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### Description Fixes the issue with IRFFT output dimension calculation as described in #13236 ### Motivation and Context Please refer to #13236 for detailed description. Specifically, [this code](https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/contrib_ops/cuda/math/fft_ops.cc#L103) computes the output dimension as: ``` out_dim = in_dim * 2 - 1 ``` while it should be this instead: ``` out_dim = 2 * (in_dim - 1) ``` (assuming the original signal has even number of samples, of course). For example, if the original signal has 4 samples, then the round trip should look something like: ``` 4 -> (one-sided RFFT) -> 3 (complex) -> (one-sided IRFFT) -> 4 ``` with the current code the output will be a signal with 5 points. --------- Co-authored-by: Alexey Kamenev <akamenev@nvidia.com> Co-authored-by: Nick Geneva <nicholasgeneva@gmail.com> |
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| c_cxx | ||
| execution_providers/images | ||
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| 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 | ||
| ORT_Use_Trtion_Kernel.md | ||
| ORTMobilePackageOperatorTypeSupport.md | ||
| ORTModule_Convergence_Notes.md | ||
| ORTModule_ModuleWithLoss_Wrapper.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 | ||
