Encoder configuration

As with conventional codecs, there is a trade-off between Cool-chic encoding time and compression performance. The encoding settings of Cool-chic are set in a configuration file. Examples of such configuration files are located in cfg/enc/. They include the following parameters:

Parameters relative to the encoder configuration

Parameter	Role	Example value
recipe	Training preset	c3x
start_lr	Initial learning rate	1e-2
n_itr	Number of training iterations	1e4`
n_train_loops	Number of independent encodings	1`

Tip

Each parameter listed in the configuration file can be overridden through a command line argument:

(venv) ~/Cool-Chic python coolchic/encode.py \
  --enc_cfg=example.cfg   # example.cfg has start_lr=1e-2
  --start_lr=1e-3         # This override the value present in example.cfg

Some existing configuration files

Some configuration files are proposed in cfg/enc/:

Existing encoder configuration files.

Name	Description
fast.cfg	Reasonable compression performance & fast training
medium.cfg	Balance compression performance & training duration
slow.cfg	Best performance at the cost of a longer training

Recipes

Cool-chic encoding works with tweakable recipes i.e. different training parameters. Currently available recipes are:

• c3x Inspired by C3: High-performance and low-complexity neural compression from a single image or video, Kim et al. It is composed of two main phases:

  1. additive noise model and softround for the latent quantization

  2. Actual quantization with softround in the backward

• debug Extremely fast preset with very bad performance only for debugging purposes.

All recipes feature a decreasing learning rate starting from start_lr.

The number of iterations in the first (and longest) phase of the c3x recipe is set using n_itr.

In order to circumvent some training irregularities, it is possible to perform several independent encoding, keeping only the best one. We call that a training loop. The number of training loops is set by n_train_loops.