* feat: adding multimodal (only image for now) support in trtllm-bench
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
* fix: add in load_dataset() calls to maintain the v2.19.2 behavior
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
* re-adding prompt_token_ids and using that for prompt_len
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
* updating the datasets version in examples as well
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
* api changes are not needed
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
* moving datasets requirement and removing a missed api change
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
* addressing review comments
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
* refactoring the quickstart example
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
---------
Signed-off-by: Rakib Hasan <rhasan@nvidia.com>
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.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* implement variable window attention by breaking the block manager into window block managers per window size
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* revert isCyclic to be true if the min attention window is reached, not per window size
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* add explanatory comment to mCyclicThreshold
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* load correct gemma config
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* don't shadow inputLength in addSequence - it should remain the function scope input length between window size loop iterations
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix KVCacheManagerVariableWindowAttentionWithReuseTest for multiple window block managers
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* if TYPE_CHECKING
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* set temp_attention_window_inputs to None explicitly
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* set temp_attention_window_inputs to None explicitly
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* pass dtype as well
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* test_gemma variable sliding window attention
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* allot a fraction of primary/secondaryBlocks to different window size heaps, depending on the window size's total contribution to the kvcache size (i.e., including all layers)
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* remove || mEnableBlockReuse which erroneously triggers beamsearch code for cyclic variable attention window code
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* turn off request delaying for MaxUtil
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* make comments better
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* windowSizesTotalSum using std::accumulate
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix error handling of forwardAsync - forwardAsync catch-all catch cleanup code that runs terminateRequest can also fail and must be caught
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix comments
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* remove assert that kills disagg tests, since it isn't necessary
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix corrupted expression: 'isNewTask && (peftCacheManager ?' -> '(isNewTask && peftCacheManager) ?' which caused boolean algebra. Main is correct
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* add Gemma3 to SUPPORTED_HF_ARCHITECTURES
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* support Gemma3
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* finally fix test_gemma - always spread at least {} into generate_summary_cmd, never None
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* finally fix test_gemma - always spread at least {} into generate_summary_cmd, never None
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix kvfactor field for deepseek
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix comment
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix gemma-3 entries in testlist to include vswa
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* only quantize gemma2 VSWA
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
remove misleading comment
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
fix test_gemma
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix test_gemma
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix test_gemma
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* in sendRequestInfo, fromOldAllocatedBlockIds->fromOldAllocatedBlockIds, like in main
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
* fix: disable KV cache reuse if using attention sink (#3021)
* fix: disable KV cache reuse if using attention sink
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* fix: disable KV cache reuse if sink bubble
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* add comment
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
---------
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
---------
Signed-off-by: Netanel Haber <58652339+netanel-haber@users.noreply.github.com>
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
Co-authored-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* added files for nemotron-h
Signed-off-by: Luis Vega <lvega@nvidia.com>
* use try/except to import RMSNorm
Signed-off-by: Luis Vega <lvega@nvidia.com>
---------
Signed-off-by: Luis Vega <lvega@nvidia.com>
Co-authored-by: QI JUN <22017000+QiJune@users.noreply.github.com>
* hmac initial implementation to encrypt worker and proxy queue
Signed-off-by: Yibin Li <109242046+yibinl-nvidia@users.noreply.github.com>
* set different hmac key for each pair of server/client queue
Signed-off-by: Yibin Li <109242046+yibinl-nvidia@users.noreply.github.com>
* fix comments
Signed-off-by: Yibin Li <109242046+yibinl-nvidia@users.noreply.github.com>
* fix style
Signed-off-by: Yibin Li <109242046+yibinl-nvidia@users.noreply.github.com>
---------
Signed-off-by: Yibin Li <109242046+yibinl-nvidia@users.noreply.github.com>
* [Infra][TRTLLM-4063] - Branch out for the TRT-LLM v0.18.0 release
Signed-off-by: Zhanrui Sun <zhanruis@nvidia.com>
(cherry picked from commit de90312020e51c22ba5e75b3502c7ee90c059265)
* [Infra][TRTLLM-3652] - Update dependencies to TRT 10.9 / CUDA 12.8.1 / DLFW 25.03(Internal)
Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
(cherry picked from commit 58db1340ef7db22f1910f878d220a92be5b830d1)
* [None][Doc] - Update docs for v0.18.0
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
(cherry picked from commit d23e75bc95619ce3b116213d55319272888e0c88)
* [Infra] - Fix or WAR issues in the package sanity check stages
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
(cherry picked from commit e874e2b127515c52ba10c8df1cc2631627f74ffe)
* [https://nvbugs/5173454] [https://nvbugs/5173432] [https://nvbugs/5175863] fix chatglm tokenizer and tmp model path
Signed-off-by: Yuki Huang <yukih@nvidia.com>
(cherry picked from commit 731811d4e182d70a66193d646152cb71dfafe83a)
* cherry-pick 'test: Updat cluster and multi node test lists and trtllm-bench' test to fix perf drop issue
Signed-off-by: Ruodi Lu <ruodil@nvidia.com>
(cherry picked from commit 5214616283fbc15ae98871a1d84c78d8e1f2e6e8)
* Revert "Merge branch 'user/yukih/fix_5173454_5173432' into 'release/0.18'"
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
(cherry picked from commit 8d34831cb2b81ee2dfa8021b68e7158b33789a5f)
* [Infra]Restrict setuptools version to avoid sasb pip install issue
Signed-off-by: Emma Qiao <qqiao@nvidia.com>
(cherry picked from commit 1e60ad29e0dafec0e295bedb5d89b716a02a707c)
* [https://nvbugs/5173454] [https://nvbugs/5173432] [https://nvbugs/5175863] fix chatglm tokenizer and tmp model path
Signed-off-by: Yuki Huang <yukih@nvidia.com>
(cherry picked from commit 3ed8164e5bfea1d5aa2039b5408439fd6cf59dac)
* WAR for bug 5173448
Signed-off-by: Thor Johnsen <tjohnsen@nvidia.com>
(cherry picked from commit b6528b2ba15322b6c6a4c81a8b74c04d4973de4f)
* [Infra][TRTLLM-3652] - Update dependencies to CUDA 12.8.1 / DLFW 25.03
Signed-off-by: Yiqing Yan <yiqingy@nvidia.com>
(cherry picked from commit 6560983d132d9d257ee15849664eb055e94adaa9)
* [Docs] - Doc changes for v0.18.0
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
(cherry picked from commit 26769b61218a947c8f9d070f73b63d576fcc20c4)
* [Doc] - Doc change for v0.18.0
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
(cherry picked from commit 4b3b5ed6bfbc2300e3775fe75456083faad7b235)
* [Infra] update version to 0.18.1
Signed-off-by: Zhanrui Sun <zhanruis@nvidia.com>
(cherry picked from commit 59e8326c75639275837d34de8e140358737a3365)
* Add back nemotron file.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix recurrentgemma reqs.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Adding WAR for bug 5173448.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Formatting.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Remove duplicated file.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update examples/prompt_lookup/requirements.txt
Co-authored-by: Zhanrui Sun <184402041+ZhanruiSunCh@users.noreply.github.com>
Signed-off-by: Daniel Cámpora <961215+dcampora@users.noreply.github.com>
* Remove glm-4-9b from model dir in chatglm test.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Remove indent change.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Yanchao Lu <yanchaol@nvidia.com>
Signed-off-by: Daniel Cámpora <961215+dcampora@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Yanchao Lu <yanchaol@nvidia.com>
Signed-off-by: Daniel Cámpora <961215+dcampora@users.noreply.github.com>
* Revert changes on l0_test.groovy.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Update dev images
Co-authored-by: Zhanrui Sun <184402041+ZhanruiSunCh@users.noreply.github.com>
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
* Remove duplicated import.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Fix custom op
Signed-off-by: Yi Zhang <187001205+yizhang-nv@users.noreply.github.com>
* Fix flashinfer & vanilla backend
Signed-off-by: Yi Zhang <187001205+yizhang-nv@users.noreply.github.com>
* Skip problematic case.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
* Skip problematic test_moe_w4a8_1_14336_4096_8_bfloat16_True_False case.
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
---------
Signed-off-by: Daniel Campora <961215+dcampora@users.noreply.github.com>
Signed-off-by: Daniel Cámpora <961215+dcampora@users.noreply.github.com>
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
Signed-off-by: Yi Zhang <187001205+yizhang-nv@users.noreply.github.com>
Co-authored-by: Zhanrui Sun <zhanruis@nvidia.com>
Co-authored-by: Yiqing Yan <yiqingy@nvidia.com>
Co-authored-by: Yanchao Lu <yanchaol@nvidia.com>
Co-authored-by: Yuki Huang <yukih@nvidia.com>
Co-authored-by: Ruodi Lu <ruodil@nvidia.com>
Co-authored-by: Emma Qiao <qqiao@nvidia.com>
Co-authored-by: Thor Johnsen <tjohnsen@nvidia.com>
Co-authored-by: Zhanrui Sun <184402041+ZhanruiSunCh@users.noreply.github.com>
Co-authored-by: Yi Zhang <187001205+yizhang-nv@users.noreply.github.com>
Co-authored-by: Tao Li @ NVIDIA <tali@nvidia.com>
* chore: unify pp_layers helpers
Fix assumptions about equal number of layers per PP rank
in prepare_attention_inputs
Signed-off-by: Aurelien Chartier <2567591+achartier@users.noreply.github.com>
* apply a tenative fix to moe bypass kernel update
* Pass none to disable final stage in moe
Co-authored-by: hlu1 <14827759+hlu1@users.noreply.github.com>
Signed-off-by: Chang Liu <lc9114@gmail.com>
---------
Signed-off-by: Chang Liu <lc9114@gmail.com>
Co-authored-by: hlu1 <14827759+hlu1@users.noreply.github.com>
* fix: Fixing issue with first gen token being returned twice with streaming
Signed-off-by: Patrice Castonguay <55748270+pcastonguay@users.noreply.github.com>
* Fixing not_expectring_strings in test
Signed-off-by: Patrice Castonguay <55748270+pcastonguay@users.noreply.github.com>
---------
Signed-off-by: Patrice Castonguay <55748270+pcastonguay@users.noreply.github.com>
Co-authored-by: QI JUN <22017000+QiJune@users.noreply.github.com>
* fix: add kv memory size per token of draft model to calculate max number
of tokens of kv cache
Signed-off-by: Hui Gao
* Fix code to get model_config of draft model
Signed-off-by: Hui Gao
---------
Signed-off-by: Hui Gao
* refactor: remove cumLogProbs and logProbs from DecoderBuffers
- Eliminated cumLogProbs and logProbs from DecoderBuffers, streamlining the buffer management.
- Updated related code in decoderBuffers.cpp and bindings.cpp to reflect these changes, ensuring that only host pointers are used for log probabilities.
These modifications enhance code clarity and maintainability by reducing redundancy in buffer management.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: streamline sequence length handling in GptDecoderBatched and StatefulGptDecoderBatched
- Updated GptDecoderBatched to directly use output.sequenceLengths for lengths assignment, removing unnecessary reshaping.
- Adjusted StatefulGptDecoderBatched to ensure sequence lengths are correctly shaped based on actual batch size and max beam width.
These changes enhance clarity and maintainability in the decoding process.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: integrate DecoderState for sequence length management in decoding process
- Updated DecoderBuffers to remove direct handling of sequence lengths, now utilizing DecoderState for this purpose.
- Adjusted MakeDecodingBatchInputOutput to accept DecoderState, enhancing clarity in the decoding input/output management.
- Refactored GptDecoderBatched and StatefulGptDecoderBatched to streamline sequence length handling, ensuring consistency across the decoding workflow.
refactor: update SlotDecoderBuffers to manage sequence lengths directly
- Introduced sequenceLengths and sequenceLengthsHost to SlotDecoderBuffers for better management of sequence lengths.
- Refactored asyncSend and recv methods to utilize the new sequenceLengths member, enhancing clarity and reducing redundancy.
- Updated TrtGptModelInflightBatching to align with the new structure, ensuring consistent handling of sequence lengths across the decoding process.
These changes improve maintainability and streamline the decoding workflow.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* refactor: Delegate to asyncSend method in SlotDecoderBuffers
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
---------
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* add test to map flashinfer rope op with triton custom rope ops and pytorch rope in fused_mha
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* add rope matcher and unit tests
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* capture cos and sin from graph
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* revert fuse_mha op change
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* minor update to address comment and remove redundant unit test
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* move view and transpose into graph nodes and update unit test to test custom op directly
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* move view into custom op, update bfs with bound, update custom op return type to be half precision
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* custom op update to support 3D input
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* handle bnsd and bsnd format, update tests, handle 3D cos/sin input to the custom op
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* add llama4 rope test, update custom op with is_neox flag
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* add llama4 style rope to matcher and update unit test
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* separate into two transformations
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* fix when num_head != num_kv_head; add support for cached position_ids and cos_sin_cache in graph; update unit tests
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* minor update, cache locally and propagate meta info of qk nodes
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* minor: fix cos_sin_cache not float
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* minor: move cache into matcher
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
---------
Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com>
* One of the tactic is not supported during dispatch.
* final_hidden_states should be unpacked if it is not min_latency_mode.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* feat: Add NVFP4 UB pattern optimization pass in torch compile
* Add an additional flag for UB fp4 pattern to avoid inverse the scale
* Add NVFP4 related UB patterns
Signed-off-by: Jin Li <59594262+liji-nv@users.noreply.github.com>
* Update atol, some points fails for B200 umbriel.
Signed-off-by: liji-nv <59594262+liji-nv@users.noreply.github.com>
---------
Signed-off-by: Jin Li <59594262+liji-nv@users.noreply.github.com>
Signed-off-by: liji-nv <59594262+liji-nv@users.noreply.github.com>
* Rename nvsmall to nemotron NAS
* Revert nvsmall to nemotron_nas rename in paths in tests that access llm_models_root/nvsmall/tests
* Add NemotronNAS to pytorch supported models table
Signed-off-by: Amit Zuker <203509407+amitz-nv@users.noreply.github.com>
* Add nested aliases for Llama 4
Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
* Fix missed alias.
Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
---------
Signed-off-by: Frank Di Natale <3429989+FrankD412@users.noreply.github.com>
Co-authored-by: Yan Chunwei <328693+Superjomn@users.noreply.github.com>
* fix: broadcast embeddings input when using speculative decoding
Signed-off-by: Maximiliano Levi <maxilevi77@gmail.com>
* fix: use shape tensor instead of tuple
Signed-off-by: Maximiliano Levi <maxilevi77@gmail.com>
* fix: comment
Signed-off-by: Maximiliano Levi <maxilevi77@gmail.com>
---------
Signed-off-by: Maximiliano Levi <maxilevi77@gmail.com>
Co-authored-by: Fanrong Li <23290157+lfr-0531@users.noreply.github.com>
* Instead of allocating UserBuffers at beginning of runtime, UB buffers
are now managed with global allocator. The allocator will dynamically
assign free UB buffer or allocate new buffer for torch tensor. It makes
userbuffers easier to use.
* In common usecase, the Userbuffers will be allocated correctly during
warm up stage. There is no dynamic allocation during inference.
* UB fusion pattern is rewroten using the new UB Allocator. It contains
following passes:
1. Fuse Quant with allreduce, replace with UB impl, and insert a
copy_to_userbuffers. Currently the normal allreduce still does not
support FP8 quant. So this need to be done in UB pass
2. Convert all supported allreduce with UB and insert copy_to_userbuffers.
3. Fuse op before ar with the copy_to_userbuffers. So the op directly
writes to the userbuffer
4. Remove userbuffers finalize if the output is connect to another UB
allreduce.
Signed-off-by: Jin Li <59594262+liji-nv@users.noreply.github.com>
* Several optimizations and fixings on the Autotuner.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Apply the new Python side Autotuner on current linear for nvFP4 data type.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Apply the new Python side Autotuner on MoE op
* Remove routers from cache key to improve inference perf
* Prevent unnecessary code profiling. Use do_preparation keyword to select which part should be executed during before evaluating any tactic.
* Remove try-catch inside moe profiling process.
* Move default tactic -1 to 0 transforms in cpp runner.
* Revise relavant tests.
* Predefined the bucketizing strategy for fused_moe
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Add specific_profile support for AutoTuner to bypass the standard cache search process for perf optimization
* Add specific_profile for moe
* Add specific profile for linear
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Fixing and revising according to reviewer's suggestions.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Use lru_cache for inference pref optimization.
* Revert gen_custom_cache_key feature
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Replace runner with runner id to achieve a serializable cache.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Code clean up and minor fixings.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Move all tunable runners and custom ops into torch_custom_ops.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* Treat min_latency_mode as a independent dynamic tensor. Modify get_valid_tactics to suit for it.
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
---------
Signed-off-by: Yukun He <23156053+hyukn@users.noreply.github.com>
* feat: Add option to run disaggregated serving without ctx servers, to benchmark gen only
Signed-off-by: Patrice Castonguay <55748270+pcastonguay@users.noreply.github.com>
* Fixing comment in sanity check
Signed-off-by: Patrice Castonguay <55748270+pcastonguay@users.noreply.github.com>
---------
Signed-off-by: Patrice Castonguay <55748270+pcastonguay@users.noreply.github.com>
* fp8 kv + bf16 ctx MLA + fp8 gen MLA
Use BF16 for context MLA.
mFP8GenerationMLA and mFP8ContextFMHA shouldn't be enabled together.
Allow mSM==90 for mFP8GenerationMLA==true.
For FMHA, dataTypeKv should be FP8.
For FP8 MLA generation, the output is still in BF16.
Refine debug info for FMHA kernel metadata.
Use inputType, outputType, SM together to hash kernel list.
Add FP8 MLA generation FMHA kernel.
Special WAR of NUM_COMPUTE_GROUPS for MLA generation kernel.
Separate the implementation of fused_multihead_attention_v2.h to CPP and print some debug info if checkIfKernelExist fails.
Refine debug info in fused_multihead_attention_v2.cpp
Correct FP8 MLA metadata.
New kernel provided by Yuxin, which outputs BF16.
smem size is not set correctly, which will lead to illegal mem access.
Yuxin fixed the error in FMHA MLA kernel: previously the BF16 isn't correctly written: some parts are repeatedly written, while some others are untouched.
There are two bmm1 scales that should be set correctly.
New kernel generated by Yuxin.
Modificatiosn to common/attentionOp for FP8 MLA on Hopper using FMHA.
Not necessary. If mFP8GenerationMLA, is_fp8_out is false, so mFP8ContextFMHA is false.
Skip a check in fmhaDispatcher.
Modifications in fmhaRunner:
- Debug dump.
- if (!isFP8GenerationMLA) skips a lot of flag setting.
- TMA descriptor modification for qo (by Yuxin).
Cleanup debug output.
Clean up o tma descriptor modifications.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Resolve conflicts.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Apply the patch of FP8 FlashMLA and resolve conflicts.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Fix compilation error.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Fix compile error.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* pick blackwell support
Signed-off-by: Dylan Chen <191843203+DylanChen-NV@users.noreply.github.com>
* Add copyright notice to fused_multihead_attention_v2.cpp.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Add license.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Add missing license.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Exclude building flashMLA kernels under sm90.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Revert "Exclude building flashMLA kernels under sm90."
This reverts commit f0c859d459.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
* Use macro to skip compiling FlashMLA for non sm90 targets.
Signed-off-by: Bo Li <bobboli0202@gmail.com>
---------
Signed-off-by: Bo Li <bobboli0202@gmail.com>
Signed-off-by: Dylan Chen <191843203+DylanChen-NV@users.noreply.github.com>
Co-authored-by: Dylan Chen <ziqingc@nvidia.com>
Co-authored-by: Dylan Chen <191843203+DylanChen-NV@users.noreply.github.com>
Co-authored-by: QI JUN <22017000+QiJune@users.noreply.github.com>
* refactor: Expose DecoderState via bindings and integrate in TRTLLMDecoder
- Introduced a new `DecoderState` class in the C++ bindings, encapsulating key functionalities for managing decoding state.
- Adjusted the Python `TRTLLMDecoder` to access properties from `decoder_state`, ensuring consistency and clarity in the decoding process.
These changes streamline the decoder's architecture and enhance maintainability.
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* chore: Remove unused new_tokens from DecoderState bindings
Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
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Signed-off-by: Robin Kobus <19427718+Funatiq@users.noreply.github.com>
* init trtllm attn no cache
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* fix: fix the seq_len issue and attn metadata prepare for qwen reward model test
fix: fix minor bugs after rebase
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: remove unnecessary debug logs and clean up commented code
refactor: update max_seq_len documentation and remove max_seq_len for decoder model contructor in PyTorchModelEngine
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: update calculate_ref_result function to accept tensor inputs and mask type, enhance test_attention_no_cache to support FULL and CAUSAL masks
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: remove unused BERT attention metadata conversion method and add type assertion for no cache attention in PyTorchModelEngine
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: remove use_kv_cache parameter from attention function and related classes, update documentation for KV cache handling
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: implement setAttentionMaskType method for better mask type handling and remove unused conversion function
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: streamline KV cache handling by replacing direct member access with useKVCache method and simplify token per block assignment
remove Debug code.
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: Resolve comments for Python code
Simplify no cache attention metadata preparation and streamline related attributes in TrtllmAttentionMetadata
Removed the private method for converting to no cache attention metadata and integrated its logic into the prepare method. Updated the test for BERT sequence classification to reflect these changes and ensure proper handling of attention metadata.
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* docs: Add is_dummy_attention field to attention metadata for simulation operations
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* refactor: add KVCacheParams to attention backend interface and import relevant metadata classes
Updated the attention backend interface to include KVCacheParams and imported TrtllmAttentionMetadata and VanillaAttentionMetadata in model_engine.py for enhanced functionality.
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* fix: fix rebase format issue
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* fix: extend attention mask type handling in MHARunnerFixedParams
Added support for additional attention mask types (BIDIRECTIONAL, BIDIRECTIONALGLM, BLOCKSPARSE) in the MHARunnerFixedParams structure to fix the mapping issue between ContextAttentionMaskType and AttentionMaskType
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* fix: enhance attention mask type handling in TllmGenFmhaRunnerParams
Updated the setAttentionMaskType method to include a switch-case structure for better handling of attention mask types, ensuring proper mapping and error handling for invalid types.
Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
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Signed-off-by: Qixiang Lin <qixiangl@nvidia.com>
* fix acceptance rate of pytorch workflow.
* revert the RequestOutput API change.
---------
Signed-off-by: Fanrong Li <23290157+lfr-0531@users.noreply.github.com>
