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@liji-nv liji-nv commented Sep 18, 2025

…ekV3

Summary by CodeRabbit

  • New Features
    • Improved multi-GPU pipeline-parallel support with torch.compile, including backend awareness of distributed mappings for better fusions.
    • Models may now return (hidden_states, residual) to preserve necessary tensors across pipeline stages.
  • Bug Fixes
    • More reliable input token detection in compiled graphs.
    • Correct handling of pipeline send/recv as in-place ops to prevent elimination during compilation.
    • Userbuffers initialization now gated to valid configurations.
  • Tests
    • Expanded multi-GPU torch.compile test coverage by removing previous skips.

Description

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Please review the following before submitting your PR:

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  • PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.

  • Test cases are provided for new code paths (see test instructions)

  • Any new dependencies have been scanned for license and vulnerabilities

  • CODEOWNERS updated if ownership changes

  • Documentation updated as needed

  • The reviewers assigned automatically/manually are appropriate for the PR.

  • Please check this after reviewing the above items as appropriate for this PR.

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liji-nv commented Sep 18, 2025

/bot run

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PR_Github #19186 [ run ] triggered by Bot

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📝 Walkthrough

Walkthrough

The change threads a Mapping object through the compilation backend and AR fusion registrations, registers pp_send/pp_recv as Torch custom ops, updates model forward returns to optionally include residuals, adapts speculative wrappers to handle tuple outputs, extends inplace op metadata, adjusts userbuffers enablement, and broadens tests to run under torch.compile with multi-GPU.

Changes

Cohort / File(s) Summary
Backend mapping threading
tensorrt_llm/_torch/compilation/backend.py
Adds mapping parameter to Backend.init and passes it into get_custom_pass; get_custom_pass signature updated to accept mapping and propagate to AR fusion registration; call detects l_position_ids_ for input token counting; minor debug hook comment.
AR fusion registration uses external Mapping
tensorrt_llm/_torch/compilation/patterns/ar_residual_norm.py
All registration functions now require a Mapping argument; removes internal Mapping creation; extends allreduce.default with explicit strategy/workspace via mapping.tp_group; register_ar_fusions and register_ub_patterns accept and pass mapping.
Custom ops for pipeline send/recv + inplace info
tensorrt_llm/_torch/distributed/communicator.py, tensorrt_llm/_torch/compilation/utils.py
Registers pp_recv and pp_send as Torch custom ops (trtllm::pp_recv/pp_send) mutating “tensor”; adds inplace mappings for these ops in inplace_info.
Model forward returns residuals
tensorrt_llm/_torch/models/modeling_deepseekv3.py, tensorrt_llm/_torch/models/modeling_llama.py, tensorrt_llm/_torch/models/modeling_utils.py, tensorrt_llm/_torch/models/modeling_speculative.py
DeepseekV3Model and LlamaModel forward now return (hidden_states, residual); type hints updated accordingly; DecoderModel.forward return type broadened to Union[tensor, tuple]; speculative wrappers unwrap first element when model returns a tuple.
Executor wiring and userbuffers gating
tensorrt_llm/_torch/pyexecutor/model_engine.py
Passes mapping into Backend constructor; enables userbuffers only when tp_size > 1 and pp_size <= 1.
Unit tests: TP mapping helper and backend wiring
tests/unittest/_torch/multi_gpu/test_user_buffers.py, tests/unittest/_torch/multi_gpu/test_ar_residual_norm.py
Introduces create_tp_mapping helper; updates Backend and model inits to use mapping; adjusts a ub.initialize_userbuffers_manager call; ar_residual_norm test passes per-rank mapping to Backend.
Integration tests: remove skips under torch.compile on multi-GPU
tests/integration/defs/accuracy/test_llm_api_pytorch.py
Removes conditional skips to allow tests to run with multi-GPU/pipeline-parallel configurations.

Sequence Diagram(s)

sequenceDiagram
  autonumber
  participant Engine as ModelEngine
  participant Backend as Backend
  participant Pass as PatternMatcherPass(es)
  participant Patterns as AR Residual-Norm Patterns
  participant Map as Mapping

  Engine->>Backend: __init__(..., mapping=Map)
  Backend->>Backend: get_custom_pass(enable_userbuffers, Map)
  Backend->>Pass: create pass list
  Backend->>Patterns: register_ar_fusions(Pass[], Map, enable_UB)
  Patterns-->>Pass: register residual-norm + quant patterns
  note right of Patterns: allreduce registered with mapping.tp_group
Loading
sequenceDiagram
  autonumber
  participant PP0 as Pipeline Stage 0
  participant PP1 as Pipeline Stage 1
  participant Comm as trtllm::pp_send/pp_recv (custom ops)
  participant Spec as Speculative Wrapper

  PP0->>PP0: forward() -> (hidden_states, residual)
  PP0->>Comm: pp_send(tensor=residual) [mutates tensor]
  PP0-->>PP1: pipeline boundary

  PP1->>Comm: pp_recv(tensor=residual) [mutates tensor]
  PP1->>PP1: forward(..., residual)
  Spec->>PP1: outputs = model(...)
  alt outputs is tuple
    Spec->>Spec: hidden_states = outputs[0]
  else
    Spec->>Spec: hidden_states = outputs
  end
Loading

Estimated code review effort

🎯 4 (Complex) | ⏱️ ~60 minutes

Pre-merge checks and finishing touches

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✅ Passed checks (1 passed)
Check name Status Explanation
Title check ✅ Passed The title clearly summarizes the main change: adding support for torch compile with pipeline parallelism (PP) for Llama and DeepSeekV3 models.
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Actionable comments posted: 1

Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (16)
tensorrt_llm/_torch/compilation/utils.py (1)

1-1: Add NVIDIA Apache-2.0 header (2025).

All source files must start with the NVIDIA Apache-2.0 copyright header for 2025.

Apply this diff at the top of the file:

+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
tensorrt_llm/_torch/models/modeling_speculative.py (4)

1-1: Add NVIDIA Apache-2.0 header (2025).

Add the standard header at file top.

+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

69-75: init annotated to return Tuple — should be None.

Constructor must return None; the current annotation is invalid.

Apply:

-    ) -> Tuple[torch.Tensor, torch.Tensor]:
+    ) -> None:

104-136: forward return type is Tensor but returns (hidden_states, residual).

Adjust annotation to reflect tuple return.

-    ) -> torch.Tensor:
+    ) -> Tuple[torch.Tensor, torch.Tensor]:

197-205: Eagle3DraftModel.forward returns a tuple but is annotated as Tensor.

Fix the return type hint.

-    ) -> torch.Tensor:
+    ) -> Tuple[torch.Tensor, torch.Tensor]:

Also applies to: 238-241

tensorrt_llm/_torch/models/modeling_utils.py (1)

1-1: Add NVIDIA Apache-2.0 header (2025).

Add the required header.

+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
tensorrt_llm/_torch/models/modeling_llama.py (6)

1-1: Add NVIDIA Apache-2.0 header (2025).

Insert the standard header.

+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

361-368: init annotated to return Tuple — should be None (Llama4DecoderLayer).

Correct the constructor annotation.

-    ) -> Tuple[torch.Tensor, torch.Tensor]:
+    ) -> None:

472-612: Llama4DecoderLayer.forward returns a tuple but is annotated as Tensor.

Fix the signature to match behavior.

-    ) -> torch.Tensor:
+    ) -> Tuple[torch.Tensor, torch.Tensor]:

617-622: init annotated to return Tuple — should be None (LlamaDecoderLayer).

Same issue as above.

-    ) -> Tuple[torch.Tensor, torch.Tensor]:
+    ) -> None:

691-701: LlamaDecoderLayer.forward returns (hidden_states, residual) but is annotated as Tensor.

Align the annotation with the return value.

-    ) -> torch.Tensor:
+    ) -> Tuple[torch.Tensor, torch.Tensor]:

Also applies to: 801-801


858-882: Llama4Model.forward returns (hidden_states, residual) but is annotated as Tensor.

Update the return type hint.

-    ) -> torch.Tensor:
+    ) -> Tuple[torch.Tensor, torch.Tensor]:
tensorrt_llm/_torch/distributed/communicator.py (1)

1-1: Add NVIDIA Apache-2.0 header (2025).

Add the standard header.

+// Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
tensorrt_llm/_torch/models/modeling_deepseekv3.py (1)

1-27: Add NVIDIA Apache-2.0 header per repo policy (preserve upstream notice).

Per coding guidelines, prepend the NVIDIA Apache-2.0 copyright header (current year)
above the upstream DeepSeek MIT notice.

tensorrt_llm/_torch/compilation/backend.py (2)

1-1: Add NVIDIA Apache-2.0 header (2025).

Required by the repo guidelines; please prepend the standard header.

+# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

69-85: Pass cache is global and ignores mapping/UB; require mapping when world_size>1.

Current singleton cache can reuse passes with a wrong Mapping/UB combo. Also, AR fusions require a non-None Mapping in multi-GPU. Fix by keying cache on (world_size, ub_enabled, hash(mapping)) and validating mapping.

-    def get_custom_pass(cls, enable_userbuffers, mapping: Mapping):
-        world_size = tensorrt_llm.mpi_world_size()
-        if not cls._custom_pass_instances:
-            # Really naive pass manager here
-            cls._custom_pass_instances = [PatternMatcherPass()]
-            if world_size > 1:
-                # Currently torch compile cannot work properly with lamport fusion kernel
-                # TO-DO: Fix this issue
-                os.environ["DISABLE_LAMPORT_REDUCE_NORM_FUSION"] = "1"
-                ub_enabled = enable_userbuffers and tensorrt_llm.bindings.internal.userbuffers.ub_supported(
-                )
-                register_ar_fusions(cls._custom_pass_instances, mapping,
-                                    ub_enabled)
-            else:
-                register_add_norm(cls._custom_pass_instances[0])
-        return cls._custom_pass_instances
+    def get_custom_pass(cls, enable_userbuffers, mapping: Optional[Mapping]):
+        world_size = tensorrt_llm.mpi_world_size()
+        ub_enabled = bool(
+            enable_userbuffers and tensorrt_llm.bindings.internal.userbuffers.ub_supported()
+        )
+        key = (world_size, ub_enabled, hash(mapping) if mapping is not None else None)
+        instances = cls._custom_pass_cache.get(key)
+        if instances is None:
+            instances = [PatternMatcherPass()]
+            if world_size > 1:
+                if mapping is None:
+                    raise ValueError("Mapping is required when world_size > 1 for AR fusions.")
+                # torch.compile cannot work properly with lamport fusion kernel yet.
+                os.environ["DISABLE_LAMPORT_REDUCE_NORM_FUSION"] = "1"
+                register_ar_fusions(instances, mapping, ub_enabled)
+            else:
+                register_add_norm(instances[0])
+            cls._custom_pass_cache[key] = instances
+        return instances
🧹 Nitpick comments (5)
tensorrt_llm/_torch/distributed/communicator.py (1)

250-259: Custom ops for pp_recv/pp_send — good; add fake/meta kernels for compile.

Registration with mutates_args is correct. For smoother torch.compile/AOTInductor support, register fake/meta implementations so the compiler can run shape propagation without executing NCCL paths. Also ensure init_pp_comm is called before these ops execute.

Would you like me to propose a small meta registration patch for these ops?

tensorrt_llm/_torch/models/modeling_deepseekv3.py (1)

1181-1182: Make residual always a Tensor to keep torch.compile graphs stable.

If num_hidden_layers == 0, residual stays None, which can force graph breaks or recompiles. Set a Tensor fallback before returning.

-        # Export residual to avoid residual pp_send get eliminated by torch.compile for pp > 1.
-        return hidden_states, residual
+        # Export residual to prevent pp_send being DCE'd by torch.compile for pp > 1.
+        if residual is None:
+            residual = hidden_states
+        return hidden_states, residual
tensorrt_llm/_torch/compilation/backend.py (3)

2-2: Type-hint fixes and cache container prep (Py3.8 compatibility).

  • Use typing.Tuple instead of PEP585 tuple[...] for 3.8 support.
  • Prepare cache container typing (ties into next comment).
-from typing import List, Optional
+from typing import Dict, List, Optional, Tuple
@@
-    _custom_pass_instances: List[PatternMatcherPass] = None
-    _graph_pool_handle: tuple[int, int] = None
+    _custom_pass_cache: Dict[Tuple[int, bool, Optional[int]], List[PatternMatcherPass]] = {}
+    _graph_pool_handle: Optional[Tuple[int, int]] = None

Also applies to: 26-28


151-163: Token-length detection may pick batch dim for input_ids; unify logic.

Prefer sequence length (last dim) when tensor is 2D+; fallback to 1D.

-        for node in gm.graph.nodes:
-            if node.op == "placeholder":
-                if node.name == "l_input_ids_":
-                    example_value = node.meta["example_value"]
-                    assert isinstance(example_value, FakeTensor)
-                    self.input_num_tokens = example_value.shape[0]
-                    break
-                if node.name == "l_position_ids_":
-                    example_value = node.meta["example_value"]
-                    assert isinstance(example_value, FakeTensor)
-                    self.input_num_tokens = example_value.shape[-1]
-                    break
+        for node in gm.graph.nodes:
+            if node.op == "placeholder":
+                if node.name in ("l_input_ids_", "l_position_ids_"):
+                    example_value = node.meta["example_value"]
+                    assert isinstance(example_value, FakeTensor)
+                    self.input_num_tokens = (
+                        example_value.shape[-1]
+                        if len(example_value.shape) > 1
+                        else example_value.shape[0]
+                    )
+                    break

Please confirm that this matches how piecewise capture interprets “num tokens” across Llama/DeepSeek inputs (seq len vs. batch size).


43-52: Make mapping Optional in Backend.init and initialize input_num_tokens.

rg shows Backend is instantiated both with and without a mapping (tests pass mapping; model_engine does not) — change is safe.

-        mapping=None,
+        mapping: Optional[Mapping] = None,
@@
         self.call_count = 0
+        self.input_num_tokens: Optional[int] = None
         self.mapping = mapping
-        self.custom_passes = Backend.get_custom_pass(enable_userbuffers,
-                                                     mapping)
+        self.custom_passes = Backend.get_custom_pass(enable_userbuffers, mapping)
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📒 Files selected for processing (12)
  • tensorrt_llm/_torch/compilation/backend.py (5 hunks)
  • tensorrt_llm/_torch/compilation/patterns/ar_residual_norm.py (7 hunks)
  • tensorrt_llm/_torch/compilation/utils.py (1 hunks)
  • tensorrt_llm/_torch/distributed/communicator.py (1 hunks)
  • tensorrt_llm/_torch/models/modeling_deepseekv3.py (2 hunks)
  • tensorrt_llm/_torch/models/modeling_llama.py (3 hunks)
  • tensorrt_llm/_torch/models/modeling_speculative.py (1 hunks)
  • tensorrt_llm/_torch/models/modeling_utils.py (1 hunks)
  • tensorrt_llm/_torch/pyexecutor/model_engine.py (2 hunks)
  • tests/integration/defs/accuracy/test_llm_api_pytorch.py (0 hunks)
  • tests/unittest/_torch/multi_gpu/test_ar_residual_norm.py (1 hunks)
  • tests/unittest/_torch/multi_gpu/test_user_buffers.py (10 hunks)
💤 Files with no reviewable changes (1)
  • tests/integration/defs/accuracy/test_llm_api_pytorch.py
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Avoid shadowing variables from an outer scope.
Initialize all externally visible members of a class in the constructor.
Prefer docstrings for interfaces that may be used outside a file; comments for in-function or file-local interfaces.
Use Google-style docstrings for classes and functions (Sphinx-parsable).
Document attributes and variables inline so they render under the class/function docstring.
Avoid reflection when a simpler, explicit approach suffices (e.g., avoid dict(**locals()) patterns).
In try/except, catch the most specific exceptions possible.
For duck-typing try/except, keep the try body minimal and use else for the main logic.

Files:

  • tensorrt_llm/_torch/compilation/utils.py
  • tensorrt_llm/_torch/models/modeling_speculative.py
  • tests/unittest/_torch/multi_gpu/test_ar_residual_norm.py
  • tensorrt_llm/_torch/models/modeling_utils.py
  • tensorrt_llm/_torch/distributed/communicator.py
  • tensorrt_llm/_torch/pyexecutor/model_engine.py
  • tensorrt_llm/_torch/compilation/patterns/ar_residual_norm.py
  • tensorrt_llm/_torch/models/modeling_llama.py
  • tensorrt_llm/_torch/compilation/backend.py
  • tests/unittest/_torch/multi_gpu/test_user_buffers.py
  • tensorrt_llm/_torch/models/modeling_deepseekv3.py
**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

Prepend the NVIDIA Apache-2.0 copyright header with current year to the top of all source files (e.g., .cpp, .h, .cu, .py).

Files:

  • tensorrt_llm/_torch/compilation/utils.py
  • tensorrt_llm/_torch/models/modeling_speculative.py
  • tests/unittest/_torch/multi_gpu/test_ar_residual_norm.py
  • tensorrt_llm/_torch/models/modeling_utils.py
  • tensorrt_llm/_torch/distributed/communicator.py
  • tensorrt_llm/_torch/pyexecutor/model_engine.py
  • tensorrt_llm/_torch/compilation/patterns/ar_residual_norm.py
  • tensorrt_llm/_torch/models/modeling_llama.py
  • tensorrt_llm/_torch/compilation/backend.py
  • tests/unittest/_torch/multi_gpu/test_user_buffers.py
  • tensorrt_llm/_torch/models/modeling_deepseekv3.py
🧬 Code graph analysis (7)
tensorrt_llm/_torch/compilation/utils.py (1)
tensorrt_llm/_torch/distributed/communicator.py (2)
  • pp_recv (251-253)
  • pp_send (257-259)
tests/unittest/_torch/multi_gpu/test_ar_residual_norm.py (2)
tensorrt_llm/_torch/compilation/backend.py (1)
  • Backend (24-176)
tests/unittest/_torch/multi_gpu/test_user_buffers.py (1)
  • create_tp_mapping (36-41)
tensorrt_llm/_torch/distributed/communicator.py (2)
cpp/tensorrt_llm/executor/cache_transmission/agent_utils/connection.cpp (2)
  • recv (124-129)
  • recv (124-124)
cpp/tensorrt_llm/thop/ncclCommunicatorOp.cpp (2)
  • recv (40-46)
  • recv (40-40)
tensorrt_llm/_torch/pyexecutor/model_engine.py (2)
tensorrt_llm/_torch/models/checkpoints/base_weight_mapper.py (1)
  • mapping (152-153)
tensorrt_llm/_torch/distributed/communicator.py (2)
  • tp_size (46-47)
  • pp_size (42-43)
tensorrt_llm/_torch/compilation/patterns/ar_residual_norm.py (1)
tensorrt_llm/mapping.py (1)
  • Mapping (32-519)
tensorrt_llm/_torch/compilation/backend.py (3)
tensorrt_llm/mapping.py (1)
  • Mapping (32-519)
tensorrt_llm/_torch/compilation/patterns/ar_residual_norm.py (1)
  • register_ar_fusions (684-697)
tensorrt_llm/_torch/autotuner.py (1)
  • FakeTensor (138-141)
tests/unittest/_torch/multi_gpu/test_user_buffers.py (3)
tensorrt_llm/_torch/distributed/communicator.py (3)
  • tp_size (46-47)
  • rank (22-23)
  • world_size (26-27)
tensorrt_llm/mapping.py (1)
  • Mapping (32-519)
tensorrt_llm/_torch/compilation/backend.py (1)
  • Backend (24-176)
🪛 Ruff (0.12.2)
tests/unittest/_torch/multi_gpu/test_ar_residual_norm.py

70-70: Undefined name create_tp_mapping

(F821)

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
  • GitHub Check: Pre-commit Check
🔇 Additional comments (21)
tensorrt_llm/_torch/compilation/utils.py (1)

80-85: In-place mappings for pp_recv/pp_send look right; verify op registration order.

The new entries align with existing 1-based arg indexing used here and match mutability of the custom ops. Please ensure communicator.py (which registers the ops) is imported before this function is executed to avoid unresolved torch.ops at import time.

tensorrt_llm/_torch/models/modeling_speculative.py (1)

425-434: Tuple-safe handling of model outputs — LGTM.

Correctly extracts hidden_states when the underlying model returns a tuple.

tensorrt_llm/_torch/models/modeling_utils.py (2)

242-251: Broadened DecoderModel.forward return type — LGTM.

Accurately reflects potential multi-output from decoders.


538-552: Handle tuple outputs before logits processing — apply suggested refactor.

Unpack model outputs (take output[0] when the model returns a tuple/list) before calling the logits processor; other call sites already unpack or pass tensors, so this is safe.

File: tensorrt_llm/_torch/models/modeling_utils.py
Lines: 538-552

-        output = self.model(
+        output = self.model(
             input_ids=input_ids,
             attn_metadata=attn_metadata,
             position_ids=position_ids,
             inputs_embeds=inputs_embeds,
             spec_metadata=spec_metadata,
             lora_params=lora_params,
         )
-
-        return self.logits_processor.forward(
-            output,
+        hidden_states = output[0] if isinstance(output, (tuple, list)) else output
+        return self.logits_processor.forward(
+            hidden_states,
             self.lm_head,
             attn_metadata,
             return_context_logits,
         )
tensorrt_llm/_torch/models/modeling_deepseekv3.py (1)

1160-1160: Return type change is fine; confirm downstream is tuple-aware.

DeepseekV3Model.forward now returns (hidden_states, residual). Ensure all call sites (wrappers, speculative paths, PP send/recv) consistently unpack or index [0] where a single tensor was expected.

tensorrt_llm/_torch/compilation/patterns/ar_residual_norm.py (8)

17-25: Good: mapping threaded into AR residual-norm registration.

Passing mapping.tp_group into the pattern ensures correct group binding in multi-GPU runs.


50-65: Validate op arg order vs trtllm.allreduce signature.

The target uses (input, residual, gamma, scale, None, workspace, mapping.tp_group, int(strategy), fusion_op, eps, trigger_completion_at_end). Double‑check this matches the registered op schema across FP16/BF16/FP8/NVFP4 variants to avoid silent misbinding.


113-129: FP8 out-quant pattern: looks consistent.

Pattern wiring with mapping.tp_group and UB gating is correct.


190-206: FP8 in-quant pattern: looks correct.

No issues spotted.


266-286: FP4 out-quant pattern: looks correct.

No issues spotted.


338-354: FP4 in-quant pattern: looks correct.

No issues spotted.


409-448: UB convert pattern: fusion op filter is precise.

Conversion to UB with copy_to_userbuffers + finalize flow looks good.


684-698: Centralized registration with mapping and UB flag is clean.

Registration order is sensible; UB-only excludes OUT_QUANT patterns.

tensorrt_llm/_torch/pyexecutor/model_engine.py (2)

368-369: Good: pass Mapping into Backend for pattern registration.

Ensures AR fusions use the correct TP group.


2448-2449: Disable UB when PP>1: intentional trade‑off; verify runtime paths.

This prevents UB allocation under PP. Confirm PP torch.compile paths don’t depend on UB (e.g., UB AR finalize patterns), or guard them behind the same condition.

tests/unittest/_torch/multi_gpu/test_user_buffers.py (6)

36-41: Helper for Mapping: LGTM.

Centralizing TP mapping via create_tp_mapping improves test clarity.


137-139: Consistent Mapping use for AllReduce in UB tests.

Good reuse of create_tp_mapping.


326-333: Consistent Mapping injection into modules.

Model pieces now share the same mapping; aligns with Backend expectations.


453-456: Backend mapping wiring in UB pass test: LGTM.

Enables AR fusion registration in compiled graphs.


684-689: AllReduce instances constructed with mapping: LGTM.

Matches communicator expectations.


984-987: Backend mapping wiring in FP4 UB pass test: LGTM.

Consistent with other tests.

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@yuxianq yuxianq changed the title [TRTLLM-7073][feat] Support torch compile for PP for Llama and DeepSe… [TRTLLM-7073][feat] Support torch compile for PP for Llama and DeepSeekV3 Nov 25, 2025
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LGTM

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Pipeline passed with automatic retried tests. Check the rerun report for details.

@liji-nv liji-nv merged commit 87e0c8a into NVIDIA:main Dec 4, 2025
5 checks passed
MinaHuai pushed a commit to davidmlw/TensorRT-LLM that referenced this pull request Dec 10, 2025
…VIDIA#8779)

The performance results of some kernels could be easily affected by the warm/cold L2 cache status. To achieve more precise profiling results, the L2 cache is cleared for every execution by the circular buffer method for better benchmarking during autotuning.

Signed-off-by: Yukun He <[email protected]>

[None][infra] Waive failed cases for main branch on 11/25 (NVIDIA#9429)

Signed-off-by: qqiao <[email protected]>

[NVIDIA#8391][chore] test_perf.py to lock clocks read from gpu_configs.yml instead of max freq (NVIDIA#9409)

Signed-off-by: Eran Geva <[email protected]>

[None][ci] Move more test stages to use OCI machines (NVIDIA#9395)

Signed-off-by: Yanchao Lu <[email protected]>
Co-authored-by: Matt Lefebvre <[email protected]>

[None][feat] Improve TRTLLM MoE in small hidden size throughput cases (NVIDIA#9377)

Signed-off-by: Anthony Chang <[email protected]>

[https://nvbugs/5537996][fix] Let KV cache manager block initialization be aware whether it is doing a dry run or not (NVIDIA#9093)

Before this commit, the kv cache manager does the same regardless, which causes a mis-calculation in free memory available to allocate for the KV cache manager, hence causing a crash.

This commit fixes this by letting KV cache manager initialization be aware whether it is doing the dry run or not. If it is a dry run, use the max_tokens setting that is already pre-calculated and filled into kv_cache_config.max_tokens.

Signed-off-by: eopXD <[email protected]>

[https://nvbugs/5667922][fix] Update long context evaluation config (NVIDIA#9426)

Signed-off-by: mni <[email protected]>

[None][fix] Mitigate test timeout issues (NVIDIA#9445)

Signed-off-by: Shixiaowei02 <[email protected]>

[None][chore] Fix trtllm-eval for PyTorchLLM (NVIDIA#9427)

Signed-off-by: Fanrong Li <[email protected]>

[None][feat] Add a parser to layer-wise benchmarks (NVIDIA#9440)

Signed-off-by: Tailing Yuan <[email protected]>

[None][feat] Support custom chat template for tool calling (NVIDIA#9297)

Signed-off-by: Pengyun Lin <[email protected]>

[TRTLLM-8160][feat] Add draft token tree runtime on CDL (NVIDIA#8586)

Signed-off-by: Yue Weng <[email protected]>

[None][ci] waive a test (NVIDIA#9458)

Signed-off-by: Yan Chunwei <[email protected]>

[https://nvbugs/5680905][fix] Relax the MMLU accuracy requirement for DS-v3.2 (NVIDIA#9439)

Signed-off-by: Fanrong Li <[email protected]>

[TRTLLM-8376][feat] top-p optimization (removes redundant softmax) (NVIDIA#9411)

Signed-off-by: ixlmar <[email protected]>

[TRTLLM-9490][feat] use FlashInfer's top_k_sampling_from_probs (NVIDIA#9457)

Signed-off-by: ixlmar <[email protected]>

[https://nvbugs/5647400] [fix] Enlarged the AllReduce workspace size to 64MB. Added AllReduce strategy to AD config. (NVIDIA#9145)

Signed-off-by: Eran Geva <[email protected]>

[TRTLLM-909][feat] Overlap context chunks in pipeline parallel mode (NVIDIA#9308)

Signed-off-by: Robin Kobus <[email protected]>

[None][chore] AutoDeploy add multi stream moe pass to default.yaml (NVIDIA#9430)

Signed-off-by: Suyog Gupta <[email protected]>

[https://nvbugs/5685143][fix] avoid cudaFree overlap with cuda graph (NVIDIA#9438)

Signed-off-by: Chuang Zhu <[email protected]>

[None][chore] Bump version to 1.2.0rc5 (NVIDIA#9455)

Signed-off-by: Yiqing Yan <[email protected]>

[TRTLLM-8936][test] Add disagg and wideep multi-node multi-gpu test cases (NVIDIA#9356)

Signed-off-by: FredricZ-2007 <[email protected]>

[None][ci] move some slow test cases of DGX-B200 to post merge (NVIDIA#9467)

Signed-off-by: junq <[email protected]>

[TRTLLM-9293][feat] Enable partial weight loading to support streaming update weights (NVIDIA#9224)

Signed-off-by: shuyix <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[TRTLLM-9264][fix] Add accuracy/unit tests/doc for phi4mm (NVIDIA#9246)

Signed-off-by: Wanli Jiang <[email protected]>

[https://nvbugs/5580099][fix] Cherry pick IMA issue fix from release/1.1 (NVIDIA#9032)

Signed-off-by: Junyi Xu <[email protected]>

[None][chore] Upgrade CuteDSL to 4.3.0 (NVIDIA#9444)

Signed-off-by: Enwei Zhu <[email protected]>

[None][feat] Support MLA chunked prefill for DeepSeek V3.2 model (NVIDIA#9376)

Signed-off-by: Chang Liu (Enterprise Products) <[email protected]>

[None][feat] Add environment variable to force spec-dec number of accepted tokens (NVIDIA#9371)

Signed-off-by: Aurelien Chartier <[email protected]>

[None][infra] Update allowed list 2025.11.25 (NVIDIA#9468)

Signed-off-by: Yuanjing Xue <[email protected]>

[None][infra] Fail the pipeline when slurm ssh dropped (NVIDIA#9157)

Signed-off-by: Yuanjing Xue <[email protected]>

[None][feat] AutoDeploy: Remove redundant copies in mamba layers (NVIDIA#9461)

Signed-off-by: Chenghao Zhang <[email protected]>
Co-authored-by: Suyog Gupta <[email protected]>

[None][feat] AutoDeploy: Add A_log fusion for Mamba layers (NVIDIA#9422)

Signed-off-by: Chenghao Zhang <[email protected]>

[None][ci] Waive blackwell test on spec gate. (NVIDIA#9502)

Signed-off-by: Zheyu Fu <[email protected]>

[https://nvbugs/5608930][fix] Fix a typo (NVIDIA#9487)

Signed-off-by: Shixiaowei02 <[email protected]>

[NVIDIA#9463][feat] Add revision option to trtllm commands (NVIDIA#9498)

Signed-off-by: Aurelien Chartier <[email protected]>

[TRTLLM-9085][doc] fix math formula rendering issues (NVIDIA#9481)

Signed-off-by: junq <[email protected]>

[None][chore] update comments in llm_args.py (NVIDIA#9472)

Signed-off-by: junq <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[https://nvbugs/5680310][fix] Fix ctx only timed out test (NVIDIA#9410)

Signed-off-by: Patrice Castonguay <[email protected]>

[https://nvbugs/5547414][fix] enable case after using local cache model (NVIDIA#9473)

Signed-off-by: Hui Gao <[email protected]>

[None][fix] Replace PYTORCH_CUDA_ALLOC_CONF with PYTORCH_ALLOC_CONF to fix deprecation warning (NVIDIA#9294)

Signed-off-by: Jiagan Cheng <[email protected]>

[https://nvbugs/5698581][fix] Init draft tokens for CUDA graph dummy request (NVIDIA#9505)

Signed-off-by: ziyixiong-nv <[email protected]>

[None][infra] Waive failed case in pre-merge on 11/27 (NVIDIA#9507)

Signed-off-by: qqiao <[email protected]>

[TRTLLM-9513][docs] Qwen3 deployment guide (NVIDIA#9488)

Signed-off-by: Lanyu Liao <[email protected]>
Co-authored-by: Lanyu Liao <[email protected]>

[None][chore] revert batch_size=1 to prevent timeout and lower accuracy reference by 0.12% as a WAR (NVIDIA#9447)

Signed-off-by: Lizhi Zhou <[email protected]>
Co-authored-by: Shi Xiaowei <[email protected]>

[TRTLLM-9279][infra] Use flexcache for gh200 nodes since they locate in Austin (NVIDIA#9405)

Signed-off-by: qqiao <[email protected]>
Signed-off-by: Emma Qiao <[email protected]>
Co-authored-by: Yanchao Lu <[email protected]>

[cherry-pick][https://nvbugs/5670793][fix] Solve trtllm-serve launch_disaggregated issue (NVIDIA#9346)

Signed-off-by: xxi <[email protected]>

[None][infra] Fix Slurm job script (NVIDIA#9508)

Signed-off-by: Yuanjing Xue <[email protected]>

[None][fix] change allreduce workspace dtype to torch.int64 to avoid overflow (NVIDIA#9479)

Signed-off-by: Zhenhuan Chen <[email protected]>

[None][feat] add qwen3-next CI test of accuracy on BF16 and NVFP4 (NVIDIA#9330)

Signed-off-by: jiant <[email protected]>

[None][fix] fix TP support for DeepSeek-V3.2 on hopper (NVIDIA#9484)

Signed-off-by: Fanrong Li <[email protected]>

[TRTLLM-9389][chore] Refactor AlltoallMethodType. (NVIDIA#9388)

Signed-off-by: Bo Li <[email protected]>

[https://nvbugs/5674665][chore] Add test coverage for https://nvbugspro.nvidia.com/bug/5674665 (NVIDIA#9518)

Signed-off-by: eopXD <[email protected]>

[TRTLLM-7288][infra] Download merged waive list in slurm script (NVIDIA#8999)

Signed-off-by: Yiqing Yan <[email protected]>
Signed-off-by: Yanchao Lu <[email protected]>
Co-authored-by: Yanchao Lu <[email protected]>

[https://nvbugs/5687820][fix] Remove self.abort() in DetokenizedGenerationResult (NVIDIA#9449)

Signed-off-by: Enwei Zhu <[email protected]>

[NVIDIA#9150][feat] AutoDeploy Nemotron-Flash support (NVIDIA#9504)

Signed-off-by: Lucas Liebenwein <[email protected]>

[None] [chore] Update to cutlass 4.3 (NVIDIA#8637)

Signed-off-by: Kaiyu Xie <[email protected]>

[https://nvbugs/5637037][chore] Update waive lists. (NVIDIA#9386)

Signed-off-by: Bo Li <[email protected]>
Signed-off-by: Enwei Zhu <[email protected]>
Co-authored-by: Enwei Zhu <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[TRTLLM-8970][infra] Fix generate report when has isolation test result (NVIDIA#8861)

Signed-off-by: qqiao <[email protected]>
Signed-off-by: Emma Qiao <[email protected]>

[https://nvbugs/5685015][fix] Update invalid max_token test (NVIDIA#9435)

Signed-off-by: Junyi Xu <[email protected]>

[None][fix] Fix on-disk cache and revise logger/statistics for AutoTuner. (NVIDIA#9211)

Signed-off-by: Yukun He <[email protected]>

[https://nvbugs/5689658][test] Fix gpu lock issue running on cluster (NVIDIA#9441)

Signed-off-by: yufeiwu <[email protected]>

[None][chore] add spec_decoding configs in perf benchmark scripts and fix typos (NVIDIA#9533)

Signed-off-by: Lanyu Liao <[email protected]>
Co-authored-by: Lanyu Liao <[email protected]>

[None][fix] Remove FP8 K/V buffer from TRTLLM sparse MLA attention kernel (NVIDIA#9529)

Signed-off-by: Chang Liu (Enterprise Products) <[email protected]>

[None] [chore] Enhancements and clean up to slurm scripts (NVIDIA#9493)

Signed-off-by: Kaiyu Xie <[email protected]>

[None][chore] Revert "[None][fix] change allreduce workspace dtype to torch.int64 t… (NVIDIA#9538)

Signed-off-by: Zhenhuan Chen <[email protected]>

[None][infra] Waive failed cases for main branch on 11/28 (NVIDIA#9539)

Signed-off-by: qqiao <[email protected]>

[None][fix] Pass checkpoint_format to create_input_processor (NVIDIA#9521)

Signed-off-by: Robin Kobus <[email protected]>

[TRTLLM-9541][infra] Use artifactory mirror for download.pytorch.org (NVIDIA#9477)

Signed-off-by: ZhanruiSunCh <[email protected]>
Signed-off-by: Zhanrui Sun <[email protected]>
Co-authored-by: Yanchao Lu <[email protected]>

[TRTLLM-9488][feat] add 'disable_flashinfer_sampling' config option (NVIDIA#9454)

Signed-off-by: ixlmar <[email protected]>

[None][infra] Waive failed case in pre-merge on 11/28 (NVIDIA#9537)

Signed-off-by: Wangshanshan <[email protected]>

[None][perf] Helix: improve all-to-all perf for large CP size (NVIDIA#9494)

Signed-off-by: Matthias Jouanneaux <[email protected]>
Signed-off-by: Zheyu Fu <[email protected]>
Co-authored-by: Zheyu Fu <[email protected]>

[None][feat] support for more accurate AR calculation (NVIDIA#9323)

Signed-off-by: binghanc <[email protected]>

[TRTLLM-9488][fix] llmapi references (NVIDIA#9547)

Signed-off-by: ixlmar <[email protected]>

[NVIDIA#8948][feat] Support custom sharding config (NVIDIA#9143)

Signed-off-by: greg-kwasniewski1 <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[None][chore] Weekly mass integration of release/1.1 -- rebase (NVIDIA#9522)

Signed-off-by: yunruis <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Wangshanshan <[email protected]>
Signed-off-by: qgai <[email protected]>
Signed-off-by: Balaram Buddharaju <[email protected]>
Signed-off-by: Yan Chunwei <[email protected]>
Signed-off-by: Junyi Xu <[email protected]>
Signed-off-by: Simeng Liu <[email protected]>
Signed-off-by: nv-guomingz <[email protected]>
Signed-off-by: Jin Li <[email protected]>
Signed-off-by: Ivy Zhang <[email protected]>
Signed-off-by: Vincent Zhang <[email protected]>
Signed-off-by: peaceh <[email protected]>
Signed-off-by: Michal Guzek <[email protected]>
Signed-off-by: Michal Guzek <[email protected]>
Signed-off-by: Chang Liu (Enterprise Products) <[email protected]>
Signed-off-by: leslie-fang25 <[email protected]>
Signed-off-by: Shunkang <[email protected]>
Signed-off-by: junq <[email protected]>
Co-authored-by: yunruis <[email protected]>
Co-authored-by: sunnyqgg <[email protected]>
Co-authored-by: brb-nv <[email protected]>
Co-authored-by: Yan Chunwei <[email protected]>
Co-authored-by: JunyiXu-nv <[email protected]>
Co-authored-by: Simeng Liu <[email protected]>
Co-authored-by: Guoming Zhang <[email protected]>
Co-authored-by: Jin Li <[email protected]>
Co-authored-by: Ivy Zhang <[email protected]>
Co-authored-by: Vincent Zhang <[email protected]>
Co-authored-by: peaceh-nv <[email protected]>
Co-authored-by: Michal Guzek <[email protected]>
Co-authored-by: Chang Liu <[email protected]>
Co-authored-by: Leslie Fang <[email protected]>
Co-authored-by: Shunkangz <[email protected]>
Co-authored-by: Shunkang <[email protected]>
Co-authored-by: QI JUN <[email protected]>

[TRTLLM-5971][feat] Integrate helix parallelism (NVIDIA#9342)

Signed-off-by: Balaram Buddharaju <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[None][infra] - Request idle time exemption for OCI jobs (NVIDIA#9528)

Signed-off-by: Yanchao Lu <[email protected]>

[None][infra] Wiave failed tests for main branch on 11/30 (NVIDIA#9555)

Signed-off-by: qqiao <[email protected]>

[None][fix] Fix port conflict in disagg tests (NVIDIA#9474)

Signed-off-by: Junyi Xu <[email protected]>

[None][ci] Split H100_PCIe-PyTorch-Post-Merge test stage (NVIDIA#9558)

Signed-off-by: Yanchao Lu <[email protected]>

[None][ci] Split H100_PCIe-PyTorch-Post-Merge test stage (NVIDIA#9559)

Signed-off-by: Yanchao Lu <[email protected]>

[TRTLLM-8958][feat] and [TRTLLM-8960]: create ConfigurableMoE and support TRTLLMGenFusedMoE as backend (NVIDIA#9486)

[None] [feat] Optimize the algorithm part of RocketKV (NVIDIA#9333)

Signed-off-by: yuhangh <[email protected]>

[https://nvbugs/5690172][fix] Fix Qwen3-235B ATP accuracy issue with PDL (NVIDIA#9530)

Signed-off-by: Enwei Zhu <[email protected]>

[TRTLLM-6222][feat] Extend cute_dsl_nvfp4_gemm to sm103. (NVIDIA#9543)

Signed-off-by: Mindy Li <[email protected]>

[None][fix] Correct virtual memory allocation alignment (NVIDIA#9491)

Signed-off-by: Yuan Tong <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[https://nvbugs/5684703][fix] Unwaive disagg guided decoding test (NVIDIA#9466)

Signed-off-by: Enwei Zhu <[email protected]>

[https://nvbugs/5503479][fix] Temporarily lower reference accuracy to stabilize CI (NVIDIA#9398)

Signed-off-by: Pengbo Wang <[email protected]>

[None][chore] remove qwen3-next accuracy tests (NVIDIA#9534)

Signed-off-by: jiant <[email protected]>

[None][doc] fix mtp.py typo (NVIDIA#9307)

Signed-off-by: liugaoji <[email protected]>

[None][feat] add chat template kwargs support to longbench-v2 (NVIDIA#9544)

Signed-off-by: Fanrong Li <[email protected]>

[NVIDIA#9496][fix] AutoDeploy: remove auto-tuner from nvfp4_gemm forward (NVIDIA#9497)

Signed-off-by: Neta Zmora <[email protected]>

[None][fix] Replace hash method with unique_id for cutedsl MoE runners. (NVIDIA#9569)

Signed-off-by: Yukun He <[email protected]>

[None][chore] refactor disaggregated scripts to use named arguments (NVIDIA#9581)

Signed-off-by: Zhenhuan Chen <[email protected]>

[TRTLLM-6222][feat] Several perf opt for cuteDSL nvf4 gemm (NVIDIA#9428)

Signed-off-by: Yuhan Li <[email protected]>

[None][chore] reduce the layers of the `devel` docker image (NVIDIA#9077)

Signed-off-by: Martin Marciniszyn Mehringer <[email protected]>

[https://nvbugs/5651854][infra] Enable perf metrics during accuracy testing (NVIDIA#9140)

[None][fix] Skip Allreduce init for Attention DP (NVIDIA#9542)

Signed-off-by: Enwei Zhu <[email protected]>

[None][test] [None][test] Waive main branch test failures 12/1 (NVIDIA#9566)

Signed-off-by: Yanchao Lu <[email protected]>

[None][ci] Minor change for Slurm scripts (NVIDIA#9561)

Signed-off-by: Yanchao Lu <[email protected]>

[TRTLLM-6768][infra] Fix params for not updating github status (NVIDIA#6747)

Signed-off-by: Yiqing Yan <[email protected]>

[None][infra] Update the pytest options after MI (NVIDIA#9579)

Signed-off-by: qqiao <[email protected]>

[TRTLLM-6756][feat] Add Beam Search to TorchSampler (NVIDIA#8509)

Signed-off-by: Stefan Niebler <[email protected]>

[None][chore] Defer exposing context parallel configs (NVIDIA#9552)

Signed-off-by: Balaram Buddharaju <[email protected]>

[TRTC-1943][feat] Env vars override support in LLM API (NVIDIA#9104)

Signed-off-by: Venky Ganesh <[email protected]>

[None][feat] AutoDeploy: Use the router gemm op for nemotron MOE (NVIDIA#9500)

Signed-off-by: Chenghao Zhang <[email protected]>

[NVIDIA#9198][feat] Refactor dist ops in AutoDeploy (NVIDIA#9301)

Signed-off-by: Eran Geva <[email protected]>

[None][fix] Prevent YAML partial kv_cache_config from incorrectly overriding the complete kv_cache_config (NVIDIA#9262)

Signed-off-by: Yuening Li <[email protected]>

[TRTLLM-9085][doc] fix math formula rendering issues in github (NVIDIA#9605)

Signed-off-by: junq <[email protected]>

[None][feat] Unify nvfp4 gemm backend (NVIDIA#8963)

Signed-off-by: Shijie Wang <[email protected]>
Signed-off-by: Yukun He <[email protected]>
Signed-off-by: Shijie <[email protected]>
Co-authored-by: Yukun He <[email protected]>

[None][feat] Add support for KVCache reuse for DSv32 (NVIDIA#9383)

Signed-off-by: Iman Tabrizian <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[None][chroe] Polish qwen3-next modeling code. (NVIDIA#8902)

Signed-off-by: nv-guomingz <[email protected]>

[https://nvbugs/5703953][fix] Use random port for disagg tests (NVIDIA#9582)

Signed-off-by: Junyi Xu <[email protected]>

[None][fix] Waive gb200 (NVIDIA#9580)

Signed-off-by: Xin He (SW-GPU) <[email protected]>

[FMDL-1328][feat] Add support for nano-v3 and super-v3 with pytorch backend (NVIDIA#9261)

Signed-off-by: Wanli Jiang <[email protected]>

[https://nvbugs/5582091][test] increase warmup times in testing for multi-gpu cases (NVIDIA#9578)

Signed-off-by: Ruodi Lu <[email protected]>
Co-authored-by: Ruodi Lu <[email protected]>

[None][chore] Add failed cases into waives.txt (NVIDIA#9588)

Signed-off-by: xinhe-nv <[email protected]>

[https://nvbugs/5702793][fix] Fix uncontiguous tensor view (NVIDIA#9576)

Signed-off-by: shuyix <[email protected]>

[None][infra] Waive failed cases for main branch (NVIDIA#9615)

Signed-off-by: qqiao <[email protected]>

[TRTLLM-9488][feat] use FlashInfer.sampling by default (NVIDIA#9545)

Signed-off-by: ixlmar <[email protected]>

[None][infra] Update allowlist 2025/12/01 (NVIDIA#9616)

Signed-off-by: Yuanjing Xue <[email protected]>

[None][infra] Remove an invalid test name in waives.txt (NVIDIA#9620)

Signed-off-by: qqiao <[email protected]>

Lock the gpu clocks in L0 perf tests (NVIDIA#9585)

Signed-off-by: Eran Geva <[email protected]>

[TRTLLM-9466][test] Evaluate helix parallelism with DSV3 Lite (NVIDIA#9597)

Signed-off-by: Balaram Buddharaju <[email protected]>

[None][fix] Extract GPU count from single-node stage names (NVIDIA#9599)

Signed-off-by: Chang Liu (Enterprise Products) <[email protected]>

[https://nvbugs/5667774][fix] Refine Piecewise Cuda Graph Condition for DP (NVIDIA#9393)

Signed-off-by: Jin Li <[email protected]>

[TRTLLM-9144][fix] enhance RPC robustness (NVIDIA#8711)

Signed-off-by: Superjomn <[email protected]>
Signed-off-by: Erin Ho <[email protected]>
Signed-off-by: Yan Chunwei <[email protected]>
Co-authored-by: Erin Ho <[email protected]>

[https://nvbugs/5627710][fix] Fix synchronization bugs in KvCacheTransferManager that can cause corrupted blocks (NVIDIA#9056)

Signed-off-by: thorjohnsen <[email protected]>
Signed-off-by: Thor Johnsen <[email protected]>
Co-authored-by: Iman Tabrizian <[email protected]>
Co-authored-by: Robin Kobus <[email protected]>

[TRTLLM-8980][test] Clean up spec dec tests in test_llm_api_pytorch (NVIDIA#8889)

Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[NVIDIA#9150][feat] Add code for nano v3 to custom implementation in AD (NVIDIA#9465)

* Why?

We would like to show an alternative to monkey-patching in AutoDeploy.

* What?

This commit builds on the existing custom model implementation for
NemotronH and adds the bits relevant for MoE layers.

Part of NVIDIA#9150.

Signed-off-by: William Zhang <[email protected]>

[NVIDIA#9150][feat] AutoDeploy: reviewer comments for NVIDIA#9150 (NVIDIA#9527)

Signed-off-by: Lucas Liebenwein <[email protected]>

[https://nvbugs/5651854][fix] Fix dist-serving perf by clearing CPU affinity (NVIDIA#9549)

Signed-off-by: Shixiaowei02 <[email protected]>

[NVIDIA#9550][feat] AutoDeploy: Add NVFP4 Cutlass MoE kernels  (NVIDIA#9551)

Signed-off-by: Neta Zmora <[email protected]>

[https://nvbugs/5688388][fix] fix: Reducing num request in disagg test to speed up (NVIDIA#9598)

Signed-off-by: Patrice Castonguay <[email protected]>

[TRTLLM-8946][feat] Improved heuristics to detect shardable regions (NVIDIA#9200)

Signed-off-by: Lucas Liebenwein <[email protected]>
Signed-off-by: greg-kwasniewski1 <[email protected]>
Co-authored-by: Lucas Liebenwein <[email protected]>

[NVIDIA#9632][feat] Support EXTRA_WHEEL_BUILD_ARGS during wheel build (NVIDIA#9633)

Signed-off-by: Yu Chi Li <[email protected]>

[None][chore] Waive test failing on pre-merge (NVIDIA#9638)

Signed-off-by: Balaram Buddharaju <[email protected]>

[None][chore] Remove traceback dump for multimodal input processor (NVIDIA#9634)

Signed-off-by: Chang Liu (Enterprise Products) <[email protected]>

[None][chore] Fix trtllm-eval and move GroupedGemmInputsHelper (NVIDIA#9612)

Signed-off-by: Enwei Zhu <[email protected]>

[https://nvbugs/5698434][fix] Use separate weight mapper for draft (NVIDIA#9607)

Signed-off-by: Anurag Mukkara <[email protected]>

[TRTLLM-7101][infra] Reuse passed tests (NVIDIA#6894)

Signed-off-by: Yiqing Yan <[email protected]>
Co-authored-by: Yanchao Lu <[email protected]>

[None][test] Remove duplicate test cases (NVIDIA#9623)

Signed-off-by: yufeiwu <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[None][feat] Add RocketKV usage doc and e2e accuracy test on LongBenchV2 (NVIDIA#9572)

Signed-off-by: yuhangh <[email protected]>

[TRTLLM-9242][doc] Add examples showcasing openai compatible APIs (NVIDIA#9520)

Signed-off-by: Junyi Xu <[email protected]>

[None][chore] AutoDeploy update cuda stream manager for multi-device (NVIDIA#9575)

Signed-off-by: Suyog Gupta <[email protected]>

[TRTLLM-9391][chore] Automatically estimate required workspace. (NVIDIA#9535)

Signed-off-by: Bo Li <[email protected]>

[https://nvbugs/5708475][fix] Fix e2e eval accuracy for helix parallelism (NVIDIA#9647)

Signed-off-by: Balaram Buddharaju <[email protected]>

[https://nvbugs/5561153][test] Fix log error for perf test (NVIDIA#9622)

Signed-off-by: FredricZ-2007 <[email protected]>

[TRTLLM-8241][feat] Aliasing to comply to LlmArgs (NVIDIA#9586)

Signed-off-by: Pengyun Lin <[email protected]>

[None][chore] Add failed cases into waives.txt (NVIDIA#9593)

Signed-off-by: Jie Li <[email protected]>
Co-authored-by: Jie Li <[email protected]>

[TRTLLM-6842][feat] Support Response API for general purpose (NVIDIA#9392)

Signed-off-by: Junyi Xu <[email protected]>

[None][test] Update Qwen3-next accuracy testing by setting the cuda … (NVIDIA#9613)

Signed-off-by: nv-guomingz <[email protected]>

[None][feat] update trtllm-gen nvfp4 kernels with better performance (NVIDIA#9510)

Signed-off-by: Perkz Zheng <[email protected]>

[None][doc] Replace the tensorrt icon with torch icon on overview.md (NVIDIA#9644)

Signed-off-by: nv-guomingz <[email protected]>

[https://nvbugs/5705197][chore] Unwaive timeout disagg tests (NVIDIA#9637)

Signed-off-by: Patrice Castonguay <[email protected]>

[https://nvbugs/5552132][fix] Enable LoRa for GPT OSS Torch (NVIDIA#8253)

Signed-off-by: Michal Guzek <[email protected]>

[None][fix] Fix wide ep MoE error (NVIDIA#9642)

Signed-off-by: Iman Tabrizian <[email protected]>

[https://nvbugs/5702795][fix] Remove the warning message for aten.log. (NVIDIA#9665)

Signed-off-by: nv-guomingz <[email protected]>

[https://nvbugs/5693853][fix] Fix error handling when querying machin… (NVIDIA#9483)

Signed-off-by: Gal Hubara Agam <[email protected]>

[OMNIML-2932] [feat] nvfp4 awq support (NVIDIA#8698)

Signed-off-by: weimingc <[email protected]>

[NVIDIA#9643][fix] AutoDeploy: fix nano sharding config (NVIDIA#9668)

Signed-off-by: Lucas Liebenwein <[email protected]>

[NVIDIA#9147][feat] AutoDeploy: Draft Target Speculative Decoding (NVIDIA#9275)

Signed-off-by: Govind Ramnarayan <[email protected]>

[None][feat] Update Qwen3CodeToolParser to align tool-calling parameters (NVIDIA#9540)

Signed-off-by: Wanli Jiang <[email protected]>

[TRTLLM-7181][infra] Generate test results when pytest timeout happens (NVIDIA#9396)

Signed-off-by: Yiqing Yan <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[TRTLLM-9522][fix] restore `trtllm-serve mm_embedding_serve` (NVIDIA#9669)

[TRTLLM-5093][infra] Write env variables to a file in the interactive debug session (NVIDIA#6792)

Signed-off-by: Yiqing Yan <[email protected]>

[None][fix] fix error when processing batches containing both text and mm data (NVIDIA#8381)

Signed-off-by: Nekofish-L <[email protected]>

[TRTLLM-7073][feat] Support torch compile for PP for Llama and DeepSeekV3 (NVIDIA#7838)

Signed-off-by: Jin Li <[email protected]>

[None][feat] Add weights initialization and context phase parser to layer-wise benchmarks (NVIDIA#9667)

Signed-off-by: Tailing Yuan <[email protected]>

[TRTLLM-8274][feat] Check if executor is shutdown in /health entrypoint (NVIDIA#9057)

Signed-off-by: Junyi Xu <[email protected]>

[NVIDIA#8733][feat] Add Llama4 MoE handling to AutoDeploy (NVIDIA#9556)

Signed-off-by: Tal Cherckez <[email protected]>
Signed-off-by: tcherckez-nvidia <[email protected]>
Co-authored-by: Neta Zmora <[email protected]>

[None][ci] unwaive tests (NVIDIA#9651)

Signed-off-by: Yan Chunwei <[email protected]>

[None][feat] Add NIXL-LIBFABRIC support (NVIDIA#9225)

Signed-off-by: Yoray Zack <[email protected]>
Signed-off-by: zackyoray <[email protected]>

[None][test] rename wide ep and disagg metric name in perf test (NVIDIA#9704)

Signed-off-by: Ruodi Lu <[email protected]>
Co-authored-by: Ruodi Lu <[email protected]>

[https://nvbugs/5467531][fix] Unwaive fused_moe all to all test with … (NVIDIA#9617)

Signed-off-by: Jin Li <[email protected]>

[None][fix] Recover TRTLLM MoE Perf for DEP (NVIDIA#9562)

Signed-off-by: Anthony Chang <[email protected]>

[None][chore] Add failed cases into waives.txt (NVIDIA#9662)

Signed-off-by: Xin He (SW-GPU) <[email protected]>
Signed-off-by: xinhe-nv <[email protected]>
Signed-off-by: Yanchao Lu <[email protected]>
Co-authored-by: Yanchao Lu <[email protected]>

[None][fix] Fix TLLM_SPEC_DECODE_FORCE_NUM_ACCEPTED_TOKENS for MTP/EAGLE (NVIDIA#9608)

Signed-off-by: Aurelien Chartier <[email protected]>

[None][infra] Add container notices and documentation (NVIDIA#9185)

Signed-off-by: Parker Drake <[email protected]>

[TRTLLM-5312][infra] Add triton trigger rules (NVIDIA#6440)

Signed-off-by: Yiqing Yan <[email protected]>

[None][doc] Add feature docs for helix parallelism (NVIDIA#9684)

Signed-off-by: Balaram Buddharaju <[email protected]>

[TRTLLM-9579][infra] Set mergeWaiveList stage UNSTABLE when there is any issue (NVIDIA#9692)

Signed-off-by: Yiqing Yan <[email protected]>

[None][doc] Added line about partial reuse (NVIDIA#7846)

Signed-off-by: thorjohnsen <[email protected]>

[TRTLLM-8920][feat] decouple disagg service from fastapi (NVIDIA#8714)

Signed-off-by: Lizhi Zhou <[email protected]>

[https://nvbugs/5633340][fix] start disagg workers and servers on free ports (NVIDIA#9694)

Signed-off-by: Lizhi Zhou <[email protected]>

[TRTLLM-9562] [doc] Add Deployment Guide for Kimi K2 Thinking on TensorRT LLM - Blackwell (NVIDIA#9711)

Signed-off-by: Kaiyu Xie <[email protected]>

[NVIDIA#9602][feat] AutoDeploy: Support TRTLLM Sampler (NVIDIA#9641)

Signed-off-by: Govind Ramnarayan <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[None] [tests] Unwaive EPLB tests (NVIDIA#9625)

Signed-off-by: Kaiyu Xie <[email protected]>

[https://nvbugs/5518713][test] Refactor core test lists by merging with llm_perf_cluster.yml (NVIDIA#9714)

Signed-off-by: yufeiwu <[email protected]>

[TRTLLM-7136][feat] Update load_weights method to include mapping parameter in checkpoint loaders (NVIDIA#9583)

Signed-off-by: Robin Kobus <[email protected]>

[None][refactor] Improve request processing function in sampler (NVIDIA#9671)

Signed-off-by: Robin Kobus <[email protected]>

[https://nvbugs/5670672][fix] Fix flaky KV connector tests (NVIDIA#9676)

Signed-off-by: jthomson04 <[email protected]>

[None][infra] Update allowed list 20251204 (NVIDIA#9718)

Signed-off-by: Yuanjing Xue <[email protected]>

[None][feat] AutoDeploy: Perf optimization for Attention and rmsnorm (NVIDIA#9719)

Signed-off-by: Chenghao Zhang <[email protected]>

[None][chore] Waive flakey disagg tests (NVIDIA#9749)

Signed-off-by: Mike Iovine <[email protected]>

[https://nvbugs/5601682][fix] Fix cacheTransceiver hang (NVIDIA#9311)

Signed-off-by: Iman Tabrizian <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[TRTLLM-9199][docs] KV Connector Docs (NVIDIA#9325)

Signed-off-by: jthomson04 <[email protected]>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[TRTLLM-9160][doc] add doc to llm_runtime.py (NVIDIA#9482)

Signed-off-by: Yan Chunwei <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[None][doc] VDR 1.0 trtllm-serve doc enhancement (NVIDIA#9443)

Signed-off-by: Pengyun Lin <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[TRTLLM-9086][doc] Clean up TODOs in documentation (NVIDIA#9292)

Signed-off-by: junq <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[TRTLLM-9157][doc] Guided decoding doc improvement (NVIDIA#9359)

Signed-off-by: Enwei Zhu <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[None][infra] Updated Linux installation guide (NVIDIA#9485)

Signed-off-by: Yiqing Yan <[email protected]>
Co-authored-by: Yanchao Lu <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[TRTLLM-9075][doc] refine the slurm examples (NVIDIA#9548)

Signed-off-by: Yan Chunwei <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[TRTLLM-9093][doc] update hyper links in overview (NVIDIA#9568)

Signed-off-by: junq <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[TRTLLM-9092][doc] link to modelopt checkpoints in quick start guide (NVIDIA#9571)

Signed-off-by: junq <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>
Signed-off-by: Mike Iovine <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[None][fix] Fix triton moe load_weight (NVIDIA#9649)

Signed-off-by: shuyix <[email protected]>

[None][fix] fix a bug: deepseek_fp8_block_scales in TRTLLMGEN-MoE use 2D x_sf instead of 1D (NVIDIA#9658)

Signed-off-by: xxi <[email protected]>

[TRTLLM-9372][feat] Enable CuteDSL MoE with Large EP (NVIDIA#9592)

Signed-off-by: Enwei Zhu <[email protected]>

[TRTLLM-9522][chore] implement default `attach_multimodal_embeddings` (NVIDIA#9664)

Signed-off-by: ixlmar <[email protected]>

[TRTLLM-9660][feat] Convert cuteDSL GEMM to opt-in feature (NVIDIA#9682)

Signed-off-by: Jonas Li <[email protected]>
Co-authored-by: Kaiyu Xie <[email protected]>

[None][fix] enable hmac in RPC (NVIDIA#9745)

Signed-off-by: Superjomn <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[https://nvbugs/5703953][fix] Preserving ip:port for trtllm-serve before initializing llm (NVIDIA#9646)

Signed-off-by: Junyi Xu <[email protected]>

[None][infra] Waive failed cases for main branch on 12/07 (NVIDIA#9769)

Signed-off-by: qqiao <[email protected]>

[None][fix] Several minor fixes to CI setting (NVIDIA#9765)

Signed-off-by: Yanchao Lu <[email protected]>

[OMNIML-3036][doc] Re-branding TensorRT-Model-Optimizer as Nvidia Model-Optimizer (NVIDIA#9679)

Signed-off-by: Chenjie Luo <[email protected]>

[None][feat] Enable NCCL_SYMMETRIC as default fallback for AllReduce (NVIDIA#9314)

Signed-off-by: Ludwig Schneider <[email protected]>

[TRTLLM-9000][feat] Add multi-node Perf Tests into CI (NVIDIA#8800)

Signed-off-by: Chenfei Zhang <[email protected]>

[None][test] add ntp tolerance in time metrics verification (NVIDIA#9741)

Signed-off-by: zhengd-nv <[email protected]>

[TRTLLM-9603][feat] Enable ConfigurableMoE test in the CI (NVIDIA#9645)

[https://nvbugs/5422621][test] Add GB 200 WIDEEP test case for RCCA 5422621 (NVIDIA#9506)

Signed-off-by: FredricZ-2007 <[email protected]>

[None][fix] Fix two tuning cache miss issues. (NVIDIA#9743)

Signed-off-by: Yukun He <[email protected]>

[None][infra] Check in most recent lock file from nightly pipeline

Signed-off-by: TensorRT LLM <[email protected]>

[TRTLLM-9706] [doc] Update wide EP documents (NVIDIA#9724)

Signed-off-by: Kaiyu Xie <[email protected]>

[https://nvbugs/5666804][test] only adding sampler config for limited models (NVIDIA#9512)

Signed-off-by: Ruodi Lu <[email protected]>
Co-authored-by: Ruodi Lu <[email protected]>
Co-authored-by: yufeiwu-nv <[email protected]>
Co-authored-by: Larry Xu <[email protected]>

[None][infra] Waive failed cases for main on 12/08 (NVIDIA#9773)

Signed-off-by: qqiao <[email protected]>

[None][chore] Move the rocketkv e2e test to post-merge (NVIDIA#9768)

Signed-off-by: Fanrong Li <[email protected]>

[None][chore] Enable tvm_ffi for cute dsl nvfp4_gemm to reduce host overhead. (NVIDIA#9690)

Signed-off-by: Mindy Li <[email protected]>

[TRTLLM-9431][perf] Enable multistream for Linear Attention in Qwen3-… (NVIDIA#9696)

Signed-off-by: nv-guomingz <[email protected]>

[None][chore] Remove closed bugs (NVIDIA#9770)

Signed-off-by: xinhe-nv <[email protected]>

[None][infra] update mooncake in docker images (NVIDIA#9584)

Signed-off-by: zhengd-nv <[email protected]>
Signed-off-by: Zheng Duan <[email protected]>

[None][test] Add Kimi k2 WIDEEP perf and accuracy cases (NVIDIA#9686)

Signed-off-by: FredricZ-2007 <[email protected]>
Signed-off-by: Kaiyu Xie <[email protected]>
Co-authored-by: Kaiyu Xie <[email protected]>

[https://nvbugs/5527655][test] Add test case for RCCA 5527655 (NVIDIA#9511)

Signed-off-by: FredricZ-2007 <[email protected]>

[http://nvbugs/5649010][fix] fix test_auto_scaling.py::test_worker_restart timeout (NVIDIA#9775)

Signed-off-by: Lizhi Zhou <[email protected]>

[None][fix] Switch AutoDeploy's default allreduce strategy to NCCL (NVIDIA#9666)

Signed-off-by: Eran Geva <[email protected]>

[TRTLLM-9506][fix] Fix AR for DeepSeek-R1 2 model path (NVIDIA#9661)

Signed-off-by: qgai <[email protected]>

ray + updatew works

trtllm works in async env

trtllm works in sync and async env

ray + updatew works

rebase to the updated verl

server mode

still cherry pick

still cherry pick

still cherry pick

integrated http interface

hang at RyExecutor create workers ray.remote

clean code

use tensorrt_llm.rlhf_utils

Signed-off-by: Liwei Ma <[email protected]>

placement, asyncllm, and basic tests
Signed-off-by: Erin Ho <[email protected]>

connect sleep and wakeup; Add support to pass None to update_weights
Signed-off-by: Erin Ho <[email protected]>

Batching ctx for IFB scheduler

Signed-off-by: Yuan Tong <[email protected]>

accuracy WAR for TP>1: always use AllReduceStrategy.NCCL, refactored
Signed-off-by: Erin Ho <[email protected]>

fix e2e integration

Signed-off-by: Superjomn <[email protected]>

update asyncllm, other nits
Signed-off-by: Erin Ho <[email protected]>

fix init setup

Signed-off-by: Erin Ho <[email protected]>

Fix TRTLLMSampler logprobs perf

Signed-off-by: Yuan Tong <[email protected]>

fix and cleanup
Signed-off-by: Erin Ho <[email protected]>

fix server

Signed-off-by: Erin Ho <[email protected]>

Revert "Batching ctx for IFB scheduler"

This reverts commit b51aac0

Signed-off-by: Yuan Tong <[email protected]>

update & address comments

Signed-off-by: Erin Ho <[email protected]>
usberkeley pushed a commit to usberkeley/TensorRT-LLM that referenced this pull request Dec 11, 2025
codego7250 pushed a commit to codego7250/TensorRT-LLM that referenced this pull request Dec 11, 2025
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