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

[github-actions]

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: Fri Feb 14 05:00:32 2025, metric_value: 7413785.43
timestamp: Thu Feb 13 04:54:07 2025, metric_value: 7279451.06
timestamp: Wed Feb 12 05:03:00 2025, metric_value: 7678381.49 <---- Anomaly
timestamp: Tue Feb 11 04:52:35 2025, metric_value: 6718623.04
timestamp: Mon Feb 10 04:55:37 2025, metric_value: 6760366.76
timestamp: Sun Feb  9 04:52:02 2025, metric_value: 6720928.09
timestamp: Sat Feb  8 04:58:39 2025, metric_value: 6742552.95
timestamp: Fri Feb  7 04:53:16 2025, metric_value: 6650138.19
timestamp: Thu Feb  6 04:55:17 2025, metric_value: 6656399.27
timestamp: Wed Feb  5 04:59:40 2025, metric_value: 7004130.80
timestamp: Tue Feb  4 04:51:50 2025, metric_value: 6941037.43
timestamp: Mon Feb  3 04:47:25 2025, metric_value: 6571289.29
timestamp: Sun Feb  2 04:54:28 2025, metric_value: 6630514.65