The Docs¶
The final step is to add some docs.
For each Task
in Flash, we have a docs page in docs/source/reference.
You should create a .rst
file there with the following:
a brief description of the task
the predict example
the finetuning example
any relevant API reference
Here are the contents of docs/source/reference/template.rst which breaks down each of these steps:
.. _template:
########
Template
########
********
The Task
********
Here you should add a description of your task. For example:
Classification is the task of assigning one of a number of classes to each data point.
------
*******
Example
*******
.. note::
Here you should add a short intro to your example, and then use ``literalinclude`` to add it.
To make it simple, you can fill in this template.
Let's look at the task of <describe the task> using the <data set used in the example>.
The dataset contains <describe the data>.
Here's an outline:
.. code-block::
<present the folder structure of the data or some data samples here>
Once we've downloaded the data using :func:`~flash.core.data.download_data`, we create the <link to the DataModule with ``:class:``>.
We select a pre-trained backbone to use for our <link to the Task with ``:class:``> and finetune on the <name of the data set> data.
We then use the trained <link to the Task with ``:class:``> for inference.
Finally, we save the model.
Here's the full example:
<include the example with ``literalinclude``>
.. literalinclude:: ../../../examples/template.py
:language: python
:lines: 14-
Once the docs are done, it’s finally time to open a PR and wait for some reviews!
Congratulations on adding your first Task
to Flash, we hope to see you again soon!