[pull] main from NVIDIA:main#361
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pull[bot] merged 7 commits intoyingguo-trt:mainfrom Apr 6, 2026
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Signed-off-by: Harris Nover <249353502+hnover-nv@users.noreply.github.com>
…ampler (#12358) Signed-off-by: Eran Geva <19514940+MrGeva@users.noreply.github.com>
…ts (#12724) Signed-off-by: Dongfeng Yu <dongfengy@nvidia.com>
Signed-off-by: Yuanjing Xue <197832395+yuanjingx87@users.noreply.github.com>
Signed-off-by: Govind Ramnarayan <105831528+govind-ramnarayan@users.noreply.github.com>
* Why?
We would like to be able to use a TorchLlmArgs config in
AutoDeploy's own version with minimal changes.
* What?
This commit removes the redefinition of:
- `model_kwargs`: existing usages guarded against `None` the same way
as an empty dict.
- `max_batch_size: most unit tests set it explicitly; a few configs were
updated to have the old default.
- `max_beam_width`: instead adds a validator for it.
- `att_backend`: although the default between the base class ("TRTLLM")
and autodeploy ("flashinfer") differ, the
`update_transforms_with_shortcuts` validator in practice reads the
default from `default.yaml`, which is "flashinfer".
- `sampler`: the executor code already supported both. We just tweak it
so that the "auto" value corresponds to the now removed default.
It also removes the `cuda_graph_batch_sizes` in favor of
`cuda_graph_config.batch_sizes`, with necessary adjustments to unit
tests and existing configs.
Signed-off-by: William Zhang <133824995+2ez4bz@users.noreply.github.com>
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