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### Description This PR adds support for `float64` kernels in the latest versions of operators: Floor, Ceil and IsNaN. ### Motivation and Context The lack of these kernels is non-trivial to work around and easily lead to performance losses when it is attempted. When equivalence with an existing implementation is required, precision is easily lost when casting to `float32` instead. IsNaN is common when cleaning up data in an ML pipeline. Floor and Ceil have uses for discretising values and single-precision floats are insufficient to round well when values get larger than a few million. According to my measurement this only increases the binary size by a few kilobytes (on the Python wheel of RelWithDebInfo). Closes #13673 (Round already has float64 support) Partially solves #8791 (Looks like there's parallel issues/PR open for Split, but it is also hard to work around and hence useful) Signed-off-by: jbachurski <kbachurski@gmail.com> |
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| .. | ||
| c_cxx | ||
| execution_providers/images | ||
| images | ||
| python | ||
| ABI_Dev_Notes.md | ||
| Android_testing.md | ||
| C_API_Guidelines.md | ||
| cmake_guideline.md | ||
| Coding_Conventions_and_Standards.md | ||
| ContribOperators.md | ||
| FAQ.md | ||
| How_To_Update_ONNX_Dev_Notes.md | ||
| Memory_Optimizer.md | ||
| Model_Test.md | ||
| NotesOnThreading.md | ||
| ONNX_Runtime_Server_Usage.md | ||
| onnxruntime_dependencies.dot | ||
| onnxruntime_dependencies.png | ||
| onnxruntime_extensions.md | ||
| OperatorKernels.md | ||
| ORT_Format_Update_in_1.13.md | ||
| ORTMobilePackageOperatorTypeSupport.md | ||
| ORTModule_Training_Guidelines.md | ||
| PR_Guidelines.md | ||
| Privacy.md | ||
| Python_Dev_Notes.md | ||
| Reduced_Operator_Kernel_build.md | ||
| ReleaseManagement.md | ||
| Roadmap.md | ||
| Server.md | ||
| TVM_EP.md | ||
| Versioning.md | ||
| WinML_principles.md | ||
