Su Zhou

Hi @MountPOTATO , we have merged the feature in the above PR. You should now be able to apply text normalization following the tutorial [here](https://github.com/awslabs/autogluon/blob/master/docs/tutorials/multimodal/customization.md#datatextnormalize_text)

Additionaly, `ray` osx file only started to exist starting from [2.7.1](https://anaconda.org/conda-forge/ray-default/files?version=2.7.1). Since AutoGluon moved to noarch on conda, we should make sure we pin the version to `>=2.7.1`

We need to update the conda recipe. I think we can keep as is for 1.0 and update it with the 1.1 conda release.

/benchmark module=tabular preset=tabular_medium benchmark=tabular_full time_limit=1h

/benchmark module=tabular preset=tabular_medium benchmark=tabular_full time_limit=1h [Benchmark Output][1] [1]: https://github.com/autogluon/autogluon/actions/runs/9703676393 Benchmark Test Result - Pass Evaluation Results Path: s3://autogluon-ci-benchmark/evaluation/tabular/upgrade_ray_2.3x The dashboard website is: http://autogluon-staging.s3-website-us-west-2.amazonaws.com/benchmark-dashboard/upgrade_ray_2.3x/a6dcbcb8d5723275d05fe8baf0f23edf0745d6b0/index.html [Benchmark Output][1] [1]: https://github.com/autogluon/autogluon/actions/runs/9847810310 Benchmark Test Result...

Closing now as the other fix seems to be working.

/benchmark module=tabular preset=tabular_best benchmark=tabular_full time_limit=1h

/platform_tests 297cba262dad7468729441e177e3e7a67672fa84 [Platform Tests Output][1] [1]: https://github.com/autogluon/autogluon/actions/runs/14610905957

/benchmark 297cba262dad7468729441e177e3e7a67672fa84 module=tabular preset=tabular_best benchmark=tabular_full time_limit=1h [Benchmark Output][1] [1]: https://github.com/autogluon/autogluon/actions/runs/14610930289 Benchmark Test Result - Pass Evaluation Results Path: s3://autogluon-ci-benchmark/evaluation/tabular/support_py313 The dashboard website is: http://autogluon-staging.s3-website-us-west-2.amazonaws.com/benchmark-dashboard/support_py313/8b3384d741f99fc3401c2d3cda597ef3f07edcff/index.html

/benchmark 297cba262dad7468729441e177e3e7a67672fa84 module=multimodal preset=multimodal_best benchmark=automm-image time_limit=g4_12x [Benchmark Output][1] [1]: https://github.com/autogluon/autogluon/actions/runs/14610973700 Benchmark Test Result - Pass Evaluation Results Path: s3://autogluon-ci-benchmark/evaluation/multimodal/support_py313 The dashboard website is: http://autogluon-staging.s3-website-us-west-2.amazonaws.com/benchmark-dashboard/support_py313/8b3384d741f99fc3401c2d3cda597ef3f07edcff/index.html