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@leslie-fang25 leslie-fang25 commented Aug 15, 2025

Summary by CodeRabbit

  • Documentation

    • Updated feature matrix to indicate Disaggregated Serving is supported for EAGLE-3 (One Model) and EAGLE-3 (Two Model). All other feature statuses remain unchanged.
  • Tests

    • Expanded integration coverage to test both enabled and disabled configurations of the EAGLE-3 one-model setting for disaggregated decoding.
    • Updated test listings to include additional parameterizations for the relevant scenario on H100 profiles.
    • No functional behavior changes to runtime features.

Description

This PR update the feature_combination_matrix of disaggregated and eagle3. It also add the test configuration for both eagle3 one model and eagle3 two model.

Test Coverage

clear && LLM_MODELS_ROOT="/llm-models" python -u -m pytest -s -v  tests/integration/defs/disaggregated/test_disaggregated_single_gpu.py::test_disaggregated_spec_dec_batch_slot_limit

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@leslie-fang25 leslie-fang25 requested a review from a team as a code owner August 15, 2025 09:50
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coderabbitai bot commented Aug 15, 2025

📝 Walkthrough

Walkthrough

Documentation updates reflect EAGLE-3 Disaggregated Serving support. Tests are parameterized to toggle eagle3_one_model in the disaggregated single-GPU spec-dec test, and test list entries are expanded to cover both True/False configurations.

Changes

Cohort / File(s) Summary
Docs: Feature matrix update
docs/source/torch/features/feature_combination_matrix.md
Updated EAGLE-3 One/Two Model Engine rows: Disaggregated Serving changed from No/NO to Yes; other columns unchanged.
Tests: Disaggregated serving parameterization
tests/integration/defs/disaggregated/test_disaggregated_single_gpu.py, tests/integration/test_lists/test-db/l0_h100.yml
Added eagle3_one_model parameter to the test and propagated via EagleDecodingConfig; expanded test list to run with eagle3_one_model True and False.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~8 minutes

Possibly related PRs

Suggested labels

Documentation, Disaggregated Serving, Speculative Decoding, CI

Suggested reviewers

  • litaotju
  • byshiue
  • Tabrizian

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@leslie-fang25 leslie-fang25 requested review from Tabrizian and QiJune and removed request for kaiyux and Shixiaowei02 August 15, 2025 09:50
@leslie-fang25 leslie-fang25 force-pushed the leslie/update_disaggregated_eagle3 branch from 6d33e9b to 7b073a9 Compare August 15, 2025 09:51
@leslie-fang25
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Hi @Tabrizian, I am working on updating the doc of feature combination matrix. For the combination of disaggregated and eagle3, it has been marked as False previously. Nevertheless, It seems you have added the corresponding test case in #6032. So could you help to confirm if disaggregated can work with eagle-3 both one model and two model engine?

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/bot run

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Actionable comments posted: 0

🧹 Nitpick comments (2)
docs/source/torch/features/feature_combination_matrix.md (1)

12-12: Standardize “NO” casing to “No” for consistency

Most entries use “Yes/No/Untested/WIP”. This row uses “NO” (all caps) under Overlap Scheduler, which is inconsistent.

Apply this diff:

-| EAGLE-3(Two Model Engine)  | NO                | Yes        | Yes                        | Yes                   | Yes             | No       | No                        | ---                       |               |                  |                |                        |                       |                 |
+| EAGLE-3(Two Model Engine)  | No                | Yes        | Yes                        | Yes                   | Yes             | No       | No                        | ---                       |               |                  |                |                        |                       |                 |
tests/integration/defs/disaggregated/test_disaggregated_single_gpu.py (1)

352-355: Optional: add ids to parametrization for clarity/debuggability

Adding readable ids helps when failures occur across the two eagle3 modes.

Example:

-@pytest.mark.parametrize("eagle3_one_model", [True, False])
+@pytest.mark.parametrize(
+    "eagle3_one_model",
+    [True, False],
+    ids=["eagle3_one_model=True", "eagle3_one_model=False"],
+)
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Reviewing files that changed from the base of the PR and between c2fe8b0 and 7b073a9.

📒 Files selected for processing (3)
  • docs/source/torch/features/feature_combination_matrix.md (1 hunks)
  • tests/integration/defs/disaggregated/test_disaggregated_single_gpu.py (1 hunks)
  • tests/integration/test_lists/test-db/l0_h100.yml (1 hunks)
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tests/integration/defs/disaggregated/test_disaggregated_single_gpu.py (1)
tensorrt_llm/llmapi/llm_args.py (2)
  • EagleDecodingConfig (418-444)
  • speculative_model_dir (1347-1348)
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🔇 Additional comments (5)
docs/source/torch/features/feature_combination_matrix.md (1)

11-12: Matrix update aligns with new EAGLE-3 disaggregated support

Changing Disaggregated Serving to “Yes” for both EAGLE-3 One-Model and Two-Model engines looks correct given the new test coverage. No functional concerns here.

tests/integration/test_lists/test-db/l0_h100.yml (2)

88-89: Param expansion matches new test signature

Adding both eagle3_one_model=True/False cases for test_disaggregated_spec_dec_batch_slot_limit looks good. The positional ordering in the bracket string follows the established convention in this file: [eagle3_one_model-generation_overlap-spec_dec_model_path-model].


88-89: No stale references found — 4‑arg signature present

Both occurrences in the test lists include the new leading eagle3_one_model boolean and no other matches were found under tests/integration/test_lists/**.

  • tests/integration/test_lists/test-db/l0_h100.yml:88
    • disaggregated/test_disaggregated_single_gpu.py::test_disaggregated_spec_dec_batch_slot_limit[True-False-EAGLE3-LLaMA3.1-Instruct-8B-Llama-3.1-8B-Instruct]
  • tests/integration/test_lists/test-db/l0_h100.yml:89
    • disaggregated/test_disaggregated_single_gpu.py::test_disaggregated_spec_dec_batch_slot_limit[False-False-EAGLE3-LLaMA3.1-Instruct-8B-Llama-3.1-8B-Instruct]
tests/integration/defs/disaggregated/test_disaggregated_single_gpu.py (2)

352-355: LGTM: test now parametrized over eagle3_one_model

Adding eagle3_one_model to the parametrization and function signature is correct. This cleanly exercises both one-model and two-model EAGLE-3 modes in the disaggregated spec-dec test.


359-361: Passing eagle3_one_model through EagleDecodingConfig is correct

This aligns with EagleDecodingConfig.eagle3_one_model and correctly steers spec_dec_mode to EAGLE3_ONE_MODEL vs EAGLE3.

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PR_Github #15436 [ run ] triggered by Bot

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PR_Github #15436 [ run ] completed with state FAILURE
/LLM/main/L0_MergeRequest_PR pipeline #11632 completed with status: 'FAILURE'

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Yes, it can work with both one-model and two-model. Thanks for updating this doc.

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/bot run

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PR_Github #15496 [ run ] triggered by Bot

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PR_Github #15496 [ run ] completed with state SUCCESS
/LLM/main/L0_MergeRequest_PR pipeline #11668 completed with status: 'SUCCESS'
Pipeline passed with automatic retried tests. Check the rerun report for details.

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LGTM

@QiJune QiJune merged commit ce0b13e into NVIDIA:main Aug 18, 2025
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4 participants