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Random CI failures #903

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@woodsp-ibm

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@woodsp-ibm

CI had a seeming random failure in #902 where re-running the failed job passed. In looking at the nightly CI Actions I see a few failures, such as below. The 3rd item below is what failed in #902.

Investigating if the code can be improved whereby the possibility of failure is understood and updating either the unit test and/or the mainline code would be good to avoid these,

test.gradients.test_estimator_gradient.TestEstimatorGradientV2.test_gradient_u_2_LinCombEstimatorGradient
---------------------------------------------------------------------------------------------------------

Captured traceback:
~~~~~~~~~~~~~~~~~~~
    Traceback (most recent call last):

      File "/opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/ddt.py", line 221, in wrapper
    return func(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^

      File "/home/runner/work/qiskit-machine-learning/qiskit-machine-learning/test/gradients/test_estimator_gradient.py", line 540, in test_gradient_u
    self.assertAlmostEqual(value, correct_results[i][j], 1)

      File "/opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/unittest/case.py", line 939, in assertAlmostEqual
    raise self.failureException(msg)

    AssertionError: np.float64(0.05078125) != 0.0 within 1 places (np.float64(0.05078125) difference)
test.algorithms.inference.test_qbayesian.TestQBayesianInference.test_trivial_circuit_V2
---------------------------------------------------------------------------------------

Captured traceback:
~~~~~~~~~~~~~~~~~~~
    Traceback (most recent call last):

      File "D:\a\qiskit-machine-learning\qiskit-machine-learning\test\algorithms\inference\test_qbayesian.py", line 243, in test_trivial_circuit_V2
    self.assertTrue(

      File "C:\hostedtoolcache\windows\Python\3.12.9\x64\Lib\unittest\case.py", line 727, in assertTrue
    raise self.failureException(msg)

    AssertionError: np.False_ is not true
test.gradients.test_estimator_gradient.TestEstimatorGradientV2.test_gradient_parameter_coefficient_2_LinCombEstimatorGradient
-----------------------------------------------------------------------------------------------------------------------------

Captured traceback:
~~~~~~~~~~~~~~~~~~~
    Traceback (most recent call last):

      File "/opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/ddt.py", line 221, in wrapper
    return func(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^

      File "/home/runner/work/qiskit-machine-learning/qiskit-machine-learning/test/gradients/test_estimator_gradient.py", line 614, in test_gradient_parameter_coefficient
    np.testing.assert_allclose(gradients, correct_results[i], atol=1e-1, rtol=1e-1)

      File "/opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/numpy/testing/_private/utils.py", line 1691, in assert_allclose
    assert_array_compare(compare, actual, desired, err_msg=str(err_msg),

      File "/opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/contextlib.py", line 81, in inner
    return func(*args, **kwds)
           ^^^^^^^^^^^^^^^^^^^

      File "/opt/hostedtoolcache/Python/3.12.9/x64/lib/python3.12/site-packages/numpy/testing/_private/utils.py", line 889, in assert_array_compare
    raise AssertionError(msg)

    AssertionError: 
Not equal to tolerance rtol=0.1, atol=0.1

Mismatched elements: 1 / 4 (25%)
Max absolute difference among violations: 0.19980126
Max relative difference among violations: 0.27495638
 ACTUAL: array([-0.926467, -0.528749, -0.017578, -0.92627 ])
 DESIRED: array([-0.726665, -0.490513, -0.006861, -0.922888])

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