Dockerfile for Machine Learning with PyTorch and TensorFlow
This repository contains a Dockerfile that creates a Docker image for deep learning development. The image is based on the nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu20.04 image and includes the following libraries and tools:
- Python 3.9
- JupyterLab
- pandas
- numpy
- matplotlib
- seaborn
- scikit-learn
- scipy
- PyTorch 2.0.0 with CUDA 11.8
- TensorFlow (latest version)
Build and Run Docker Image
To build and run the dl-docker image, use the following command:
docker-compose up --gpus all -d service_nameIf you want to change the external port, you can modify it in the docker-compose.yml file.
Then, access JupyterLab in your web browser at http://localhost:8888. You will need to enter the token shown in the container logs to login.
To access the notebook, open this file in a browser:
file:///root/.local/share/jupyter/runtime/nbserver-1-open.html
Or copy and paste one of these URLs:
http://(xxxx or 127.0.0.1):8888/lab?token=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxAcknowledgements
This Dockerfile is inspired by the following repositories: