[GitHub] [beam] github-actions[bot] commented on issue #27077: Performance Regression or Improvement: Pytorch image classification on 50k images of size 224 x 224 with resnet 152 with Tesla T4 GPU:mean_load_model_latency_milli_secs

["github-actions[bot] (via GitHub)" <gi...@apache.org>]

github-actions[bot] commented on issue #27077:
URL: https://github.com/apache/beam/issues/27077#issuecomment-1672227134

   
     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](https://github.com/apache/beam/tree/master/sdks/python/apache_beam/testing/analyzers/README.md#triage-performance-alert-issues).
   
   
   `Test description:` Pytorch image classification on 50k images of size 224 x 224 with resnet 152 with Tesla T4 GPU. Test link - https://github.com/apache/beam/blob/42d0a6e3564d8b9c5d912428a6de18fb22a13ac1/.test-infra/jenkins/job_InferenceBenchmarkTests_Python.groovy#L151 Test dashboard - http://104.154.241.245/d/ZpS8Uf44z/python-ml-runinference-benchmarks?orgId=1&viewPanel=7
   
   ```
   
   timestamp: Wed Aug  9 20:22:26 2023, metric_value: 224696.44 <---- Anomaly
   timestamp: Sun Aug  6 20:11:28 2023, metric_value: 168483.14
   timestamp: Sat Aug  5 20:15:50 2023, metric_value: 178606.28
   timestamp: Fri Aug  4 20:17:43 2023, metric_value: 193685.41
   timestamp: Thu Aug  3 20:33:48 2023, metric_value: 175384.55
   timestamp: Wed Aug  2 15:48:49 2023, metric_value: 180097.67
   timestamp: Tue Aug  1 20:21:43 2023, metric_value: 187113.02
   timestamp: Tue Jul 18 20:18:01 2023, metric_value: 169408.30
   timestamp: Mon Jul 17 20:17:35 2023, metric_value: 179341.26
   timestamp: Sun Jul 16 20:12:41 2023, metric_value: 163747.60
   timestamp: Fri Jul 14 20:20:19 2023, metric_value: 172176.19
   
   ```


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