tensorrt-dft-plugins | Simple implementation of TensorRT [I]RFFT[2] plugins

by Alexey-Kamenev C++ Version: Current License: Non-SPDX

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kandi X-RAY | tensorrt-dft-plugins Summary

tensorrt-dft-plugins is a C++ library. tensorrt-dft-plugins has no bugs, it has no vulnerabilities and it has low support. However tensorrt-dft-plugins has a Non-SPDX License. You can download it from GitHub.

Simple implementation of TensorRT [I]RFFT[2] plugins.

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tensorrt-dft-plugins has a low active ecosystem.

It has 1 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

tensorrt-dft-plugins has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tensorrt-dft-plugins is current.

Quality

tensorrt-dft-plugins has no bugs reported.

Security

tensorrt-dft-plugins has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

tensorrt-dft-plugins has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

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tensorrt-dft-plugins releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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tensorrt-dft-plugins Key Features

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tensorrt-dft-plugins Examples and Code Snippets

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Install tensorrt-dft-plugins

You can download it from GitHub.

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RFFT and RFFT2, which correspond to torch.fft.rfft and torch.fft.rfft2 respectively. PyTorch operators must be exported to ONNX using ONNX Contrib Rfft operator.IRFFT and IRFFT2, which correspond to torch.fft.irfft and torch.fft.irfft2 respectively. PyTorch operators must be exported to ONNX using ONNX Contrib Irfft operator.

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