knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
Although, Python and PyTorch can be installed directly from the R console, before start running rTorch
, I would recommend testing PyTorch first in a new Python or Anaconda environment. Check if PyTorch and Torchvision packages are imported alright. The advantage of doing it this way is that you could have already in advance a PyTorch version that you are sure is working alright.
If you prefer to install PyTorch and its dependencies, that can be done from rTorch through one its functions install_pytorch()
.
This function is public and can be invoked with rTorch::install_pytorch()
.
This function will allow you to indicate (i) the Python version; (ii) the PyTorch version; (iii) the name of the conda environment; (iv) which channel (stable
or nightly
); (v) if you require CUDA (GPU) computation; (vi) additional packages such as matplotlib
, pandas
; (vii) more.
install_pytorch( method = c("conda", "virtualenv", "auto"), conda = "auto", version = "default", envname = "r-torch", extra_packages = NULL, restart_session = TRUE, conda_python_version = "3.6", pip = FALSE, channel = "stable", cuda_version = NULL, dry_run = FALSE, ... )
If you prefer do it manually, use this example:
Create a conda environment with conda create -n my-torch python=3.7 -y
Activate the new environment with conda activate my-torch
Inside the new environment, install PyTorch and related packages with:
conda install python=3.6 pytorch torchvision matplotlib pandas -c pytorch
Note: If you you don't specify a version,
conda
will install the latest PyTorch. As of this writing (August-September 2020), the latest PyTorch version is 1.6.
Alternatively, you could create and install a conda environment a specific PyTorch version with:
conda create -n my-torch python=3.6 pytorch=1.3 torchvision matplotlib pandas -c pytorch -y
conda
will resolve the dependencies and versions of the other packages automatically, or let you know your options.
Note. matplotlib
and pandas
are not really necessary, but I was asked if matplotlib
or pandas
would work in PyTorch. Then, I decided to put them for testing and experimentation. They both work.
In rTorch there is an automatic detection of Python built in in the package that will ask you to install Miniconda
first if you don't have any Python installed in your machine. For instance, in macOS
, Miniconda will be installed under PREFIX=/Users/user_name/Library/r-miniconda
.
After Miniconda is installed, you could proceed to install the flavor or PyTorch you want, and the packages you want, with a command like this:
rTorch:::install_conda(package="pytorch=1.4", envname="r-torch", conda="auto", conda_python_version = "3.6", pip=FALSE, channel="pytorch", extra_packages=c("torchvision", "cpuonly", "matplotlib", "pandas"))
The command above will install the stable PyTorch 1.4 version on Python 3.6, including three additional packages: torchvision
, cpuonly
, matplotlib
and pandas.
NOTE. My experience with
Miniconda
is spotty and not 100% reliable, specially in macOS. I would strongly recommend using full conda for your PyTorch installation.
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