mlx-examples/flow/README.md

Normalizing flow

Real NVP normalizing flow for density estimation and sampling from Dinh et al. (2016), implemented using mlx.

The example is written in a somewhat more object-oriented style than strictly necessary, with an eye towards extension to other use cases that could from arbitrary distributions and bijectors.

Basic usage

import mlx.core as mx
from flows import RealNVP

model = RealNVP(n_transforms=8, d_params=4, d_hidden=256, n_layers=4)

x = mx.random.normal(shape=(32, 4))

# Evaluate log-density
model.log_prob(x=x)

# Draw samples
model.sample(sample_shape=(32, 4))

Running the example

Install the dependencies:

pip install -r requirements.txt

The example can be run with:

python main.py

which trains the normalizing flow on the two moons dataset and plots the result in samples.png.

By default the example runs on the GPU. To run on the CPU, do:

python main.py --cpu

For all available options, run:

python main.py --help

Results