Hi all,
Thanks for your replies. I had a look at the greta package
(https://github.com/greta-dev/greta) on CRAN that uses tensorflow,
which seemingly exports the install_tensorflow function but still
requires the user to call it, so it looks like that's the best way to
go for now. I'll submit our
FWIW the tensorflow authors didn't opt for automatic lazy installation:
> run_example("hello.R")
Error: Installation of TensorFlow not found.
Python environments searched for 'tensorflow' package:
/usr/bin/python2.7
/usr/bin/python3.5
You can install TensorFlow using the install_t
The problem with requiring explicit tensor flow installation is that
it is tantamount to a system dependency in many ways, and those are
annoying. Herve points out the problems with installing at load time.
My suggestion was to install the package the first time someone tries
to e.g. load an R matr
Hi Hervé, Michael,
Thanks for your feedback. I will add in the reticulate check to ensure
tensorflow is installed prior to running and appropriate sections in
the vignettes. We have one package essentially ready for submission to
bioc, so is the best route forward to submit now or wait until
tenso
On 03/28/2018 02:41 PM, Hervé Pagès wrote:
Hi Kieran,
Note that you can execute arbitrary code at load time by defining
an .onLoad() hook in your package. So you *could* put something
like this in your package:
.onUnload <- function(libpath)
{
if (!reticulate::py_module_available("te
Hi Kieran,
Note that you can execute arbitrary code at load time by defining
an .onLoad() hook in your package. So you *could* put something
like this in your package:
.onUnload <- function(libpath)
{
if (!reticulate::py_module_available("tensorflow"))
tensorflow::install_tensorf
Presumably the installation of tensor flow only has to happen once, so you
could factor your interface such that it installs tensor flow lazily.
Michael
On Wed, Mar 28, 2018 at 9:23 AM, Kieran Campbell
wrote:
> Hi all,
>
> Rstudio have released the Tensorflow package for R -
> https://tensorflo
Hi all,
Rstudio have released the Tensorflow package for R -
https://tensorflow.rstudio.com/tensorflow/ - and we have started
incorporating it into some of our genomics packages for the heavy
numerical computation.
We would ideally like these to be submitted to Bioconductor, but
there's a custom
