Prepare for PyG 2.7 release (#10501)

Fix empty dataframe handling in WebQSPDataset

Add G-retriever (GNN+LLM) example (#9167)

1. #9462
2. #9480
3. #9481
4. **->** #9167

---

repro:
Latest NVIDIA PyG container
+
`git config --global credential.helper store; huggingface-cli login; cd
/opt/pyg; pip uninstall -y torch-geometric; rm -rf pytorch_geometric;
git clone -b gnn-llm-model-integration
https://github.com/pyg-team/pytorch_geometric.git; cd
/opt/pyg/pytorch_geometric; pip install .; pip install peft datasets
transformers pcst_fast sentencepiece; python3
examples/llm_plus_gnn/g_retriever.py`

old PR: #9154

note: pure cpu is 220x slower than pure GPU using a single Grace Hopper
(for llama-7b)

info:
tried gemma, performs worse in all train/val/test metrics. most likely
needs some tuning, will leave this as future work as part of the
community sprint to try many LLM and GNN combos and tune them. Therefore
keeping the default llama2

the new gemma-v2 is also much worse than llama2

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Akihiro Nitta <[email protected]>
Co-authored-by: rusty1s <[email protected]>

update

pyg 2.5.2

update

update

Bump up version (#8182)

Update cugraph conv layers for `pylibcugraphops=23.04` (#7023)

This PR updates cugraph models to reflect breaking changes in
`pylibcugraphops=23.04`.
~~Right now, it is **blocked** by RAPIDS 23.04 release.~~

CC: @MatthiasKohl @stadlmax

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Conda builds (#7018)