How do I install a specific PyTorch version in rTorch

[f0nzie]

No description provided.

[f0nzie]

From the R prompt in RStudio.

This will install the latest stable PyTorch for Python 3.6:

rTorch:::install_conda(package="pytorch", envname="r-torch", conda="auto", conda_python_version = "3.6", pip=FALSE, channel="pytorch", extra_packages=c("torchvision", "cpuonly", "matplotlib", "pandas"))

This will install PyTorch 1.2 under Python 3.7:

rTorch:::install_conda(package="pytorch=1.2", envname="r-torch", conda="auto", conda_python_version = "3.7", pip=FALSE, channel="pytorch", extra_packages=c("torchvision", "cpuonly", "matplotlib", "pandas"))

This will install PyTorch 1.5 under Python 3.8:

rTorch:::install_conda(package="pytorch=1.5", envname="r-torch", conda="auto", conda_python_version = "3.8", pip=FALSE, channel="pytorch", extra_packages=c("torchvision", "cpuonly", "matplotlib", "pandas", "bokeh"))

These commands have been tested in:

• MacOS Mojave running R 3.6 inside RStudio 1.2.5001. rTorch 0.0.3 was installed from CRAN.
• Windows 10 running R 3.6 inside RStudio 1.3.959. rTorch 0.0.3 was installed from CRAN.

[beew]

Hi, I wonder if there is a way for rTorch to choose from among python and pytorch versions already installed in the system without conda. What I mean is like tenorflow-r, where you can use the function use_python('path/to/python/binary") or Sys.setenv(RETICULATE_PYTHON="path/to/python/binary") to choose from the python versions already installed in the system without needing to create a conda along with all the extra junks that it pulls in.

I have 4 pythons on my system. python2.7 and python3.5.4 which come with the system and I don't use for developmental purpose. I have python-3.7.8 and 3.8.5 installed in local folders for development (each with its own configuration script) and I have tested tensorflow-r using the use_python function and the RETICULATE_PYTHON environmental variable described above. Is it possible to do something similar with rTorch?

OS is Ubuntu Linux.

[beew]

OK, it works just like r-tensorflow. use_python() will do the job

[f0nzie]

I borrowed functions from reticulate and tensorflow for the PyTorch installation under Python. I adapted those functions for PyTorch. They worked fine until PyTorch 1.2. Then, PyTorch introduced changes that made it a little bit different. So, my function install_pytorch() stopped working. But the lower level functions do work. Such as rTorch:::install_conda(). I am working these days on a newer version that takes changes in PyTorch 1.6. If you want to try, all is the develop branch.

[beew]

Actually I just tested with PyTorch-1.4 and it works.

[beew]

Actually it works for PyTorch 1.6.0 as well (I have several pythons installed locally) , except for a small issue with reticulate rstudio/reticulate#836 (comment)

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> Sys.setenv(LD_LIBRARY_PATH = paste("/home/bee/opt/python385/lib", Sys.getenv("LD_LIBRARY_PATH"), sep = ":"))
> library(rTorch)
> use_python("/home/bee/opt/python385/bin/python")
> torch_config()
PyTorch v1.6.0 (~/opt/python385/lib/python3.8/site-packages/torch)

Python v3.8 (~/opt/python385/bin/python)

> bt <- torch$ByteTensor(3L, 3L)
> ft <- torch$FloatTensor(3L, 3L)
> dt <- torch$DoubleTensor(3L, 3L
+ )
> lt <- torch$LongTensor(3L, 3L)
> Bt <- torch$BoolTensor(5L, 5L)
> ft
tensor([[1.2019e+36, 4.5758e-41, 1.2019e+36],
        [4.5758e-41, 0.0000e+00, 0.0000e+00],
        [0.0000e+00, 0.0000e+00, 0.0000e+00]])
> Bt
tensor([[ True,  True,  True,  True,  True],
        [ True, False, False,  True,  True],
        [ True,  True,  True,  True, False],
        [False,  True, False, False, False],
        [False, False, False, False,  True]])
> 

[f0nzie]

Awesome!