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Tools to deploy 'TensorFlow' <https://www.tensorflow.org/> models across multiple services. Currently, it provides a local server for testing 'cloudml' compatible services.
| Version: | 0.6.1 |
| Imports: | httpuv, httr, jsonlite, magrittr, reticulate, swagger, tensorflow |
| Suggests: | cloudml, knitr, pixels, processx, testthat, yaml, stringr |
| Published: | 2019-06-14 |
| Author: | Javier Luraschi [aut, ctb], Daniel Falbel [cre, ctb], RStudio [cph] |
| Maintainer: | Daniel Falbel <daniel at rstudio.com> |
| License: | Apache License 2.0 |
| NeedsCompilation: | no |
| Materials: | README |
| In views: | ModelDeployment |
| CRAN checks: | tfdeploy results |
| Reference manual: | tfdeploy.pdf |
| Vignettes: |
Deploying TensorFlow Models Using Saved Models from R |
| Package source: | tfdeploy_0.6.1.tar.gz |
| Windows binaries: | r-devel: tfdeploy_0.6.1.zip, r-release: tfdeploy_0.6.1.zip, r-oldrel: tfdeploy_0.6.1.zip |
| macOS binaries: | r-release (arm64): tfdeploy_0.6.1.tgz, r-oldrel (arm64): tfdeploy_0.6.1.tgz, r-release (x86_64): tfdeploy_0.6.1.tgz, r-oldrel (x86_64): tfdeploy_0.6.1.tgz |
| Old sources: | tfdeploy archive |
Please use the canonical form https://CRAN.R-project.org/package=tfdeploy to link to this page.
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.
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