Fastai v2 code walk-thru 5

fastai fastai dev
2

These are my notes in random order from today:

Sep 10, 2019

Digging Deep in Transforms

  • 02_data_transforms.ipynb notebook
  • no order in v2 of the library for DataBlock API so can’t have mistakes when order is not correct as it was in v1
  • filt knows which set transform is applied to
  • transform creates a callable object, after creating you should call it and pass some data
  • _TfmMeta is meta class of Transform
  • ... for pass in Python (or do nothing)
  • Foo2 = type(‘Foo2’, (object), {}) will create a class called Foo2
  • type is class that constructs things
  • reason for meta classes is to change how Python works underneath the hood
  • meta class is a way to not use type constructor, but some other constructor in fastai v2
  • meta class is called every time we create a class (not when objects are created)
  • :star::star::star:3. Data model — Python 3.7.4 documentation
  • class’s namespace is __dict__ object
  • _TfmMeta uses _TfmDict instead of plain dict as the namespace dict
  • it behaves as the normal dict except for cases when ‘encodes’ and ‘decodes’ parameters are passed
  • TypeDispatch — allows for the same function to work differently for different types
  • Python method dispatching — can be single or multiple
  • Multiple Dispatching — Python 3 Patterns, Recipes and Idioms
  • Method dispatching in Python
  • PEP 443 — Single-dispatch generic functions | Python.org
  • TypeDispatch has dict funcs where key is a type and value is the function to call (NICE!)
  • _p1_anno grabs the first parameter annotation
  • how to use Transform subclass as a decorator? This will allow to dynamically add functionality to a given transform later outside the class definition.
  • Using class as decorator needs to be a callable, but not in the __init__ sense. We need to reimplement __call__() method. If parameter is callable it will be added to class’s methods.
  • __new__() should have an expectable Shift + Tab autocomplete for the signature. Signature is customized in __new__() for Transform
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