Qwen3vl ViT Runner#

class Qwen3VLViTRunner : public trt_edgellm::rt::QwenViTRunner#

Qwen3-VL / Qwen3.5 vision encoder. Extends the Qwen2-VL base with FAST-POS-EMBED + DEEPSTACK, a 3D temporal resize budget, and per-frame timestamped video sub-spans. Mirror of HF modeling_qwen3_vl.py.

Subclassed by trt_edgellm::rt::Cosmos3EdgeViTRunner, trt_edgellm::rt::Qwen3OmniViTRunner

Public Functions

virtual std::vector<std::reference_wrapper<rt::Tensor>> getDeepstackFeatures(
) override#

Get deepstack features for Qwen3-VL models.

Returns:

Writable raw features before embedding lookup; empty when the model has no deepstack

QwenViTRunner(
std::string const &engineDir,
int32_t llmMaxBatchSize,
int32_t llmMaxSequenceLength,
cudaStream_t stream
)#

Constructor for QwenViTRunner.

Parameters:

  • engineDir – [in] Directory containing the TensorRT engine files

  • llmMaxBatchSize – [in] Maximum batch size from LLM engine

  • llmMaxSequenceLength – [in] Maximum sequence length from LLM engine

  • stream – [in] CUDA stream for execution

Throws:

  • std::runtime_error – if engine directory does not contain engine files, or if buffer allocation fails

  • json::type_error – if JSON configuration contains unexpected datatypes