Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

We use magic, just like that:
%run -i data_preparation/v0.py
%run -i model_configuration/v1.py
%run -i model_training/v0.py
Since we’re using the -i option, it works exactly as if we had copied the code from
the files into a cell and executed it.
Jupyter’s Magic Commands
You probably noticed the somewhat unusual %%writefile and %run
commands above. These are built-in magic commands. [50] A magic is a kind of
shortcut that extends a notebook’s capabilities.
We are using the following two magics to better organize our code:
• %%writefile [51] : As its name says, it writes the contents of the cell to a
file, but it does not run it, so we need to use yet another magic.
• %run [52] : It runs the named file inside the notebook as a program—but
independent of the rest of the notebook, so we need to use the -i
option to make all variables available, from both the notebook and the
file (technically speaking, the file is executed in IPython’s namespace).
In a nutshell, a cell containing one of our three fundamental parts will be
written to a versioned file inside the folder corresponding to that part.
In the example above, we write the cell to the data_preparation folder,
name it v0.py, and then execute it using the %run -i magic.
Model Configuration
We have seen plenty of this part: from defining parameters b and w manually, then
wrapping them up using the Module class, to using layers in a Sequential model.
We have also defined a loss function and an optimizer for our particular linear
regression model.
For the purpose of organizing our code, we’ll include the following elements in the
model configuration part:
Putting It All Together | 117