Fix Missing Labels in FER2013 Dataset #8118

[NSalberg]

In the current implementation, labels are not provided for test split.

The FER2013 dataset provides labels for both training and testing in the icml_face_data.csv file.

This pull request reads the data from the icml_face_data.csv instead, providing labels for both the train and test splits.

[pytorch-bot]

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❌ 3 New Failures

As of commit e0a702d with merge base 5181a85 ():

NEW FAILURES - The following jobs have failed:

• Build Windows Conda / pytorch/vision / upload / conda-py3_8-cpu (gh)
  Unable to find an artifact with the name: pytorch_vision__3.8_cpu_
• Lint / python-source-and-configs / linux-job (gh)
  RuntimeError: Command docker exec -t f523634b115c92bd5161eea17076334e37803db0a094f151803d340ffd09dc2a /exec failed with exit code 1
• Lint / python-types / linux-job (gh)
  RuntimeError: Command docker exec -t 9873dadb74de790f7e9b2b8bd18fe087ca35a70667913224b1d081538672fdb6 /exec failed with exit code 1

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[NicolasHug]

Thank you for the PR @NSalberg .

The feature request looks reasonable, however I think we should avoid forcing the existence of icml_face_data.csv because that will potentially break existing users who only have downloaded train.csv and test.csv.

Perhaps we should instead check the existence of icml_face_data.csv and use it if it exists, and otherwise fall back to train.csv and test.csv?