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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2022/04/26 05:59:00 UTC
[jira] [Work logged] (BEAM-14068) RunInference Benchmarking tests
[ https://issues.apache.org/jira/browse/BEAM-14068?focusedWorklogId=762129&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-762129 ]
ASF GitHub Bot logged work on BEAM-14068:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 26/Apr/22 05:58
Start Date: 26/Apr/22 05:58
Worklog Time Spent: 10m
Work Description: asf-ci commented on PR #17462:
URL: https://github.com/apache/beam/pull/17462#issuecomment-1109377414
Can one of the admins verify this patch?
Issue Time Tracking
-------------------
Worklog Id: (was: 762129)
Time Spent: 20m (was: 10m)
> RunInference Benchmarking tests
> -------------------------------
>
> Key: BEAM-14068
> URL: https://issues.apache.org/jira/browse/BEAM-14068
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Anand Inguva
> Assignee: Anand Inguva
> Priority: P2
> Time Spent: 20m
> Remaining Estimate: 0h
>
> RunInference benchmarks will evaluate performance of Pipelines, which represent common use cases of Beam + Dataflow in Pytorch, sklearn and possibly TFX. These benchmarks would be the integration tests that exercise several software components using Beam, PyTorch, Scikit learn and TensorFlow extended.
> we would use the datasets that's available publicly (Eg; Kaggle).
> Size: small / 10 GB / 1 TB etc
> The default execution runner would be Dataflow unless specified otherwise.
> These tests would be run very less frequently(every release cycle).
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