normalizing_flow

Normalizing Flow

An example of a normalizing flow for density estimation and sampling implemented in MLX. This example implements the real NVP (non-volume preserving) model.¹

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
log_prob = model.log_prob(x=x)

# Draw samples
x_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 [--cpu]

This trains the normalizing flow on the two moons dataset and plots the result in samples.png. The optional --cpu flag can be used to run the example on the CPU, otherwise it will use the GPU by default.

For all available options, run:

python main.py --help

Results

Footnotes

1. This example is from Density estimation using Real NVP, Dinh et al. (2016) ↩