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Add ONNX Runtime tensor conversions
- #19
#19
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yuanknv
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feature/torch-conversions-py
ros2/rosidl_buffer_backends:feature/torch-conversions-py
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feature/onnxruntime-conversions
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Add ONNX Runtime tensor conversions
#19
yuanknv
wants to merge 54 commits into
feature/torch-conversions-py
ros2/rosidl_buffer_backends:feature/torch-conversions-py
from
feature/onnxruntime-conversions
ros2/rosidl_buffer_backends:feature/onnxruntime-conversions
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Commits on Sep 10, 2026
feat: add ONNX Runtime tensor conversions (#14)
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refactor: split ONNX Runtime CPU and CUDA packages (#14)
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feat: unify ONNX Runtime conversions across CPU and CUDA (#14)
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feat: vendor Python ONNX Runtime (#14)
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fix: require explicit CUDA streams for ONNX conversions (#14)
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refactor: make ONNX conversions platform-independent (#14)
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refactor: split ONNX Runtime providers and add ARM support (#14)
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refactor: remove redundant ONNX package files (#14)
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refactor: preserve Python ONNX Runtime wheels (#14)
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refactor: select Python ONNX backend by package (#14)
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refactor: register Python ONNX backends (#14)
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fix: select Python ONNX wheel from CUDA toolkit (#14)
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docs: add ONNX Runtime conversions guide (#14)
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docs: clarify ONNX conversion installation (#14)
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refactor: rename ONNX Runtime conversion packages
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refactor: rename conversion backends to adapters
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fix: clean CUDA conversion linkage
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refactor: split ONNX Runtime conversions into CPU and CUDA plugins
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docs: document ONNX Runtime conversion plugin packages
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refactor(onnxruntime_conversions)!: build on the framework-free DLPack core
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fix(onnxruntime_conversions): copy device values and keep tests CPU-buildable
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docs: describe the framework-free ONNX Runtime layout
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fix(onnxruntime_conversions): build CUDA tests only against a CUDA-capable runtime
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test(onnxruntime_conversions): serialize test models instead of depending on onnx
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fix: declare cuda-toolkit instead of nvidia-cuda
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chore: carry one version across the repo
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feat(onnxruntime_vendor): unify the stack on ONNX Runtime 1.29.0
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test(onnxruntime_conversions): drop the onnx package dependency
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docs: refresh the ONNX Runtime version and vendor story
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fix(onnxruntime_conversions): depend on one ONNX Runtime provider
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fix(dlpack_conversions): resolve the default backend per call
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docs(onnxruntime_conversions): trim redundant dependency comments
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refactor(torch_conversions): take the execution stream from the caller
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Commits on Sep 11, 2026
refactor(onnxruntime_conversions): use native CPU and CUDA plugins
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refactor(onnxruntime_vendor): remove embedded artifact digests
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chore: remove local Docker validation files
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Merge updated Torch conversion base
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Merge remote-tracking branch 'origin/feature/torch-conversions-py' into pr19
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chore: trim ONNX Runtime pull request
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test: consolidate ONNX Runtime test scaffolding
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Merge remote-tracking branch 'origin/feature/torch-conversions-py' into pr19
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test: combine overlapping ONNX Runtime GTests
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Clean up ONNX Runtime conversions and regression tests
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Merge Torch audit cleanup into ONNX Runtime branch
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Commits on Sep 12, 2026
Merge Torch stream and device fixes into ONNX Runtime branch
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Add portable ONNX Runtime streams and tighten device handling
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Commits on Sep 14, 2026
Clarify ONNX Runtime publication examples and test live bindings
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Merge Torch publication updates into ONNX Runtime branch
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docs: simplify conversion READMEs
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Commits on Sep 17, 2026
Merge Torch README cleanup into ONNX Runtime branch
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Reuse compatible ONNX Runtime providers with CUDA 12 and 13
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Build ONNX test models with the native model API
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Use the generic CUDA toolkit dependency for ONNX Runtime
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Support ARM ONNX Runtime vendors and simplify provider discovery
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