A snow-route dispatch desk exported the same refined encoder as a PyTorch checkpoint, an ONNX graph, and a TensorRT engine. How should they choose the Triton backend?
Select an answer to reveal the explanation.
Short Explanation
PyTorch checkpoint, ONNX graph, or TensorRT engine: pick the Triton backend that matches the file you will actually deploy. Do not invent a product that eats all three, force NCCL, or shove ONNX through a video pipeline.
Full Explanation
The Triton backend follows the file you exported: a PyTorch checkpoint, an ONNX graph, or a TensorRT engine each has a matching backend family. That is an associate selection, not an engine-build-flag drill and not a new product name. NCCL is not a substitute backend for those three artifacts. Pushing ONNX through a multimodal video path does not make the format match, and inventing an NVIDIA product is out of bounds.