Performance Regression or Improvement: pytorch_image_classification_benchmarks-resnet101-mean_inference_batch_latency_micro_secs:mean_inference_batch_latency_micro_secs

[github-actions]

Performance change found in the
test: pytorch_image_classification_benchmarks-resnet101-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 101.
Test link -

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

Line 34 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: Tue Nov  5 04:27:04 2024, metric_value: 4710233.41
timestamp: Mon Nov  4 04:26:17 2024, metric_value: 5839550.05
timestamp: Sun Nov  3 04:22:51 2024, metric_value: 5553802.41 <---- Anomaly
timestamp: Sat Nov  2 04:20:46 2024, metric_value: 4664255.10
timestamp: Fri Nov  1 04:25:53 2024, metric_value: 4676853.64
timestamp: Thu Oct 31 04:19:57 2024, metric_value: 4707798.19
timestamp: Wed Oct 30 04:23:19 2024, metric_value: 4883029.11
timestamp: Tue Oct 29 04:21:39 2024, metric_value: 4738389.88
timestamp: Mon Oct 28 04:27:57 2024, metric_value: 5592143.01
timestamp: Sun Oct 27 04:24:54 2024, metric_value: 4695381.08
timestamp: Sat Oct 26 04:20:24 2024, metric_value: 4804058.29
timestamp: Fri Oct 25 04:25:01 2024, metric_value: 4619860.13
timestamp: Thu Oct 24 04:21:30 2024, metric_value: 4927378.06