[None][feat] AutoDeploy: VLMs with subgraphs + cudagraph/compile #8203
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⚠️ Outside diff range comments (8)
tensorrt_llm/_torch/auto_deploy/transform/library/compile_model.py (1)
52-58: Do not passcompile_backendback into the backend ctor.
self.config.model_dump()still includescompile_backendeven though we already used it to choosecompiler_cls. Every backend constructor I checked (CompileBackendTorchSimple,CompileBackendTorchCompile, etc.) does not accept acompile_backendkeyword, so this call will raise aTypeError: __init__() got an unexpected keyword argument 'compile_backend'. Please exclude that field (e.g.,self.config.model_dump(exclude={"compile_backend"})) before splatting into the ctor.tensorrt_llm/_torch/auto_deploy/models/patches/pixtral.py (1)
112-121: Respect caller-providedreturn_dict.
Line 117 currently forcesreturn_dict=True, so callers requestingreturn_dict=False(or relying on the config default whenNone) now get a dict regardless, diverging from the Hugging Face contract. Please plumb the argument through instead of overriding it.@@ - out = self.transformer( + if return_dict is None: + return_dict = getattr(self.config, "use_return_dict", True) + + out = self.transformer( @@ - return_dict=True, + return_dict=return_dict,tensorrt_llm/_torch/auto_deploy/transform/library/load_weights.py (1)
1-1: Add NVIDIA Apache-2.0 header (2025) at file top.Required by repo guidelines. Add the standard header before the docstring.
As per coding guidelines
+# 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/auto_deploy/transform/library/kvcache_transformers.py (1)
1-1: Add NVIDIA Apache-2.0 header (2025) at file top.Required by repo guidelines.
As per coding guidelines
+# 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/auto_deploy/models/hf.py (1)
1-1: Add NVIDIA Apache-2.0 header (2025) at file top.Required by repo guidelines.
As per coding guidelines
+# 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/auto_deploy/custom_ops/attention_interface.py (1)
1-1: Add NVIDIA Apache-2.0 header (2025) at file top.Required by repo guidelines.
As per coding guidelines
+# 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/auto_deploy/transform/interface.py (1)
1-1: Add NVIDIA Apache-2.0 header (2025) at file top.Required by repo guidelines.
As per coding guidelines
+# 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/auto_deploy/transform/library/build_model.py (1)
1-1: Add NVIDIA Apache-2.0 header (compliance).File is missing the required NVIDIA Apache-2.0 header with current year.
As per coding guidelines, prepend:
+# 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.As per coding guidelines
🧹 Nitpick comments (13)
tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_mamba_cached_op.py (1)
186-186: Remove obsolete input_ids comment.Leftover commented code is noise now that the metadata path no longer consumes
input_ids. Please drop it to keep the fixture tight.- # input_ids = torch.randint(0, 1000, (b, s), device=device)tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_attention_op.py (1)
472-472: Trim the stale input_ids comment.Same as the mamba test, this commented line can go now that the signature no longer takes
input_ids.- # input_ids = torch.randint(0, 1000, (batch_size, seq_len_val), device=device)tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_quantization.py (1)
40-41: Silence the unused parameter warning.
modelisn’t used; rename it to_model(or similar) so Ruff stops flagging ARG002.Apply this diff:
- def get_export_infos(self, model: nn.Module) -> List[SubModuleExportInfo]: + def get_export_infos(self, _model: nn.Module) -> List[SubModuleExportInfo]:tensorrt_llm/_torch/auto_deploy/transform/library/load_weights.py (2)
39-45: Silence unused-arg warnings for cm/shared_config.Prefix with underscores to satisfy linters without behavioral change.
- def _apply_to_full_model( - self, - mod: nn.Module, - cm: CachedSequenceInterface, - factory: ModelFactory, - shared_config: SharedConfig, - ) -> Tuple[nn.Module, TransformInfo]: + def _apply_to_full_model( + self, + mod: nn.Module, + _cm: CachedSequenceInterface, + factory: ModelFactory, + _shared_config: SharedConfig, + ) -> Tuple[nn.Module, TransformInfo]:
46-51: Minor: avoid redundant move when devices match.If adconfig_checkpoint_device equals target device, the extra move_to_device is redundant. Optional micro-optimization.
tensorrt_llm/_torch/auto_deploy/transform/library/kvcache_transformers.py (1)
193-207: Add safety guard for missing_gmwhen using patched forward.Prevents obscure AttributeError if called before profiling step attaches
_gm.def forward_with_prepare_metadata(mod: nn.Module, **cm_kwargs): """Run prepare_metadata as pre-processing step, add to kwargs, and then run regular forward.""" - gm = mod._gm + assert hasattr(mod, "_gm"), "Expected `mod._gm` set by detection pass before cached forward." + gm = mod._gmtensorrt_llm/_torch/auto_deploy/models/hf.py (1)
453-455: Silence unused-arg warning in get_export_infos.Rename param to
_modelto match usage.- def get_export_infos(self, model: nn.Module) -> List[SubModuleExportInfo]: + def get_export_infos(self, _model: nn.Module) -> List[SubModuleExportInfo]:tensorrt_llm/_torch/auto_deploy/custom_ops/attention_interface.py (1)
270-275: Use tuple unpacking instead of concatenation.Slightly cleaner and matches ruff suggestion.
- return ("position_ids",) + self._cached_arg_names + return ("position_ids", *self._cached_arg_names)tensorrt_llm/_torch/auto_deploy/transform/interface.py (1)
342-351: Improve exception logging; keep skip-on-error behavior.Capture stack with ad_logger.exception for easier debugging.
- except Exception as e: - error_msg = f"Transform {t_name} failed" - ad_logger.warning(f"{error_msg}: {e}") + except Exception: + ad_logger.exception("Transform %s failed", t_name) info_apply = TransformInfo(skipped=True, num_matches=0)tensorrt_llm/_torch/auto_deploy/transform/library/export_to_gm.py (2)
51-56: Capture hook: support positional args and silence unused param.
- Current assert breaks if a submodule is invoked positionally.
- Inner hook param mod is unused (ARG001).
Refactor to normalize args→kwargs and avoid the assert.
- def _capture_kwargs(mod: nn.Module, args, kwargs) -> None: - assert not args, "positional arguments are not supported for capture" - captured_kwargs.clear() - captured_kwargs.update(kwargs) + def _capture_kwargs(_m: nn.Module, args, kwargs) -> None: + # Normalize positional + keyword args to kwargs using the callee's signature. + try: + sig = inspect.signature(_m.forward) + bound = sig.bind_partial(*args, **(kwargs or {})) + normalized = bound.arguments + except Exception: + # Fallback to raw kwargs if signature binding fails. + normalized = kwargs or {} + captured_kwargs.clear() + captured_kwargs.update(normalized) return None
161-164: Guard dynamic_shapes lookup to avoid KeyError.If a captured Tensor arg lacks an entry in dynamic_shape_lookup, this will KeyError.
- dynamic_shapes = { - k: e_info.dynamic_shape_lookup[k] if isinstance(v, torch.Tensor) else None - for k, v in captured_kwargs.items() - } + dynamic_shapes = { + k: (e_info.dynamic_shape_lookup.get(k) if isinstance(v, torch.Tensor) else None) + for k, v in captured_kwargs.items() + }Optionally log missing keys for visibility.
tensorrt_llm/_torch/auto_deploy/transform/library/build_model.py (2)
39-46: Silence unused parameters in signature.mod, cm, shared_config unused (ARG002). Rename to underscore to appease linters while keeping API.
- def _apply_to_full_model( - self, - mod: nn.Module, - cm: CachedSequenceInterface, - factory: ModelFactory, - shared_config: SharedConfig, - ) -> Tuple[nn.Module, TransformInfo]: + def _apply_to_full_model( + self, + _mod: nn.Module, + _cm: CachedSequenceInterface, + factory: ModelFactory, + _shared_config: SharedConfig, + ) -> Tuple[nn.Module, TransformInfo]:
68-75: Silence unused parameters in signature.Same here for mod and shared_config.
- def _apply_to_full_model( - self, - mod: nn.Module, - cm: CachedSequenceInterface, - factory: ModelFactory, - shared_config: SharedConfig, - ) -> Tuple[nn.Module, TransformInfo]: + def _apply_to_full_model( + self, + _mod: nn.Module, + cm: CachedSequenceInterface, + factory: ModelFactory, + _shared_config: SharedConfig, + ) -> Tuple[nn.Module, TransformInfo]:
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📒 Files selected for processing (43)
tensorrt_llm/_torch/auto_deploy/config/default.yaml(4 hunks)tensorrt_llm/_torch/auto_deploy/config/transformers.yaml(1 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/attention_interface.py(6 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/cuda_backend_causal_conv.py(2 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/flashinfer_attention.py(2 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/mla.py(2 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_attention.py(2 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_causal_conv.py(2 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_mamba.py(2 hunks)tensorrt_llm/_torch/auto_deploy/custom_ops/triton_attention.py(2 hunks)tensorrt_llm/_torch/auto_deploy/export/export.py(3 hunks)tensorrt_llm/_torch/auto_deploy/export/interface.py(2 hunks)tensorrt_llm/_torch/auto_deploy/models/__init__.py(1 hunks)tensorrt_llm/_torch/auto_deploy/models/factory.py(3 hunks)tensorrt_llm/_torch/auto_deploy/models/hf.py(8 hunks)tensorrt_llm/_torch/auto_deploy/models/mistral3.py(0 hunks)tensorrt_llm/_torch/auto_deploy/models/patches/llama4.py(4 hunks)tensorrt_llm/_torch/auto_deploy/models/patches/mistral3.py(3 hunks)tensorrt_llm/_torch/auto_deploy/models/patches/pixtral.py(5 hunks)tensorrt_llm/_torch/auto_deploy/models/patches/starcoder.py(1 hunks)tensorrt_llm/_torch/auto_deploy/shim/ad_executor.py(0 hunks)tensorrt_llm/_torch/auto_deploy/shim/interface.py(1 hunks)tensorrt_llm/_torch/auto_deploy/transform/interface.py(9 hunks)tensorrt_llm/_torch/auto_deploy/transform/library/build_model.py(3 hunks)tensorrt_llm/_torch/auto_deploy/transform/library/compile_model.py(3 hunks)tensorrt_llm/_torch/auto_deploy/transform/library/export_to_gm.py(3 hunks)tensorrt_llm/_torch/auto_deploy/transform/library/kvcache.py(5 hunks)tensorrt_llm/_torch/auto_deploy/transform/library/kvcache_transformers.py(6 hunks)tensorrt_llm/_torch/auto_deploy/transform/library/load_weights.py(3 hunks)tensorrt_llm/_torch/auto_deploy/transform/optimizer.py(1 hunks)tensorrt_llm/_torch/auto_deploy/transformations/_graph.py(6 hunks)tests/unittest/_torch/auto_deploy/_utils_test/_graph_test_helpers.py(2 hunks)tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py(1 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_cuda_causal_conv_cached_op.py(1 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_attention_op.py(2 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_causal_conv_cached_op.py(1 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_mamba_cached_op.py(1 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.py(2 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_mistral3.py(0 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_mistral3_patches.py(3 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py(2 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_kv_cache.py(3 hunks)tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_quantization.py(3 hunks)
💤 Files with no reviewable changes (3)
- tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_mistral3.py
- tensorrt_llm/_torch/auto_deploy/shim/ad_executor.py
- tensorrt_llm/_torch/auto_deploy/models/mistral3.py
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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:
tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_causal_conv_cached_op.pytensorrt_llm/_torch/auto_deploy/export/interface.pytests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_mistral3_patches.pytensorrt_llm/_torch/auto_deploy/models/patches/starcoder.pytests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_cuda_causal_conv_cached_op.pytensorrt_llm/_torch/auto_deploy/custom_ops/cuda_backend_causal_conv.pytensorrt_llm/_torch/auto_deploy/custom_ops/flashinfer_attention.pytests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_quantization.pytensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_causal_conv.pytests/unittest/_torch/auto_deploy/_utils_test/_graph_test_helpers.pytensorrt_llm/_torch/auto_deploy/transform/optimizer.pytests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.pytensorrt_llm/_torch/auto_deploy/transform/library/compile_model.pytensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_mamba.pytensorrt_llm/_torch/auto_deploy/shim/interface.pytests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.pytensorrt_llm/_torch/auto_deploy/transformations/_graph.pytensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_attention.pytensorrt_llm/_torch/auto_deploy/transform/library/export_to_gm.pytests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_kv_cache.pytests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.pytensorrt_llm/_torch/auto_deploy/custom_ops/mla.pytests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_attention_op.pytensorrt_llm/_torch/auto_deploy/models/patches/mistral3.pytensorrt_llm/_torch/auto_deploy/export/export.pytensorrt_llm/_torch/auto_deploy/models/patches/pixtral.pytensorrt_llm/_torch/auto_deploy/models/__init__.pytests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_mamba_cached_op.pytensorrt_llm/_torch/auto_deploy/transform/library/build_model.pytensorrt_llm/_torch/auto_deploy/transform/library/load_weights.pytensorrt_llm/_torch/auto_deploy/custom_ops/triton_attention.pytensorrt_llm/_torch/auto_deploy/transform/library/kvcache.pytensorrt_llm/_torch/auto_deploy/custom_ops/attention_interface.pytensorrt_llm/_torch/auto_deploy/models/hf.pytensorrt_llm/_torch/auto_deploy/transform/library/kvcache_transformers.pytensorrt_llm/_torch/auto_deploy/models/patches/llama4.pytensorrt_llm/_torch/auto_deploy/transform/interface.pytensorrt_llm/_torch/auto_deploy/models/factory.py
🧠 Learnings (1)
📚 Learning: 2025-08-06T03:47:16.802Z
Learnt from: venkywonka
PR: NVIDIA/TensorRT-LLM#6650
File: tests/integration/test_lists/qa/llm_perf_cluster.yml:33-37
Timestamp: 2025-08-06T03:47:16.802Z
Learning: Ministral is a valid model name from Mistral AI, distinct from the regular Mistral models. In TensorRT-LLM test configurations, "ministral_8b" and "ministral_8b_fp8" are correct model identifiers and should not be changed to "mistral_8b".
Applied to files:
tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py
🧬 Code graph analysis (30)
tensorrt_llm/_torch/auto_deploy/export/interface.py (4)
tensorrt_llm/llmapi/llm_args.py (1)
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tensorrt_llm/_torch/auto_deploy/custom_ops/mla.py (1)
tensorrt_llm/_torch/auto_deploy/custom_ops/attention_interface.py (2)
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tensorrt_llm/_torch/auto_deploy/models/patches/mistral3.py (1)
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PixtralVisionModel(170-256)
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ModelFactory(94-334)load_or_random_init(239-280)tensorrt_llm/_torch/auto_deploy/transformations/_graph.py (1)
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tensorrt_llm/_torch/auto_deploy/export/interface.py (4)
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tensorrt_llm/_torch/auto_deploy/transform/interface.py (5)
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get_export_infos(40-41)tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_quantization.py (1)
get_export_infos(40-41)
🪛 Ruff (0.13.3)
tensorrt_llm/_torch/auto_deploy/custom_ops/cuda_backend_causal_conv.py
83-83: Unused function argument: input_pos
(ARG001)
83-83: Unused function argument: cache_loc
(ARG001)
83-83: Unused function argument: pages_per_seq
(ARG001)
83-83: Unused function argument: page_size
(ARG001)
tensorrt_llm/_torch/auto_deploy/custom_ops/flashinfer_attention.py
216-216: Unused function argument: input_pos
(ARG001)
216-216: Unused function argument: pages_per_seq
(ARG001)
216-216: Unused function argument: slot_idx
(ARG001)
216-216: Unused function argument: page_size
(ARG001)
tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_quantization.py
40-40: Unused method argument: model
(ARG002)
tensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_causal_conv.py
169-169: Unused function argument: input_pos
(ARG001)
169-169: Unused function argument: cache_loc
(ARG001)
169-169: Unused function argument: pages_per_seq
(ARG001)
169-169: Unused function argument: page_size
(ARG001)
tests/unittest/_torch/auto_deploy/_utils_test/_graph_test_helpers.py
44-44: Unused method argument: model
(ARG002)
tensorrt_llm/_torch/auto_deploy/transform/library/compile_model.py
46-46: Unused method argument: factory
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47-47: Unused method argument: shared_config
(ARG002)
tensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_mamba.py
144-144: Unused function argument: input_pos
(ARG001)
144-144: Unused function argument: cache_loc
(ARG001)
144-144: Unused function argument: pages_per_seq
(ARG001)
144-144: Unused function argument: page_size
(ARG001)
tensorrt_llm/_torch/auto_deploy/custom_ops/torch_backend_attention.py
381-381: Unused function argument: pages_per_seq
(ARG001)
381-381: Unused function argument: slot_idx
(ARG001)
381-381: Unused function argument: page_size
(ARG001)
tensorrt_llm/_torch/auto_deploy/transform/library/export_to_gm.py
51-51: Unused function argument: mod
(ARG001)
85-85: Avoid specifying long messages outside the exception class
(TRY003)
130-130: Unused method argument: shared_config
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tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_kv_cache.py
40-40: Unused method argument: model
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tensorrt_llm/_torch/auto_deploy/custom_ops/mla.py
199-199: Unused function argument: position_ids
(ARG001)
199-199: Unused function argument: pages_per_seq
(ARG001)
199-199: Unused function argument: slot_idx
(ARG001)
199-199: Unused function argument: page_size
(ARG001)
tensorrt_llm/_torch/auto_deploy/models/patches/pixtral.py
59-59: Unused function argument: max_width
(ARG001)
tensorrt_llm/_torch/auto_deploy/transform/library/build_model.py
41-41: Unused method argument: mod
(ARG002)
42-42: Unused method argument: cm
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44-44: Unused method argument: shared_config
(ARG002)
70-70: Unused method argument: mod
(ARG002)
73-73: Unused method argument: shared_config
(ARG002)
tensorrt_llm/_torch/auto_deploy/transform/library/load_weights.py
42-42: Unused method argument: cm
(ARG002)
44-44: Unused method argument: shared_config
(ARG002)
71-71: Unused method argument: factory
(ARG002)
72-72: Unused method argument: shared_config
(ARG002)
tensorrt_llm/_torch/auto_deploy/custom_ops/triton_attention.py
311-311: Unused function argument: pages_per_seq
(ARG001)
311-311: Unused function argument: slot_idx
(ARG001)
311-311: Unused function argument: page_size
(ARG001)
tensorrt_llm/_torch/auto_deploy/transform/library/kvcache.py
246-246: Unused method argument: factory
(ARG002)
247-247: Unused method argument: shared_config
(ARG002)
323-323: Unused method argument: factory
(ARG002)
324-324: Unused method argument: shared_config
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tensorrt_llm/_torch/auto_deploy/custom_ops/attention_interface.py
274-274: Consider ("position_ids", *self._cached_arg_names) instead of concatenation
Replace with ("position_ids", *self._cached_arg_names)
(RUF005)
tensorrt_llm/_torch/auto_deploy/models/hf.py
453-453: Unused method argument: model
(ARG002)
508-508: Loop control variable embed_name not used within loop body
(B007)
512-515: Avoid specifying long messages outside the exception class
(TRY003)
560-563: Avoid specifying long messages outside the exception class
(TRY003)
tensorrt_llm/_torch/auto_deploy/transform/library/kvcache_transformers.py
114-114: Unused method argument: factory
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115-115: Unused method argument: shared_config
(ARG002)
tensorrt_llm/_torch/auto_deploy/transform/interface.py
346-346: Do not catch blind exception: Exception
(BLE001)
⏰ 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 (23)
tensorrt_llm/_torch/auto_deploy/models/patches/starcoder.py (1)
3-3: Comment update looks good.The added TODO note makes the removal condition explicit and keeps maintenance intent clear.
tensorrt_llm/_torch/auto_deploy/config/transformers.yaml (1)
9-31: LGTM! Consistent per-GM execution disablement.The addition of
run_per_gm: falseacross these transforms aligns with the broader migration toward full-model processing rather than per-graph-module subgraphs, as described in the PR objectives.tests/unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py (2)
75-78: LGTM! Enables torch-opt backend for Llama-4.This change aligns with the PR objective to add
torch-optsupport for llama4 models and removes the previous skip, expanding test coverage.
89-93: LGTM! Enables torch-cudagraph backend for Mistral.This change aligns with the PR objective to add
torch-cudagraphsupport for mistral3 models.tensorrt_llm/_torch/auto_deploy/export/export.py (3)
6-6: LGTM! Required import for new function signature.The
Callabletype is needed for thecapture_fnparameter in the newrun_forward_for_capturefunction.
198-250: LGTM! Well-designed abstraction for capture operations.The new
run_forward_for_capturefunction effectively extracts common logic for running capture operations with patches and meta device handling. The implementation is clean, well-documented, and provides good flexibility through thecapture_fnparameter.
288-297: LGTM! Clean refactoring with improved separation of concerns.The refactored
torch_export_to_gmnow delegates capture orchestration torun_forward_for_capturewhile keeping export-specific logic in the internal_capture_fnhelper. This improves code maintainability and reusability.tensorrt_llm/_torch/auto_deploy/transform/library/kvcache.py (3)
7-7: LGTM! Required import for nn.Module annotations.The import is necessary for the updated method signatures that use
nn.Moduleinstead ofGraphModule.
242-248: LGTM! Consistent interface migration to full-model processing.The method signature update from
_applywithGraphModuleto_apply_to_full_modelwithnn.Modulealigns with the broader migration toward full-model transformations described in the PR objectives.Note: The static analysis warnings about unused
factoryandshared_configparameters are expected, as these are required by theBaseTransforminterface signature (see relevant code snippets frominterface.py).
319-325: LGTM! Consistent interface migration.The
InitializeCachetransform follows the same interface pattern asResizeKVCache, consistently updating to full-model processing.tests/unittest/_torch/auto_deploy/unit/singlegpu/custom_ops/test_torch_causal_conv_cached_op.py (1)
171-188: LGTM! Test updated to reflect prepare_metadata API changes.The removal of
input_idsfrom thetorch_causal_conv_prepare_metadatacall aligns with the broader API refactor that shifts to usingposition_idsfor sequence-length sanitization, as indicated in the AI summary.tensorrt_llm/_torch/auto_deploy/models/__init__.py (1)
1-2: LGTM! Aligns with mistral3 deprecation.Removing
mistral3from the public exports is consistent with the broader de-emphasis of mistral3 support in this PR, including marking the mistral3 patch as disabled by default.tensorrt_llm/_torch/auto_deploy/models/patches/mistral3.py (2)
1-15: LGTM! Clear documentation of disabled patch status.The updated docstring and import clearly communicate that this patch is disabled by default and retained for potential future use. This aligns with the broader patch system changes introducing disabled patches.
167-169: LGTM! Consistent with disabled patch pattern.The change to inherit from
DisabledBaseExportPatchaligns with the broader patch system modernization, allowing the patch to remain registered while being disabled by default (consistent with similar changes inllama4.pyandpixtral.py).tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.py (2)
60-60: LGTM! Updated to new patch configuration API.The change from
patch_listtopatch_configswith an explicitenabledflag provides more flexible control over patch application and aligns with the modernized patch system introduced in this PR.
89-97: LGTM! Consistent patch configuration format.The migration to
patch_configsdictionary format with explicit configurations for each patch improves clarity and aligns with the updatedapply_export_patchesAPI that accepts patch configurations (see relevant code snippet frominterface.py).tests/unittest/_torch/auto_deploy/_utils_test/_graph_test_helpers.py (1)
13-17: Export-info override looks good.Thanks for wiring FakeFactory into the new export-info contract; this keeps the test helper compliant with ModelFactory’s abstract interface.
Also applies to: 44-46
tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_kv_cache.py (2)
1-16: DummyFactory export-info hook LGTM.Covering the abstract get_export_infos with FullModelExportInfo keeps these tests aligned with the factory API refresh. 👍
Also applies to: 40-42
175-183: run_per_gm flags acknowledged.Setting
run_per_gm=Falsefor the factory and export stages mirrors the new single-pass export flow, so no concerns here.tensorrt_llm/_torch/auto_deploy/custom_ops/flashinfer_attention.py (1)
176-177: Position-id based sanitization looks correct.Switching both real and fake paths to sanitize via
position_idskeeps flashinfer in sync with the rest of the metadata APIs. Looks good.Also applies to: 216-219
tensorrt_llm/_torch/auto_deploy/transform/library/kvcache_transformers.py (1)
124-128: Verifyprofiling_metadataplumbs through model.forward for all target models.Some HF model forwards may not expect/forward this kwarg; ensure tested on llama4, mistral3, Qwen2.5-VL.
tensorrt_llm/_torch/auto_deploy/transform/interface.py (1)
83-86: Confirm default run_per_gm=True matches intended full-model flow.Current default runs per-GraphModule; many transforms now implement _apply_to_full_model. Verify pipeline config overrides as expected.
tensorrt_llm/_torch/auto_deploy/transform/library/export_to_gm.py (1)
186-191: Remove version-compat fallback for set_submodule
torch.nn.Module.set_submodule is supported from PyTorch 2.6 onward; if your project requires ≥2.6, you can drop the getattr/setattr fallback.
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Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com>
Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com>
Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com>
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…DIA#8203) Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com>
4 participants
Summary by CodeRabbit
New Features
Breaking Changes
Deprecations/Removals
Description
Note: contains changes from #8157, Please only review final commit
torch-cudagraphandtorch-optfor VLMstorch-opt/torch-cudagraphfor llama4 + mistral3Qwen/Qwen2.5-VL-7B-Instructincluding opt/cudagraph. Was previously blocked on complex dynamism, see Support Qwen 2.5 VL nv-auto-deploy/TensorRT-LLM#127Test Coverage
PR Checklist
Please review the following before submitting your PR:
PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
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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