Performance Regression or Improvement: pytorch_image_classification_benchmarks-resnet152-mean_inference_batch_latency_micro_secs:mean_inference_batch_latency_micro_secs

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Performance change found in the
test: pytorch_image_classification_benchmarks-resnet152-mean_inference_batch_latency_micro_secs for the metric: mean_inference_batch_latency_micro_secs.

For more information on how to triage the alerts, please look at
Triage performance alert issues section of the README.

Test description: Pytorch image classification on 50k images of size 224 x 224 with resnet 152. Test link -

beam/.test-infra/jenkins/job_InferenceBenchmarkTests_Python.groovy

Line 63 in 42d0a6e

test : 'apache_beam.testing.benchmarks.inference.pytorch_image_classification_benchmarks',

Test dashboard - http://metrics.beam.apache.org/d/ZpS8Uf44z/python-ml-runinference-benchmarks?orgId=1&viewPanel=2

timestamp: Wed Aug 23 18:46:03 2023, metric_value: 6420228.70
timestamp: Tue Aug 22 18:49:52 2023, metric_value: 6576663.77
timestamp: Mon Aug 21 18:50:58 2023, metric_value: 6452809.12
timestamp: Sun Aug 20 18:43:33 2023, metric_value: 6494424.32
timestamp: Sat Aug 19 18:43:36 2023, metric_value: 6429134.98
timestamp: Fri Aug 18 18:47:48 2023, metric_value: 6607798.99
timestamp: Thu Aug 17 18:45:56 2023, metric_value: 6490357.56 <---- Anomaly
timestamp: Wed Aug 16 18:46:14 2023, metric_value: 6749735.14
timestamp: Tue Aug 15 18:48:33 2023, metric_value: 6528966.06
timestamp: Mon Aug 14 18:46:50 2023, metric_value: 6711545.85
timestamp: Sun Aug 13 18:43:21 2023, metric_value: 6476609.99
timestamp: Sat Aug 12 18:43:16 2023, metric_value: 6642396.34
timestamp: Fri Aug 11 18:48:57 2023, metric_value: 6698904.45
timestamp: Thu Aug 10 18:59:14 2023, metric_value: 6568815.25
timestamp: Wed Aug  9 18:50:50 2023, metric_value: 6646631.05
timestamp: Tue Aug  8 20:01:50 2023, metric_value: 6567408.72
timestamp: Mon Aug  7 18:46:51 2023, metric_value: 6508698.54