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Remove reimplementation of np.testing.assert_allclose #562

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Remove reimplementation of np.testing.assert_allclose #562

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4 changes: 2 additions & 2 deletions doc/extending/creating_an_op.rst
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Expand Up @@ -569,9 +569,9 @@ 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
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5 changes: 2 additions & 3 deletions tests/link/c/test_params_type.py
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Expand Up @@ -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())
Expand Down Expand Up @@ -355,5 +354,5 @@ 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)
3 changes: 1 addition & 2 deletions tests/link/test_vm.py
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Expand Up @@ -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):
Expand Down Expand Up @@ -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(
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11 changes: 5 additions & 6 deletions tests/scalar/test_basic.py
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Expand Up @@ -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
Expand Down Expand Up @@ -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():
Expand Down
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