mirror of
https://github.com/saymrwulf/onnxruntime.git
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398ef677ba
1. Now we use a released version of ONNX, so we can directly download a prebuilt package from pypi.org. We do not need to build one from source. 2. Update protobuf python package's version to match the C/C++ version we are using. 3. Update tensorboard python python because the current one is incompatible with the newer protobuf version. |
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| .. | ||
| inference | ||
| scripts | ||
| Dockerfile.manylinux2_28_cpu | ||
| Dockerfile.manylinux2_28_cuda | ||
| Dockerfile.manylinux2_28_rocm | ||
| Dockerfile.manylinux2_28_training_cuda11_8 | ||
| Dockerfile.manylinux2014_aten_cpu | ||
| Dockerfile.manylinux2014_lort_cpu | ||
| Dockerfile.package_ubi8_cuda11_8_tensorrt8_6 | ||
| Dockerfile.package_ubuntu_cuda11_8_tensorrt8_6 | ||
| Dockerfile.ubuntu_cuda11_6_tensorrt8_4 | ||
| Dockerfile.ubuntu_cuda11_8_tensorrt8_5 | ||
| Dockerfile.ubuntu_cuda11_8_tensorrt8_6 | ||
| Dockerfile.ubuntu_gpu_training | ||
| Dockerfile.ubuntu_openvino | ||
| Dockerfile.ubuntu_tensorrt_bin | ||
| Dockerfile_manylinux2014_openvino_multipython | ||
| manylinux.patch | ||
| migraphx-ci-pipeline-env.Dockerfile | ||