Performance Regression or Improvement: pytorch_image_classification_benchmarks-resnet101-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-resnet101-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 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=7

timestamp: Fri Jul 26 04:26:14 2024, metric_value: 109851.49
timestamp: Thu Jul 25 04:26:33 2024, metric_value: 121648.75
timestamp: Wed Jul 24 04:34:15 2024, metric_value: 114960.04 <---- Anomaly
timestamp: Tue Jul 23 04:26:45 2024, metric_value: 108010.63
timestamp: Mon Jul 22 04:26:04 2024, metric_value: 108092.15
timestamp: Sun Jul 21 04:23:32 2024, metric_value: 103478.60
timestamp: Sat Jul 20 04:22:56 2024, metric_value: 104693.11
timestamp: Fri Jul 19 04:23:51 2024, metric_value: 109316.49
timestamp: Thu Jul 18 04:39:38 2024, metric_value: 110972.85
timestamp: Wed Jul 17 04:27:52 2024, metric_value: 108361.69
timestamp: Tue Jul 16 04:24:59 2024, metric_value: 108979.83
timestamp: Mon Jul 15 04:25:45 2024, metric_value: 108501.94
timestamp: Sun Jul 14 04:22:48 2024, metric_value: 104355.11