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https://issues.apache.org/jira/browse/BEAM-14068?focusedWorklogId=778288&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-778288
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ASF GitHub Bot logged work on BEAM-14068:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 03/Jun/22 20:14
Start Date: 03/Jun/22 20:14
Worklog Time Spent: 10m
Work Description: AnandInguva commented on PR #17462:
URL: https://github.com/apache/beam/pull/17462#issuecomment-1146326503
@tvalentyn Changed the last few things. I kept run() and run_pipeline() as
separate because there are plans to return an pipeline object from
`run_pipeline()` for benchmark tests(still working on that). So I thought may
be its better to have a separate method. Right now, I have a different PR
working on top of this code by returning a pipeline object from
`run_pipeline()` in a different file. I will try to refactor the code later if
thats okay.
Issue Time Tracking
-------------------
Worklog Id: (was: 778288)
Time Spent: 10h (was: 9h 50m)
> 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: 10h
> 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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