Using conda env with cpu 0. conda create --name keras_cpu tensorflow keras pandas matplotlib jupyterlab dask
- conda activate keras_cpu
- jupyter lab
Using docker:
- docker run --name jupyter-tensorflow-rnn -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes -v ${PWD}:/home/jovyan/work jupyter/tensorflow-notebook:58169ec3cfd3
- docker start jupyter-tensorflow-rnn -a
In case of using tensorflow-gpu and to check if gpu is good to go paste the folowing in terminal:
- python
- import tensorflow as tf
- sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
Using conda env with gpu 0. conda create --name keras_theano_gpu numpy=1.15.4 theano pygpu keras pandas matplotlib jupyterlab dask
- conda activate keras_theano_gpu
- jupyter lab