Schematic and overall process of colab service

Schematic of colab.com service

Fig.1 overall process of colab.com service

Fig.1 shows the overall process of colab.com service.

Example

The document below demonstrates how to upload files in PC, project in GitHub and execute Python code in Colab.

First, Clone project from GitHub to Colab using!git clone https://github.com/tensorflow/models.gitcommand.

Fig.2 clone project from GitHub to Colab

Upload files from PC to Colab using the libraryfilesingoogle.colabFig.3 upload files from PC to Colab

Fig.3 shows upload files from PC to Colab using the libraryfilesingoogle.colab, then upload files by clicking "選擇檔案" button

Move to the project folder usingcdcommand with the folder path

Fig.4 move to the project folder

check which files and folder in/content/models/tutorials/rnn/ptbfolder using!lscommand

Fig.5 check which files and folder in this path

Execute ".py" file using!pythoncommand, with parameters--data_pathand--modelthen Colab output to browser

Fig.6 execute the .py file

End of the execution

Fig.7 end of the execution

Reference

[0] Recurrent Neural Network

https://www.tensorflow.org/tutorials/recurrent

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Fig.1 schematic of colab.com service

Fig.1 shows the relationship between Colab, PC and GitHub. Colab.com is the service for GPU machine learning. PC is the computer operare Colab by command. And a project using Python language stored in GitHub.