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R Interface to 'ONNX' - Open Neural Network Exchange <https://onnx.ai/>. 'ONNX' provides an open source format for machine learning models. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types.
Version: | 0.0.3 |
Depends: | R (≥ 3.1) |
Imports: | reticulate (≥ 1.4) |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2021-04-16 |
DOI: | 10.32614/CRAN.package.onnx |
Author: | Yuan Tang [aut, cre], ONNX Authors [aut, cph], Facebook, Inc. [cph], Microsoft Corporation [cph] |
Maintainer: | Yuan Tang <terrytangyuan at gmail.com> |
BugReports: | https://github.com/onnx/onnx-r/issues |
License: | MIT License + file LICENSE |
URL: | https://github.com/onnx/onnx-r |
NeedsCompilation: | no |
Materials: | README NEWS |
In views: | ModelDeployment |
CRAN checks: | onnx results |
Reference manual: | onnx.pdf |
Vignettes: |
Load and Run an ONNX Model Creating ONNX Protobuf |
Package source: | onnx_0.0.3.tar.gz |
Windows binaries: | r-devel: onnx_0.0.3.zip, r-release: onnx_0.0.3.zip, r-oldrel: onnx_0.0.3.zip |
macOS binaries: | r-release (arm64): onnx_0.0.3.tgz, r-oldrel (arm64): onnx_0.0.3.tgz, r-release (x86_64): onnx_0.0.3.tgz, r-oldrel (x86_64): onnx_0.0.3.tgz |
Old sources: | onnx archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.