mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-06-13 01:09:22 +00:00
207c57219a
Add support for ViT optimization in optimizer.py As ViT architecture follows BERT rather closely, we can easily reuse BERT fusions for ViT. The only difference is that ViT does not have attention mask, which means there is no Add node in qk paths. Make the necessary changes in onnx_exporter.py to be able to cover optimizations with test. |
||
|---|---|---|
| .. | ||
| backend | ||
| datasets | ||
| providers/tvm | ||
| tools | ||
| torch_cpp_extensions | ||
| training | ||
| __init__.py | ||
| _ld_preload.py | ||
| _pybind_state.py.in | ||
| exported_symbols.lst | ||
| numpy_helper.h | ||
| onnxruntime_collect_build_info.py | ||
| onnxruntime_inference_collection.py | ||
| onnxruntime_pybind.h | ||
| onnxruntime_pybind_exceptions.cc | ||
| onnxruntime_pybind_exceptions.h | ||
| onnxruntime_pybind_iobinding.cc | ||
| onnxruntime_pybind_mlvalue.cc | ||
| onnxruntime_pybind_mlvalue.h | ||
| onnxruntime_pybind_module.cc | ||
| onnxruntime_pybind_ortvalue.cc | ||
| onnxruntime_pybind_schema.cc | ||
| onnxruntime_pybind_sparse_tensor.cc | ||
| onnxruntime_pybind_state.cc | ||
| onnxruntime_pybind_state.h | ||
| onnxruntime_pybind_state_common.cc | ||
| onnxruntime_pybind_state_common.h | ||
| onnxruntime_validation.py | ||
| pybind.def | ||
| version_script.lds | ||
| version_script_expose_onnx_protobuf.lds | ||