First, it's possible to use keras 2 (i.e., library(keras) with TF 2.16. To make that work presently, you can install legacy keras as tf_keras, and then make sure an env var is set when keras is first loaded.
tensorflow::install_tensorflow(
version = "release" # or "2.16" or "2.17"
envname = "r-tensorflow",
extra_packages = "tf_keras", # legacy keras
python_version = "3.10"
)
# New R session
Sys.setenv("TF_USE_LEGACY_KERAS"="1")
tensorflow::tf_config() # initialize python, load tensorflow+keras
keras:::keras_version() < "3.0" # confirm legacy Keras in use
This would mean that we would need to add some more things to startup, but overall it's great to know that this is all possible, and we can push back against using keras 3 for at least a little bit longer
From @ t-kalinowski at https://github.com/rstudio/tensorflow/issues/602
This would mean that we would need to add some more things to startup, but overall it's great to know that this is all possible, and we can push back against using keras 3 for at least a little bit longer