'R' implementation and interface of the Machine Learning platform
'PyTorch' <https://pytorch.org/> developed in 'Python'. It requires a 'conda'
environment with 'torch' and 'torchvision' Python packages to provide
'PyTorch' functions, methods and classes. The key object in 'PyTorch' is the
tensor which is in essence a multidimensional array. These tensors are fairly
flexible in performing calculations in CPUs as well as 'GPUs' to accelerate
tensor operations.
| Version: |
0.4.2 |
| Depends: |
R (≥ 3.1) |
| Imports: |
reticulate (≥ 1.10), jsonlite (≥ 1.2), utils, methods, rstudioapi (≥ 0.7) |
| Suggests: |
testthat, knitr, rmarkdown |
| Published: |
2020-10-12 |
| DOI: |
10.32614/CRAN.package.rTorch |
| Author: |
Alfonso R. Reyes [aut, cre, cph] |
| Maintainer: |
Alfonso R. Reyes <alfonso.reyes at oilgainsanalytics.com> |
| BugReports: |
https://github.com/f0nzie/rTorch/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/f0nzie/rTorch |
| NeedsCompilation: |
no |
| SystemRequirements: |
"conda (python>=3.6 pytorch torchvision cpuonly
numpy ( >= 1.14.0) matplotlib pandas -c pytorch);
python-minimal, pandoc pandoc-citeproc, qpdf; Python (>=3.6),
pytorch (>=1.4), torchvision, cpuonly, numpy ( >= 1.14.0);
pandoc (>= 2.0), qpdf ( >= 7.0) on Solaris" |
| Materials: |
README NEWS |
| CRAN checks: |
rTorch results |