Documentation

Finding API Help

Every framework has thousands of functions and classes. You won’t memorize them — you’ll look them up.

Two Python builtins do most of the work:

  • dir(module) — what’s in here?
  • help(thing) (or ?thing in Jupyter) — how do I use it?

Plus the official docs: pytorch.org, jax.dev, tensorflow.org, mxnet.apache.org.

dir: discovering the API

Standard import:

import torch

dir(...) lists names in a module. Filter private names and show a small prefix on slides; in a notebook you can inspect the full list interactively:

print([name for name in dir(torch.distributions)
       if not name.startswith('_')][:20])
['AbsTransform', 'AffineTransform', 'Bernoulli', 'Beta', 'Binomial', 'CatTransform', 'Categorical', 'Cauchy', 'Chi2', 'ComposeTransform', ...

help: usage details

Once you have the name, help(...) prints the docstring with arguments, defaults, and a usage example:

help(torch.ones)
Help on built-in function ones in module torch:

ones(...)
    ones(*size, *, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False) -> Tensor

    Returns a tensor filled with the scalar value `1`, with the shape defined
...
        >>> torch.ones(2, 3)
        tensor([[ 1.,  1.,  1.],
                [ 1.,  1.,  1.]])

        >>> torch.ones(5)
        tensor([ 1.,  1.,  1.,  1.,  1.])

Then run a one-liner to confirm the call:

torch.ones(4)
tensor([1., 1., 1., 1.])

Recap

  • dir(module) — list contents.
  • help(symbol) (or symbol? in Jupyter) — show the docstring.
  • Notebook autocomplete (Tab) is your fastest discovery tool.
  • For prose-heavy explanations, deep links into the framework’s official documentation beat the inline help.