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: Mon Oct 27 09:52:41 2025, metric_value: 108283.82
timestamp: Sun Oct 26 09:48:08 2025, metric_value: 116804.33
timestamp: Sat Oct 25 09:52:55 2025, metric_value: 110032.30
timestamp: Fri Oct 24 21:22:35 2025, metric_value: 114048.00 <---- Anomaly
timestamp: Fri Oct 24 13:50:52 2025, metric_value: 117670.75
timestamp: Fri Oct 24 02:55:17 2025, metric_value: 120804.62
timestamp: Thu Oct  9 00:55:35 2025, metric_value: 124572.40
timestamp: Fri Sep 12 09:35:29 2025, metric_value: 120755.78
timestamp: Thu Sep 11 10:09:23 2025, metric_value: 122038.18
timestamp: Wed Sep 10 09:57:38 2025, metric_value: 123256.57
timestamp: Tue Sep  9 09:32:55 2025, metric_value: 119402.92
timestamp: Mon Sep  8 09:35:29 2025, metric_value: 126086.77
timestamp: Sat Sep  6 09:26:53 2025, metric_value: 119414.80
timestamp: Thu Sep  4 09:53:11 2025, metric_value: 121251.18