* Fix AllReduce kernel hang issue when both tp and pp are enabled.
Allocate one workspace for each pp rank to avoid potential race.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* update waive list
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
---------
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* refactor: Move executor recv functions into classes
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Enhance MPI logging and error handling
- Updated MPI logging to include destination and tag information for better traceability during send and receive operations.
- Added error checking for MPI_Wait and MPI_Cancel calls to ensure proper handling of multi-device requests.
- Improved code structure for clarity and maintainability.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Introduce MpiTag enumeration and update MPI function signatures
- Added a new header file `mpiTags.h` to define an enumeration for MPI tags, improving code readability and maintainability.
- Updated function signatures in `mpiUtils.h` and `mpiUtils.cpp` to use the new `MpiTag` type instead of raw integers for tags.
- Refactored various MPI calls across the codebase to utilize the new `MpiTag` enumeration, enhancing type safety and clarity.
- Removed redundant MPI tag constants from several classes, streamlining the code.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* fixup! refactor: Introduce MpiTag enumeration and update MPI function signatures
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Rename tags for consistency
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
---------
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* Remove the WAR for test items incompleted
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Complete test item manually
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix another test definition file
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Complete test name
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix some other test names
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix another test name after rebase
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Update name for waived case name, too
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix name for multi-gpu tests
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix test name after rebase
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix another test name
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix typo
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix test name after rebase
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix other qa tests
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
* Fix tests name after rebase
Signed-off-by: qqiao <qqiao@nvidia.com>
* Fix name after rebase
Signed-off-by: qqiao <qqiao@nvidia.com>
* Correct test names in waive.txt
Signed-off-by: qqiao <qqiao@nvidia.com>
* Add new test_durations file
Signed-off-by: qqiao <qqiao@nvidia.com>
* Fix names after rebase
Signed-off-by: qqiao <qqiao@nvidia.com>
* Update test duration to latest
Signed-off-by: qqiao <qqiao@nvidia.com>
---------
Signed-off-by: EmmaQiaoCh <qqiao@nvidia.com>
Signed-off-by: qqiao <qqiao@nvidia.com>
* refactor: Move ModelSpec from tests to core library
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Move ModelSpec from runtime to separatedir
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Use new bindings path and clean up
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Updated licenses
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove script_dir from path
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
---------
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* feat: Add rename_weights_with_regex function for dynamic weight key renaming
Introduced a new utility function to rename weight keys in a dictionary based on regex pattern matching. This allows for flexible mapping of keys from Hugging Face naming conventions to TRT-LLM naming conventions, enhancing model compatibility and usability.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* feat: Implement SiglipVisionModel and related components
Added the SiglipVisionModel along with its associated classes, including SiglipAttention, SiglipEncoderLayer, and SiglipEncoder.
Additionally, a new test suite for the SiglipVisionModel has been created to ensure compatibility with Hugging Face outputs.
Currently SiglipVisionModel support batch size larger than one. Also, inputs and outputs shape are same with the HF for compatibility.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* feat: Add CLIPVisionModel and associated components
Introduced the CLIPVisionModel along with its related classes, including CLIPAttention, CLIPEncoderLayer, CLIPEncoder, and CLIPVisionTransformer. This implementation aligns with Hugging Face's CLIP architecture, ensuring compatibility in input and output shapes.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* feat: Enhance CLIPVisionModel with attention metadata preparation and unit tests
Updated the CLIPVisionModel to include a method for preparing attention metadata, simplifying the model's usage. Additionally, added a comprehensive unit test suite for the CLIPVisionModel, ensuring compatibility with Hugging Face outputs and validating model performance across various scenarios.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* feat: Refactor SiglipVisionModel with attention metadata preparation and update unit tests
Enhanced the SiglipVisionModel by adding a method to prepare attention metadata, streamlining its usage. Updated unit tests to validate model performance and compatibility with Hugging Face outputs, including adjustments to the configuration and test scenarios.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* refactor: Remove unused rotary_emb parameter from CLIP and Siglip attention classes
Eliminated the rotary_emb parameter from the CLIPAttention and SiglipAttention classes to streamline the code. Updated unit tests to reflect changes in the model configurations, including clarifications in the default configurations sourced from Hugging Face.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* feat: Integrate CLIPVisionModel into LlavaNextInputProcessor and enhance weight loading
Added CLIPVisionModel to the LlavaNextInputProcessor for improved vision processing. Updated the model loading mechanism to ensure compatibility with the new vision model and added attention metadata preparation. Removed debug print statements from weight renaming function for cleaner code.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* refactor: Remove unused max_position_embeddings from CLIPAttention and update Siglip classes to use CLIP components
Removed the unused max_position_embeddings variable from the CLIPAttention class. Updated the Siglip classes to utilize CLIP components, specifically replacing SiglipEncoder and SiglipAttention with their CLIP counterparts, streamlining the codebase and enhancing consistency across models.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* refactor: Consolidate weight loading logic into a shared implementation
Refactored the weight loading process across CLIP and Siglip models by using a new utility function, _load_weights_impl, to streamline the loading mechanism. This change enhances code maintainability and reduces redundancy in weight handling, ensuring consistent behavior across different model architectures.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* refactor: Simplify output handling in CLIP and Siglip models by removing output_hidden_states parameter
Removed the output_hidden_states parameter from the CLIPEncoder and SiglipVisionTransformer classes, streamlining the output handling process. Updated the corresponding unit tests to reflect these changes and ensure compatibility with the new output structure.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
* feat: Enhance LlavaNextInputProcessor with dynamic model loading and memory optimization
Updated the LlavaNextInputProcessor to support dynamic model loading from local paths or Hugging Face, improving memory efficiency by partially loading the model components. Integrated the LlavaNextMultiModalProjector and adjusted weight loading to ensure compatibility with the new architecture.
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
---------
Signed-off-by: qixiang-99 <203170375+qixiang-99@users.noreply.github.com>
Co-authored-by: Haohang Huang <31998628+symphonylyh@users.noreply.github.com>
* 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>
* support return logprob in llmapi
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
update and add test
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
stability test
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
* revert removal of old flag
Signed-off-by: Erin Ho <erinh@nvidia.com>
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
---------
Signed-off-by: Erin Ho <14718778+hchings@users.noreply.github.com>
Signed-off-by: Erin Ho <erinh@nvidia.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>
* Move world options to a different group for clarity.
Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
* Add eos_id option.
Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
---------
Signed-off-by: Frank Di Natale <3429989+FrankD412@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>
* Squash of dev commits
Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>
* Add timer + waive test with suspected GptSession bug
Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>
* Respond to reviewer comments
Signed-off-by: domb <3886319+DomBrown@users.noreply.github.com>
---------
Signed-off-by: Dom Brown <3886319+DomBrown@users.noreply.github.com>
Signed-off-by: domb <3886319+DomBrown@users.noreply.github.com>
This MR integrates Conan into the build system, so that it can be used to fetch dependencies in future changes.
Also installs all requirements-dev.txt inside a virtualenv instead of the system, since some of Conan's dependencies may conflict with the system packages. Virtualenv is used instead of venv because the triton server backend container has only virtualenv installed. This also allows developers to cache the requirements-dev.txt packages between container launches.
Signed-off-by: Tyler Burt <195370667+tburt-nv@users.noreply.github.com>
Replace libtensorrt_llm_nvrtc_wrapper.so with its source code, which
consists of two parts:
1. NVRTC glue code
2. XQA kernel code
During TensorRT-LLM build, XQA kernel code is embedded as C++ arries via
gen_cpp_header.py and passed to NVRTC for JIT compilation.
Signed-off-by: Ming Wei <2345434+ming-wei@users.noreply.github.com>
* Add mIsGenerationMLA to differentiate ctx and gen MLA in AttentionOp.
For Generation MLA, if FlashMLA is used, do not check the existence of FMHA based MLA kernel.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Run pre-commit.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Fix compile error.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
---------
Signed-off-by: Bo Li <bobboli0202@gmail.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>
