The Neuron Model Cache is a remote cache for compiled Neuron models in the neff
format.
It is integrated into the [NeuronTrainer
and `NeuronModelForCausalLM] classes to enable loading pretrained models from the cache instead of compiling them locally.
The Neuron Model Cache is hosted on the Hugging Face Hub and includes compiled files for all popular and supported optimum-neuron
pre-trained models.
When loading a Transformers or Diffusion model, it needs to be compiled to neuron format with torch-neuronx
,
in order to run on Neuron platforms.
The compilation produces several compilation files stored in a local directory, usually /var/tmp/neuron-compile-cache
.
This means that every time you train or export a model on a new host, you need to recompile it, which takes a lot of time.
We created the Neuron 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.
Many factors can trigger compilation among which:
These parameters are used to compute a hash that uniquely identifies each compilation file.
It is important to keep in mind that even a small change in the model configuration will trigger a recompilation.
The public model cache will be used when you use the [NeuronTrainer
or `NeuronModelForCausalLM] classes. There are no additional changes needed.
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:
To alleviate that you can create your own private cache repository using the optimum-cli
or set the environment variable CUSTOM_CACHE_REPO
.
The Optimum CLI offers 2 subcommands for cache creation and setting:
create
: To create a new cache repository that you can use as a private Neuron Model cache.set
: To set the name of the Neuron cache repository locally, the repository needs to exists
and will be used by default by optimum-neuron
.Create a new Neuron 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 Neuron cache repo, if not set the default name will be used. The --public
flag allows you to make your Neuron cache public as it will be created as a private repository by default.
Example:
optimum-cli neuron cache create
Neuron cache created on the Hugging Face Hub: michaelbenayoun/optimum-neuron-cache [private].
Neuron cache name set locally to michaelbenayoun/optimum-neuron-cache in /home/michael/.cache/huggingface/optimum_neuron_custom_cache.
Set a different Trainiun cache repository:
usage: optimum-cli neuron cache set [-h] name
positional arguments:
name The name of the repo to use as remote cache.
optional arguments:
-h, --help show this help message and exit
Example:
optimum-cli neuron cache set michaelbenayoun/optimum-neuron-cache
Neuron 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 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 your 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
At each the beginning of each training step, the NeuronTrainer 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 NeuronTrainer 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.
The Optimum CLI can be used to perform various cache-related tasks, as described by the optimum-cli neuron cache
command usage message:
usage: optimum-cli neuron cache [-h] {create,set,add,list} ...
positional arguments:
{create,set,add,list}
create Create a model repo on the Hugging Face Hub to store Neuron X compilation files.
set Set the name of the Neuron cache repo to use locally (trainium only).
add Add a model to the cache of your choice (trainium only).
list List models in a cache repo (trainium only).
synchronize Synchronize local compiler cache with the hub cache (inferentia only).
optional arguments:
-h, --help show this help message and exit
It is possible to add a model compilation files to a cache repo via the optimum-cli neuron cache add
command:
usage: optimum-cli neuron cache add [-h] -m MODEL --task TASK --train_batch_size TRAIN_BATCH_SIZE [--eval_batch_size EVAL_BATCH_SIZE] [--sequence_length SEQUENCE_LENGTH]
[--encoder_sequence_length ENCODER_SEQUENCE_LENGTH] [--decoder_sequence_length DECODER_SEQUENCE_LENGTH]
[--gradient_accumulation_steps GRADIENT_ACCUMULATION_STEPS] --precision {fp,bf16} --num_cores
{1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32} [--max_steps MAX_STEPS]
When running this command a small training session will be run and the resulting compilation files will be pushed.
If at least one of those requirements is not met, the command will fail.
Example:
optimum-cli neuron cache add \
--model prajjwal1/bert-tiny \
--task text-classification \
--train_batch_size 16 \
--eval_batch_size 16 \
--sequence_length 128 \
--gradient_accumulation_steps 32 \
--num_cores 32 \
--precision bf16
This will push compilation files for the prajjwal1/bert-tiny
model on the Neuron cache repo that was set up for the specified parameters.
It can also be convenient to request the cache repo to know which compilation files are available. This can be done via the optimum-cli neuron cache list
command:
usage: optimum-cli neuron cache list [-h] [-m MODEL] [-v VERSION] [name]
positional arguments:
name The name of the repo to list. Will use the locally saved cache repo if left unspecified.
optional arguments:
-h, --help show this help message and exit
-m MODEL, --model MODEL
The model name or path of the model to consider. If left unspecified, will list all available models.
-v VERSION, --version VERSION
The version of the Neuron X Compiler to consider. Will list all available versions if left unspecified.
As you can see, it is possible to:
-v / --version
argument.-m / --model
argument.Example:
optimum-cli neuron cache list aws-neuron/optimum-neuron-cache