[None][feat] Default GLM-5 to the Python KV-cache transceiver by chuangz0 · Pull Request #16524 · NVIDIA/TensorRT-LLM

chuangz0 · 2026-07-17T03:56:39Z

…in disagg

GLM-5 and GLM-5.2 (GlmMoeDsaForCausalLM / glm_moe_dsa) share the DeepseekV3ForCausalLM implementation class; override get_preferred_transceiver_runtime() to opt GLM checkpoints into the Python (v2) transceiver, differentiated per checkpoint so DeepSeek-V3/ V3.2 keep the C++ default. The preference is adopted only when the user leaves cache_transceiver_config.transceiver_runtime at 'auto' and the effective backend is NIXL.

Set transceiver_runtime: PYTHON explicitly in the GLM-5 perf-sanity disaggregated NIXL configs, and switch the GLM-5 disagg stress-test config from backend DEFAULT to NIXL + PYTHON so the TRTLLM_USE_UCX_KVCACHE=1 fallback cannot silently revert it to the C++ transceiver.

Add unit tests covering the per-architecture preference and the end-to-end 'auto' resolution for GLM-5 on NIXL.

Summary by CodeRabbit

New Features
- Added automatic Python runtime selection for GLM-5 transceiver configurations.
- GLM-5 deployments using the NIXL backend now default to the Python transceiver runtime.
Configuration
- Updated disaggregated inference and performance configurations to explicitly use the Python transceiver runtime.
Tests
- Added coverage verifying GLM-5 detection, default behavior, and automatic runtime resolution.

Description

Test Coverage

PR Checklist

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PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
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chuangz0 · 2026-07-17T03:57:05Z

/bot run --disable-fail-fast

coderabbitai · 2026-07-17T04:00:56Z

📝 Walkthrough

Walkthrough

Adds GLM-5-specific transceiver runtime selection to DeepseekV3ForCausalLM, tests automatic resolution to PYTHON, and updates disaggregated NIXL configurations for context and generation workers.

Changes

GLM-5 transceiver runtime

Layer / File(s)	Summary
GLM-5 runtime preference hook `tensorrt_llm/_torch/models/modeling_deepseekv3.py`	Adds `get_preferred_transceiver_runtime`, returning `PYTHON` for GLM-5 architecture or model-type identifiers and `None` otherwise.
Runtime resolution tests `tests/unittest/llmapi/test_llm_args.py`	Tests architecture matching, missing configurations, and automatic NIXL resolution to `PYTHON`.
Disaggregated runtime configurations `tests/integration/defs/disaggregated/test_configs/`, `tests/scripts/perf-sanity/disaggregated/glm-5*`	Sets NIXL and explicit `PYTHON` transceiver runtimes for context and generation workers.

Estimated code review effort: 3 (Moderate) | ~20 minutes

Sequence Diagram(s)

sequenceDiagram
  participant TorchLlmArgs
  participant _resolve_transceiver_runtime_auto
  participant DeepseekV3ForCausalLM
  TorchLlmArgs->>_resolve_transceiver_runtime_auto: Resolve auto runtime with NIXL configuration
  _resolve_transceiver_runtime_auto->>DeepseekV3ForCausalLM: Inspect pretrained GLM-5 configuration
  DeepseekV3ForCausalLM-->>_resolve_transceiver_runtime_auto: Return PYTHON
  _resolve_transceiver_runtime_auto-->>TorchLlmArgs: Set transceiver_runtime to PYTHON

Possibly related PRs

NVIDIA/TensorRT-LLM#15966: Updates disaggregated performance configurations with Python transceiver runtimes.
NVIDIA/TensorRT-LLM#16164: Adds the automatic transceiver-runtime resolution flow used by this model preference hook.
NVIDIA/TensorRT-LLM#16390: Updates DeepSeek/GLM-5 disaggregated configurations to use Python with NIXL.

Suggested labels: api-compatible

Suggested reviewers: qijune, nv-xtf, bowenfu

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 40.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title matches the main change: defaulting GLM-5 to the Python KV-cache transceiver.
Description check	✅ Passed	The description explains the problem, solution, and test coverage, though it is not fully structured into the template sections.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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Actionable comments posted: 1

🧹 Nitpick comments (2)

tensorrt_llm/_torch/models/modeling_deepseekv3.py (1)
1896-1899: 📐 Maintainability & Code Quality | 🔵 Trivial | ⚡ Quick win

Narrow the hook’s configuration type.

Any defeats the new interface contract. Use PretrainedConfig | None and Literal["PYTHON"] | None; add Google-style Args/Returns documentation for the hook.

Based on coding guidelines: “Annotate every function, use None for non-returning functions, avoid Any … and use … |.”
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@tensorrt_llm/_torch/models/modeling_deepseekv3.py` around lines 1896 - 1899,
Update the classmethod get_preferred_transceiver_runtime signature to accept
PretrainedConfig | None and return Literal["PYTHON"] | None, replacing Any and
Optional annotations. Add Google-style Args and Returns documentation describing
the configuration parameter and optional runtime result.
Source: Coding guidelines
tests/unittest/llmapi/test_llm_args.py (1)
3170-3211: 📐 Maintainability & Code Quality | 🔵 Trivial | 💤 Low value

Annotate the newly added test functions.

Add precise parameter and return annotations to _pretrained_config and the three test methods, including -> None for tests.

Based on coding guidelines: “Annotate every function … [and] avoid Any.”
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@tests/unittest/llmapi/test_llm_args.py` around lines 3170 - 3211, Annotate
`_pretrained_config` with concrete parameter and return types, avoiding `Any`,
and add precise parameter annotations plus `-> None` to
`test_preference_per_architecture`, `test_no_config_defers_to_cpp`, and
`test_glm5_resolves_auto_to_python_on_nixl`. Use types matching the architecture
list, model type, expected runtime value, and test fixtures already used.
Source: Coding guidelines

🤖 Prompt for all review comments with AI agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@tests/unittest/llmapi/test_llm_args.py`:
- Around line 3178-3189: Update test_preference_per_architecture in
tests/unittest/llmapi/test_llm_args.py to isolate both production predicates:
add a GLM architecture paired with a non-GLM model_type expecting "PYTHON", and
add a non-GLM architecture paired with model_type="glm_moe_dsa" expecting the
fallback result. The existing coverage is insufficient until these cases are
included; no follow-up outside this test file is needed.

---

Nitpick comments:
In `@tensorrt_llm/_torch/models/modeling_deepseekv3.py`:
- Around line 1896-1899: Update the classmethod
get_preferred_transceiver_runtime signature to accept PretrainedConfig | None
and return Literal["PYTHON"] | None, replacing Any and Optional annotations. Add
Google-style Args and Returns documentation describing the configuration
parameter and optional runtime result.

In `@tests/unittest/llmapi/test_llm_args.py`:
- Around line 3170-3211: Annotate `_pretrained_config` with concrete parameter
and return types, avoiding `Any`, and add precise parameter annotations plus `->
None` to `test_preference_per_architecture`, `test_no_config_defers_to_cpp`, and
`test_glm5_resolves_auto_to_python_on_nixl`. Use types matching the architecture
list, model type, expected runtime value, and test fixtures already used.

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Fix all unresolved CodeRabbit comments on this PR:

Push a commit to this branch (recommended)
Create a new PR with the fixes

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📥 Commits

Reviewing files that changed from the base of the PR and between 1228fed and 0e80777.

📒 Files selected for processing (15)

tensorrt_llm/_torch/models/modeling_deepseekv3.py
tests/integration/defs/disaggregated/test_configs/disagg_config_ctxtp4ep4_gentp4ep4_glm5_nvfp4_dp_tllm.yaml
tests/scripts/perf-sanity/disaggregated/gb200_glm-5-fp4_1k1k_con1_ctx1_dep4_gen1_tep4_eplb0_mtp3_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb200_glm-5-fp4_1k1k_con4096_ctx1_dep4_gen1_dep8_eplb256_mtp1_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb200_glm-5-fp4_1k1k_con512_ctx1_dep4_gen1_dep32_eplb0_mtp3_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb200_glm-5-fp4_8k1k_con1024_ctx1_dep4_gen1_dep8_eplb256_mtp1_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb200_glm-5-fp4_8k1k_con1_ctx1_dep4_gen1_tep8_eplb0_mtp3_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb200_glm-5-fp4_8k1k_con512_ctx1_dep4_gen1_dep32_eplb0_mtp3_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb300_glm-5-fp4_1k1k_con1_ctx1_dep2_gen1_tep4_eplb0_mtp3_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb300_glm-5-fp4_1k1k_con4096_ctx1_dep2_gen1_dep8_eplb256_mtp1_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb300_glm-5-fp4_1k1k_con512_ctx1_dep2_gen1_dep32_eplb0_mtp3_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb300_glm-5-fp4_8k1k_con1024_ctx1_dep2_gen1_dep8_eplb256_mtp1_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb300_glm-5-fp4_8k1k_con1_ctx1_dep2_gen1_tep8_eplb0_mtp3_ccb-NIXL.yaml
tests/scripts/perf-sanity/disaggregated/gb300_glm-5-fp4_8k1k_con512_ctx1_dep2_gen1_dep32_eplb0_mtp3_ccb-NIXL.yaml
tests/unittest/llmapi/test_llm_args.py

tensorrt-cicd · 2026-07-17T04:02:31Z

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chuangz0 · 2026-07-20T03:30:10Z

/bot run --disable-fail-fast

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/bot run --disable-fail-fast --stage-list "GB200PerfSanity*,GB300PerfSanity*"

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…in disagg GLM-5 and GLM-5.2 (GlmMoeDsaForCausalLM / glm_moe_dsa) share the DeepseekV3ForCausalLM implementation class; override get_preferred_transceiver_runtime() to opt GLM checkpoints into the Python (v2) transceiver, differentiated per checkpoint so DeepSeek-V3/ V3.2 keep the C++ default. The preference is adopted only when the user leaves cache_transceiver_config.transceiver_runtime at 'auto' and the effective backend is NIXL. Set transceiver_runtime: PYTHON explicitly in the GLM-5 perf-sanity disaggregated NIXL configs, and switch the GLM-5 disagg stress-test config from backend DEFAULT to NIXL + PYTHON so the TRTLLM_USE_UCX_KVCACHE=1 fallback cannot silently revert it to the C++ transceiver. Add unit tests covering the per-architecture preference and the end-to-end 'auto' resolution for GLM-5 on NIXL. Signed-off-by: Chuang Zhu <111838961+chuangz0@users.noreply.github.com>

…ansceiver test Address review: the GLM-positive case satisfied both predicates at once, so deleting either production check still passed. Add one case per predicate in isolation (GLM architecture with a non-GLM model_type, and a non-GLM architecture with model_type=glm_moe_dsa). Signed-off-by: Chuang Zhu <111838961+chuangz0@users.noreply.github.com>

chuangz0 · 2026-07-22T01:48:51Z

/bot run --stage-list "A10-PyTorch-1, A10-PyTorch-2"

chuangz0 · 2026-07-22T08:37:42Z

/bot run --stage-list "A10-PyTorch-1, A10-PyTorch-2"

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…string Replace the MagicMock pretrained config in the GLM-5 transceiver-preference tests with a real transformers.PretrainedConfig, and rewrap the preference docstring in modeling_deepseekv3.py at 100 columns. Signed-off-by: Chuang Zhu <111838961+chuangz0@users.noreply.github.com>

chuangz0 · 2026-07-23T07:54:32Z

/bot run --stage-list "A10-PyTorch-1, A10-PyTorch-2"

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/bot skip --comment "required tests have passed"

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…nnahz/dep-1083-port-flashinfer-stable-va-lifecycle-for-native-all-reduce * 'main' of https://github.com/NVIDIA/TensorRT-LLM: (83 commits) [None][feat] Bind SourceIdentity to checkpoint artifacts (NVIDIA#16159) [None][infra] Waive 4 failed cases for main in pre-merge 49550 (NVIDIA#16798) [None][fix] Make FlashInfer sampling op wrappers opaque to Dynamo (NVIDIA#16732) [None][feat] top-k: route decode to CuTe DSL GVR top-k in e2e (NVIDIA#16420) [None][feat] Default GLM-5 to the Python KV-cache transceiver (NVIDIA#16524) [None][chore] Add NVTX ranges to per-iteration ADP sync points in PyExecutor (NVIDIA#16422) [https://nvbugs/6426850][test] Unwaive Qwen3.5 397B NVFP4 ADP4 TRTLLM test (NVIDIA#16348) [https://nvbugs/6445456][fix] Restore inplace ops for functionalization v2 (NVIDIA#16410) [None][infra] Waive 1 failed cases for main in pre-merge 49229 (NVIDIA#16786) [None][fix] Load DeepSeek V4 mixed-precision NVFP4 checkpoints (NVIDIA#16433) [None][feat] ADP conversation router: configurable least-queued placement for new conversations (NVIDIA#16294) [None][infra] Waive 1 failed cases for main in pre-merge 49424 (NVIDIA#16780) [None][infra] Waive 1 failed cases for main in pre-merge 49424 (NVIDIA#16781) [TRTLLMINF-188][infra] Require approval for PerfSanity wildcard runs (NVIDIA#16777) [TRTLLM-13969][feat] Support MiniMax M3 for Disaggregated Serving (NVIDIA#16017) [NVIDIA#11932][fix] Filter CUTLASS MoE GEMM tile configs by device shared memory on SM121 (NVIDIA#12704) [None][chore] Remove attention backend test waivers (NVIDIA#16723) [TRTLLM-14540][perf] Skip fp32 state round-trip in FlashInfer GDN pre… (NVIDIA#16703) [TRTLLM-13694][feat] Add IBDB recipe provenance and refresh configs (NVIDIA#16254) [None][infra] Preview/bump/main (NVIDIA#16758) ... Signed-off-by: Hannah Zhang <hannahz@nvidia.com>

…#16524) Signed-off-by: Chuang Zhu <111838961+chuangz0@users.noreply.github.com>

chuangz0 requested review from a team as code owners July 17, 2026 03:56

chuangz0 requested review from dc3671, kaiyux, mikeiovine, nv-ananjappa, nv-xtf, reasonsolo, ruodil, tongyuantongyu and yingguo-trt July 17, 2026 03:56

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chuangz0 force-pushed the glm_model_default_python_transceiver branch 2 times, most recently from 03682f8 to 88cae70 Compare July 20, 2026 03:30

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coderabbitai Bot mentioned this pull request Jul 21, 2026

[None][feat] Default GLM-5 to the Python KV-cache transceiver (duplicate of #16524 for parallel CI) #16656

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chuangz0 force-pushed the glm_model_default_python_transceiver branch from 461cf84 to 8bd681c Compare July 22, 2026 01:48

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chuangz0 enabled auto-merge (squash) July 23, 2026 13:42

chuangz0 merged commit e16dcc5 into NVIDIA:main Jul 23, 2026
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yuanjingx87 pushed a commit to yuanjingx87/TensorRT-LLM that referenced this pull request Jul 26, 2026

[None][feat] Default GLM-5 to the Python KV-cache transceiver (NVIDIA…

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…#16524) Signed-off-by: Chuang Zhu <111838961+chuangz0@users.noreply.github.com>

coderabbitai Bot mentioned this pull request Jul 27, 2026

[None][feat] Prefer V2 transceiver backend for Gemma and Llama #16787

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