Target Determinator Indexer Workflow (#118824)
As described in [this talk](https://www.youtube.com/watch?v=I95KmF6KSIA) and [this repo](https://github.com/osalpekar/llm-target-determinator), we are experimenting with using CodeLlama-powered information retrieval for target determination.
The idea is that we create embeddings for PyTorch test functions, and store this index in S3. Then when a new PR comes in, we create embedding(s) for that PR, compare them to the index of test embeddings, and run only the most relevant tests.
This PR creates a workflow that does the indexing part (creating embeddings for functions and store in S3). All the logic for running the indexer is in [osalpekar/llm-target-determinator](https://github.com/osalpekar/llm-target-determinator). This workflow just checks out the relevant repos, installs the dependencies, runs the torchrun command to trigger indexing, and uploads the artifacts to S3.
Co-authored-by: Catherine Lee <csl@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/118824
Approved by: https://github.com/izaitsevfb, https://github.com/huydhn
