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* Make ORT as Pytorch JIT backend LORT likely doesn't work with aten fallback so we only test LORT in its own CI. * Revert changes to enable external CUDA allocator. Will add it later. Revert "Revert changes to enable external CUDA allocator. Will add it later." This reverts commit d5487f2e193014c805505afae8fb577c53667658. Fix external allocator * Relax tolerance and remove commented code * Print more information in CI * Fix pointer * Address comments. 1. Reuse ORT-eager mode's environment. 2. Remove unused ctor. * Use Pytorch master branch as all PRs are merged Fix * Refine based on cpplint feedbacks * Revert changes to allow custom CUDA allocator in public APIs * Use torch.testing.assert_close * Use unittest framework * Switch docker repo * Rename *.cpp to *.cc * Address comments * Add comment * Use same pipeline file for eager and lort pipelines * Address comments * Add yaml comment * Fix cmake files * Address comments * Rename flags, remove printing code, remove dead comment |
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| .. | ||
| docker | ||
| ort_minimal | ||
| tvm | ||
| build_cuda_c_api_package.sh | ||
| build_yocto.sh | ||
| copy_strip_binary.sh | ||
| create_package.sh | ||
| extract_and_bundle_gpu_package.sh | ||
| java_copy_strip_binary.sh | ||
| java_linux_final_test.sh | ||
| run_build.sh | ||
| run_dockerbuild.sh | ||
| test_custom_ops_pytorch_export.sh | ||
| upload_code_coverage_data.sh | ||
| upload_ortsrv_binaries.sh | ||
| yocto_build_toolchain.sh | ||