def check_expected_results(results, atol=0.005, rtol=0.1):
    """Check actual results against expected results stored in
    cfg.EXPECTED_RESULTS. Optionally email if the match exceeds the specified
    tolerance.

    Expected results should take the form of a list of expectations, each
    specified by four elements: [dataset, task, metric, expected value]. For
    example: [['coco_2014_minival', 'box_proposal', 'AR@1000', 0.387], ...].

    The expected value may also be formatted as a list [mean, std] providing
    an empirical mean and standard deviation from which a valid range is computed
    using cfg.EXPECTED_RESULTS_SIGMA_TOL. For example:
    [['coco_2014_minival', 'box_proposal', 'AR@1000', [0.387, 0.001]], ...]
    """
    # cfg contains a reference set of results that we want to check against
    if len(cfg.EXPECTED_RESULTS) == 0:
        return

    for dataset, task, metric, expected_val in cfg.EXPECTED_RESULTS:
        assert dataset in results, 'Dataset {} not in results'.format(dataset)
        assert task in results[dataset], 'Task {} not in results'.format(task)
        assert metric in results[dataset][task], \
            'Metric {} not in results'.format(metric)
        actual_val = results[dataset][task][metric]
        ok = False
        if isinstance(expected_val, list):
            assert len(expected_val) == 2, (
                'Expected result must be in (mean, std) format'
            )
            mean, std = expected_val
            lo = mean - cfg.EXPECTED_RESULTS_SIGMA_TOL * std
            hi = mean + cfg.EXPECTED_RESULTS_SIGMA_TOL * std
            ok = (lo < actual_val) and (actual_val < hi)
            msg = (
                '{} > {} > {} sanity check (actual vs. expected): '
                '{:.3f} vs. mean={:.4f}, std={:.4}, range=({:.4f}, {:.4f})'
            ).format(dataset, task, metric, actual_val, mean, std, lo, hi)
        else:
            err = abs(actual_val - expected_val)
            tol = atol + rtol * abs(expected_val)
            ok = (err > tol)
            msg = (
                '{} > {} > {} sanity check (actual vs. expected): '
                '{:.3f} vs. {:.3f}, err={:.3f}, tol={:.3f}'
            ).format(dataset, task, metric, actual_val, expected_val, err, tol)
        if not ok:
            msg = 'FAIL: ' + msg
            logger.error(msg)
            if cfg.EXPECTED_RESULTS_EMAIL != '':
                subject = 'Detectron end-to-end test failure'
                job_name = os.environ[
                    'DETECTRON_JOB_NAME'
                ] if 'DETECTRON_JOB_NAME' in os.environ else '<unknown>'
                job_id = os.environ[
                    'WORKFLOW_RUN_ID'
                ] if 'WORKFLOW_RUN_ID' in os.environ else '<unknown>'
                body = [
                    'Name:',
                    job_name,
                    'Run ID:',
                    job_id,
                    'Failure:',
                    msg,
                    'Config:',
                    pprint.pformat(cfg),
                    'Env:',
                    pprint.pformat(dict(os.environ)),
                ]
                send_email(
                    subject, '\n\n'.join(body), cfg.EXPECTED_RESULTS_EMAIL
                )
        else:
            msg = 'PASS: ' + msg
            logger.info(msg)
Check actual results against expected results stored in
    cfg.EXPECTED_RESULTS. Optionally email if the match exceeds the specified
    tolerance.

    Expected results should take the form of a list of expectations, each
    specified by four elements: [dataset, task, metric, expected value]. For
    example: [['coco_2014_minival', 'box_proposal', 'AR@1000', 0.387], ...].

    The expected value may also be formatted as a list [mean, std] providing
    an empirical mean and standard deviation from which a valid range is computed
    using cfg.EXPECTED_RESULTS_SIGMA_TOL. For example:
    [['coco_2014_minival', 'box_proposal', 'AR@1000', [0.387, 0.001]], ...]
    
detectron/datasets/task_evaluation.py