[Feature Request] AutoDeploy: enable DeepSeek R1 MTP

## Summary Enable AutoDeploy support for DeepSeek R1 MTP / one-model speculative decoding. ## Motivation DeepSeek R1 exposes MTP layers in the DeepSeek-V3-family checkpoint layout, but AutoDeploy currently does not have full DeepSeek-V3-family MTP/Eagle drafter support. This blocks reduced smoke coverage and eventual real-weight validation for DeepSeek R1 MTP through AutoDeploy. ## Requested Support - Register DeepSeek-V3-family MTP with AutoDeploy's Eagle/MTP drafter path. - Support DeepSeek R1 MTP checkpoint remapping from target model layer indices into the drafter. - Keep shared target embedding and lm_head behavior aligned with the PyTorch backend. - Preserve realistic quantization behavior, including not graph-quantizing shared target modules that are called outside the exported graph. ## Initial Validation The first step is reduced smoke coverage because the full DeepSeek R1 model cannot be run in this local environment. The smoke should verify that the AutoDeploy MTP path initializes, loads the reduced checkpoint layout, compiles, and runs end to end. ## Follow-Up Accuracy Validation Add a full-model accuracy test in `test_llm_api_autodeploy.py` for DeepSeek R1 with MTP enabled. The test should verify that enabling MTP does not degrade accuracy relative to the non-MTP AutoDeploy path, and it should enforce a minimum acceptance-rate threshold so we know the drafter is actually useful rather than merely functional. ## Acceptance Criteria - A reduced-layer DeepSeek R1 + MTP AutoDeploy smoke test runs end to end. - A no-MTP reduced DeepSeek R1 AutoDeploy smoke remains passing. - Quantized DeepSeek R1 configs keep `lm_head` excluded when required by shared-head MTP execution. - A full-model AutoDeploy accuracy test covers DeepSeek R1 MTP in `test_llm_api_autodeploy.py`. - The accuracy test checks no accuracy degradation with MTP and enforces a minimum acceptance rate.