Closed VicenteFR closed 4 years ago
I think the issue is you probably have tensorflow 2.0 installed. Can you check this with
tensorflow::tf_config()
cellassign was written in tensorflow 1.X and we've been dreading the day the 2.0 candidate was released. The moral of the story is don't develop in tensorflow.
If the above does indeed show you have 2.X installed, you can downgrade via
install_tensorflow(your_options, version='1.14')
@Irrationone looks like there might be a quick fix via the use_compat
function https://www.rdocumentation.org/packages/tensorflow/versions/1.14.0/topics/use_compat
Got ya'!
Problem solved! Now there are a lot of warnings output, but all of them related to the new tensorflow version.
Thanks, thanks!
Hi, i get the same issue. whatever the ways i use that you post above, it can not be solved. I use the conda to install the cellassign, and then i enter the R to type the tensorflow::tf_config(), it alway showing the tensorflow's path '~/miniconda3/envs/reticulate_venv/lib/python3.8/site-packages/'. But the conda environment that i install the cellassign was in "/test/Data/software/mini_conda/Miniconda3/envs/Cellassign" . It was very weird. how can i change the tensorflow path in the conda environment that i use. Any advice would be grateful. Best, hanhuihong
The conda environment's tensorflow'R package:
But the tensorflow: tensorflow::tf_config() TensorFlow v2.5.0 (/home/test/miniconda3/envs/reticulate_venv/lib/python3.8/site-packages/tensorflow) Python v3.8 (/home/test/miniconda3/envs/reticulate_venv/bin/python)
@Irrationone looks like there might be a quick fix via the
use_compat
function https://www.rdocumentation.org/packages/tensorflow/versions/1.14.0/topics/use_compat It can not be work on my case. it still load into tensorflow 2.5
Hi, everyone!
I was trying to process the data sets from SingleCellExperiment package as shown in the tutorial but, when trying to run:
I've faced this error from tensorflow:
Apparently, it has something to do with the way the module tensorflow could be imported in a python session as commented in this thread. Any suggestions to solve this?
Thanks so much!