[#12477][feat] AutoDeploy: Mistral4 Eagle Support#12759
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govind-ramnarayan wants to merge 1 commit intoNVIDIA:mainfrom
Draft
[#12477][feat] AutoDeploy: Mistral4 Eagle Support#12759govind-ramnarayan wants to merge 1 commit intoNVIDIA:mainfrom
govind-ramnarayan wants to merge 1 commit intoNVIDIA:mainfrom
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Add Eagle one-model speculative decoding support for Mistral-Small-4-119B: - Mistral4-specific Eagle layer (Mistral4EagleMLA, Mistral4EagleMLP, Mistral4EagleDecoderLayer) with dispatch table entry - EagleOneModelFactory gains TargetModelExportInfo/DraftModelExportInfo with scalar-sentinel DCE prevention matching hf.py pattern - Factory delegation so Mistral4's custom target factory is used - Mistral3 wrapper delegation methods (get_input/output_embeddings, config) - FP8 checkpoint loading improvements for Mistral4 - Hidden-state capture guard against double-apply - MLA RoPE deinterleave hook ordering fix for Eagle path - LlmArgs Eagle config defaults and MTP one-model routing Configs: mistral4_eagle_119b.yaml (8-GPU), mistral_small_4_119b_eagle.yaml, mistral_small_4_119b_lite.yaml, mistral_small_4_119b_torch_mla.yaml Tests: hierarchical unit tests (AD ops vs PyTorch reference), hidden-state capture detection, torch.export + AD pipeline integration, 1-layer and 3-layer Eagle one-model E2E smoke, layer subgraph debug, framework-level spec-dec config/KV-cache tests. Signed-off-by: Govind Ramnarayan <gramnarayan@nvidia.com> Signed-off-by: Govind Ramnarayan <105831528+govind-ramnarayan@users.noreply.github.com>
| eagle3_model_arch: mistral_large3 | ||
| eagle3_layers_to_capture: [-1] | ||
| speculative_model_kwargs: | ||
| num_hidden_layers: 2 |
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Should not be overridden
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| # Config for Mistral Small 4 119B with Eagle3 speculative decoding. | |||
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Wait which one is used? This other the other configs?
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| runtime: trtllm | |||
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This shouldn't be here; tests only
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PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
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