Photo by Andrew Neel on Unsplash Use Google ColabĬolaboratory, or “Colab” for short, allows us to run Python code with zero configuration and computation resources, like GPU / TPU, available. Using this, we can even run some bash commands by putting a prefix % before the CLI command. The benefit of this approach is that it is free and it allows importing files/dataset from Drive or Github. It is well integrated with Google Drive that we can write code to automatically load some dataset from Drive and save the network/result to Drive. Once the limit is reached, it will stop running the code and shortly after, the files / variable values are lost. However, the limit is not that restricting. I found it to be good enough for training a Neural Network on some dataset, such as the Leaf Classification dataset. Moreover, it is possible to connect to a local runtime in case you need bigger computation usage/resource.Īnother drawback is that you can’t close the browser tab for too long, that is for more than 90 minutes. In my experience, this can be prolonged by connecting to a local runtime. Lastly, it may lose the log written when the tab is closed. This may be an issue when you need to keep all the log written in the Jupyter Notebook file. Some ways to handle this is to log the outputs into another file or use a specific logger. There are ways to run a Jupyter Notebook file as a python script. After that, we can run the output file the way we run a typical python file: python file_name.py The simplest way is to open the Jupyter Notebook file in a browser, click File > Download as > Python (.py). However, log printed on the Jupyter Notebook files will get lost.Īnother way is to run the jupyter notebook using CLI directly. It will allow us to keep all the logging printed in the jupyter notebook files throughout execution. There are two choices of program to use for this purpose, runipy or nbconvert. If we use nbconvert and have it installed, to run a jupyter notebook we can type: jupyter nbconvert -to notebook -execute mynotebook.ipynb To save the output of each cell back to the notebook file, run: runipy MyNotebookFileName.ipynb If we use runipy and have it installed, to run a jupyter notebook we can type: runipy MyNotebookFileName.ipynb # Using pip pip install ipython # Using conda conda install ipython To install runipy or nbconvert, we can use pip/conda. The are several other configuration options, such as timeout, report generation, and output files generation which can be found in these two sites, for runipy and nbconvert respectively. VBox ipywidget containing view control widgets Plotting iso-surfaces with Mayavi ¶ Nglviewer ipywidget for direct interaction. The returned object has two shortcuts members. The viewer supports any Atoms objectand any sequence of Atoms objects. Navigate with a TOC On the notebook toolbar, use the Table of contents tool to display or hide the table of contents. Select the tool to show the variable explorer window. Returns the nglviewer + some control widgets in the VBox ipywidget. On the notebook toolbar, use the Variable explorer tool to show the name, type, length, and sample values for all variables that have been created in your notebook. To reset the map to default call the method without parameters. General crystal structures and surfaces.
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