TensorFlow has supported Docker containers that could save the time from installing lots of stuffs on our operating system and messing around. Besides typing long Docker commands each time in the terminal for launching the container, using Docker Compose file is another easy way to achieve it.
To begin with, create a new file called
TensorFlow.yml and paste everything below into that file. Freely to change the path in
volumes in accordance with our computer's path.
version: '3.1' services: TernsorFlow: container_name: TensorFlow image: tensorflow/tensorflow:latest-py3 restart: unless-stopped network_mode: "bridge" ports: - 6006:6006 tty: true command: /bin/bash volumes: - /Users/AndyWu/Documents/Docker/TensorFlow:/TensorFlow
To create and start a new TensorFlow container from docker compose file, run the command below.
docker-compose -f TensorFlow.yml up -d
Now our newly created container should start running. Execute the
bash shell in the container and interact with the pseudo-TTY by providing the options
docker exec -it TensorFlow bash
We are now able to run our TensorFlow codes with python in the container:)