Trainium Model Cache

The Trainium Model Cache is a remote cache for compiled Trainium models in the neff format. It is integrated into the TrainiumTrainer class to enable loading pretrained models from the cache instead of compiling them locally. This can speed up the training process by about –3x.

The Trainium Model Cache is hosted on the Hugging Face Hub and includes compiled files for all popular and supported pre-trained models optimum-neuron.

When training a Transformers or Diffusion model with vanilla torch-neuronx, the models needs to be first compiled. The compiled version is stored in a local directory, usually /var/tmp/neuron-compile-cache. This means that every time you train a new model in a new environment, you need to recompile it, which takes a lot of time.

We created the Trainium Model Cache to solve this limitation by providing a public cache of precompiled available models and a private cache to create your private, secured, remote model cache.

The Trainium Model Cache plugs into the local cache directory of the Hugging Face Hub. During training, the TrainiumTrainer will check if compilation files are available on the Hub and download them if they are found, allowing you to save both time and cost by skipping the compilation phase.

How the caching system works

Hash computation

Many factors can trigger compilation among which:

The model weights
The input shapes
The precision of the model, full-precision or bf16
The version of the Neuron X compiler
The number of Neuron cores used

These parameters are used to compute a hash. This hash is then used to compare local hashes for our training session against hashes stored on the Hugging Face Hub, and act accordingly (download or push).

How to use the Trainium model cache

The Public model cache will be used when your training script uses the TrainiumTrainer. There are no additional changes needed.

How to use a private Trainium model cache

The repository for the public cache is aws-neuron/optimum-neuron-cache. This repository includes all precompiled files for commonly used models so that it is publicly available and free to use for everyone. But there are two limitations:

You will not be able to push your own compiled files on this repo
It is public and you might want to use a private repo for private models

To alleviate that you can create your own private cache repository using the optimum-cli or set the environment variable CUSTOM_CACHE_REPO.

Using the Optimum CLI

The Optimum CLI has 2 subcommands for cache management: you can create a new cache repository that you can use as a private Trainium Model cache. The other command can be used to set the name of the Trainium cache repository, the repository needs to exists.

usage: optimum-cli neuron cache [-h] {create,set} ...

positional arguments:
  {create,set}
    create      Create a model repo on the Hugging Face Hub to store Neuron X compilation files.
    set         Set the name of the Trainium cache repo to use locally.

optional arguments:
  -h, --help    show this help message and exit

Create a new Trainium cache repository:

optimum-cli neuron cache create --help

usage: optimum-cli neuron cache create [-h] [-n NAME] [--public]

optional arguments:
  -h, --help            show this help message and exit
  -n NAME, --name NAME  The name of the repo that will be used as a remote cache for the compilation files.
  --public              If set, the created repo will be public. By default the cache repo is private.

The -n / --name option allows you to specify a name for the Trainium cache repo, if not set the default name will be used. The --public flag allows you to make your Trainium cache public as it will be created as a private repository by default.

Example:

optimum-cli neuron cache create

Trainium cache created on the Hugging Face Hub: michaelbenayoun/optimum-neuron-cache [private].
Trainium cache name set locally to michaelbenayoun/optimum-neuron-cache in /home/michael/.cache/huggingface/optimum_neuron_custom_cache.

Set a different Trainiun cache repository:

optimum-cli neuron cache set

usage: optimum-cli neuron cache set [-h] -n NAME

optional arguments:
  -h, --help            show this help message and exit
  -n NAME, --name NAME  The name of the repo that to use as remote cache.

Example:

optimum-cli neuron cache set -n michaelbenayoun/optimum-neuron-cache

Trainium cache name set locally to michaelbenayoun/optimum-neuron-cache in /home/michael/.cache/huggingface/optimum_neuron_custom_cache

The optimum-cli neuron cache set command is useful when working on a new instance to use your own cache.

Using the environment variable `CUSTOM_CACHE_REPO`

Using the CLI is not always feasible, and not very practical for small testing. In this case, you can simply set the environment variable CUSTOM_CACHE_REPO.

For example, if you cache repo is called michaelbenayoun/my_custom_cache_repo, you just need to do:

CUSTOM_CACHE_REPO="michaelbenayoun/my_custom_cache_repo" torchrun ...

or:

export CUSTOM_CACHE_REPO="michaelbenayoun/my_custom_cache_repo"
torchrun ...

You have to be logged into the Hugging Face Hub to be able to push and pull files from your private cache repository.

Cache system flow

Cache system flow

At each the beginning of each training step, the TrainiumTrainer computes a NeuronHash and checks the cache repo(s) (official and custom) on the Hugging Face Hub to see if there are compiled files associated to this hash. If that is the case, the files are downloaded directly to the local cache directory and no compilation is needed. Otherwise compilation is performed.

Just as for downloading compiled files, the TrainiumTrainer will keep track of the newly created compilation files at each training step, and upload them to the Hugging Face Hub at save time or when training ends. This assumes that you have writing access to the cache repo, otherwise nothing will be pushed.

Optimum Neuron