* Move all casters to customCasters.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Use customCasters in all bindings.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Added customCasters to userbuffers.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
---------
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* feat: Add group_rms_norm kernel to normalize multiple inputs in a single operator.
Previously, the RMSNorm implementation only supported a single input tensor. With group_rms_norm, multiple tensors can be normalized together:
```python
input_a, input_b, ... = group_rms_norm([input_a, input_b, ...])
```
All input tensors must share the same batch dimension. The kernel partitions work by dynamically assigning warp groups proportional to the last dimension of each input, improving launch efficiency and reducing overhead.
This MR provides two implementations:
GroupRMSNormKernel: Optimized for small-to-medium batch sizes
GroupRMSNormKernelLargeBatch: Contains additional optimizations for large batch sizes
Both kernels are currently exposed as custom PyTorch ops. A future MR will implement heuristic-based kernel selection and expose a unified interface.
Signed-off-by: Simeng Liu <simengl@nvidia.com>
* Resolve comments and fix typo with IS_FLASHINFER_AVAILABLE
Signed-off-by: Simeng Liu <simengl@nvidia.com>
---------
Signed-off-by: Simeng Liu <simengl@nvidia.com>
When input size is larger than the max workspace size, we shall fallback to NCCL + corresponding pre/post function to ensure the functionality of AllReduce.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* support lp in pytorch backend
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
* fix tp
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
---------
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
* add qwen3 dense model pytorch backend support, initial commit
solve the results error issue
add qwen3 moe model pytorch backend support
reformat the code
* perf - use flash_infer rmsnorm for qwen3
* feat - support qwen3 moe rmsnorm
* Put the computation of Q and K norm (in attn) into a single CUDA stream, and get a 5% - 8% throughput improvement on Qwen3 4B and Qwen3 - moe 30B - A3B.
* Put the computation of Q and K norm (in attn) into a single CUDA stream, and get a 5% - 8% throughput improvement on Qwen3 4B and Qwen3 - moe 30B - A3B. -- Forgot to update all modifications.
* fix bugs of running qwen3 public models and fp8 models
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
* fix bugs due to rebase
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
* fix bugs captured by pre-commi
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
* fix bug of attention
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
---------
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
Co-authored-by: Keddy Jin <jin.gq@aliyun.com>
Co-authored-by: Jiying Dong <87510204+dongjiyingdjy@users.noreply.github.com>
Co-authored-by: shao <shao@nvidia.com>
* Add a new param to LlmRequest and Request to natively support mm
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* update comment
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* Update tests to match the new LlmRequest constructor parameters
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* Modify unitTest and modify mm_embeding's dict name in llama4
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* Fix based on comments
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* Fix comment
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* Fix LlmRequest initialization in kvCacheManagerTest
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* Clean up code for promt_tuning_config
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
* Clean up prompt_tuning_config in GenerationRequest
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
---------
Signed-off-by: Kate Cheng <yunhsuanc@nvidia.com>
Co-authored-by: Haohang Huang <31998628+symphonylyh@users.noreply.github.com>
* Replace deepseek_allreduce op with the new unified allreduce op and moe_allreduce op.
* Minor revision of moe_allreduce op argument names.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
(1) match quant exclude modules names to TRTLLM names
(2) No need for any special weight loading for quantization scales weights (#3891)
Signed-off-by: Tomer Asida <57313761+tomeras91@users.noreply.github.com>
* add parallel_q_b_proj_and_concat
Signed-off-by: junliu <65336694+hello-11@users.noreply.github.com>
* code cleanup
Signed-off-by: junliu <65336694+hello-11@users.noreply.github.com>
* one gemm/concat and then split the latent_cache and pass them separately to context/gen
Signed-off-by: junliu <65336694+hello-11@users.noreply.github.com>
---------
Signed-off-by: junliu <65336694+hello-11@users.noreply.github.com>
test: add test cases for 0.19 release (#3608)
* fix test name
* add quickstart test for nemotron-ultra
* add rcca multi-node test case for deepseek-v3
* add rcca info
---------
squash (#3642)
fix: nvbugs/5187237: fix deterministic mode crash (#3448)
* nvbugs/5187237 nvbugs/5112075: fix deterministic mode error
* remove waive
* Revert "remove waive"
This reverts commit 0bf5486d19906d692bfb7a6262333c296b0087ac.
* revert ar fusion
---------
update fp8 doc (#3647)
tests: change qa perf test to trtllm-bench (#3619)
fix: FP8 quantized lm_head (NvBug 5214229) (#3567)
infra: Add PR approval protection for the release branch (#3634)
fix: nvbugs/5231298: pytorch allreduce issue (#3673)
Fix: nvbugs/5222698 variable not defined (#3630)
* Fix: nvbugs/5222698 variable not defined
* Tidy code
---------
test:sync waives.txt from main branch by disabling test_perf/gpt_350m-cppmanager case (#3685)
test:restore fp8 kv cache testing for L0 (#3671)
doc: Update DeepSeek perf docs (#3693)
* Update DeepSeek perf docs
* update
* Apply suggestions from code review
---------
tests: waive test_llm_multi_node (#3664)
fix: update test_user_buffers_mm_add_prologue atol (#3711)
Fix: cherry-pick hmac encryption from main branch (#3635)
* security fix cherry-pick changes from main
* fix hmac in remote mpi session (#3649)
---------
Un-waive DS-V3-Lite tests. (#3621)
fix: FP8 kv accuracy (#3675)
* fix FP8 kv accuracy
* update doc
---------
Fix script options for engines. (#3622)
unwaive multi-node test (#3721)
chore : Split more tests out of gpt tests (#3524) (#3674)
doc:add torch examples link into torch backend documentation (#3749)
test: Get Eagle tests working (#3593) (#3722)
Waive L0 test (#3756)
waive failed case in perf test, change default max_batch_size to 512 and write config.json to output log (#3656)
Update ds v3 parameters in stress test. (#3676)
waive gemma on L20 (#3766)
https://nvbugs/5141291: Fix convert.py script for Qwen model. (#3758)
Include Qwen2VLDecoderLayer in the smooth_qwen2_model function.
fix: PP4 fixes and cleanup (#3688)
remove benchmark test list (#3643)
skip disagg deepseek test if sm!=90 (#3720)
test: skip failed cases on B200 (#3710)
* add skip condition to tests
* fix error
---------
test: [nvbug: 5234494] skip_pre_ada for fp8 cases (#3718)
* skip_pre_ada for fp8 cases
* update
* update after rebase
---------
add know issue to deepseek doc. (#3800)
Fix ModelOpt Mixtral AWQ OOM (#3714) (#3761)
Waive L0 tests (#3826)
fix: Reduce memory usage in fused moe op associated with AutoTuning and fix moe fallback issue. (#3793)
* Reduce memory usage in fused moe op associated with AutoTuning.
* Replace pre-defined bucket size strategy with a generating function based on the tune_max_num_tokens.
* Add free_memory logic of workspace in min_latency_mode fused moe path.
* Fix fused_moe fallback issue. (#3652)
min_latency_mode is only set to False during warmup phase. Thus when it becomes true during inference, all tactics fall back to the default one and thus cause perf regression.
---------
[doc] Better document for Draft-Target-Model (DTM) speculative decoding (#3797)
Fix pre-commit
Fix again
Address some review comments for the MI
Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>
Co-authored-by: Zhanrui Sun <184402041+ZhanruiSunCh@users.noreply.github.com>
Signed-off-by: Hao Lu <14827759+hlu1@users.noreply.github.com@users.noreply.github.com>
Co-authored-by: Hao Lu <14827759+hlu1@users.noreply.github.com@users.noreply.github.com>
* fix bug of create cuda stream as default parameter which will be initialized during importing
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
* add torch.cuda.Stream() for the leader node
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
* fix pre-commit issue
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
---------
Signed-off-by: bhsueh <11360707+byshiue@users.noreply.github.com>
* add MNNVL memory mapping support
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* add more MPI environment for trtllm-llmapi-launch
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* add MoE communication and prepare kernels
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* add MNNVL AlltoAll support for DeepSeekV3
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* add output dump for throughput benchmark
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* support dynamic kernel launch grid
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* address review comments
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* address review comments #2
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
---------
Signed-off-by: Dongxu Yang <78518666+dongxuy04@users.noreply.github.com>
* Use updateDecoderBuffers in python decoder.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix synchronize in trtllm decoder.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Enable by default.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Use guided_decoder to setup seqslots and free them.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Use always decode_async and update_requests.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update decoder buffers.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix speculative decoding tests.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Send new_tensors_host instead of assuming dict.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Make default False in enable_trtllm_decoder.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Partially fix mtp, partially fix py_executor.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update request states before sending disagg ctx cache.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix disagg test for torch decoder.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Make isend_tensor_list and recv_tensor_list for sending the tensors_host.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Formatting.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix rebase.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Add disagg serving case to guided decoder.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Get overlap scheduling to work.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update cutlass to main.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update after rebasing.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Formatting.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update to use decode async and update requests.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Properly pass information to update_requests
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Formatting.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Make disaggregated serving a step closer to working.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix rebase.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix rebase and format.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Copy new device tokens more pythonic.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Restore MTP add dummy reqs.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Add ordereddict import to py_executor.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Formatting.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Added seq slot manager. Add test.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Use transmission for single tensor except when list of tensors is received.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Add TRTLLMDecoder allocation to estimate max kv cache tokens.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Add stream synchronization
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Formatting.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Make memory calculation of decoder adapt to the chosen decoder. Recognize decoder option passed in executorconfig. Make overlap scheduler test run on TinyLlama.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Format
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Add decoder creation to estimate max kv.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Formatting.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update submodule UCXX inline with main.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
---------
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* add passing E2E LoRA flow
Signed-off-by: Shahar Mor <smor@nvidia.com>
* add experimental feature
Signed-off-by: Shahar Mor <smor@nvidia.com>
* fix llma_args definition
Signed-off-by: Shahar Mor <smor@nvidia.com>
* decreased manually size of max loras to address OOM
Signed-off-by: Shahar Mor <smor@nvidia.com>
---------
Signed-off-by: Shahar Mor <smor@nvidia.com>
* generalizing cudagraph to multiple dynamic inputs
Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com>
* fix for failing test
Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com>
---------
Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com>
* Rewrite unit test for unified allreduce op. Removing the legacy unit test.
* Revise formats, fusion_op bindings. Put all tensors as optional inputs.
* Move the MoeAllreduceOp to a separate custom op.
* Move all the fusion patterns to the new version of the AllReduce fusion kernel. Remove the AllReduce strategy config. Revise the AllReduce strategies and fusion pattern definitions.
* Add more TODOs, fixing minor bugs, and remove legacy code.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
