From d736c7f2908e69c47988108d7dff49770bf29719 Mon Sep 17 00:00:00 2001 From: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com> Date: Wed, 7 Jan 2026 20:16:53 -0500 Subject: [PATCH 01/16] [https://nvbugs/5761665][fix] AutoDeploy: handle bugs for 25.12 dlfw upgrade (#10511) Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com> --- .../auto_deploy/_utils_test/_model_test_utils.py | 4 ++-- .../unit/singlegpu/models/test_hybrid_patches.py | 9 ++++----- .../singlegpu/models/test_modeling_nemotron_h.py | 9 ++++----- .../library/test_attention_matcher.py | 16 ++++++++-------- .../library/test_attention_matcher_hf.py | 2 +- .../transformations/library/test_fuse_rmsnorm.py | 2 +- .../library/test_fused_add_rms_norm.py | 5 +++-- .../library/test_gather_logits_before_lm_head.py | 2 +- .../library/test_rope_transformation.py | 4 ++-- .../singlegpu/transformations/test_export.py | 10 +++++----- 10 files changed, 31 insertions(+), 32 deletions(-) diff --git a/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py b/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py index af821955d4..5adb8e5a73 100644 --- a/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py +++ b/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py @@ -278,8 +278,8 @@ class FakeFP8Linear(nn.Linear): def generate_dynamic_shapes(max_batch_size, max_seq_len): dynamic_shapes = ( { - 0: Dim("batch_size", max=max_batch_size), - 1: Dim("seq_len", max=max_seq_len), + 0: Dim.DYNAMIC, + 1: Dim.DYNAMIC, }, ) return dynamic_shapes diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_hybrid_patches.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_hybrid_patches.py index 6ea5c0efa1..430add5a28 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_hybrid_patches.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_hybrid_patches.py @@ -72,12 +72,11 @@ def test_bamba_patches( position_ids = torch.arange(input_ids.shape[1], device=input_ids.device).repeat( input_ids.shape[0], 1 ) + batch_size_dynamic = Dim.DYNAMIC + seq_len_dynamic = Dim.DYNAMIC dynamic_shapes = ( - {0: Dim("batch_size", min=0, max=8), 1: Dim("seq_len", min=0, max=512)}, - { - 0: Dim("batch_size", min=0, max=8), - 1: Dim("seq_len", min=0, max=512), - }, + {0: batch_size_dynamic, 1: seq_len_dynamic}, + {0: batch_size_dynamic, 1: seq_len_dynamic}, ) def _run_torch_export_to_gm(): diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_modeling_nemotron_h.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_modeling_nemotron_h.py index 94b22ed14f..d5d624e721 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_modeling_nemotron_h.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/models/test_modeling_nemotron_h.py @@ -184,12 +184,11 @@ def test_custom_model_implementation_can_be_exported( position_ids = torch.arange(input_ids.shape[1], device=input_ids.device).repeat( input_ids.shape[0], 1 ) + batch_size_dynamic = Dim.DYNAMIC + seq_len_dynamic = Dim.DYNAMIC dynamic_shapes = ( - {0: Dim("batch_size", min=0, max=8), 1: Dim("seq_len", min=0, max=512)}, - { - 0: Dim("batch_size", min=0, max=8), - 1: Dim("seq_len", min=0, max=512), - }, + {0: batch_size_dynamic, 1: seq_len_dynamic}, + {0: batch_size_dynamic, 1: seq_len_dynamic}, ) def _run_torch_export_to_gm(): diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher.py index c3b1830317..40a331025a 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher.py @@ -84,7 +84,7 @@ class RepeatKVModel(torch.nn.Module): return output def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} class RepeatKVModel2(RepeatKVModel): @@ -185,7 +185,7 @@ class EagerAttentionModel(torch.nn.Module): return output def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} class ComplexEagerAttentionModel(torch.nn.Module): @@ -274,7 +274,7 @@ class ComplexEagerAttentionModel(torch.nn.Module): return output def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} class CounterExampleModel(torch.nn.Module): @@ -329,7 +329,7 @@ class CounterExampleModel(torch.nn.Module): return features_case1 def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} class GroupedAttentionModel(torch.nn.Module): @@ -403,7 +403,7 @@ class GroupedAttentionModel(torch.nn.Module): return output def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} def _get_match_repeat_kv_optimizer() -> Callable: @@ -907,7 +907,7 @@ class CausalAttentionModel(torch.nn.Module): return output def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} class Llama3CausalAttentionModel(torch.nn.Module): @@ -1013,7 +1013,7 @@ class Llama3CausalAttentionModel(torch.nn.Module): return output def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} class AttentionLayoutModel(torch.nn.Module): @@ -1102,7 +1102,7 @@ class AttentionLayoutModel(torch.nn.Module): return output def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=4, max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} class BsndAttentionModel(AttentionLayoutModel): diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher_hf.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher_hf.py index 3ae7775c6a..661f1863ee 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher_hf.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_attention_matcher_hf.py @@ -117,7 +117,7 @@ def test_match_llama_attention(config: Dict[str, Any], attn_implementation: str) "attn_implementation": attn_implementation, **config, } - dynamic_shapes = {0: Dim("batch_size", max=8), 1: Dim("seq_len", min=2, max=8)} + dynamic_shapes = {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} # Build and export model on meta device with init_empty_weights(): diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fuse_rmsnorm.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fuse_rmsnorm.py index fe88a866f5..d354f9d50f 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fuse_rmsnorm.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fuse_rmsnorm.py @@ -59,7 +59,7 @@ def _run_test(model, op, variant): return any(is_op(n, op) for n in gm.graph.nodes) x = torch.randn(2, 1024, device="cuda", dtype=torch.float16) - dynamic_shapes = {0: Dim("batch_size", max=8)} + dynamic_shapes = {0: Dim.DYNAMIC} gm = torch_export_to_gm(model, args=(x,), dynamic_shapes=(dynamic_shapes,), clone=True) gm_transformed = InferenceOptimizer( None, diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fused_add_rms_norm.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fused_add_rms_norm.py index 8cfb59756a..6926e980c9 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fused_add_rms_norm.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_fused_add_rms_norm.py @@ -37,8 +37,9 @@ def _run_test(model): residual = torch.randn(bsz, seq_len, hidden, device="cuda", dtype=torch.bfloat16) # Dynamic shapes - ds_x = {0: Dim("batch_size", max=8)} - ds_res = {0: Dim("batch_size", max=8)} + dyn_batch_size = Dim.DYNAMIC + ds_x = {0: dyn_batch_size} + ds_res = {0: dyn_batch_size} gm = torch_export_to_gm(model, args=(x, residual), dynamic_shapes=(ds_x, ds_res), clone=True) diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_gather_logits_before_lm_head.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_gather_logits_before_lm_head.py index 42cd57752c..abf5d6e1d5 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_gather_logits_before_lm_head.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_gather_logits_before_lm_head.py @@ -189,7 +189,7 @@ class TestGatherLogitsBeforeLmHeadTransform: else: # dynamic_shapes should be a tuple matching the number of positional args dynamic_shapes = ( - {0: Dim("batch_size", min=1, max=max_batch_size)}, # hidden_states + {0: Dim.DYNAMIC}, # hidden_states None, # logit_gather_ids (static) None, # seq_len (static) ) diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_rope_transformation.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_rope_transformation.py index ffa2c0ccd8..291cd377bd 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_rope_transformation.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/library/test_rope_transformation.py @@ -135,7 +135,7 @@ class RoPEModel(torch.nn.Module): return out.to(torch.float16) if self.mode == "match" else out def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} @pytest.mark.parametrize( @@ -387,7 +387,7 @@ class DSModel(torch.nn.Module): return torch.cat([q_out, k_out], dim=-1) def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=8), 1: Dim("seq_len", max=16)} + return {0: Dim.DYNAMIC, 1: Dim.DYNAMIC} @pytest.mark.parametrize( diff --git a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/test_export.py b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/test_export.py index 3c28697f3b..7a5b5e2446 100644 --- a/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/test_export.py +++ b/tests/unittest/_torch/auto_deploy/unit/singlegpu/transformations/test_export.py @@ -47,7 +47,7 @@ class MLPForExport(ModuleForExport): return torch.randn(2, 10) def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=100)} + return {0: Dim.DYNAMIC} class MLPDuplicate(ModuleForExport): @@ -72,7 +72,7 @@ class MLPDuplicate(ModuleForExport): return {"fc3.weight"} def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=100)} + return {0: Dim.DYNAMIC} class ModuleWithWhere(ModuleForExport): @@ -90,7 +90,7 @@ class ModuleWithWhere(ModuleForExport): return torch.randn(2, 10) def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=100)} + return {0: Dim.DYNAMIC} def check_xfail(self, f_export, use_dynamic_shape, device) -> bool: return ( @@ -129,7 +129,7 @@ class ModuleWithRouting(ModuleForExport): return torch.randn(self.seq_len, self.num_experts) def get_dynamic_shapes(self): - return {0: Dim("seq_len", max=100)} + return {0: Dim.DYNAMIC} def check_xfail(self, f_export, use_dynamic_shape, device) -> bool: return ( @@ -153,7 +153,7 @@ class ModuleWithModuleList(ModuleForExport): return torch.randn(2, 10, device=self.fcs[0].weight.device) def get_dynamic_shapes(self): - return {0: Dim("batch_size", max=100)} + return {0: Dim.DYNAMIC} def check_xfail(self, f_export, use_dynamic_shape, device) -> bool: # non-strict mode only works with our hack in torch_export_to_gm From 81f878c2793693a788550e63641ba0b31abf6f97 Mon Sep 17 00:00:00 2001 From: xxi <95731198+xxi-nv@users.noreply.github.com> Date: Thu, 8 Jan 2026 09:17:59 +0800 Subject: [PATCH 02/16] [https://nvbugs/5707392][fix] unwaive test_fused_moe_fp8_blockwise_wide_ep[NotEnabled] (#10428) Signed-off-by: xxi --- tests/integration/test_lists/waives.txt | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt index a71d0475c0..f211cdb1fd 100644 --- a/tests/integration/test_lists/waives.txt +++ b/tests/integration/test_lists/waives.txt @@ -370,7 +370,6 @@ accuracy/test_llm_api_pytorch_multimodal.py::TestQwen2_5_VL_7B::test_auto_dtype accuracy/test_llm_api_pytorch_multimodal.py::TestLlava_V1_6_Mistral_7B::test_auto_dtype SKIP (https://nvbugs/5707087) accuracy/test_llm_api_pytorch_multimodal.py::TestPhi4MMFusedVisionLora::test_auto_dtype SKIP (https://nvbugs/5707087) disaggregated/test_disaggregated.py::test_disaggregated_ctxtp2pp2_gentp2pp2[TinyLlama-1.1B-Chat-v1.0] SKIP (https://nvbugs/5705199) -unittest/_torch/modules/test_fused_moe.py::test_fused_moe_fp8_blockwise_wide_ep[NotEnabled] SKIP (https://nvbugs/5707392) accuracy/test_llm_api_pytorch.py::TestLlama3_3NemotronSuper49Bv1::test_auto_dtype_tp2 SKIP (https://nvbugs/5707145) accuracy/test_llm_api_pytorch.py::TestLlama3_3NemotronSuper49Bv1::test_fp8_prequantized_tp2 SKIP (https://nvbugs/5707145) accuracy/test_llm_api_pytorch.py::TestNemotronH_56B_Base::test_auto_dtype[tp8-cuda_graph=True] SKIP (https://nvbugs/5640697) From 09d9878385a7ac52c11491e6981d9f98a326449d Mon Sep 17 00:00:00 2001 From: Yukun He <23156053+hyukn@users.noreply.github.com> Date: Thu, 8 Jan 2026 10:21:02 +0800 Subject: [PATCH 03/16] [TRTLLM-9661][chore] Further reduce tuning time for cuteDSL nvFP4 dense gemm. (#10339) Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com> --- .../_torch/custom_ops/cute_dsl_custom_ops.py | 35 +++++++++++++------ 1 file changed, 25 insertions(+), 10 deletions(-) diff --git a/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py b/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py index ae61e2b64c..771e7ed7c8 100644 --- a/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py +++ b/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py @@ -6,7 +6,7 @@ import torch from tensorrt_llm.logger import logger from ..._utils import get_sm_version -from ...math_utils import pad_up +from ...math_utils import ceil_div, pad_up from ..autotuner import (AutoTuner, ConstraintSpec, DistributedTuningStrategy, DynamicTensorSpec, OptimizationProfile, TunableRunner, TuningConfig) @@ -314,6 +314,16 @@ class GatherGroupedGemmInputsHelper(GroupedGemmInputsHelper): num_non_exiting_tiles, global_sf) +def get_dense_gemm_approximate_cta_nums( + M: int, N: int, tile_mn: Tuple[int, int], + cluster_shape_mn: Tuple[int, int]) -> int: + tile_m, tile_n = tile_mn + cluster_m, cluster_n = cluster_shape_mn + clustered_ctas_m = pad_up(ceil_div(M, tile_m), cluster_m) + clustered_ctas_n = pad_up(ceil_div(N, tile_n), cluster_n) + return clustered_ctas_m * clustered_ctas_n + + if IS_CUTLASS_DSL_AVAILABLE: import cutlass @@ -360,15 +370,6 @@ if IS_CUTLASS_DSL_AVAILABLE: def unique_id(self): return (self.output_dtype, self.to_userbuffers, self.use_tvm_ffi) - def __hash__(self): - return hash( - (self.output_dtype, self.to_userbuffers, self.use_tvm_ffi)) - - def __eq__(self, other): - if not isinstance(other, self.__class__): - return False - return self.output_dtype == other.output_dtype and self.to_userbuffers == other.to_userbuffers and self.use_tvm_ffi == other.use_tvm_ffi - def get_valid_tactics( self, inputs: List[torch.Tensor], @@ -454,6 +455,7 @@ if IS_CUTLASS_DSL_AVAILABLE: (4, 4), ] swap_ab_candidates = [True, False] + # prune: prefetch is beneficial only when K is large enough use_prefetch_candidates = [True, False] valid_tactics = [] @@ -484,6 +486,19 @@ if IS_CUTLASS_DSL_AVAILABLE: b_major, c_major, ): + # Prefetch pruning to save tuning time + cta_nums = get_dense_gemm_approximate_cta_nums( + m, n, mma_tiler_mn, cluster_shape_mn) + cta_wave_ratio = cta_nums / torch.cuda.get_device_properties( + ).multi_processor_count + if use_prefetch and not any(( + # CTA waves ratio between 0.5 and 1.0 + 0.5 < cta_wave_ratio < 1.0, + # K is large enough + real_k >= 8192, + )): + continue + valid_tactics.append( (mma_tiler_mn, cluster_shape_mn, swap_ab, use_prefetch)) From b85c447ceb1ff91c5d4df6b71de2256a5fabfe9d Mon Sep 17 00:00:00 2001 From: Yuxian Qiu <142763828+yuxianq@users.noreply.github.com> Date: Thu, 8 Jan 2026 10:32:50 +0800 Subject: [PATCH 04/16] [https://nvbugs/5784543][fix] Setup dist before using autotuner. (#10491) Signed-off-by: Yuxian Qiu <142763828+yuxianq@users.noreply.github.com> --- tests/unittest/_torch/modules/test_fused_moe.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/tests/unittest/_torch/modules/test_fused_moe.py b/tests/unittest/_torch/modules/test_fused_moe.py index 5a0b641f1b..29be45b8fd 100644 --- a/tests/unittest/_torch/modules/test_fused_moe.py +++ b/tests/unittest/_torch/modules/test_fused_moe.py @@ -24,6 +24,7 @@ from utils.util import (check_accuracy, skip_blackwell, skip_blackwell_geforce, skip_pre_hopper) from tensorrt_llm._torch.autotuner import AutoTuner, autotune +from tensorrt_llm._torch.distributed import MPIDist, TorchDist from tensorrt_llm._torch.model_config import ModelConfig from tensorrt_llm._torch.modules.fused_moe.fused_moe_cute_dsl import \ CuteDslFusedMoE @@ -44,7 +45,7 @@ from tensorrt_llm._torch.modules.fused_moe.quantization import \ from tensorrt_llm._torch.modules.fused_moe.fused_moe_triton import \ IS_TRITON_KERNELS_AVAILABLE from tensorrt_llm._torch.modules.gated_mlp import GatedMLP -from tensorrt_llm._utils import get_sm_version, mpi_rank +from tensorrt_llm._utils import get_sm_version, mpi_disabled, mpi_rank from tensorrt_llm.mapping import Mapping from tensorrt_llm.models.modeling_utils import QuantAlgo, QuantConfig @@ -104,6 +105,12 @@ def test_fused_moe(moe_backend, mapping = mapping or Mapping() mapping.rank = mpi_rank() + if mpi_disabled(): + dist = TorchDist(mapping=mapping) + else: + dist = MPIDist(mapping=mapping) + + AutoTuner.get().setup_distributed_state(mapping, dist) torch.cuda.set_device(mapping.rank) From f8b2a8fd30ca22cc464d7192e7bf2cd481d3800e Mon Sep 17 00:00:00 2001 From: yingguo-trt <244492186+yingguo-trt@users.noreply.github.com> Date: Thu, 8 Jan 2026 10:51:36 +0800 Subject: [PATCH 05/16] [None][chore] Support multiple job submission at the same time (#10492) Signed-off-by: FredricZ-2007 <226039983+fredricz-20070104@users.noreply.github.com> Co-authored-by: FredricZ-2007 <226039983+fredricz-20070104@users.noreply.github.com> --- tests/integration/defs/perf/disagg/README.md | 145 ++++++++++++- .../integration/defs/perf/disagg/conftest.py | 193 +++++++++++++++++- .../defs/perf/disagg/execution/executor.py | 4 +- .../perf/disagg/execution/subprocess_utils.py | 19 +- .../defs/perf/disagg/test_disagg.py | 39 ++-- 5 files changed, 365 insertions(+), 35 deletions(-) diff --git a/tests/integration/defs/perf/disagg/README.md b/tests/integration/defs/perf/disagg/README.md index 28ba839c6e..5921900b70 100644 --- a/tests/integration/defs/perf/disagg/README.md +++ b/tests/integration/defs/perf/disagg/README.md @@ -132,6 +132,141 @@ poetry run pytest --disagg test_disagg.py -s -vv -m accuracy poetry run pytest --disagg test_disagg.py -s -vv -k "deepseek-r1-fp4_1k1k" ``` +## Batch Job Submission + +The framework supports automatic batch job submission to maximize parallelism in SLURM cluster environments. Instead of submitting jobs one-by-one, it groups test cases into batches and submits entire batches when needed. + +### Quick Start + +**Default batch size (5 jobs per batch):** +```bash +# Run all tests with default batching +poetry run pytest --disagg test_disagg.py -s -vv + +# Run with test list +poetry run pytest --disagg test_disagg.py -s -vv --disagg-test-list=./testlist/all.txt +``` + +**Custom batch size:** +```bash +# Set batch size via command line +poetry run pytest --disagg test_disagg.py -s -vv --disagg-batch-size=10 + +# Set batch size via environment variable +export DISAGG_BATCH_SIZE=20 +poetry run pytest --disagg test_disagg.py -s -vv + +# Submit all jobs at once (unlimited batch) +poetry run pytest --disagg test_disagg.py -s -vv --disagg-batch-size=0 +``` + +### How Batch Submission Works + +``` +Pytest Collection Phase: + - Collects all test cases (e.g., 100 tests) + - BatchManager splits them into batches (e.g., 20 batches of 5) + +Pytest Execution Phase: + Test 0 runs: + -> Triggers submission of Batch 0 (jobs 0-4) + -> Waits for job 0 to complete + + Test 1-4 run: + -> Batch 0 already submitted, directly wait for completion + + Test 5 runs: + -> Triggers submission of Batch 1 (jobs 5-9) + -> Waits for job 5 to complete + + ... and so on +``` + +### Key Benefits + +- **Parallel Execution**: All jobs in a batch run simultaneously on SLURM cluster +- **Reduced Wait Time**: Total time ≈ MAX(job time) instead of SUM(job times) +- **Automatic Management**: No need to manually split test lists +- **Lazy Loading**: Only submits batches when needed + +### Configuration Options + +**Priority**: Command line option > Environment variable > Default (5) + +**Examples:** + +```bash +# Small batch for quick testing +poetry run pytest --disagg test_disagg.py -s -vv --disagg-batch-size=3 \ + --disagg-test-list=./testlist/debug.txt + +# Large batch for production +poetry run pytest --disagg test_disagg.py -s -vv --disagg-batch-size=50 \ + --disagg-test-list=./testlist/all.txt + +# Submit all at once +poetry run pytest --disagg test_disagg.py -s -vv --disagg-batch-size=0 +``` + +### Timeout Configuration + +The default timeout for waiting for job completion is **10 hours (36000 seconds)**, which accounts for: +- SLURM queue wait time +- Job execution time +- Buffer for delays + +### Performance Comparison + +**Before (Sequential Submission):** +``` +Case 1: submit + wait (1.5h) = 1.5h +Case 2: submit + wait (1.5h) = 1.5h +Case 3: submit + wait (1.5h) = 1.5h +... +Total: 50 × 1.5h = 75 hours +``` + +**After (Batch Submission, batch_size=50):** +``` +Batch 0 (50 jobs): submitted in parallel + Case 1: wait (1.5h) + Case 2-50: wait (0s, already done) + +Total: ~1.5 hours +``` + +**Speedup: 50x** + +### Troubleshooting + +**Check BatchManager initialization:** +``` +====================================================================== +Batch Manager Initialized +Batch size: 5 jobs per batch +====================================================================== + +Total test configs: 20 +Total batches: 4 +``` + +**Monitor batch submission:** +``` +====================================================================== +Submitting Batch 0 +Range: [0:5] (5 jobs) +====================================================================== + + [ 1/5] Job 1234 <- test_config_id_1 + [ 2/5] Job 1235 <- test_config_id_2 + ... +``` + +**If jobs timeout frequently:** +- Check SLURM queue status +- Consider reducing batch size to avoid resource contention +- Verify that timeout (36000s) is sufficient for your workload + ## Test Naming Convention Tests are automatically named using the format: @@ -193,6 +328,7 @@ Test results are saved to: - `GPU_TYPE`: Current GPU type (default: GB200) - `OUTPUT_PATH`: Directory for test results and logs - `WORK_DIR`: Working directory for benchmark execution +- `DISAGG_BATCH_SIZE`: Default batch size for job submission (default: 5) - `DEBUG_MODE`: Enable debug mode (set to "1" to skip job submission) - `DEBUG_JOB_ID`: Job ID to use in debug mode @@ -212,10 +348,11 @@ The framework consists of: 1. **ConfigLoader**: Scans and loads YAML configurations 2. **ConfigValidator**: Validates configuration correctness -3. **JobManager**: Handles SLURM job submission and monitoring -4. **LogParser**: Extracts metrics from benchmark logs -5. **TestCaseTracker**: Tracks test execution timing -6. **ResultSaver**: Saves results to CSV +3. **BatchManager**: Manages batch job submission for parallel execution +4. **JobManager**: Handles SLURM job submission and monitoring +5. **LogParser**: Extracts metrics from benchmark logs +6. **TestCaseTracker**: Tracks test execution timing +7. **ResultSaver**: Saves results to CSV ## Benefits diff --git a/tests/integration/defs/perf/disagg/conftest.py b/tests/integration/defs/perf/disagg/conftest.py index 2dabeda1cd..a4b88542df 100644 --- a/tests/integration/defs/perf/disagg/conftest.py +++ b/tests/integration/defs/perf/disagg/conftest.py @@ -1,9 +1,11 @@ """Pytest configuration for disagg tests. Only collects tests in this directory when --disagg parameter is provided. -Can share options like --disagg-test-list defined in this conftest.py. +Provides batch job submission capability to improve parallelism. """ +import os + import pytest from utils.logger import logger @@ -23,6 +25,15 @@ def pytest_addoption(parser): help="Path to a file containing test IDs (one per line) to run. " "Example: pytest --disagg --disagg-test-list=testlist/testlist_gb200.txt", ) + parser.addoption( + "--disagg-batch-size", + action="store", + type=int, + default=None, + help="Number of jobs to submit per batch. Default: from env DISAGG_BATCH_SIZE or 5. " + "Set to 0 for unlimited (submit all at once). " + "Example: pytest --disagg --disagg-batch-size=10", + ) def pytest_collect_directory(path, parent): @@ -45,7 +56,6 @@ def pytest_collect_directory(path, parent): return True # With --disagg parameter, proceed with normal collection - # Can subsequently use --disagg-test-list and other options from main conftest.py for filtering return None @@ -88,7 +98,7 @@ def pytest_collection_modifyitems(config, items): for item in items: # item.nodeid is the full test identifier like: - # "test_disagg_simple.py::TestDisaggBenchmark::test_benchmark[deepseek-r1-fp4:1k1k:...]" + # "test_disagg.py::TestDisaggBenchmark::test_benchmark[deepseek-r1-fp4:1k1k:...]" if item.nodeid in wanted_tests: selected.append(item) else: @@ -112,3 +122,180 @@ def pytest_collection_modifyitems(config, items): logger.warning(f"Please check that the test IDs in {test_list_file} are correct.") logger.info(f"{'=' * 70}\n") + + +class BatchManager: + """Batch job submission manager for disagg tests. + + Automatically splits test cases into batches and submits them on-demand + to maximize parallelism in SLURM cluster environments. + + Key features: + - Lazy batch submission: only submits when needed + - Configurable batch size via CLI or environment variable + - Maintains job_id mapping for all submitted jobs + """ + + def __init__(self, batch_size=5): + """Initialize batch manager. + + Args: + batch_size: Number of jobs per batch. None or 0 means unlimited (submit all at once). + Default is 5 if not specified. + """ + # Normalize batch_size: None, 0, or negative means unlimited + if batch_size is None or batch_size <= 0: + self.batch_size = None + else: + self.batch_size = batch_size + + self.submitted_batches = set() # Track which batch numbers have been submitted + self.job_mapping = {} # Map test_id -> SLURM job_id + self.all_configs = [] # Ordered list of all test configs + + logger.info(f"\n{'=' * 70}") + logger.info("Batch Manager Initialized") + if self.batch_size: + logger.info(f"Batch size: {self.batch_size} jobs per batch") + else: + logger.info("Batch size: unlimited (submit all at once)") + logger.info(f"{'=' * 70}\n") + + def add_config(self, test_config): + """Add a test configuration to the manager. + + Called during initialization to build the ordered list of configs. + + Args: + test_config: TestConfig object to add + """ + self.all_configs.append(test_config) + + def get_job_id(self, test_config): + """Get SLURM job ID for a test config, submitting batch if needed. + + This is the main entry point. It: + 1. Determines which batch the test belongs to + 2. Submits the entire batch if not already submitted + 3. Returns the job_id for this specific test + + Args: + test_config: TestConfig object to get job_id for + + Returns: + str: SLURM job ID, or None if submission failed + """ + # Find the index of this config in the ordered list + try: + idx = next( + i for i, c in enumerate(self.all_configs) if c.test_id == test_config.test_id + ) + except StopIteration: + logger.error(f"Config not found in manager: {test_config.test_id}") + return None + + # Calculate which batch this test belongs to + if self.batch_size: + batch_num = idx // self.batch_size + else: + batch_num = 0 # All tests in one batch + + # Submit the batch if not already submitted + if batch_num not in self.submitted_batches: + self._submit_batch(batch_num) + + # Return the cached job_id + return self.job_mapping.get(test_config.test_id) + + def _submit_batch(self, batch_num): + """Submit all jobs in a specific batch. + + Args: + batch_num: Batch number to submit (0-indexed) + """ + from execution.executor import JobManager + + # Calculate batch range + if self.batch_size: + start_idx = batch_num * self.batch_size + end_idx = min(start_idx + self.batch_size, len(self.all_configs)) + else: + start_idx = 0 + end_idx = len(self.all_configs) + + batch_configs = self.all_configs[start_idx:end_idx] + + logger.info(f"\n{'=' * 70}") + logger.info(f"Submitting Batch {batch_num}") + logger.info(f"Range: [{start_idx}:{end_idx}] ({len(batch_configs)} jobs)") + logger.info(f"{'=' * 70}\n") + + # Submit all jobs in this batch + success_count = 0 + for i, config in enumerate(batch_configs, 1): + try: + success, job_id = JobManager.submit_test_job(config) + if success and job_id: + self.job_mapping[config.test_id] = job_id + success_count += 1 + # Truncate test_id for display + display_id = ( + config.test_id[:60] + "..." if len(config.test_id) > 60 else config.test_id + ) + logger.success(f" [{i:3d}/{len(batch_configs)}] Job {job_id} <- {display_id}") + else: + self.job_mapping[config.test_id] = None + logger.error(f" [{i:3d}/{len(batch_configs)}] Failed: {config.test_id[:50]}") + except Exception as e: + self.job_mapping[config.test_id] = None + logger.error(f" [{i:3d}/{len(batch_configs)}] Error: {e}") + + # Mark batch as submitted + self.submitted_batches.add(batch_num) + + logger.info(f"\n{'=' * 70}") + logger.success( + f"Batch {batch_num} Complete: {success_count}/{len(batch_configs)} succeeded" + ) + logger.info(f"{'=' * 70}\n") + + +@pytest.fixture(scope="session") +def batch_manager(request): + """Provide batch manager fixture for test methods. + + This session-scoped fixture creates and initializes the BatchManager + with all collected test configs. + + Returns: + BatchManager: Initialized batch manager instance + """ + # Get batch size from CLI option or environment variable + batch_size = request.config.getoption("--disagg-batch-size") + if batch_size is None: + env_batch_size = os.getenv("DISAGG_BATCH_SIZE") + if env_batch_size: + try: + batch_size = int(env_batch_size) + except ValueError: + logger.warning(f"Invalid DISAGG_BATCH_SIZE: {env_batch_size}, using default 5") + batch_size = 5 + else: + batch_size = 5 # Default batch size + + # Create batch manager + manager = BatchManager(batch_size=batch_size) + + # Extract all test configs from collected items + for item in request.session.items: + if hasattr(item, "callspec") and "test_config" in item.callspec.params: + manager.add_config(item.callspec.params["test_config"]) + + # Log statistics + logger.info(f"Total test configs: {len(manager.all_configs)}") + if manager.batch_size: + total_batches = (len(manager.all_configs) + manager.batch_size - 1) // manager.batch_size + logger.info(f"Total batches: {total_batches}") + logger.info("") + + return manager diff --git a/tests/integration/defs/perf/disagg/execution/executor.py b/tests/integration/defs/perf/disagg/execution/executor.py index d454765c53..547b63aa8c 100644 --- a/tests/integration/defs/perf/disagg/execution/executor.py +++ b/tests/integration/defs/perf/disagg/execution/executor.py @@ -114,7 +114,9 @@ class JobManager: logger.debug(f"Script: {script_path}") logger.debug(f"Log file: {output_log_file}") - output = exec_cmd_with_output(sbatch_args, timeout=60) + # Use check=False to allow submission even with Kerberos warnings + # (mimics submit.py behavior) + output = exec_cmd_with_output(sbatch_args, timeout=60, check=False) job_id = output.strip() # Parse job ID (--parsable returns just the job ID) diff --git a/tests/integration/defs/perf/disagg/execution/subprocess_utils.py b/tests/integration/defs/perf/disagg/execution/subprocess_utils.py index 9ab7771426..39a3f0ac4b 100644 --- a/tests/integration/defs/perf/disagg/execution/subprocess_utils.py +++ b/tests/integration/defs/perf/disagg/execution/subprocess_utils.py @@ -33,19 +33,22 @@ def exec_cmd(*popenargs, timeout: Optional[float] = None, **kwargs) -> int: return result.returncode -def exec_cmd_with_output(*popenargs, timeout: Optional[float] = None, **kwargs) -> str: +def exec_cmd_with_output( + *popenargs, timeout: Optional[float] = None, check: bool = True, **kwargs +) -> str: """Execute command and return output as string. Args: *popenargs: Command and arguments timeout: Timeout in seconds + check: If True, raise CalledProcessError on non-zero exit code (default: True) **kwargs: Additional subprocess arguments Returns: stdout as string (decoded from bytes) Raises: - subprocess.CalledProcessError: If command returns non-zero exit code + subprocess.CalledProcessError: If check=True and command returns non-zero exit code subprocess.TimeoutExpired: If timeout is reached """ result = subprocess.run( @@ -53,11 +56,15 @@ def exec_cmd_with_output(*popenargs, timeout: Optional[float] = None, **kwargs) stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=timeout, - check=True, + check=check, **kwargs, ) - # Log stderr if it exists + # Log stderr if it exists (as warning if check=False, as error if check=True) if result.stderr: - stderr_output = result.stderr.decode() - logger.error(f"Command stderr: {stderr_output}") + stderr_output = result.stderr.decode().strip() + if stderr_output: + if check: + logger.error(f"Command stderr: {stderr_output}") + else: + logger.warning(f"Command stderr: {stderr_output}") return result.stdout.decode() diff --git a/tests/integration/defs/perf/disagg/test_disagg.py b/tests/integration/defs/perf/disagg/test_disagg.py index 39008ca11a..b60ba85196 100644 --- a/tests/integration/defs/perf/disagg/test_disagg.py +++ b/tests/integration/defs/perf/disagg/test_disagg.py @@ -62,7 +62,7 @@ class TestDisaggBenchmark: @pytest.mark.perf @pytest.mark.parametrize("test_config", PERF_TEST_CASES) - def test_benchmark(self, request, test_config: TestConfig): + def test_benchmark(self, request, batch_manager, test_config: TestConfig): """Performance benchmark test for YAML configurations.""" full_test_name = request.node.name @@ -101,15 +101,14 @@ class TestDisaggBenchmark: ) job_id = EnvManager.get_debug_job_id() else: - # Submit job using JobManager - success, job_id = JobManager.submit_test_job(test_config) + # Get job_id from batch manager (auto-submits batch if needed) + job_id = batch_manager.get_job_id(test_config) # Validate submission result - assert success, f"Job submission failed: {test_config.test_id}" - assert job_id, "Unable to get job ID" + assert job_id, f"Failed to get job_id for {test_config.test_id}" - # Wait for completion (timeout/early failure handled inside) - JobManager.wait_for_completion(job_id, 7200, test_config, check_early_failure=True) + # Wait for completion (timeout: 10 hours = 36000 seconds) + JobManager.wait_for_completion(job_id, 36000, test_config, check_early_failure=True) # End tracking test case test_tracker.end_test_case() @@ -136,7 +135,7 @@ class TestDisaggBenchmark: @pytest.mark.accuracy @pytest.mark.parametrize("test_config", ACCURACY_TEST_CASES) - def test_accuracy(self, request, test_config: TestConfig): + def test_accuracy(self, request, batch_manager, test_config: TestConfig): """Accuracy test for YAML configurations.""" full_test_name = request.node.name @@ -179,15 +178,14 @@ class TestDisaggBenchmark: ) job_id = EnvManager.get_debug_job_id() else: - # Submit job using JobManager - success, job_id = JobManager.submit_test_job(test_config) + # Get job_id from batch manager (auto-submits batch if needed) + job_id = batch_manager.get_job_id(test_config) # Validate submission result - assert success, f"Job submission failed: {test_config.test_id}" - assert job_id, "Unable to get job ID" + assert job_id, f"Failed to get job_id for {test_config.test_id}" - # Wait for completion (timeout/early failure handled inside) - JobManager.wait_for_completion(job_id, 10800, test_config, check_early_failure=True) + # Wait for completion (timeout: 10 hours = 36000 seconds) + JobManager.wait_for_completion(job_id, 36000, test_config, check_early_failure=True) # End tracking test case test_tracker.end_test_case() @@ -216,7 +214,7 @@ class TestDisaggBenchmark: @pytest.mark.stress @pytest.mark.parametrize("test_config", STRESS_TEST_CASES) - def test_stress(self, request, test_config: TestConfig): + def test_stress(self, request, batch_manager, test_config: TestConfig): """Stress test combining performance benchmarks and accuracy validation. This test type is designed for stress testing scenarios where both @@ -265,15 +263,14 @@ class TestDisaggBenchmark: ) job_id = EnvManager.get_debug_job_id() else: - # Submit job using JobManager - success, job_id = JobManager.submit_test_job(test_config) + # Get job_id from batch manager (auto-submits batch if needed) + job_id = batch_manager.get_job_id(test_config) # Validate submission result - assert success, f"Job submission failed: {test_config.test_id}" - assert job_id, "Unable to get job ID" + assert job_id, f"Failed to get job_id for {test_config.test_id}" - # Wait for completion (longer timeout for stress tests: 4 hours) - JobManager.wait_for_completion(job_id, 10800, test_config, check_early_failure=True) + # Wait for completion (timeout: 10 hours = 36000 seconds) + JobManager.wait_for_completion(job_id, 36000, test_config, check_early_failure=True) # End tracking test case test_tracker.end_test_case() From 342a47bf47b298d5eedc95d93a2923b697c50688 Mon Sep 17 00:00:00 2001 From: TensorRT LLM <90828364+tensorrt-cicd@users.noreply.github.com> Date: Thu, 8 Jan 2026 03:12:25 +0000 Subject: [PATCH 06/16] [None][infra] Check in most recent lock file from nightly pipeline Signed-off-by: TensorRT LLM <90828364+tensorrt-cicd@users.noreply.github.com> --- security_scanning/docs/poetry.lock | 6 ++--- .../examples/auto_deploy/poetry.lock | 6 ++--- .../examples/draft_target_model/poetry.lock | 6 ++--- security_scanning/examples/eagle/poetry.lock | 6 ++--- .../llm-eval/lm-eval-harness/poetry.lock | 6 ++--- .../examples/lookahead/poetry.lock | 6 ++--- security_scanning/examples/medusa/poetry.lock | 6 ++--- .../models/contrib/baichuan/poetry.lock | 20 ++++++++-------- .../examples/models/contrib/bloom/poetry.lock | 6 ++--- .../models/contrib/chatglm-6b/poetry.lock | 6 ++--- .../models/contrib/chatglm2-6b/poetry.lock | 6 ++--- .../contrib/chatglm3-6b-32k/poetry.lock | 6 ++--- .../examples/models/contrib/dbrx/poetry.lock | 6 ++--- .../models/contrib/deepseek_v1/poetry.lock | 6 ++--- .../models/contrib/deepseek_v2/poetry.lock | 6 ++--- .../models/contrib/falcon/poetry.lock | 6 ++--- .../examples/models/contrib/gptj/poetry.lock | 6 ++--- .../models/contrib/gptneox/poetry.lock | 6 ++--- .../examples/models/contrib/grok/poetry.lock | 6 ++--- .../models/contrib/internlm/poetry.lock | 6 ++--- .../examples/models/contrib/jais/poetry.lock | 6 ++--- .../examples/models/contrib/mmdit/poetry.lock | 6 ++--- .../examples/models/contrib/mpt/poetry.lock | 6 ++--- .../examples/models/contrib/opt/poetry.lock | 6 ++--- .../models/contrib/skywork/poetry.lock | 6 ++--- .../examples/models/contrib/smaug/poetry.lock | 6 ++--- .../examples/models/contrib/stdit/poetry.lock | 16 ++++++------- .../examples/models/core/commandr/poetry.lock | 6 ++--- .../examples/models/core/gemma/poetry.lock | 6 ++--- .../examples/models/core/glm-4-9b/poetry.lock | 6 ++--- .../examples/models/core/gpt/poetry.lock | 6 ++--- .../examples/models/core/llama/poetry.lock | 6 ++--- .../examples/models/core/mamba/poetry.lock | 6 ++--- .../examples/models/core/mixtral/poetry.lock | 6 ++--- .../examples/models/core/mllama/poetry.lock | 6 ++--- .../examples/models/core/nemotron/poetry.lock | 6 ++--- .../examples/models/core/phi/poetry.lock | 6 ++--- .../examples/models/core/qwen/poetry.lock | 6 ++--- .../models/core/qwen2audio/poetry.lock | 6 ++--- .../examples/models/core/qwenvl/poetry.lock | 20 ++++++++-------- .../models/core/recurrentgemma/poetry.lock | 6 ++--- .../examples/models/core/whisper/poetry.lock | 6 ++--- security_scanning/examples/ngram/poetry.lock | 6 ++--- .../examples/quantization/poetry.lock | 20 ++++++++-------- .../examples/ray_orchestrator/poetry.lock | 24 +++++++++---------- .../examples/redrafter/poetry.lock | 6 ++--- security_scanning/examples/serve/poetry.lock | 6 ++--- .../examples/trtllm-eval/poetry.lock | 6 ++--- security_scanning/metadata.json | 4 ++-- security_scanning/poetry.lock | 24 +++++++++---------- security_scanning/pyproject.toml | 4 ++-- security_scanning/triton_backend/poetry.lock | 6 ++--- 52 files changed, 198 insertions(+), 198 deletions(-) diff --git a/security_scanning/docs/poetry.lock b/security_scanning/docs/poetry.lock index 86ab05727b..f012c4737f 100644 --- a/security_scanning/docs/poetry.lock +++ b/security_scanning/docs/poetry.lock @@ -1195,13 +1195,13 @@ typing-extensions = ">=4.12.0" [[package]] name = "urllib3" -version = "2.6.2" +version = "2.6.3" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" files = [ - {file = "urllib3-2.6.2-py3-none-any.whl", hash = "sha256:ec21cddfe7724fc7cb4ba4bea7aa8e2ef36f607a4bab81aa6ce42a13dc3f03dd"}, - {file = "urllib3-2.6.2.tar.gz", hash = "sha256:016f9c98bb7e98085cb2b4b17b87d2c702975664e4f060c6532e64d1c1a5e797"}, + {file = "urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4"}, + {file = "urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed"}, ] [package.extras] diff --git a/security_scanning/examples/auto_deploy/poetry.lock b/security_scanning/examples/auto_deploy/poetry.lock index e4e3db4c5d..607bf79e0c 100644 --- a/security_scanning/examples/auto_deploy/poetry.lock +++ b/security_scanning/examples/auto_deploy/poetry.lock @@ -3635,13 +3635,13 @@ files = [ [[package]] name = "urllib3" -version = "2.6.2" +version = "2.6.3" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" files = [ - {file = "urllib3-2.6.2-py3-none-any.whl", hash = "sha256:ec21cddfe7724fc7cb4ba4bea7aa8e2ef36f607a4bab81aa6ce42a13dc3f03dd"}, - {file = "urllib3-2.6.2.tar.gz", hash = "sha256:016f9c98bb7e98085cb2b4b17b87d2c702975664e4f060c6532e64d1c1a5e797"}, + {file = "urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4"}, + {file = "urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed"}, ] [package.extras] diff --git a/security_scanning/examples/draft_target_model/poetry.lock b/security_scanning/examples/draft_target_model/poetry.lock index fa46e1e5db..9175f8b9ec 100644 --- a/security_scanning/examples/draft_target_model/poetry.lock +++ b/security_scanning/examples/draft_target_model/poetry.lock @@ -1831,13 +1831,13 @@ files = [ [[package]] name = "urllib3" -version = "2.6.2" +version = "2.6.3" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" files = [ - {file = "urllib3-2.6.2-py3-none-any.whl", hash = "sha256:ec21cddfe7724fc7cb4ba4bea7aa8e2ef36f607a4bab81aa6ce42a13dc3f03dd"}, - {file = "urllib3-2.6.2.tar.gz", hash = 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models in text, vision, audio, and multimodal models, for both inference and training." optional = false python-versions = ">=3.10.0" files = [ - {file = "transformers-5.0.0rc1-py3-none-any.whl", hash = "sha256:8b9604700769872cab4280dbcde201f557e93f72ee5a85c4592275ab4f15d330"}, - {file = "transformers-5.0.0rc1.tar.gz", hash = "sha256:1fdde557b96ef8ea277c45b8e0d558f1e167fe28a98593f4c4aec0277e335821"}, + {file = "transformers-5.0.0rc2-py3-none-any.whl", hash = "sha256:f8f2a14060ab11f20a0eec39d827af54c1589c327c5799d82808ae3f4167418a"}, + {file = "transformers-5.0.0rc2.tar.gz", hash = "sha256:9f2fa5e132433dd7eb910dc224b32de0baf758f3b6ffc918dbb632e0af85c07a"}, ] [package.dependencies] @@ -1912,15 +1912,15 @@ typer-slim = "*" [package.extras] accelerate = ["accelerate (>=1.1.0)"] -all = ["Pillow (>=10.0.1,<=15.0)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=1.1.0)", "accelerate (>=1.1.0)", "av", "codecarbon (>=2.8.1)", "jinja2 (>=3.1.0)", "jmespath (>=1.0.1)", "kenlm", "kernels (>=0.10.2,<0.11)", "librosa", "mistral-common[opencv] (>=1.6.3)", "num2words", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "timm (!=1.0.18,<=1.0.19)", "tokenizers (>=0.22.0,<=0.23.0)", "torch (>=2.2)", "torchaudio", "torchvision"] +all = ["Pillow (>=10.0.1,<=15.0)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=1.1.0)", "accelerate (>=1.1.0)", "av", "codecarbon (>=2.8.1)", "jinja2 (>=3.1.0)", "jmespath (>=1.0.1)", "kenlm", "kernels (>=0.10.2,<0.11)", "librosa", "mistral-common[opencv] (>=1.6.3)", "num2words", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "timm (>=1.0.23)", "tokenizers (>=0.22.0,<=0.23.0)", "torch (>=2.2)", "torchaudio", "torchvision"] audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"] benchmark = ["optimum-benchmark (>=0.3.0)"] chat-template = ["jinja2 (>=3.1.0)", "jmespath (>=1.0.1)"] codecarbon = 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b/security_scanning/examples/models/contrib/stdit/poetry.lock @@ -784,20 +784,20 @@ i18n = ["Babel (>=2.7)"] [[package]] name = "jsonschema" -version = "4.25.1" +version = "4.26.0" description = "An implementation of JSON Schema validation for Python" optional = false -python-versions = ">=3.9" +python-versions = ">=3.10" files = [ - {file = "jsonschema-4.25.1-py3-none-any.whl", hash = "sha256:3fba0169e345c7175110351d456342c364814cfcf3b964ba4587f22915230a63"}, - {file = "jsonschema-4.25.1.tar.gz", hash = "sha256:e4a9655ce0da0c0b67a085847e00a3a51449e1157f4f75e9fb5aa545e122eb85"}, + {file = "jsonschema-4.26.0-py3-none-any.whl", hash = "sha256:d489f15263b8d200f8387e64b4c3a75f06629559fb73deb8fdfb525f2dab50ce"}, + {file = "jsonschema-4.26.0.tar.gz", hash = "sha256:0c26707e2efad8aa1bfc5b7ce170f3fccc2e4918ff85989ba9ffa9facb2be326"}, ] [package.dependencies] attrs = ">=22.2.0" jsonschema-specifications = ">=2023.03.6" referencing = ">=0.28.4" -rpds-py = ">=0.7.1" +rpds-py = ">=0.25.0" 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b/security_scanning/examples/models/core/commandr/poetry.lock index a9fec7edd0..350b5d05f7 100644 --- a/security_scanning/examples/models/core/commandr/poetry.lock +++ b/security_scanning/examples/models/core/commandr/poetry.lock @@ -1753,13 +1753,13 @@ files = [ [[package]] name = "urllib3" -version = "2.6.2" +version = "2.6.3" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" files = [ - {file = "urllib3-2.6.2-py3-none-any.whl", hash = "sha256:ec21cddfe7724fc7cb4ba4bea7aa8e2ef36f607a4bab81aa6ce42a13dc3f03dd"}, - {file = "urllib3-2.6.2.tar.gz", hash = "sha256:016f9c98bb7e98085cb2b4b17b87d2c702975664e4f060c6532e64d1c1a5e797"}, + {file = "urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4"}, + {file = "urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed"}, ] [package.extras] diff --git 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b/security_scanning/examples/models/core/qwenvl/poetry.lock @@ -2927,13 +2927,13 @@ telegram = ["requests"] [[package]] name = "transformers" -version = "5.0.0rc1" +version = "5.0.0rc2" description = "Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training." optional = false python-versions = ">=3.10.0" files = [ - {file = "transformers-5.0.0rc1-py3-none-any.whl", hash = "sha256:8b9604700769872cab4280dbcde201f557e93f72ee5a85c4592275ab4f15d330"}, - {file = "transformers-5.0.0rc1.tar.gz", hash = "sha256:1fdde557b96ef8ea277c45b8e0d558f1e167fe28a98593f4c4aec0277e335821"}, + {file = "transformers-5.0.0rc2-py3-none-any.whl", hash = "sha256:f8f2a14060ab11f20a0eec39d827af54c1589c327c5799d82808ae3f4167418a"}, + {file = "transformers-5.0.0rc2.tar.gz", hash = "sha256:9f2fa5e132433dd7eb910dc224b32de0baf758f3b6ffc918dbb632e0af85c07a"}, ] [package.dependencies] @@ -2951,15 +2951,15 @@ 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"b85c447ceb1ff91c5d4df6b71de2256a5fabfe9d", + "timestamp": "2026-01-08T02:42:38Z" } diff --git a/security_scanning/poetry.lock b/security_scanning/poetry.lock index 6d04c2d679..4ef7b31b7a 100644 --- a/security_scanning/poetry.lock +++ b/security_scanning/poetry.lock @@ -1838,20 +1838,20 @@ files = [ [[package]] name = "jsonschema" -version = "4.25.1" +version = "4.26.0" description = "An implementation of JSON Schema validation for Python" optional = false -python-versions = ">=3.9" +python-versions = ">=3.10" files = [ - {file = "jsonschema-4.25.1-py3-none-any.whl", hash = "sha256:3fba0169e345c7175110351d456342c364814cfcf3b964ba4587f22915230a63"}, - {file = "jsonschema-4.25.1.tar.gz", hash = "sha256:e4a9655ce0da0c0b67a085847e00a3a51449e1157f4f75e9fb5aa545e122eb85"}, + {file = "jsonschema-4.26.0-py3-none-any.whl", hash = "sha256:d489f15263b8d200f8387e64b4c3a75f06629559fb73deb8fdfb525f2dab50ce"}, + {file = "jsonschema-4.26.0.tar.gz", hash = "sha256:0c26707e2efad8aa1bfc5b7ce170f3fccc2e4918ff85989ba9ffa9facb2be326"}, ] [package.dependencies] attrs = ">=22.2.0" jsonschema-specifications = ">=2023.03.6" referencing = ">=0.28.4" -rpds-py = ">=0.7.1" +rpds-py = ">=0.25.0" [package.extras] format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"] @@ -3852,13 +3852,13 @@ xmp = ["defusedxml"] [[package]] name = "plotly" -version = "6.5.0" +version = "6.5.1" description = "An open-source interactive data visualization library for Python" optional = false python-versions = ">=3.8" files = [ - {file = "plotly-6.5.0-py3-none-any.whl", hash = "sha256:5ac851e100367735250206788a2b1325412aa4a4917a4fe3e6f0bc5aa6f3d90a"}, - {file = "plotly-6.5.0.tar.gz", hash = "sha256:d5d38224883fd38c1409bef7d6a8dc32b74348d39313f3c52ca998b8e447f5c8"}, + {file = "plotly-6.5.1-py3-none-any.whl", hash = "sha256:5adad4f58c360612b6c5ce11a308cdbc4fd38ceb1d40594a614f0062e227abe1"}, + {file = "plotly-6.5.1.tar.gz", hash = "sha256:b0478c8d5ada0c8756bce15315bcbfec7d3ab8d24614e34af9aff7bfcfea9281"}, ] [package.dependencies] @@ -5930,13 +5930,13 @@ files = [ [[package]] name = "urllib3" -version = "2.6.2" +version = "2.6.3" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" files = [ - {file = "urllib3-2.6.2-py3-none-any.whl", hash = "sha256:ec21cddfe7724fc7cb4ba4bea7aa8e2ef36f607a4bab81aa6ce42a13dc3f03dd"}, - {file = "urllib3-2.6.2.tar.gz", hash = "sha256:016f9c98bb7e98085cb2b4b17b87d2c702975664e4f060c6532e64d1c1a5e797"}, + {file = "urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4"}, + {file = "urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed"}, ] [package.extras] @@ -6339,4 +6339,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.13" -content-hash = "04c93699fd51f42c19b5111e408e5240d4dc0616a9d2501c7d159c01b3331ca2" +content-hash = "dab9694d64d1c91b512eb62bbd31da9d0cdb8c93e99941a7022f2f46aea905e3" diff --git a/security_scanning/pyproject.toml b/security_scanning/pyproject.toml index bc7ac1222e..f8addf4b75 100644 --- a/security_scanning/pyproject.toml +++ b/security_scanning/pyproject.toml @@ -59,7 +59,7 @@ einops = "^0.8.1" flashinfer-python = ">=0.3.0,<0.4.0" xgrammar = "0.1.25" llguidance = "0.7.29" -jsonschema = "^4.25.1" +jsonschema = "^4.26.0" backoff = "^2.2.1" nvtx = "^0.2.14" matplotlib = "^3.10.8" @@ -73,7 +73,7 @@ tiktoken = "^0.12.0" blobfile = "^3.1.0" openai-harmony = "0.0.4" nvidia-cutlass-dsl = "4.3.4" -plotly = "^6.5.0" +plotly = "^6.5.1" numexpr = "<2.14.0" partial-json-parser = "^0.2.1.1.post7" torch-c-dlpack-ext = "0.1.3" diff --git a/security_scanning/triton_backend/poetry.lock b/security_scanning/triton_backend/poetry.lock index 6fa35b5ad7..2c00043517 100644 --- a/security_scanning/triton_backend/poetry.lock +++ b/security_scanning/triton_backend/poetry.lock @@ -982,13 +982,13 @@ files = [ [[package]] name = "urllib3" -version = "2.6.2" +version = "2.6.3" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.9" files = [ - {file = "urllib3-2.6.2-py3-none-any.whl", hash = "sha256:ec21cddfe7724fc7cb4ba4bea7aa8e2ef36f607a4bab81aa6ce42a13dc3f03dd"}, - {file = "urllib3-2.6.2.tar.gz", hash = "sha256:016f9c98bb7e98085cb2b4b17b87d2c702975664e4f060c6532e64d1c1a5e797"}, + {file = "urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4"}, + {file = "urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed"}, ] [package.extras] From 30f8455d295cd287ef11e5777d33312bddb2c595 Mon Sep 17 00:00:00 2001 From: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com> Date: Wed, 7 Jan 2026 23:33:45 -0500 Subject: [PATCH 07/16] [https://nvbugs/5747878][fix] unwaive llama4 scout tests (#10468) Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com> --- tests/integration/test_lists/waives.txt | 3 --- .../_torch/auto_deploy/_utils_test/_model_test_utils.py | 2 +- 2 files changed, 1 insertion(+), 4 deletions(-) diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt index f211cdb1fd..469772a681 100644 --- a/tests/integration/test_lists/waives.txt +++ b/tests/integration/test_lists/waives.txt @@ -403,8 +403,6 @@ examples/test_phi.py::test_llm_phi_quantization_1gpu[phi-2-fp8-bfloat16] SKIP (h test_e2e.py::test_trtllm_bench_llmapi_launch[pytorch_backend-llama-v3-llama3-8b] SKIP (https://nvbugs/5744432) test_e2e.py::test_trtllm_serve_multimodal_example SKIP (https://nvbugs/5747920) test_e2e.py::test_trtllm_serve_example SKIP (https://nvbugs/5747938) -unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py::test_build_ad[meta-llama/Llama-4-Scout-17B-16E-Instruct-llm_extra_args8] SKIP (https://nvbugs/5747878) -unittest/_torch/auto_deploy/unit/singlegpu/test_ad_build_small_single.py::test_build_ad[meta-llama/Llama-4-Scout-17B-16E-Instruct-llm_extra_args9] SKIP (https://nvbugs/5747878) triton_server/test_triton.py::test_opt[opt] SKIP (https://nvbugs/5739981) unittest/llmapi/test_llm_pytorch.py::test_tinyllama_logits_processor[False] SKIP (https://nvbugs/5771838) unittest/llmapi/test_llm_pytorch.py::test_tinyllama_logits_processor[True] SKIP (https://nvbugs/5771838) @@ -415,7 +413,6 @@ accuracy/test_cli_flow.py::TestPhi3Mini128kInstruct::test_auto_dtype SKIP (https accuracy/test_cli_flow.py::TestPhi3Small8kInstruct::test_auto_dtype SKIP (https://nvbugs/5744293) accuracy/test_cli_flow.py::TestPhi3Small128kInstruct::test_auto_dtype SKIP (https://nvbugs/5744293) accuracy/test_cli_flow.py::TestPhi3_5MiniInstruct::test_auto_dtype SKIP (https://nvbugs/5744293) -unittest/_torch/auto_deploy/unit/singlegpu/models/test_llama4_vlm_patch.py::test_build_run_llama4_vlm SKIP (https://nvbugs/5747878) accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4_4gpus_online_eplb[fp8kv=True-moe_backend=TRTLLM] SKIP (https://nvbugs/5740377) cpp/test_multi_gpu.py::TestDisagg::test_symmetric_executor[gpt-2proc-mpi_kvcache-90] SKIP (https://nvbugs/5755941) examples/test_bert.py::test_llm_bert_general[compare_hf-enable_remove_input_padding-use_attention_plugin-enable_context_fmha-tp:1-pp:1-float16-BertForQuestionAnswering-bert/bert-base-cased-squad2] SKIP (https://nvbugs/5608979) diff --git a/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py b/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py index 5adb8e5a73..a71a09b465 100644 --- a/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py +++ b/tests/unittest/_torch/auto_deploy/_utils_test/_model_test_utils.py @@ -393,7 +393,7 @@ _SMALL_MODEL_CONFIGS = { }, }, "meta-llama/Llama-4-Scout-17B-16E-Instruct": { - "llm_models_subdir": "Llama-4-Scout-17B-16E-Instruct", + "llm_models_subdir": "llama4-models/Llama-4-Scout-17B-16E-Instruct", "model_factory": "AutoModelForImageTextToText", "model_kwargs": { "text_config": { From f57aab5255159b63bc0f35916cbf6d93ab7de631 Mon Sep 17 00:00:00 2001 From: Barry Kang <43644113+Barry-Delaney@users.noreply.github.com> Date: Thu, 8 Jan 2026 14:58:55 +0800 Subject: [PATCH 08/16] [https://nvbugs/5775402][fix] Fix concurrency list in Wide-EP perf tests (#10529) Signed-off-by: Barry Kang <43644113+Barry-Delaney@users.noreply.github.com> --- ...22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-NIXL.yaml | 2 +- ...A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-UCX.yaml | 2 +- ...2B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-NIXL.yaml | 2 +- ...22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-UCX.yaml | 2 +- ...-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml | 2 +- ...k-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-UCX.yaml | 2 +- ...r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml | 2 +- ...-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-UCX.yaml | 2 +- ...-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml | 2 +- ...k-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-UCX.yaml | 2 +- ...-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml | 2 +- ...k-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-UCX.yaml | 2 +- ...v32-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml | 2 +- ...32-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml | 2 +- ...v32-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml | 2 +- ...v32-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml | 2 +- 16 files changed, 16 insertions(+), 16 deletions(-) diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-NIXL.yaml index 705e683aab..3c33b288e5 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-NIXL.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: 512 1075 + concurrency_list: 512 1024 input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-UCX.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-UCX.yaml index 53dcaef3df..0a6135f34a 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-UCX.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx1_gen1_dep16_bs64_eplb288_mtp3_ccb-UCX.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: 512 1075 + concurrency_list: 512 1024 input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-NIXL.yaml index 29251630c9..3c0b8d2e7a 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-NIXL.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '2150' + concurrency_list: '2048' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-UCX.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-UCX.yaml index 409e2284c1..2dd7fd80b2 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-UCX.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/Qwen3-235B-A22B-FP4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp1_ccb-UCX.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '2150' + concurrency_list: '2048' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml index ce4527e18b..fedb8825b2 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '1075' + concurrency_list: '1024' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-UCX.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-UCX.yaml index d1d2792ed4..5766454980 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-UCX.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-UCX.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '1075' + concurrency_list: '1024' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml index f2f39b906f..4d4f8cb7db 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '2150' + concurrency_list: '2048' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-UCX.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-UCX.yaml index 58df066b58..fc12422943 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-UCX.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-UCX.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '2150' + concurrency_list: '2048' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml index bdb222ece4..60b022a21d 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '1075' + concurrency_list: '1024' input_length: 8192 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-UCX.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-UCX.yaml index e1330be1ed..f4cfcda4e6 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-UCX.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-UCX.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '1075' + concurrency_list: '1024' input_length: 8192 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml index 2fc065b480..dafc6a7df7 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '538' + concurrency_list: '512' input_length: 8192 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-UCX.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-UCX.yaml index b4efd20397..bb54d661a5 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-UCX.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-r1-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-UCX.yaml @@ -22,7 +22,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '538' + concurrency_list: '512' input_length: 8192 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml index 451a995e30..4dd4d7fb46 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx1_gen1_dep32_bs32_eplb288_mtp0_ccb-NIXL.yaml @@ -23,7 +23,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '1075' + concurrency_list: '1024' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml index f67ff56f88..ca80042c69 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_1k1k_ctx2_gen1_dep16_bs128_eplb288_mtp3_ccb-NIXL.yaml @@ -23,7 +23,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '2150' + concurrency_list: '2048' input_length: 1024 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml index 4d3a716c67..c262e3f661 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx6_gen1_dep16_bs64_eplb288_mtp0_ccb-NIXL.yaml @@ -23,7 +23,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '1075' + concurrency_list: '1024' input_length: 8192 output_length: 1024 dataset_file: diff --git a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml index 441aebf189..0b7bc63e3f 100644 --- a/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml +++ b/tests/integration/defs/perf/disagg/test_configs/wideep/perf/deepseek-v32-fp4_8k1k_ctx8_gen1_dep32_bs16_eplb288_mtp3_ccb-NIXL.yaml @@ -23,7 +23,7 @@ benchmark: multi_round: 8 benchmark_ratio: 0.8 streaming: true - concurrency_list: '538' + concurrency_list: '512' input_length: 8192 output_length: 1024 dataset_file: From 22c81cb5fa2c37aa60768ef312abaf77baf8cb2e Mon Sep 17 00:00:00 2001 From: HuiGao-NV Date: Thu, 8 Jan 2026 15:15:30 +0800 Subject: [PATCH 09/16] [None][chore] Enable seg fault cases since one race condition is fixed (#10398) Signed-off-by: Hui Gao --- tests/integration/test_lists/waives.txt | 6 ------ 1 file changed, 6 deletions(-) diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt index 469772a681..ec161196b8 100644 --- a/tests/integration/test_lists/waives.txt +++ b/tests/integration/test_lists/waives.txt @@ -382,8 +382,6 @@ accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[moe_backend=CUT accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_2gpus[cutlass-two_model-overlap_scheduler] SKIP (https://nvbugs/5702826) accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_eagle3_4gpus[cutlass-two_model-overlap_scheduler] SKIP (https://nvbugs/5702826) unittest/llmapi/test_llm_pytorch.py::test_llm_reward_model SKIP (https://nvbugs/5670458) -accuracy/test_llm_api_pytorch.py::TestQwen3_235B_A22B::test_nvfp4[latency_moe_cutlass] SKIP (https://nvbugs/5740377) -accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[dep4_latency_moe_trtllm-torch_compile=False] SKIP (https://nvbugs/5740377) accuracy/test_disaggregated_serving.py::TestDeepSeekV3Lite::test_guided_decoding[llguidance-mtp_nextn=2] SKIP (https://nvbugs/5740075) accuracy/test_disaggregated_serving.py::TestDeepSeekV3Lite::test_guided_decoding[xgrammar-mtp_nextn=2] SKIP (https://nvbugs/5740075) unittest/_torch/modeling/test_modeling_out_of_tree.py::TestOutOfTree::test_llm_api[False] SKIP (https://nvbugs/5739981) @@ -395,8 +393,6 @@ accuracy/test_llm_api_pytorch.py::TestQwen3_235B_A22B::test_nvfp4[latency_moe_tr accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8_4gpus[tp4-fp8kv=True-attn_backend=FLASHINFER-torch_compile=True] SKIP (https://nvbugs/5741304) unittest/_torch/multi_gpu/test_allreduce.py::test_allreduce_fusion_patterns[2-residual_rms_norm_out_quant_fp8-hidden:7168-seqlen:8192] SKIP (https://nvbugs/5741392) unittest/executor/test_rpc.py::TestRpcCorrectness::test_incremental_task_async SKIP (https://nvbugs/5741476) -accuracy/test_llm_api_pytorch.py::TestLlama3_1_8BInstruct::test_fp8_4gpus[pp4-fp8kv=True-attn_backend=TRTLLM-torch_compile=False] SKIP (https://nvbugs/5740377) -accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[dep4_latency_moe_cutlass-torch_compile=False] SKIP (https://nvbugs/5740377) examples/test_phi.py::test_phi_fp8_with_bf16_lora[phi-2] SKIP (https://nvbugs/5744293) examples/test_phi.py::test_llm_phi_1node_2gpus_summary[Phi-3.5-MoE-instruct-nb:1] SKIP (https://nvbugs/5744293) examples/test_phi.py::test_llm_phi_quantization_1gpu[phi-2-fp8-bfloat16] SKIP (https://nvbugs/5744293) @@ -413,7 +409,6 @@ accuracy/test_cli_flow.py::TestPhi3Mini128kInstruct::test_auto_dtype SKIP (https accuracy/test_cli_flow.py::TestPhi3Small8kInstruct::test_auto_dtype SKIP (https://nvbugs/5744293) accuracy/test_cli_flow.py::TestPhi3Small128kInstruct::test_auto_dtype SKIP (https://nvbugs/5744293) accuracy/test_cli_flow.py::TestPhi3_5MiniInstruct::test_auto_dtype SKIP (https://nvbugs/5744293) -accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4_4gpus_online_eplb[fp8kv=True-moe_backend=TRTLLM] SKIP (https://nvbugs/5740377) cpp/test_multi_gpu.py::TestDisagg::test_symmetric_executor[gpt-2proc-mpi_kvcache-90] SKIP (https://nvbugs/5755941) examples/test_bert.py::test_llm_bert_general[compare_hf-enable_remove_input_padding-use_attention_plugin-enable_context_fmha-tp:1-pp:1-float16-BertForQuestionAnswering-bert/bert-base-cased-squad2] SKIP (https://nvbugs/5608979) examples/test_bert.py::test_llm_bert_general[compare_hf-enable_remove_input_padding-use_attention_plugin-enable_context_fmha-tp:1-pp:1-float16-RobertaForQuestionAnswering-bert/roberta-base-squad2] SKIP (https://nvbugs/5608979) @@ -482,7 +477,6 @@ accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B_Instruct_2507::test_skip_sof accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B_Instruct_2507::test_skip_softmax_attention[target_sparsity_0.9] SKIP (https://nvbugs/5774869) triton_server/test_triton.py::test_llava_onevision[llava_onevision] SKIP (https://nvbugs/5775205) triton_server/test_triton.py::test_gpt_ib_lad[gpt-ib-lad] SKIP (https://nvbugs/5775223) -accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[dep4_latency_moe_trtllm-torch_compile=True] SKIP (https://nvbugs/5740377) unittest/_torch/modules/test_fused_moe.py::test_fused_moe_fp8_blockwise_cute_dsl_multi_gpu[MoEWeightLoadingMode.FUSED_GATE_UP_PROJ-DefaultMoeRoutingMethod-1] SKIP (https://nvbugs/5775256) unittest/_torch/auto_deploy/unit/multigpu/transformations/library/test_ep_sharding.py::test_ep_shard[3-2] SKIP (https://nvbugs/5777041) unittest/_torch/auto_deploy/unit/multigpu/transformations/library/test_ep_sharding.py::test_ep_shard[8-2] SKIP (https://nvbugs/5777041) From 8d4b09dac63ada893c90eb17a78d72affa581ec7 Mon Sep 17 00:00:00 2001 From: dongfengy <99041270+dongfengy@users.noreply.github.com> Date: Thu, 8 Jan 2026 15:30:53 +0800 Subject: [PATCH 10/16] [None][doc] Update GPTOSS Doc (#10536) Signed-off-by: Dongfeng Yu --- docs/source/models/supported-models.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/docs/source/models/supported-models.md b/docs/source/models/supported-models.md index 2185e38473..332304f5d5 100644 --- a/docs/source/models/supported-models.md +++ b/docs/source/models/supported-models.md @@ -40,10 +40,11 @@ Note: Support for other models may vary. Features marked "N/A" are not applicabl | `Qwen3MoeForCausalLM` | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | N/A | Yes | Yes | | `Qwen3NextForCausalLM` | Yes | Yes | No | Untested | Yes | No | No | No | Yes | Yes | No | No | Untested | Untested | | `Llama4ForConditionalGeneration` | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Untested | N/A | Yes | Yes | -| `GptOssForCausalLM` | Yes | Yes | Yes | Yes | No | No | Yes | No | Yes | Yes | No | N/A | Yes | Yes | +| `GptOssForCausalLM` | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes [^3] | Yes | Yes | Yes | N/A | Yes | Yes | [^1]: Chunked Prefill for MLA can only be enabled on SM100/SM103. [^2]: KV cache reuse for MLA can only be enabled on SM90/SM100/SM103 and in BF16/FP8 KV cache dtype. +[^3]: Overlap scheduler isn't supported when using EAGLE-3(Two Model Engine) for GPT-OSS. # Multimodal Feature Support Matrix (PyTorch Backend) From 43839c7d9b4b5d3898388b83dc58763e8eaba1ae Mon Sep 17 00:00:00 2001 From: Emma Qiao Date: Thu, 8 Jan 2026 15:33:48 +0800 Subject: [PATCH 11/16] [TRTLLM-9642][infra] Increase pytest verbosity for failed tests (#9657) Signed-off-by: qqiao Signed-off-by: Emma Qiao --- jenkins/L0_Test.groovy | 2 +- tests/integration/defs/test_unittests.py | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/jenkins/L0_Test.groovy b/jenkins/L0_Test.groovy index f3a8226167..a6fef33a63 100644 --- a/jenkins/L0_Test.groovy +++ b/jenkins/L0_Test.groovy @@ -808,7 +808,7 @@ def getPytestBaseCommandLine( portEnvVars, pytestUtil, "pytest", - "-v", + "-vv", testFilter[(DETAILED_LOG)] ? "-s" : "", "--timeout-method=thread", "--apply-test-list-correction", diff --git a/tests/integration/defs/test_unittests.py b/tests/integration/defs/test_unittests.py index d2cd80692c..707426f822 100644 --- a/tests/integration/defs/test_unittests.py +++ b/tests/integration/defs/test_unittests.py @@ -126,8 +126,8 @@ def test_unittests_v2(llm_root, llm_venv, case: str, output_dir, request): f'results-sub-unittests-{case_fn}.xml') command = [ - '-m', 'pytest', ignore_opt, "-v", "--tb=short", "-rF", "--timeout=2400", - "--timeout-method=thread" + '-m', 'pytest', ignore_opt, "-vv", "--tb=short", "-rF", + "--timeout=2400", "--timeout-method=thread" ] if test_prefix: command += [f"--test-prefix={test_prefix}"] From dc6b743fb69f4b3b0030d13e533145fe3185265b Mon Sep 17 00:00:00 2001 From: Yiqing Yan Date: Thu, 8 Jan 2026 17:51:44 +0800 Subject: [PATCH 12/16] [None][chore] Bump version to 1.2.0rc8 (#10542) Signed-off-by: Yiqing Yan --- README.md | 2 +- examples/constraints.txt | 2 +- tensorrt_llm/version.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index c1476bfef1..9e78da9a47 100644 --- a/README.md +++ b/README.md @@ -10,7 +10,7 @@ state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.< [![python](https://img.shields.io/badge/python-3.10-green)](https://www.python.org/downloads/release/python-31012/) [![cuda](https://img.shields.io/badge/cuda-13.0.0-green)](https://developer.nvidia.com/cuda-downloads) [![torch](https://img.shields.io/badge/torch-2.9.0-green)](https://pytorch.org) -[![version](https://img.shields.io/badge/release-1.2.0rc7-green)](https://github.com/NVIDIA/TensorRT-LLM/blob/main/tensorrt_llm/version.py) +[![version](https://img.shields.io/badge/release-1.2.0rc8-green)](https://github.com/NVIDIA/TensorRT-LLM/blob/main/tensorrt_llm/version.py) [![license](https://img.shields.io/badge/license-Apache%202-blue)](https://github.com/NVIDIA/TensorRT-LLM/blob/main/LICENSE) [Architecture](https://nvidia.github.io/TensorRT-LLM/developer-guide/overview.html)   |   [Performance](https://nvidia.github.io/TensorRT-LLM/developer-guide/perf-overview.html)   |   [Examples](https://nvidia.github.io/TensorRT-LLM/quick-start-guide.html)   |   [Documentation](https://nvidia.github.io/TensorRT-LLM/)   |   [Roadmap](https://github.com/NVIDIA/TensorRT-LLM/issues?q=is%3Aissue%20state%3Aopen%20label%3Aroadmap) diff --git a/examples/constraints.txt b/examples/constraints.txt index 2637847500..02571fa1b6 100644 --- a/examples/constraints.txt +++ b/examples/constraints.txt @@ -1,3 +1,3 @@ -tensorrt_llm==1.2.0rc7 +tensorrt_llm==1.2.0rc8 evaluate~=0.4.1 rouge_score~=0.1.2 diff --git a/tensorrt_llm/version.py b/tensorrt_llm/version.py index 504baf79de..434ba8f8e2 100644 --- a/tensorrt_llm/version.py +++ b/tensorrt_llm/version.py @@ -12,4 +12,4 @@ # 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. -__version__ = "1.2.0rc7" +__version__ = "1.2.0rc8" From bea61bb17d7e7b15d1ffc95e47606af5e201598d Mon Sep 17 00:00:00 2001 From: bhsueh_NV <11360707+byshiue@users.noreply.github.com> Date: Thu, 8 Jan 2026 19:38:49 +0800 Subject: [PATCH 13/16] [None][fix] Mistral large 3 few code refine (#10405) Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com> --- .../models/core/mistral_large_3/README.md | 3 +- .../checkpoints/mistral/config_loader.py | 7 +- .../_torch/models/modeling_mistral.py | 64 +++++++++++-------- tensorrt_llm/evaluate/lm_eval.py | 31 ++++++--- tensorrt_llm/inputs/utils.py | 6 -- .../defs/accuracy/accuracy_core.py | 2 + .../defs/accuracy/references/mmlu.yaml | 4 +- .../defs/accuracy/references/mmmu.yaml | 3 +- .../test_llm_api_pytorch_multimodal.py | 15 ++++- .../test-db/l0_gb200_multi_gpus.yml | 4 +- tests/integration/test_lists/waives.txt | 3 - 11 files changed, 84 insertions(+), 58 deletions(-) diff --git a/examples/models/core/mistral_large_3/README.md b/examples/models/core/mistral_large_3/README.md index 5ea730c9f1..da219bf7b0 100644 --- a/examples/models/core/mistral_large_3/README.md +++ b/examples/models/core/mistral_large_3/README.md @@ -19,7 +19,8 @@ mpirun -n 1 --allow-run-as-root --oversubscribe python3 examples/llm-api/quickst --max_tokens 100 \ --checkpoint_format mistral \ --model_type mistral_large_3 \ - --moe_backend TRTLLM + --moe_backend TRTLLM \ + --image_format pil ``` ## LLM-only run diff --git a/tensorrt_llm/_torch/models/checkpoints/mistral/config_loader.py b/tensorrt_llm/_torch/models/checkpoints/mistral/config_loader.py index b72cb6da38..c679734fcf 100644 --- a/tensorrt_llm/_torch/models/checkpoints/mistral/config_loader.py +++ b/tensorrt_llm/_torch/models/checkpoints/mistral/config_loader.py @@ -103,17 +103,14 @@ def _remap_mistral_yarn_args(config: dict) -> dict: "apply_scale": "apply_yarn_scaling", } yarn_config = config.get("yarn") or {} - config["rope_parameters"] = { + config["rope_scaling"] = { "rope_type": "yarn", "mscale_all_dim": 1, } - if rope_theta := config.pop("rope_theta", None): - config["rope_parameters"]["rope_theta"] = rope_theta - for old_name, new_name in yarn_config_map.items(): if old_name in yarn_config: - config["rope_parameters"][new_name] = yarn_config.pop(old_name) + config["rope_scaling"][new_name] = yarn_config.pop(old_name) assert len(yarn_config) == 0, f"Unparsed yarn config: {yarn_config}" diff --git a/tensorrt_llm/_torch/models/modeling_mistral.py b/tensorrt_llm/_torch/models/modeling_mistral.py index ea06b5e100..99ff8169c1 100644 --- a/tensorrt_llm/_torch/models/modeling_mistral.py +++ b/tensorrt_llm/_torch/models/modeling_mistral.py @@ -46,6 +46,7 @@ from tensorrt_llm.inputs import (BaseMultimodalDummyInputsBuilder, MultimodalPlaceholderPlacement, TextPrompt, register_input_processor) from tensorrt_llm.inputs.multimodal import MultimodalParams +from tensorrt_llm.inputs.utils import encode_base64_image from tensorrt_llm.llmapi import SamplingParams from tensorrt_llm.logger import logger @@ -58,16 +59,28 @@ class MistralAttention(Attention): layer_idx: int | None = None, ): config = model_config.pretrained_config + rope_params = RopeParams.from_config(config) + rope_params_section = getattr(config, "rope_scaling", None) or getattr( + config, "rope_parameters", None) + rope_type = getattr(rope_params_section, "rope_type", None) + if rope_type == "yarn": + pos_embd_params = PositionalEmbeddingParams( + type=PositionEmbeddingType.yarn, + rope=rope_params, + is_neox=False) + else: + pos_embd_params = PositionalEmbeddingParams( + type=PositionEmbeddingType.rope_gpt_neox, + rope=rope_params, + ) + super().__init__( hidden_size=config.hidden_size, num_attention_heads=config.num_attention_heads, num_key_value_heads=config.num_key_value_heads, max_position_embeddings=config.max_position_embeddings, bias=False, - pos_embd_params=PositionalEmbeddingParams( - type=PositionEmbeddingType.rope_gpt_neox, - rope=RopeParams.from_config(config), - ), + pos_embd_params=pos_embd_params, layer_idx=layer_idx, dtype=config.torch_dtype, config=model_config, @@ -266,20 +279,18 @@ class MistralCommonImageProcessor: } def get_num_tokens_per_image(self, image_sizes): - # FIXME avoid double loading with custom loader h, w = image_sizes ncols, nrows = self.image_processor._image_to_num_tokens( Image.new("RGB", (w, h))) return ncols * nrows + nrows - def __call__(self, text, images, media, **kwargs): - assert media is not None - if isinstance(media, str): - media = [media] - - mm_items = [{"type": "image_url", "image_url": url} for url in media] - - logger.debug(f"text: {text}") + def __call__(self, text, images, **kwargs): + mm_items = [] + if images: + mm_items = [{ + "type": "image", + "base64": encode_base64_image(image) + } for image in images] conversation = [{ "role": "user", @@ -292,19 +303,20 @@ class MistralCommonImageProcessor: encoded = self.tokenizer.transformers_tokenizer.apply_chat_template( conversation, tokenize=True, return_dict=True, return_tensors='pt') - logger.debug( - f"encoded.pixel_values.shape: {encoded.pixel_values.shape}, encoded.input_ids: {encoded.input_ids[0][-20:]}" - ) - logger.debug( - f"encoded.input_ids list: {self.tokenizer.transformers_tokenizer.apply_chat_template(conversation)}" - ) - processed = { "input_ids": encoded.input_ids, - "pixel_values": encoded.pixel_values.to(self.dtype), - "attention_mask": encoded.attention_mask, - "image_sizes": torch.tensor([encoded.pixel_values.shape[2:]]) } + + # text-only mode for VLM + if "pixel_values" in encoded: + processed.update({ + "pixel_values": + encoded.pixel_values.to(self.dtype), + "attention_mask": + encoded.attention_mask, + "image_sizes": + torch.tensor([encoded.pixel_values.shape[2:]]) + }) return processed @@ -376,7 +388,6 @@ class Mistral3InputProcessor(BaseMultimodalInputProcessor, self, inputs: TextPrompt, sampling_params: SamplingParams ) -> Tuple[List[int], ExtraProcessedInputs | None]: images = inputs.get("multi_modal_data", {}).get("image") - mm_processor_kwargs = inputs.get("mm_processor_kwargs", {}) do_rescale = getattr(self.processor.image_processor, "do_rescale", False) if images is not None and isinstance(images[0], torch.Tensor): @@ -384,18 +395,15 @@ class Mistral3InputProcessor(BaseMultimodalInputProcessor, # format is "pt" (pytorch tensors), but not for "pil" (PIL images). do_rescale = False - if mm_processor_kwargs: - # Currently, we only support image modality in MistralCommonImageProcessor. + if images is not None: processed = self.processor( text=inputs["prompt"], images=images, do_rescale=do_rescale, - **mm_processor_kwargs, ) else: processed = self.text_processor( text=inputs["prompt"], - images=images, do_rescale=do_rescale, ) input_ids = processed.pop("input_ids").tolist()[0] diff --git a/tensorrt_llm/evaluate/lm_eval.py b/tensorrt_llm/evaluate/lm_eval.py index a3a59c3f5f..4a877d75f4 100644 --- a/tensorrt_llm/evaluate/lm_eval.py +++ b/tensorrt_llm/evaluate/lm_eval.py @@ -52,7 +52,9 @@ class LmEvalWrapper(TemplateLM): llm: Union[LLM, PyTorchLLM], sampling_params: Optional[SamplingParams] = None, streaming: bool = False, - chat_template_kwargs: Optional[dict[str, Any]] = None): + chat_template_kwargs: Optional[dict[str, Any]] = None, + model_type: str | None = None, + is_force_single_image: bool = False): super().__init__() self.llm = llm self.sampling_params = sampling_params @@ -163,7 +165,9 @@ class MultimodalLmEvalWrapper(LmEvalWrapper): sampling_params: Optional[SamplingParams] = None, streaming: bool = False, max_images: int = 999, - chat_template_kwargs: Optional[dict[str, Any]] = None): + chat_template_kwargs: Optional[dict[str, Any]] = None, + model_type: str | None = None, + is_force_single_image: bool = False): """ Initialize the multimodal wrapper. @@ -179,7 +183,9 @@ class MultimodalLmEvalWrapper(LmEvalWrapper): self.MULTIMODAL = True self.max_images = max_images self.chat_template_kwargs = chat_template_kwargs - self.model_type = self._get_model_type(llm) + self.model_type = model_type if model_type is not None else self._get_model_type( + llm) + self.is_force_single_image = is_force_single_image # NOTE: In TRT-LLM, currently we do not support interleaved text and image. Instead, we are adding image placeholders at the end of the text or at the beginning of the text. # So, until we support interleaved text and image, we set this to False. @@ -287,9 +293,14 @@ class MultimodalLmEvalWrapper(LmEvalWrapper): prompt = prompt_inputs(prompt) # NOTE: Convert RGBA format to RGB format - images = [ - convert_image_mode(img, "RGB") for img in media_data["visual"] - ] + if self.is_force_single_image: + # NOTE: This is a workaround to force single image for models which only support single image. + images = [convert_image_mode(media_data["visual"][0], "RGB")] + else: + images = [ + convert_image_mode(img, "RGB") + for img in media_data["visual"] + ] prompt["multi_modal_data"] = {"image": images} sampling_params = self._get_sampling_params(gen_kwargs) @@ -429,14 +440,18 @@ class LmEvalEvaluator(Evaluator): llm: Union[LLM, PyTorchLLM], sampling_params: Optional[SamplingParams] = None, streaming: bool = False, - scores_filter: str = None) -> float: + scores_filter: str = None, + model_type: str = None, + is_force_single_image: bool = False) -> float: import lm_eval lm_cls = MultimodalLmEvalWrapper if self.MULTIMODAL else LmEvalWrapper results = lm_eval.evaluate( lm=lm_cls(llm, sampling_params=sampling_params, streaming=streaming, - chat_template_kwargs=self.chat_template_kwargs), + chat_template_kwargs=self.chat_template_kwargs, + model_type=model_type, + is_force_single_image=is_force_single_image), task_dict=self.task_dict, limit=self.num_samples, apply_chat_template=self.apply_chat_template, diff --git a/tensorrt_llm/inputs/utils.py b/tensorrt_llm/inputs/utils.py index a6f7e49fa8..bbbd5f4f8f 100644 --- a/tensorrt_llm/inputs/utils.py +++ b/tensorrt_llm/inputs/utils.py @@ -774,12 +774,6 @@ def default_multimodal_input_loader( mm_placeholder_counts=[mm_placeholder_counts]) input = {"prompt": prompt} - # When the tokenizer is a MistralTokenizer, we need to keep the source media to handle in processor later. - from tensorrt_llm._torch.models.checkpoints.mistral.tokenizer import \ - MistralTokenizer - if isinstance(tokenizer, MistralTokenizer): - input["mm_processor_kwargs"] = {"media": media} - if mm_placeholder_counts: if mm_embeddings is not None: input[ diff --git a/tests/integration/defs/accuracy/accuracy_core.py b/tests/integration/defs/accuracy/accuracy_core.py index f96ac7d618..e30c6e2c2c 100644 --- a/tests/integration/defs/accuracy/accuracy_core.py +++ b/tests/integration/defs/accuracy/accuracy_core.py @@ -402,6 +402,8 @@ class MMMU(AccuracyTask): is_multimodal=True, apply_chat_template=True) + EVALUATE_KWARGS = dict(model_type=None, is_force_single_image=False) + class PassKeyRetrieval64k(AccuracyTask): DATASET = "passkey_retrieval_64k" diff --git a/tests/integration/defs/accuracy/references/mmlu.yaml b/tests/integration/defs/accuracy/references/mmlu.yaml index a0e38d67c1..9cbd7a9f73 100644 --- a/tests/integration/defs/accuracy/references/mmlu.yaml +++ b/tests/integration/defs/accuracy/references/mmlu.yaml @@ -345,9 +345,9 @@ mistralai/Mistral-Nemo-12b-Base: - quant_algo: FP8 accuracy: 69.66 mistral/Mistral-Large-3-675B: - - accuracy: 87.54 + - accuracy: 85.30 - spec_dec_algo: Eagle - accuracy: 87.54 + accuracy: 85.30 nvidia/Nemotron-Super-V3: - accuracy: 81.07 - quant_algo: NVFP4 diff --git a/tests/integration/defs/accuracy/references/mmmu.yaml b/tests/integration/defs/accuracy/references/mmmu.yaml index a2fb8f4a77..37819c3f14 100644 --- a/tests/integration/defs/accuracy/references/mmmu.yaml +++ b/tests/integration/defs/accuracy/references/mmmu.yaml @@ -25,4 +25,5 @@ microsoft/Phi-4-multimodal-instruct: Qwen/Qwen3-VL-30B-A3B-Instruct: - accuracy: 55.33 mistral/Mistral-Large-3-675B: - - accuracy: 60.00 +# Mistral Large 3 675B only supports single image input, so accuracy is lower. + - accuracy: 47 diff --git a/tests/integration/defs/accuracy/test_llm_api_pytorch_multimodal.py b/tests/integration/defs/accuracy/test_llm_api_pytorch_multimodal.py index 78e0f3e401..c3a812b195 100644 --- a/tests/integration/defs/accuracy/test_llm_api_pytorch_multimodal.py +++ b/tests/integration/defs/accuracy/test_llm_api_pytorch_multimodal.py @@ -293,8 +293,19 @@ class TestMistralLarge3_675B(LlmapiAccuracyTestHarness): ], ) def test_nvfp4_4gpus( - self, tp_size, pp_size, ep_size, attention_dp, cuda_graph, overlap_scheduler, moe_backend + self, + tp_size, + pp_size, + ep_size, + attention_dp, + cuda_graph, + overlap_scheduler, + moe_backend, + mocker, ): + mocker.patch.dict( + MMMU.EVALUATE_KWARGS, {"model_type": "mistral_large_3", "is_force_single_image": True} + ) pytorch_config = dict( disable_overlap_scheduler=not overlap_scheduler, cuda_graph_config=CudaGraphConfig() if cuda_graph else None, @@ -315,4 +326,4 @@ class TestMistralLarge3_675B(LlmapiAccuracyTestHarness): kv_cache_config=kv_cache_config, ) as llm: task = MMMU(self.MODEL_NAME) - task.evaluate(llm, sampling_params=self.sampling_params, model_type="mistral_large_3") + task.evaluate(llm, sampling_params=self.sampling_params) diff --git a/tests/integration/test_lists/test-db/l0_gb200_multi_gpus.yml b/tests/integration/test_lists/test-db/l0_gb200_multi_gpus.yml index 2241aea415..62c0af24f8 100644 --- a/tests/integration/test_lists/test-db/l0_gb200_multi_gpus.yml +++ b/tests/integration/test_lists/test-db/l0_gb200_multi_gpus.yml @@ -72,7 +72,7 @@ l0_gb200_multi_gpus: - accuracy/test_llm_api_pytorch.py::TestQwen3NextInstruct::test_nvfp4[tp4ep4-cutlass] - accuracy/test_llm_api_pytorch.py::TestQwen3NextInstruct::test_nvfp4[no_cuda_graph_overlap-cutlass] - accuracy/test_llm_api_pytorch.py::TestQwen3NextInstruct::test_nvfp4[tp4ep4-trtllm] - - accuracy/test_llm_api_pytorch.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm_eagle] TIMEOUT (90) + - accuracy/test_llm_api_pytorch_multimodal.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm] TIMEOUT (90) - condition: ranges: system_gpu_count: @@ -105,4 +105,4 @@ l0_gb200_multi_gpus: - accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_w4_4gpus_online_eplb[enable_configurable_moe-fp8] - accuracy/test_llm_api_pytorch.py::TestQwen3_235B_A22B::test_nvfp4_4gpus[latency_moe_trtllm_eagle3] TIMEOUT (90) - accuracy/test_llm_api_pytorch.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm] TIMEOUT (90) - - accuracy/test_llm_api_pytorch_multimodal.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm] TIMEOUT (90) + - accuracy/test_llm_api_pytorch.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm_eagle] TIMEOUT (90) diff --git a/tests/integration/test_lists/waives.txt b/tests/integration/test_lists/waives.txt index ec161196b8..563a38a76e 100644 --- a/tests/integration/test_lists/waives.txt +++ b/tests/integration/test_lists/waives.txt @@ -441,8 +441,6 @@ test_e2e.py::test_ptp_quickstart_advanced_2gpus_sm120[Nemotron-Super-49B-v1-BF16 unittest/_torch/multi_gpu/test_mnnvl_allreduce.py::test_row_linear_residual_norm_fusion[no_fusion-strategy:8-dtype:bfloat16-hidden:8192-seqlen:[15]] SKIP (https://nvbugs/5761364) triton_server/test_triton.py::test_gpt_speculative_decoding[gpt-speculative-decoding] SKIP (https://nvbugs/5762854) accuracy/test_llm_api_pytorch.py::TestLlama3_1_8B_Instruct_RocketKV::test_auto_dtype SKIP (https://nvbugs/5762822) -accuracy/test_llm_api_pytorch.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm] SKIP (https://nvbugs/5762852) -accuracy/test_llm_api_pytorch.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm_eagle] SKIP (https://nvbugs/5762852) unittest/_torch/sampler/test_return_logits.py SKIP (https://nvbugs/5764627) examples/serve/test_serve.py::test_config_file_loading[--config] SKIP (https://nvbugs/5754977) full:RTXPro6000D/accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4_4gpus[moe_backend=CUTLASS-mtp_nextn=2-tp2pp2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=False-torch_compile=False] SKIP (https://nvbugs/5740075) @@ -456,7 +454,6 @@ full:sm89/accuracy/test_disaggregated_serving.py::TestLlama3_1_8BInstruct::test_ accuracy/test_disaggregated_serving.py::TestLlama3_1_8BInstruct::test_ngram SKIP (https://nvbugs/5768068) test_e2e.py::test_eagle3_output_consistency_4gpus[Qwen3/saved_models_Qwen3-235B-A22B_fp8_hf-Qwen3/qwen3-235B-eagle3] SKIP (https://nvbugs/5685010) examples/test_mistral.py::test_mistral_with_bf16_lora_torch[mistral-7b-v0.1] SKIP (https://nvbugs/5769855) -accuracy/test_llm_api_pytorch_multimodal.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm] SKIP (TBD) accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_w4_4gpus[dp4-trtllm-fp8] SKIP (https://nvbugs/5772396) full:sm100/accuracy/test_llm_api_pytorch.py::TestGPTOSS::test_w4_4gpus[dp4-trtllm-auto] SKIP (https://nvbugs/5772396) accuracy/test_llm_api_pytorch.py::TestGLM4_6::test_nvfp4_2_model_mtp[2model_trtllm] SKIP (https://nvbugs/5772360) From 6511dbaea0a9197a07f546e9bfc307a583c14fc8 Mon Sep 17 00:00:00 2001 From: Eran Geva <19514940+MrGeva@users.noreply.github.com> Date: Thu, 8 Jan 2026 13:43:41 +0200 Subject: [PATCH 14/16] [#10417][fix] AutoDepoloy - Reverted to direct computation of minusA (#10509) Signed-off-by: Eran Geva <19514940+MrGeva@users.noreply.github.com> --- .../models/custom/modeling_nemotron_h.py | 13 +------------ 1 file changed, 1 insertion(+), 12 deletions(-) diff --git a/tensorrt_llm/_torch/auto_deploy/models/custom/modeling_nemotron_h.py b/tensorrt_llm/_torch/auto_deploy/models/custom/modeling_nemotron_h.py index 40dc215b34..259f997afd 100644 --- a/tensorrt_llm/_torch/auto_deploy/models/custom/modeling_nemotron_h.py +++ b/tensorrt_llm/_torch/auto_deploy/models/custom/modeling_nemotron_h.py @@ -113,11 +113,6 @@ class NemotronHMamba2Mixer(nn.Module): A = torch.arange(1, self.num_heads + 1) self.A_log = nn.Parameter(torch.log(A)) self.A_log._no_weight_decay = True - # Instead of recomputing `torch.exp(self.A_log.float())` on every forward pass, we will register a hook - # that sets this appropriately when loading weights. - # NOTE: we explicitly register this as a non-persistent buffer so that it does not appear in the state dict of - # this module, or an equivalent graph module trace from it, but still gets included in e.g. `to()` calls. - self.register_buffer("_minus_A", -A.float(), persistent=False) self.norm = MambaRMSNormGated( self.intermediate_size, eps=self.layer_norm_epsilon, @@ -129,8 +124,6 @@ class NemotronHMamba2Mixer(nn.Module): self.out_proj = nn.Linear(self.intermediate_size, self.hidden_size, bias=config.use_bias) self.use_bias = config.use_bias - self.register_load_state_dict_post_hook(self._load_state_dict_post_hook) - def torch_forward(self, input_states): batch_size, seq_len, _ = input_states.shape dtype = input_states.dtype @@ -166,7 +159,7 @@ class NemotronHMamba2Mixer(nn.Module): ) # 3. SSM transformation - A = self._minus_A + A = -torch.exp(self.A_log.float()) y = torch.ops.auto_deploy.torch_ssm( hidden_states=hidden_states.view(batch_size, seq_len, -1, self.head_dim), A=A, @@ -193,10 +186,6 @@ class NemotronHMamba2Mixer(nn.Module): def forward(self, hidden_states): return self.torch_forward(hidden_states) - @staticmethod - def _load_state_dict_post_hook(module, incompatible_keys) -> None: - module._minus_A.data = -torch.exp(module.A_log.float()) - class NemotronHRMSNorm(nn.Module): def __init__(self, hidden_size, eps=1e-6): From c0ae6bbdbea3a0b31b03769b6a362405d8adb844 Mon Sep 17 00:00:00 2001 From: William Zhang <133824995+2ez4bz@users.noreply.github.com> Date: Thu, 8 Jan 2026 03:45:54 -0800 Subject: [PATCH 15/16] [None][feat] EPD for Qwen3 VL (#10470) * Why? We would like to support EPD disaggregated serving for Qwen3 VL. * What? This commit adds such support, and extends existing unit tests for correctness checks. Some minor (protected) interface changes had to be made to the weight mapper as a side-effect. Signed-off-by: William Zhang <133824995+2ez4bz@users.noreply.github.com> --- .../models/checkpoints/base_weight_mapper.py | 11 +- .../checkpoints/hf/qwen3vl_weight_mapper.py | 19 +++ .../_torch/models/modeling_qwen3vl.py | 110 ++++++++++++++++-- .../multimodal/test_mm_encoder_standalone.py | 5 +- 4 files changed, 132 insertions(+), 13 deletions(-) diff --git a/tensorrt_llm/_torch/models/checkpoints/base_weight_mapper.py b/tensorrt_llm/_torch/models/checkpoints/base_weight_mapper.py index 4d78b3dcb1..790be65eed 100644 --- a/tensorrt_llm/_torch/models/checkpoints/base_weight_mapper.py +++ b/tensorrt_llm/_torch/models/checkpoints/base_weight_mapper.py @@ -29,9 +29,6 @@ class BaseWeightMapper(ABC): raise ValueError("model must have a config attribute") self._tp_size = 1 if model.model_config.mapping.enable_attention_dp else model.model_config.mapping.tp_size - self._head_dim = model.config.head_dim if hasattr( - model.config, 'head_dim' - ) and model.config.head_dim is not None else model.config.hidden_size // model.config.num_attention_heads self.map_weights() @@ -173,3 +170,11 @@ class BaseWeightMapper(ABC): if self._model is None: raise RuntimeError("Weight mapper is not initialized") return self._model + + @property + def _head_dim(self) -> int: + model = self.model + head_dim = model.config.head_dim if hasattr( + model.config, 'head_dim' + ) and model.config.head_dim is not None else model.config.hidden_size // model.config.num_attention_heads + return head_dim diff --git a/tensorrt_llm/_torch/models/checkpoints/hf/qwen3vl_weight_mapper.py b/tensorrt_llm/_torch/models/checkpoints/hf/qwen3vl_weight_mapper.py index 41b3da875e..24a3602db9 100644 --- a/tensorrt_llm/_torch/models/checkpoints/hf/qwen3vl_weight_mapper.py +++ b/tensorrt_llm/_torch/models/checkpoints/hf/qwen3vl_weight_mapper.py @@ -1,3 +1,8 @@ +from transformers.models.qwen3_vl.configuration_qwen3_vl import ( + Qwen3VLTextConfig, + Qwen3VLVisionConfig, +) + from tensorrt_llm._torch.models.checkpoints.hf.weight_mapper import HfWeightMapper from tensorrt_llm._torch.models.modeling_utils import register_mapper @@ -6,3 +11,17 @@ from tensorrt_llm._torch.models.modeling_utils import register_mapper class Qwen3VLHfWeightMapper(HfWeightMapper): def preprocess_weights(self, weights: dict) -> dict: return weights + + @property + def _head_dim(self) -> int: + config = self.model.config + if (head_dim := getattr(config, "head_dim", None)) is not None: + return head_dim + if isinstance(config, Qwen3VLTextConfig): + num_heads = config.num_attention_heads + elif isinstance(config, Qwen3VLVisionConfig): + num_heads = config.num_heads + else: + raise TypeError(f"Unexpected config class {type(config).__name__}.") + + return config.hidden_size // num_heads diff --git a/tensorrt_llm/_torch/models/modeling_qwen3vl.py b/tensorrt_llm/_torch/models/modeling_qwen3vl.py index f89d801f94..d073f6745b 100644 --- a/tensorrt_llm/_torch/models/modeling_qwen3vl.py +++ b/tensorrt_llm/_torch/models/modeling_qwen3vl.py @@ -25,6 +25,7 @@ from ...inputs import ( MultimodalPlaceholderPlacement, TextPrompt, register_input_processor, + support_multimodal_disaggregated, ) from ...inputs.multimodal import MultimodalParams from ...logger import logger @@ -350,6 +351,85 @@ class Qwen3VLInputProcessorBase(BaseMultimodalInputProcessor, BaseMultimodalDumm "multimodal_data": multimodal_data, } + def get_prompt_token_ids( + self, inputs: TextPrompt, mm_handles: List[Dict[str, Any]] + ) -> Tuple[List[int], List[int], List[int]]: + """ + Build input token ids with multimodal placeholders expanded to the number of MM tokens. + + Args: + inputs: Text prompt input container. Must contain a non-empty prompt string. + mm_handles: List of multimodal embedding handles. Currently only a single handle is supported. + + Returns: + Tuple[List[int], List[int], List[int]]: + - expanded_ids: token ids with each image token expanded to a placeholder repeated per MM token + - mm_token_length: per-image MM token lengths + - mm_token_offsets: start offsets (positions) for each image's MM tokens within expanded_ids + """ + # TODO: Move this function to the base input processor class when extending for more models + text_prompt = inputs.get("prompt") + if not text_prompt: + raise ValueError("Text prompt is required but not provided") + + if not isinstance(mm_handles, list): + raise TypeError("mm_handles must be a list") + + if len(mm_handles) > 1: + # TODO: only support single multimodal item within a request for now + raise NotImplementedError("Only one mm_handle is supported for Qwen3 VL for now") + + hidden_size = mm_handles[0]["tensor_size"][1] + num_deepstack_levels = len(self.config.vision_config.deepstack_visual_indexes) + # This is because, unlike previous Qwen VL models, the embeddings are concatenated with + # feature maps from deepstack layers. + expected_size = self.config.text_config.hidden_size * (1 + num_deepstack_levels) + if hidden_size != expected_size: + raise RuntimeError( + f"Expected multimodal embedding to have hidden size {expected_size}, got {hidden_size}." + ) + + input_ids = self.tokenizer(text_prompt, return_tensors="pt").input_ids[0] + + # TODO: what about `video_token_id`? + image_token_index = self.config.image_token_id + + image_mask = input_ids == image_token_index + image_positions = torch.where(image_mask)[0] + num_images = len(image_positions) + assert num_images == len(mm_handles), "Number of images must match number of mm_handles" + total_mm_tokens = sum(mm_handle["tensor_size"][0] for mm_handle in mm_handles) + final_length = len(input_ids) - num_images + total_mm_tokens + # Create output tensor + expanded_ids = torch.empty(final_length, dtype=input_ids.dtype) + placeholder_id = self.tllm_multimodal_token_id + + # Fill the expanded sequence + write_pos = 0 + image_cnt = 0 + mm_token_length = [] + mm_token_offsets = [] + for read_pos in range(len(input_ids)): + if input_ids[read_pos] == image_token_index: + # Replace with placeholder id + mm_token_num = mm_handles[image_cnt]["tensor_size"][0] + expanded_ids[write_pos : write_pos + mm_token_num] = placeholder_id + mm_token_offsets.append(write_pos) + mm_token_length.append(mm_token_num) + write_pos += mm_token_num + image_cnt += 1 + else: + # Copy text token as-is + expanded_ids[write_pos] = input_ids[read_pos] + write_pos += 1 + + assert write_pos == final_length, f"Write position mismatch: {write_pos} != {final_length}" + assert mm_token_length[-1] + mm_token_offsets[-1] <= final_length, ( + f"mm_token_length[-1] + mm_token_offsets[-1] ({mm_token_length[-1] + mm_token_offsets[-1]}) should be less " + f"than or equal to final_length ({final_length})" + ) + return expanded_ids.to(torch.int32).tolist(), mm_token_length, mm_token_offsets + class Qwen3VLVisionAttention(Qwen2_5_VLVisionAttention): def __init__(self, model_config, layer_idx): @@ -825,6 +905,7 @@ class Qwen3VLModelBase(PreTrainedModel): llm_model_config.pretrained_config.architectures = ["Qwen3MoeForCausalLM"] else: raise ValueError(f"Unsupported architecture: {self.original_arch}") + # Qwen3ForCausalLM. self.llm = AutoModelForCausalLM.from_config(llm_model_config) if not _is_disagg(): @@ -953,22 +1034,16 @@ class Qwen3VLModelBase(PreTrainedModel): # NOTE: Qwen*-VL series has mrope_config even on the text-only prompts, # so we need to separate the mm_multimodal_params from the text-only prompts. - mm_multimodal_params = [ - multimodal_param - for multimodal_param in multimodal_params - if multimodal_param.multimodal_data.get("image", {}).get("pixel_values") is not None - or multimodal_param.multimodal_data.get("video", {}).get("pixel_values_videos") - is not None - ] + mm_multimodal_params = self._get_requests_with_mm_data(multimodal_params) if len(mm_multimodal_params) > 0: if not _is_disagg(): mm_embeds = get_multimodal_embeddings( encoder_forward_fn=self.mm_encoder.forward, multimodal_params=mm_multimodal_params, ) - else: + elif not getattr(self, "support_mm_disagg", False): raise NotImplementedError( - "Qwen3VLModel does not support disaggregated inference yet. Please unset " + f"{type(self)} does not support disaggregated inference yet. Please unset " "the TLLM_MULTIMODAL_DISAGGREGATED environment variable, or set it to '0'." ) mm_embeds = find_input_mm_embeds(mm_embeds, mm_multimodal_params) @@ -1008,7 +1083,24 @@ class Qwen3VLModelBase(PreTrainedModel): logger.debug(f"output shape: {output_prob.shape}") return output_prob + def _get_requests_with_mm_data(self, multimodal_params): + mm_multimodal_params = [] + for multimodal_param in multimodal_params: + data = multimodal_param.multimodal_data + if ( + # The first 2 conditions check whether there is input on which inference should be run. + data.get("image", {}).get("pixel_values") is not None + or data.get("video", {}).get("pixel_values_videos") is not None + # This condition corresponds to when the embeddings are already populated, as is e.g. + # the case in EPD disagg in the prefill worker. + or data.get("multimodal_embedding") + ): + mm_multimodal_params.append(multimodal_param) + return mm_multimodal_params + + +@support_multimodal_disaggregated @register_vision_encoder(Qwen3VisionModelBase, vlm_base_model=Qwen3VisionModel) @register_auto_model("Qwen3VLForConditionalGeneration") @register_input_processor( diff --git a/tests/unittest/_torch/multimodal/test_mm_encoder_standalone.py b/tests/unittest/_torch/multimodal/test_mm_encoder_standalone.py index 99154dd074..993559879b 100644 --- a/tests/unittest/_torch/multimodal/test_mm_encoder_standalone.py +++ b/tests/unittest/_torch/multimodal/test_mm_encoder_standalone.py @@ -21,10 +21,12 @@ example_images = [ _LLAVA_DIR = llm_models_root() / "multimodals" / "llava-v1.6-mistral-7b-hf" _QWEN_2_5_VL_DIR = llm_models_root() / "Qwen2.5-VL-3B-Instruct" +_QWEN_3_VL_DIR = llm_models_root() / "Qwen3" / "Qwen3-VL-2B-Instruct" # TODO: Add multi-image in single chat test -@pytest.mark.parametrize("model_dir", [_LLAVA_DIR, _QWEN_2_5_VL_DIR]) +@pytest.mark.parametrize("model_dir", + [_LLAVA_DIR, _QWEN_2_5_VL_DIR, _QWEN_3_VL_DIR]) @pytest.mark.parametrize("pd_disagg", [False, True]) def test_single_image_chat(model_dir, pd_disagg): """Test processing single image using encoder (pass mm_embeddings) + LLM API. @@ -180,6 +182,7 @@ def test_single_image_chat(model_dir, pd_disagg): # Qwen2.5 VL's vision encoder seems to output different embeddings based on this value. # The test only passes with this set to 1. (_QWEN_2_5_VL_DIR, 1), + (_QWEN_3_VL_DIR, 3), ], ) def test_multi_request_batch_chat(model_dir, encoder_max_batch_size): From e0331297a620475fc41791a5906e09b453af7335 Mon Sep 17 00:00:00 2001 From: mpikulski <206748156+ixlmar@users.noreply.github.com> Date: Thu, 8 Jan 2026 12:47:39 +0100 Subject: [PATCH 16/16] [TRTLLM-9522][fix] broken cast (#9975) Signed-off-by: ixlmar <206748156+ixlmar@users.noreply.github.com> --- tensorrt_llm/llmapi/llm.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tensorrt_llm/llmapi/llm.py b/tensorrt_llm/llmapi/llm.py index 6d3410bf3c..ac869d765a 100644 --- a/tensorrt_llm/llmapi/llm.py +++ b/tensorrt_llm/llmapi/llm.py @@ -491,8 +491,8 @@ class BaseLLM: elif 'multi_modal_embeddings' in inputs: mm_embedding_info = inputs['multi_modal_embeddings'] prompt_token_ids, extra_processed_inputs = cast( - self.input_processor, - BaseMultimodalInputProcessor).attach_multimodal_embeddings( + BaseMultimodalInputProcessor, + self.input_processor).attach_multimodal_embeddings( inputs, mm_embedding_info, sampling_params) else: with nvtx_range_debug("input_processor"):