install_gluonts | R Documentation |
install_gluonts()
: Installs GluonTS
Probabilisitic Deep Learning Time Series Forecasting Software
using reticulate::py_install()
.
A Python
Environment will be created named r-gluonts
.
When loaded with library(modeltime.gluonts)
, the modeltime.gluonts
R package
will connect to the r-gluonts
Python environment by default. See "Details" for
connecting to custom python environments.
If fresh_install
, will remove any prior installations of the "r-gluonts" python environment
If include_pytorch
, will install additional dependencies needed for the optional
pytorch backend that is available in some algorithms.
uninstall_gluonts()
: Will remove the "r-gluonts" python environment and python packages
install_gluonts(fresh_install = FALSE, include_pytorch = FALSE)
uninstall_gluonts()
fresh_install |
If |
include_pytorch |
If |
Options for Connecting to Python
Recommended Use Pre-Configured Python Environment: Use install_gluonts()
to
install GluonTS Python Libraries into a conda environment named 'r-gluonts'.
Advanced Use a Custom Python Environment: Before running library(modeltime.gluonts)
,
use Sys.setenv(GLUONTS_PYTHON = 'path/to/python')
to set the path of your
python executable in an environment that has 'gluonts', 'mxnet', 'numpy', 'pandas',
and 'pathlib' available as dependencies.
Package Manager Support (Python Environment)
Conda Environments: Currently, install_gluonts()
supports Conda and Miniconda Environments.
Virtual Environments: are not currently supported with the default installation method, install_gluonts()
.
However, you can connect to virtual environment that you have created using
Sys.setenv(GLUONTS_PYTHON = 'path/to/python')
prior to running library(modeltime.ensemble)
.
## Not run:
install_gluonts()
## End(Not run)
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