_underlying_scalar_constant_value(
+        node.inputs[1], only_process_constants=True, raise_not_constant=False
+    )
     if cst == 0:
         return [alloc_like(1, node.outputs[0], fgraph)]
     if cst == 1:
@@ -1923,7 +1918,12 @@ def local_intdiv_by_one(fgraph, node):
 @node_rewriter([int_div, true_div])
 def local_zero_div(fgraph, node):
     """0 / x -> 0"""
-    if get_constant(node.inputs[0]) == 0:
+    if (
+        get_underlying_scalar_constant_value(
+            node.inputs[0], only_process_constants=True, raise_not_constant=False
+        )
+        == 0
+    ):
         ret = alloc_like(0, node.outputs[0], fgraph)
         ret.tag.values_eq_approx = values_eq_approx_remove_nan
         return [ret]
@@ -1936,8 +1936,12 @@ def local_pow_specialize(fgraph, node):
     odtype = node.outputs[0].dtype
     xsym = node.inputs[0]
     ysym = node.inputs[1]
-    y = get_constant(ysym)
-    if (y is not None) and not broadcasted_by(xsym, ysym):
+    try:
+        y = get_underlying_scalar_constant_value(ysym, only_process_constants=True)
+    except NotScalarConstantError:
+        return
+
+    if not broadcasted_by(xsym, ysym):
         rval = None
 
         if np.all(y == 2):
@@ -1971,10 +1975,14 @@ def local_pow_to_nested_squaring(fgraph, node):
     """
 
     # the idea here is that we have pow(x, y)
+    xsym, ysym = node.inputs
+
+    try:
+        y = get_underlying_scalar_constant_value(ysym, only_process_constants=True)
+    except NotScalarConstantError:
+        return
+
     odtype = node.outputs[0].dtype
-    xsym = node.inputs[0]
-    ysym = node.inputs[1]
-    y = get_constant(ysym)
 
     # the next line is needed to fix a strange case that I don't
     # know how to make a separate test.
@@ -1990,7 +1998,7 @@ def local_pow_to_nested_squaring(fgraph, node):
             y = y[0]
         except IndexError:
             pass
-    if (y is not None) and not broadcasted_by(xsym, ysym):
+    if not broadcasted_by(xsym, ysym):
         rval = None
         # 512 is too small for the cpu and too big for some gpu!
         if abs(y) == int(abs(y)) and abs(y) <= 512:
@@ -2057,7 +2065,9 @@ def local_mul_specialize(fgraph, node):
             nb_neg_node += 1
 
         # remove special case arguments of 1, -1 or 0
-        y = get_constant(inp)
+        y = get_underlying_scalar_constant_value(
+            inp, only_process_constants=True, raise_not_constant=False
+        )
         if y == 1.0:
             nb_cst += 1
         elif y == -1.0:

tests/tensor/rewriting/test_math.py

@@ -4440,11 +4440,13 @@ def test_local_add_neg_to_sub(first_negative):
     assert np.allclose(f(x_test, y_test), exp)
 
 
-def test_local_add_neg_to_sub_const():
+@pytest.mark.parametrize("const_left", (True, False))
+def test_local_add_neg_to_sub_const(const_left):
     x = vector("x")
-    const = 5.0
+    const = np.full((3, 2), 5.0)
+    out = -const + x if const_left else x + (-const)
 
-    f = function([x], x + (-const), mode=Mode("py"))
+    f = function([x], out, mode=Mode("py"))
 
     nodes = [
         node.op