Deprecate redefinition of np.testing.assert_allclose

Author: Dhruvanshu-Joshi

doc/extending/creating_an_op.rst

@@ -551,7 +551,6 @@ exception. You can use the ``assert`` keyword to automatically raise an
 
     import numpy as np
     import pytensor
-    from tests import unittest_tools as utt
 
 
     class TestDouble(utt.InferShapeTester):
@@ -569,9 +568,9 @@ exception. You can use the ``assert`` keyword to automatically raise an
             inp = np.asarray(rng.random((5, 4)), dtype=pytensor.config.floatX)
             out = f(inp)
             # Compare the result computed to the expected value.
-            utt.assert_allclose(inp * 2, out)
+            np.testing.assert_allclose(inp * 2, out)
 
-We call ``utt.assert_allclose(expected_value, value)`` to compare
+We call ``np.testing.assert_allclose(expected_value, value)`` to compare
 NumPy ndarray.This raise an error message with more information. Also,
 the default tolerance can be changed with the PyTensor flags
 ``config.tensor__cmp_sloppy`` that take values in 0, 1 and 2. The

tests/graph/test_replace.py

@@ -12,7 +12,6 @@
     vectorize_node,
 )
 from pytensor.tensor import dvector, fvector, vector
-from tests import unittest_tools as utt
 from tests.graph.utils import MyOp, MyVariable, op_multiple_outputs
 
 
@@ -133,10 +132,10 @@ def test(x, y, mention_y):
             return function([], out)()
 
         x = shared(np.asarray(0.0, dtype=config.floatX))
-        utt.assert_allclose(
+        np.testing.assert_allclose(
             test(x, pt.sum((x + 1) ** 2), mention_y=False), 1.21000003815
         )
-        utt.assert_allclose(
+        np.testing.assert_allclose(
             test(x, pt.sum((x + 1) ** 2), mention_y=True), 1.21000003815
         )
 

tests/link/c/test_params_type.py

@@ -9,7 +9,6 @@
 from pytensor.link.c.type import EnumList, Generic
 from pytensor.scalar import ScalarType
 from pytensor.tensor.type import TensorType, matrix
-from tests import unittest_tools as utt
 
 
 tensor_type_0d = TensorType("float64", shape=tuple())
@@ -354,5 +353,5 @@ def test_op_params(self):
         vy1 = f1(vx)
         vy2 = f2(vx)
         ref = a * (vx**2) + b * vx + c
-        utt.assert_allclose(vy1, vy2)
-        utt.assert_allclose(ref, vy1)
+        np.testing.assert_allclose(vy1, vy2)
+        np.testing.assert_allclose(ref, vy1)

tests/link/test_vm.py

@@ -19,7 +19,6 @@
 from pytensor.tensor.math import cosh, tanh
 from pytensor.tensor.type import lscalar, scalar, scalars, vector, vectors
 from pytensor.tensor.variable import TensorConstant
-from tests import unittest_tools as utt
 
 
 class SomeOp(Op):
@@ -221,7 +220,7 @@ def test_partial_function(linker):
     assert f(3, output_subset=[0, 1, 2]) == f(3)
     assert f(4, output_subset=[0, 2]) == [f(4)[0], f(4)[2]]
 
-    utt.assert_allclose(f(5), np.array([32.0, 16.0, 1.7857142857142858]))
+    np.testing.assert_allclose(f(5), np.array([32.0, 16.0, 1.7857142857142858]))
 
 
 @pytest.mark.parametrize(

tests/scalar/test_basic.py

@@ -3,7 +3,6 @@
 
 import pytensor
 import pytensor.tensor as pt
-import tests.unittest_tools as utt
 from pytensor.compile.mode import Mode
 from pytensor.graph.fg import FunctionGraph
 from pytensor.link.c.basic import DualLinker
@@ -477,11 +476,11 @@ def test_grad_inrange():
         # x is equal to the lower or higher bound but in that case
         # PyTensor defines the gradient to be zero for stability.
         f = pytensor.function([x, low, high], [gx, glow, ghigh])
-        utt.assert_allclose(f(0, 1, 5), [0, 0, 0])
-        utt.assert_allclose(f(1, 1, 5), [0, 0, 0])
-        utt.assert_allclose(f(2, 1, 5), [0, 0, 0])
-        utt.assert_allclose(f(5, 1, 5), [0, 0, 0])
-        utt.assert_allclose(f(7, 1, 5), [0, 0, 0])
+        np.testing.assert_allclose(f(0, 1, 5), [0, 0, 0])
+        np.testing.assert_allclose(f(1, 1, 5), [0, 0, 0])
+        np.testing.assert_allclose(f(2, 1, 5), [0, 0, 0])
+        np.testing.assert_allclose(f(5, 1, 5), [0, 0, 0])
+        np.testing.assert_allclose(f(7, 1, 5), [0, 0, 0])
 
 
 def test_grad_abs():