Course stanford

The pre-configured and ready-to-use runtime environment for the CS231n course - Convolutional Neural Networks for Visual Recognition, Stanford University, Spring 2017. It includes latest versions of Python 3, TensorFlow, and PyTorch. The software stack is optimized for running on CPU.

Configuration

Full settings

keras

Version: 2.1.2

pytorch

Version: 0.3.0

tensorflow

Version: 1.5.0

python

Python version: Python 3.6.3
Path to interpreter: /jet/bin/python

init

Services control

Available services: cron jupyter_notebook orientation
Start all services: start
Stop all services: stop
Service commands: available|enabled|disabled|enable|disable|start|stop|status|restart servicename

jupyter_notebook

Configuration

Jupyter version: | 4.3.0 Jupyter notebook version: | 5.1.0 Config: | /jet/etc/jupyter_notebook/jupyter_notebook_config.py Bind address: | 0.0.0.0 Address: | http://server_address:8888 Password: | empty

Daemon management

Start: | start jupyter_notebook Stop: | stop jupyter_notebook Restart: | restart jupyter_notebook

perl

Perl version: v5.26.1
Path to interpreter: /jet/bin/perl

config

Directories

Configurations: /jet/etc
Log files: /jet/log
Applications: /jet/app
Applications data: /jet/var
Temporary files: /jet/tmp
Persistent data: /jet/prs

enter

Entry point: /jet/enter
Working directory: /jet/prs/workspace