Using ResNet50 pre-trained Weights I am trying to build a classifier. The code base is fully implemented in Keras high-level Tensorflow API. The complete code is posted in t
I was having the same problem while running Tensorflow container with Docker and Jupyter notebook. I was able to fix this problem by increasing the container memory.
On Mac OS, you can easily do this from:
Docker Icon > Preferences > Advanced > Memory
Drag the scrollbar to maximum (e.g. 4GB). Apply and it will restart the Docker engine.
Now run your tensor flow container again.
It was handy to use the docker stats command in a separate terminal
It shows the container memory usage in realtime, and you can see how much memory consumption is growing:
CONTAINER ID NAME CPU % MEM USAGE / LIMIT MEM % NET I/O BLOCK I/O PIDS
3170c0b402cc mytf 0.04% 588.6MiB / 3.855GiB 14.91% 13.1MB / 3.06MB 214MB / 3.13MB 21