Move clone_replace tests to tests.graph.test_basic

tests/graph/test_basic.py

@@ -4,7 +4,7 @@ from itertools import count
 import numpy as np
 import pytest
 
-from aesara import shared
+from aesara import config, function, shared
 from aesara import tensor as at
 from aesara.graph.basic import (
     Apply,
@@ -13,6 +13,7 @@ from aesara.graph.basic import (
     applys_between,
     as_string,
     clone,
+    clone_replace,
     equal_computations,
     general_toposort,
     get_var_by_name,
@@ -27,9 +28,18 @@ from aesara.graph.basic import (
 from aesara.graph.op import HasInnerGraph, Op
 from aesara.graph.type import Type
 from aesara.tensor.math import max_and_argmax
-from aesara.tensor.type import TensorType, iscalars, matrix, scalars
+from aesara.tensor.type import (
+    TensorType,
+    dvector,
+    fvector,
+    iscalars,
+    matrix,
+    scalars,
+    vector,
+)
 from aesara.tensor.type_other import NoneConst
 from aesara.tensor.var import TensorVariable
+from tests import unittest_tools as utt
 
 
 class MyType(Type):
@@ -537,3 +547,118 @@ def test_get_var_by_name():
     (res,) = get_var_by_name([o1, o2], "igo1")
 
     assert res == igo_out_1
+
+
+class TestCloneReplace:
+    def test_cloning_no_replace_strict_copy_inputs(self):
+        # This has nothing to do with scan, but it refers to the clone
+        # function that scan uses internally and that pfunc uses now and
+        # that users might want to use
+        x = vector("x")
+        y = vector("y")
+        z = shared(0.25)
+
+        f1 = z * (x + y) ** 2 + 5
+        f2 = clone_replace(f1, replace=None, strict=True, share_inputs=True)
+        f2_inp = graph_inputs([f2])
+
+        assert z in f2_inp
+        assert x in f2_inp
+        assert y in f2_inp
+
+    def test_cloning_no_replace_strict_not_copy_inputs(self):
+        # This has nothing to do with scan, but it refers to the clone
+        # function that scan uses internally and that pfunc uses now and
+        # that users might want to use
+        x = vector("x")
+        y = vector("y")
+        z = shared(0.25)
+
+        f1 = z * (x + y) ** 2 + 5
+        f2 = clone_replace(f1, replace=None, strict=True, share_inputs=False)
+        f2_inp = graph_inputs([f2])
+
+        assert z not in f2_inp
+        assert x not in f2_inp
+        assert y not in f2_inp
+
+    def test_cloning_replace_strict_copy_inputs(self):
+        # This has nothing to do with scan, but it refers to the clone
+        # function that scan uses internally and that pfunc uses now and
+        # that users might want to use
+        x = vector("x")
+        y = vector("y")
+        y2 = vector("y2")
+        z = shared(0.25)
+
+        f1 = z * (x + y) ** 2 + 5
+        f2 = clone_replace(f1, replace={y: y2}, strict=True, share_inputs=True)
+        f2_inp = graph_inputs([f2])
+        assert z in f2_inp
+        assert x in f2_inp
+        assert y2 in f2_inp
+
+    def test_cloning_replace_not_strict_copy_inputs(self):
+        # This has nothing to do with scan, but it refers to the clone
+        # function that scan uses internally and that pfunc uses now and
+        # that users might want to use
+        x = vector("x")
+        y = fvector("y")
+        y2 = dvector("y2")
+        z = shared(0.25)
+
+        f1 = z * (x + y) ** 2 + 5
+        f2 = clone_replace(f1, replace={y: y2}, strict=False, share_inputs=True)
+        f2_inp = graph_inputs([f2])
+        assert z in f2_inp
+        assert x in f2_inp
+        assert y2 in f2_inp
+
+    def test_cloning_replace_strict_not_copy_inputs(self):
+        # This has nothing to do with scan, but it refers to the clone
+        # function that scan uses internally and that pfunc uses now and
+        # that users might want to use
+        x = vector("x")
+        y = vector("y")
+        y2 = vector("y2")
+        z = shared(0.25)
+
+        f1 = z * (x + y) ** 2 + 5
+        f2 = clone_replace(f1, replace=[(y, y2)], strict=True, share_inputs=False)
+        f2_inp = graph_inputs([f2])
+        assert z not in f2_inp
+        assert x not in f2_inp
+        assert y2 not in f2_inp
+
+    def test_cloning_replace_not_strict_not_copy_inputs(self):
+        # This has nothing to do with scan, but it refers to the clone
+        # function that scan uses internally and that pfunc uses now and
+        # that users might want to use
+        x = vector("x")
+        y = fvector("y")
+        y2 = dvector("y2")
+        z = shared(0.25)
+
+        f1 = z * (x + y) ** 2 + 5
+        f2 = clone_replace(f1, replace=[(y, y2)], strict=False, share_inputs=False)
+        f2_inp = graph_inputs([f2])
+        assert z not in f2_inp
+        assert x not in f2_inp
+        assert y2 not in f2_inp
+
+    def test_clone(self):
+        def test(x, y, mention_y):
+            if mention_y:
+                d = 0.1 + 0 * y
+            else:
+                d = 0.1
+            out = clone_replace(y, replace={x: x + d})
+            return function([], out)()
+
+        x = shared(np.asarray(0.0, dtype=config.floatX))
+        utt.assert_allclose(
+            test(x, at.sum((x + 1) ** 2), mention_y=False), 1.21000003815
+        )
+        utt.assert_allclose(
+            test(x, at.sum((x + 1) ** 2), mention_y=True), 1.21000003815
+        )

tests/scan/test_basic.py

@@ -36,7 +36,7 @@ from aesara.gradient import (
     hessian,
     jacobian,
 )
-from aesara.graph.basic import Apply, clone_replace, graph_inputs
+from aesara.graph.basic import Apply, clone_replace
 from aesara.graph.fg import MissingInputError
 from aesara.graph.op import Op
 from aesara.misc.safe_asarray import _asarray
@@ -2060,106 +2060,6 @@ class TestScan:
 
         utt.assert_allclose(out, vR)
 
-    def test_cloning_no_replace_strict_copy_inputs(self):
-        # This has nothing to do with scan, but it refers to the clone
-        # function that scan uses internally and that pfunc uses now and
-        # that users might want to use
-        x = vector("x")
-        y = vector("y")
-        z = shared(0.25)
-
-        f1 = z * (x + y) ** 2 + 5
-        f2 = clone_replace(f1, replace=None, strict=True, share_inputs=True)
-        f2_inp = graph_inputs([f2])
-
-        assert z in f2_inp
-        assert x in f2_inp
-        assert y in f2_inp
-
-    def test_cloning_no_replace_strict_not_copy_inputs(self):
-        # This has nothing to do with scan, but it refers to the clone
-        # function that scan uses internally and that pfunc uses now and
-        # that users might want to use
-        x = vector("x")
-        y = vector("y")
-        z = shared(0.25)
-
-        f1 = z * (x + y) ** 2 + 5
-        f2 = clone_replace(f1, replace=None, strict=True, share_inputs=False)
-        f2_inp = graph_inputs([f2])
-
-        assert z not in f2_inp
-        assert x not in f2_inp
-        assert y not in f2_inp
-
-    def test_cloning_replace_strict_copy_inputs(self):
-        # This has nothing to do with scan, but it refers to the clone
-        # function that scan uses internally and that pfunc uses now and
-        # that users might want to use
-        x = vector("x")
-        y = vector("y")
-        y2 = vector("y2")
-        z = shared(0.25)
-
-        f1 = z * (x + y) ** 2 + 5
-        f2 = clone_replace(
-            f1, replace=OrderedDict([(y, y2)]), strict=True, share_inputs=True
-        )
-        f2_inp = graph_inputs([f2])
-        assert z in f2_inp
-        assert x in f2_inp
-        assert y2 in f2_inp
-
-    def test_cloning_replace_not_strict_copy_inputs(self):
-        # This has nothing to do with scan, but it refers to the clone
-        # function that scan uses internally and that pfunc uses now and
-        # that users might want to use
-        x = vector("x")
-        y = fvector("y")
-        y2 = dvector("y2")
-        z = shared(0.25)
-
-        f1 = z * (x + y) ** 2 + 5
-        f2 = clone_replace(
-            f1, replace=OrderedDict([(y, y2)]), strict=False, share_inputs=True
-        )
-        f2_inp = graph_inputs([f2])
-        assert z in f2_inp
-        assert x in f2_inp
-        assert y2 in f2_inp
-
-    def test_cloning_replace_strict_not_copy_inputs(self):
-        # This has nothing to do with scan, but it refers to the clone
-        # function that scan uses internally and that pfunc uses now and
-        # that users might want to use
-        x = vector("x")
-        y = vector("y")
-        y2 = vector("y2")
-        z = shared(0.25)
-
-        f1 = z * (x + y) ** 2 + 5
-        f2 = clone_replace(f1, replace=[(y, y2)], strict=True, share_inputs=False)
-        f2_inp = graph_inputs([f2])
-        assert z not in f2_inp
-        assert x not in f2_inp
-        assert y2 not in f2_inp
-
-    def test_cloning_replace_not_strict_not_copy_inputs(self):
-        # This has nothing to do with scan, but it refers to the clone
-        # function that scan uses internally and that pfunc uses now and
-        # that users might want to use
-        x = vector("x")
-        y = fvector("y")
-        y2 = dvector("y2")
-        z = shared(0.25)
-
-        f1 = z * (x + y) ** 2 + 5
-        f2 = clone_replace(f1, replace=[(y, y2)], strict=False, share_inputs=False)
-        f2_inp = graph_inputs([f2])
-        assert z not in f2_inp
-        assert x not in f2_inp
-        assert y2 not in f2_inp
-
     # TEST RE-ordering of inputs
     # some rnn with multiple outputs and multiple inputs; other
     # dimension instead of scalars/vectors
@@ -4325,23 +4225,6 @@ class TestScan:
         f = function([v], grad(y.sum(), W))
         utt.assert_allclose(f([1, 2]), [[0, 0, 0], [1, 1, 1], [1, 1, 1]])
 
-    def test_clone(self):
-        def test(x, y, mention_y):
-            if mention_y:
-                d = 0.1 + 0 * y
-            else:
-                d = 0.1
-            out = clone_replace(y, replace={x: x + d})
-            return function([], out)()
-
-        x = shared(np.asarray(0.0, dtype=config.floatX))
-        utt.assert_allclose(
-            test(x, at_sum((x + 1) ** 2), mention_y=False), 1.21000003815
-        )
-        utt.assert_allclose(
-            test(x, at_sum((x + 1) ** 2), mention_y=True), 1.21000003815
-        )
-
     def test_grad_find_input(self):
         w = shared(np.array(0, dtype="float32"), name="w")
         init = fscalar("init")