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Google Colab Secure Shell connector that automates Ngrok tunnels creation (for SSH, TPU, TensorBoard, etc.) and facilitates Kaggle API data downloads.

Reason this release was yanked:

wrong Python directory name

Project description

ssh-Colab

ssh-Colab is a Python module to facilitate remote access to Google Colaboratory (Colab) through Secure Shell (SSH) connections, secured by a third-party software, ngrok. ssh-Colab automates the tedious routine to set up ngrok tunnels needed for TPU runtime applications and services like TensorBoard. It also includes the function to facilitate the routine of Kaggle API installation/authentication and competition data downloads.

license python version

Prerequisites

  • ngrok tunnel authtoken.
  • Google account to access a Colab notebook.
  • Local code editors such as VS Code or PyCharm to make the most of coding on Colab.

Usage

  1. Launch a Colab notebook. Choose a runtime type you prefer.

  2. Install ssh-Colab. Type and run the following command in a notebook cell:

    !pip install ssh-Colab
    
  3. Initiate the establishment of tunnels:

    import ssh-Colab
    ssh-Colab.connect()
    

    The default TensorBoard log directory is /log/fit. You can reset it by passing into connect() the new value LOG_DIR=/new/path/to/log.

  4. Retrieve information that is used for establishing the SSH connection:

    ssh-Colab.info()
    

    If you are using non-TPU runtimes, the setup instruction of TPU resolver is ignored.

  5. Run function kaggle() to automate Kaggle API installation/authentication and data downloads. The data is unzipped to the destination folder /kaggle/input.

    ssh-Colab.kaggle([data='name-of-competition'])
    

    Note that the default competition name is "tabular-playground-series-mar-2021."

  6. To disable ngrok tunnels created, run the command below:

    ssh-Colab.kill()
    

Quickstart

A quickstart Colab notebook template is provided in the link below. Users can find a simple end-to-end application starting from SSH-Colab installation, SSH tunnel creation, to the use of TensorBoard after training a 3-layer MNIST convolutional neural network.

Open In Colab

What's missed in this quickstart is how to may our way to Colab instances from local machines. The reference listed below can be a start point for interested users:

  1. Remote development over SSH on local VS Code
  2. Run SSH terminal on local PyCharm

Feedback

Comments and suggestions are welcome and appreciated. They can be sent to lipin.juan02@gmail.com.

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