This article gathers some common problems users may encounter while installing or using Ruta.
If you are using Ruta over an Anaconda installation, you will need to
choose the correct conda environment where Tensorflow and Keras are
installed. To do this, you can try asking reticulate to use it (replace
"deeplearning" with the name of your condaenv):
reticulate::use_condaenv("deeplearning", required = TRUE)If reticulate still uses a different Python installation, you can opt
to set the RETICULATE_PYTHON environment variable
before reticulate is initialized. That is, in a new R
session, execute the following command:
Sys.setenv(RETICULATE_PYTHON = PATH)where PATH is the path to the convenient Python
executable (you can discover this path by looking at available versions
in reticulate::py_config()).
CUBLAS_STATUS_NOT_INITIALIZED
Reset your R session and try allowing Tensorflow to grow the size of allocated memory:
config = tensorflow::tf$ConfigProto(gpu_options = list(allow_growth = TRUE))
sess = tensorflow::tf$Session(config = config)
keras::k_set_session(session = sess)