feat: optional deps handling for ONNX runtime#3792
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This makes it possible to load docling with ONNX without needing torch/transformer deps: - Moved the module-level torch and transformers imports down into the load methods. - Fixed device selection to gracefully fall back to CPU when torch isn't around - Wrapped engine registration in a guarded loader. If an optional backend (like TableFormer v2) is missing, we just skip it now instead of crashing the factory setup. - Added a numpy image processor fallback for ONNX. This handles the RT-DETR layout presets without needing torch. Output is identical to the transformers version. Signed-off-by: Amin Ya <aminyahyaabadi74@gmail.com>
Signed-off-by: Amin Ya <aminyahyaabadi74@gmail.com>
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Added the unit test |
docling-ibm-models imports torch/torchvision Signed-off-by: Amin Ya <aminyahyaabadi74@gmail.com>
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This makes it possible to load docling with ONNX without needing torch/transformer deps:
Checklist: