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Docs test issue with roc_auc #2985

@vfdev-5

Description

@vfdev-5

Docs test issue with roc_auc, probably related to the new scikit-learn release:

File "../../ignite/contrib/metrics/roc_auc.py", line ?, in default
Failed example:
    roc_auc = RocCurve()
    #The ``output_transform`` arg of the metric can be used to perform a sigmoid on the ``y_pred``.
    roc_auc.attach(default_evaluator, 'roc_auc')
    y_pred = torch.tensor([0.0474, 0.5987, 0.7109, 0.9997])
    y_true = torch.tensor([0, 0, 1, 0])
    state = default_evaluator.run([[y_pred, y_true]])
    print("FPR", [round(i, 3) for i in state.metrics['roc_auc'][0].tolist()])
    print("TPR", [round(i, 3) for i in state.metrics['roc_auc'][1].tolist()])
    print("Thresholds", [round(i, 3) for i in state.metrics['roc_auc'][2].tolist()])
Expected:
    FPR [0.0, 0.333, 0.333, 1.0]
    TPR [0.0, 0.0, 1.0, 1.0]
    Thresholds [2.0, 1.0, 0.711, 0.047]
Got:
    FPR [0.0, 0.333, 0.333, 1.0]
    TPR [0.0, 0.0, 1.0, 1.0]
    Thresholds [inf, 1.0, 0.711, 0.047]
5 items passed all tests:
   1 tests in 1
   1 tests in 2
   1 tests in 3
   1 tests in 4
   1 tests in 5
**********************************************************************
1 items had failures:
   1 of   2 in default
7 tests in 6 items.
6 passed and 1 failed.
***Test Failed*** 1 failures.

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