Performance Regression or Improvement: apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks_21:mean_load_model_latency_milli_secs

[AnandInguva]

Performance change found in the test: apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks_21 for the metric: mean_load_model_latency_milli_secs.
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timestamp: Sun Dec 11 16:54:38 2022, metric_value: 111908.9
timestamp: Sat Dec 10 16:58:10 2022, metric_value: 107900.74
timestamp: Fri Dec 9 16:56:08 2022, metric_value: 106021.94
timestamp: Thu Dec 8 16:55:37 2022, metric_value: 107807.34666666666
timestamp: Wed Dec 7 16:57:05 2022, metric_value: 106788.94
timestamp: Tue Dec 6 16:55:53 2022, metric_value: 112162.67333333334
timestamp: Mon Dec 5 16:55:01 2022, metric_value: 112656.33333333333
timestamp: Sun Dec 4 16:54:55 2022, metric_value: 111517.0
timestamp: Sat Dec 3 16:55:05 2022, metric_value: 120645.27333333333
timestamp: Fri Dec 2 16:57:08 2022, metric_value: 109179.68
timestamp: Thu Dec 1 16:54:21 2022, metric_value: 111348.03333333334 <---- Anomaly
timestamp: Wed Nov 30 16:55:38 2022, metric_value: 138255.18666666668
timestamp: Tue Nov 29 17:15:51 2022, metric_value: 127745.75333333333
timestamp: Tue Nov 29 17:02:49 2022, metric_value: 134328.98666666666
timestamp: Mon Nov 28 16:56:35 2022, metric_value: 133028.40666666668
timestamp: Sun Nov 27 16:54:57 2022, metric_value: 128420.05333333333
timestamp: Sat Nov 26 16:54:09 2022, metric_value: 130647.56666666667
timestamp: Fri Nov 25 16:56:15 2022, metric_value: 129729.48666666666
timestamp: Thu Nov 24 16:56:12 2022, metric_value: 135499.94666666666
timestamp: Wed Nov 23 18:08:48 2022, metric_value: 127772.04666666666
timestamp: Tue Nov 22 17:07:59 2022, metric_value: 126505.05555555556