[Model] Add minimal native RWKV7 serving support

[123123213weqw]

Summary

This PR adds minimal native vLLM serving support for non-hybrid, linear-recurrent RWKV7 causal-LM checkpoints.

• Adds RWKV7Config and RWKV7ForCausalLM to the native config and model registries.
• Integrates RWKV7's attention-shift, recurrent-WKV, and FFN-shift states with the existing Mamba state-cache plumbing.
• Keeps weights and pipeline-parallel intermediate activations in the requested model dtype while keeping recurrent runtime state in fp32.
• Supports batched prefill/decode and the V1 scheduler's chunked-prefill path without adding an external runtime dependency or a new scheduler policy.
• Adds registry, initialization, CPU, CUDA, state-cache, dtype, optional FLA-reference, and CUDA-graph-padding coverage.

Relationship to #48686

This is a current-main rescue/rebase of #48686, not an independent competing implementation. The original author is credited as a co-author of the squashed commit. We could not update the original fork branch directly, so this is opened as a draft to unblock review on a clean base. Please do not merge both PRs; if the original branch is updated to the same commit, this draft can be closed.

The branch is based on vllm-project/vllm@0164022c907014a27e81c514cd4dff6091904c2b and removes the stale merge conflicts from the original PR.

Scope and maintenance boundary

This is intentionally a minimum complete serving integration. It does not add:

• vendored RWKV CUDA/Triton kernels;
• a new external runtime dependency;
• RWKV-specific tokenizer, sampling, tool-parser, or prompt behavior;
• a scheduler-specific cache policy;
• quantization or speculative-decoding claims.

Those can be proposed independently after the baseline model is accepted.

CUDA graph padding fix

The rebase found an additional correctness issue. CUDA-graph metadata may include zero-length padded requests in num_decodes, while num_decode_tokens counts only real decode tokens and state_indices_tensor ends with PAD_SLOT_ID=-1.

RWKV7 must therefore gather decode state slots with num_decode_tokens, not num_decodes. Otherwise a padded graph batch can select slot -1 or produce a shape mismatch. This PR includes the fix and a regression comparing padded metadata with the equivalent unpadded decode.

Validation

Environment: RTX 4080, Python 3.12, PyTorch 2.11.0+cu130.

CUDA_VISIBLE_DEVICES=0 \
PYTHONPATH=<rebased-current-main-tree> \
python -m pytest -q tests/model_executor/test_rwkv7.py

Result: 15 passed, 2 skipped. The skipped tests are the opt-in external-FLA parity tests. The passing set includes the CUDA custom-op path, CUDA batched decode, batched prefill, recurrent-state updates, dtype behavior, prefix-cache configuration, and padded CUDA-graph metadata.

All applicable pre-commit hooks pass, including Ruff, formatting, mypy, SPDX, forbidden-import, and config validation checks.

Real-checkpoint checks:

• A 0.1B HF-format checkpoint resolves to RWKV7ForCausalLM and loads its complete 0.36 GiB safetensors checkpoint.
• V1 generation completed for two differently sized prompts with chunked prefill enabled, producing 32 output tokens in one batched request. This was a compatibility smoke test, not a performance claim.
• A real 1.5B converted checkpoint maps 795/795 parameters with no missing, unexpected, or shape-mismatched tensors.
• Independent HF-adapter validation against the official RWKV implementation produced 64/64 greedy-token agreement and cosine similarity of approximately 0.999998.

The 4080 host currently has a v0.20.1 binary extension. Current-main Python reaches successful RWKV7 config resolution and weight loading, but a fully current engine run needs a matching current-main wheel because the older binary lacks an unrelated _C.rotary_embedding operator. The successful end-to-end compatibility smoke used the exact RWKV7 model file plus a small test-environment adapter for the Mamba backend enum API difference.

The earlier external-FLA and large-checkpoint evidence remains documented in #48686.

AI assistance

AI assistance was used during development and testing. The human submitter reviewed the changes, test evidence, and PR text and is responsible for the contribution.

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[mergify]

Documentation preview: https://vllm--49875.org.readthedocs.build/en/49875/

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[chatgpt-codex-connector]

Create tied embeddings on the final pipeline rank

When tie_word_embeddings=true and pipeline parallelism uses more than one rank, RWKV7Model creates embed_tokens only on the first rank, so this branch assigns the final rank's lm_head to a PPMissingLayer. compute_logits therefore has no output weight and tied RWKV7 checkpoints cannot serve with PP; create the embedding on the last rank as well, or construct a real tied LM head there.

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