Thanks for the suggestion. I am already only installing "nomkl" for macOS
with "if (Sys.info()["sysname"] == "Darwin") "nomkl==3.0" else c()".
On Sat, Jul 8, 2023 at 11:09 PM Aaron Lun <
infinite.monkeys.with.keyboa...@gmail.com> wrote:
> Not hard to have OS-specific environments, see for example
Not hard to have OS-specific environments, see for example:
https://github.com/alanocallaghan/snifter/blob/devel/R/basilisk.R
-A
On 7/6/23 20:23, Kasper Daniel Hansen wrote:
This sounds excellent Kim!
Here you can get 2.10 for Windows: https://anaconda.org/anaconda/tensorflow
although my expe
Thanks! I now only used the anaconda channel to install both tensorflow and
tensorflow-probability.
This works fine for Linux and Windows, but now macOS crashes with "Intel
MKL FATAL ERROR: Cannot load libmkl_intel_thread.1.dylib" (
https://github.com/cbg-ethz/pareg/actions/runs/5489390187/jobs/100
This sounds excellent Kim!
Here you can get 2.10 for Windows: https://anaconda.org/anaconda/tensorflow
although my experience is that I hate mixing channels on conda. It is also
quite interesting that this conda package also has Windows at an older
version (but just 2.10 vs. 2.12)
This really spe
Thank you all so much for your input and the references!
@Kasper: I mostly rely on tensorflow and tensorflow-probability, so I might
somehow get rid of the keras dependency but it would require some work.
After being inspired by the lovely orthos package (thanks Charlotte!), I
decided to play aro
That's great news. FWIW I am finding that the advice at
https://rstudio.github.io/reticulate/articles/python_dependencies.html
can work to produce properly resolved python dependencies. Just don't
follow the example literally; the requested
scipy version may not exist. Version 1.11.1 does. Stay
Hi,
in case it's useful: we have a package (orthos) in review
(https://github.com/Bioconductor/Contributions/issues/3042) which uses basilisk
to set up a conda environment with tensorflow and keras. It builds and runs
fine both on GitHub Actions (GitHub repo here:
https://github.com/fmicompbi
So I think Kim is interfacing to tensorflow by using the keras package from
CRAN (partly authored by the Rstudio people). This package leaves it to the
user to install tensorflow, which is a highly non-trivial installation
task. There is some partly helpful instructions for using conda together
wit
I'll try to get clearer on the basilisk situation; I forked your repo
and will plunge in soon.
It may take a while. In the mean time I hope the BBS python stack can
be looked at
to see what the issue might be. @Jennifer Wokaty is it possible with
the recent R upgrades that
tensorflow and tensorfl
Thanks a lot for your response!
The Config/reticulate approach in DESCRIPTION looks very neat. I hope we
can use it at some point.
Could the issue you are facing with the conda install be, that the package
is called "tensorflow-probability" instead of "tensorflow_probability" (
https://anaconda.o
Sorry to hear about this. Our informal outlook on python
interoperation in Bioconductor packages is that
the basilisk discipline should be used. This allows you to pin
specific versions of all python dependencies
and use python for your R functions from an insulated conda environment.
There is a
Hello,
The latest builds of my package 'pareg' started failing on BioC 3.17 for
Linux and macOS but not Windows:
https://master.bioconductor.org/checkResults/3.17/bioc-LATEST/pareg/nebbiolo1-buildsrc.html
.
In both cases, the error messages is "Python module tensorflow_probability
was not found".
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