.. _function_transforms

.. _function_transforms:

Function Transforms
===================

.. currentmodule:: mlx.core

MLX uses composable function transformations for automatic differentiation and
vectorization. The key idea behind composable function transformations is that
every transformation returns a function which can be further transformed. 

Here is a simple example:

.. code-block:: shell

   >>> dfdx = mx.grad(mx.sin)
   >>> dfdx(mx.array(mx.pi))
   array(-1, dtype=float32)
   >>> mx.cos(mx.array(mx.pi))
   array(-1, dtype=float32)


The output of :func:`grad` on :func:`sin` is simply another function. In this
case it is the gradient of the sine function which is exactly the cosine
function. To get the second derivative you can do: