Performance Regression or Improvement: pytorch_image_classification_benchmarks-resnet152-GPU-mean_load_model_latency_milli_secs:mean_load_model_latency_milli_secs

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Performance change found in the
test: pytorch_image_classification_benchmarks-resnet152-GPU-mean_load_model_latency_milli_secs for the metric: mean_load_model_latency_milli_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 with Tesla T4 GPU.
Test link -

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

Line 151 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=7

timestamp: Tue Dec 31 06:55:07 2024, metric_value: 122599.20
timestamp: Mon Dec 30 06:45:37 2024, metric_value: 121750.85
timestamp: Sun Dec 29 06:48:51 2024, metric_value: 126396.92
timestamp: Sat Dec 28 06:44:31 2024, metric_value: 125432.50
timestamp: Fri Dec 27 06:51:24 2024, metric_value: 121294.73
timestamp: Thu Dec 26 06:46:05 2024, metric_value: 129072.67
timestamp: Wed Dec 25 06:41:52 2024, metric_value: 123215.38 <---- Anomaly
timestamp: Tue Dec 24 06:47:03 2024, metric_value: 131301.53
timestamp: Mon Dec 23 06:41:45 2024, metric_value: 135701.47
timestamp: Sun Dec 22 06:47:14 2024, metric_value: 124859.53
timestamp: Sat Dec 21 06:49:36 2024, metric_value: 130251.48
timestamp: Fri Dec 20 07:04:18 2024, metric_value: 132378.50
timestamp: Thu Dec 19 06:45:36 2024, metric_value: 130731.92
timestamp: Wed Dec 18 07:03:29 2024, metric_value: 127310.20
timestamp: Tue Dec 17 06:55:13 2024, metric_value: 128287.22
timestamp: Mon Dec 16 06:52:53 2024, metric_value: 129442.85
timestamp: Sun Dec 15 07:04:53 2024, metric_value: 138440.13