[Model] MTP fallback to eager for DeepSeek v32

[luccafong]

Purpose

1. Cudagraph + MTP V32 is still under progress, enable eager for now on MTP part by default which verified acceptance and eval and piecewise used with MTP enabled
2. Fix Eagle tests as well MTP tests (@njhill )

Test Plan

VLLM_SKIP_DEEP_GEMM_WARMUP=1 vllm serve "deepseek-ai/DeepSeek-V3.2-Exp" --max_model_len=20000 --gpu_memory_utilization=0.9 --tensor_parallel_size 8 --max_num_seqs=256 --speculative_config '{"num_speculative_tokens":1, "method":"mtp"}'  --no-enable-prefix-caching --compilation_config

lm_eval --model local-completions --tasks gsm8k     --model_args model=deepseek-ai/DeepSeek-V3.2-Exp,base_url=http://127.0.0.1:8000/v1/completions,num_concurrent=200,max_retries=3,tokenized_requests=False --batch_size 32 --num_fewshot 20 

Test Result

Tasks	Version	Filter	n-shot	Metric		Value		Stderr
gsm8k	3	flexible-extract	20	exact_match	↑	0.9507	±	0.006
		strict-match	20	exact_match	↑	0.9500	±	0.006

Note: it takes 9:58 with MTP, w/o MTP it is 12:08 (25% speedup)

^[[1;36m(APIServer pid=1007953)^[[0;0m INFO 09-30 12:31:58 [metrics.py:96] SpecDecoding metrics: Mean acceptance length: 1.92, Accepted throughput: 80.90 tokens/s, Drafted throughput: 88.00 tokens/s, Accepted: 809 tokens, Drafted: 880 tokens, Per-position acceptance rate: 0.919, Avg Draft acceptance rate: 91.9%

---

Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
• (Optional) Release notes update. If your change is user facing, please update the release notes draft in the Google Doc.

[gemini-code-assist]

Code Review

This pull request introduces a fallback to eager execution mode for DeepSeek v32 models when using Medusa-style Token Prediction (MTP) for speculative decoding. This is a temporary measure to address an issue where CUDA graph is not yet supported for this specific combination.

The changes are well-contained and logical:

1. A new enforce_eager flag is added to SpeculativeConfig to allow overriding the default execution mode.
2. This flag is automatically enabled for DeepSeek v32 models when MTP is used.
3. The EagleProposer, which handles MTP, now checks this flag to disable CUDA graph when necessary.

The implementation is correct and effectively resolves the issue described. The changes are specific to the problematic configuration and should not affect other models or execution paths. Overall, this is a good, targeted fix.

[LucasWilkinson]

LGTM; thanks!

[njhill]

@luccafong fyi I pushed a similar fix that was needed to test_mtp.py.

[luccafong]

@luccafong fyi I pushed a similar fix that was needed to test_mtp.py.

thx!