/saxml

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Saxml (aka Sax)

Saxml is an experimental system that serves Paxml, JAX, and PyTorch models for inference.

A Sax cell (aka Sax cluster) consists of an admin server and a group of model servers. The admin server keeps track of model servers, assigns published models to model servers to serve, and helps clients locate model servers serving specific published models.

The example below walks through setting up a Sax cell and starting a TPU or GPU model server in the cell.

Install Sax

Install and set up the gcloud tool

Install the gcloud CLI and set the default account and project:

gcloud config set account <your-email-account>
gcloud config set project <your-project>

Create a Cloud Storage bucket to store Sax server states

Create a Cloud Storage bucket:

GSBUCKET=sax-data
gcloud storage buckets create gs://${GSBUCKET}

Create a Compute Engine VM instance for the admin server

Create a Compute Engine VM instance:

gcloud compute instances create sax-admin \
  --zone=us-central1-b \
  --machine-type=e2-standard-8 \
  --boot-disk-size=200GB \
  --scopes=https://www.googleapis.com/auth/cloud-platform

Create a Cloud TPU VM instance for a TPU model server

Use this guide to enable the Cloud TPU API in a Google Cloud project.

Create a Cloud TPU VM instance:


gcloud compute tpus tpu-vm create sax-tpu \
  --zone=us-central2-b \
  --accelerator-type=v4-8 \
  --version=tpu-vm-v4-base \
  --scopes=https://www.googleapis.com/auth/cloud-platform

Create a Compute Engine VM instance for a GPU model server

Alternatively or in addition to the Cloud TPU VM instance, create a Compute Engine VM instance with GPUs:

gcloud compute instances create sax-gpu \
  --zone=us-central1-b \
  --machine-type=n1-standard-32 \
  --accelerator=count=4,type=nvidia-tesla-v100 \
  --maintenance-policy=TERMINATE \
  --boot-disk-size=200GB \
  --scopes=https://www.googleapis.com/auth/cloud-platform

Consider creating a VM instance using the "GPU-optimized Debian 10 with CUDA 11.0" image instead, so the Nvidia CUDA stack doesn't need to be manually installed as described below.

Start the Sax admin server

SSH to the Compute Engine VM instance:

gcloud compute ssh --zone=us-central1-b sax-admin

Inside the VM instance, clone the Sax repo and initialize the environment:

git clone https://github.com/google/saxml.git
cd saxml
saxml/tools/init_cloud_vm.sh

Configure the Sax admin server. This only needs to be done once:

bazel run saxml/bin:admin_config -- \
  --sax_cell=/sax/test \
  --sax_root=gs://${GSBUCKET}/sax-root \
  --fs_root=gs://${GSBUCKET}/sax-fs-root \
  --alsologtostderr

Start the Sax admin server:

bazel run saxml/bin:admin_server -- \
  --sax_cell=/sax/test \
  --sax_root=gs://${GSBUCKET}/sax-root \
  --port=10000 \
  --alsologtostderr

Start the Sax TPU model server

SSH to the Cloud TPU VM instance:

gcloud compute tpus tpu-vm ssh --zone=us-central2-b sax-tpu

Inside the VM instance, clone the Sax repo and initialize the environment:

git clone https://github.com/google/saxml.git
cd saxml
saxml/tools/init_cloud_vm.sh

Start the Sax model server:

SAX_ROOT=gs://${GSBUCKET}/sax-root \
bazel run saxml/server:server -- \
  --sax_cell=/sax/test \
  --port=10001 \
  --platform_chip=tpuv4 \
  --platform_topology=2x2x1 \
  --alsologtostderr

You should see a log message "Joined [admin server IP:port]" from the model server to indicate it has successfully joined the admin server.

Start the Sax GPU model server

SSH to the Compute Engine VM instance:

gcloud compute ssh --zone=us-central1-b sax-gpu

Install the Nvidia GPU driver, CUDA, and cuDNN. Note that Sax by default requires CUDA 11. To switch to CUDA 12, edit requirements-cuda.txt and replace jaxlib==0.4.7+cuda11.cudnn86 with jaxlib==0.4.7+cuda12.cudnn88.

Inside the VM instance, clone the Sax repo and initialize the environment:

git clone https://github.com/google/saxml.git
cd saxml
saxml/tools/init_cloud_vm.sh

Enable the GPU-specific requirements.txt file:

cp requirements-cuda.txt requirements.txt

Start the Sax model server:

SAX_ROOT=gs://${GSBUCKET}/sax-root \
bazel run saxml/server:server -- \
  --sax_cell=/sax/test \
  --port=10001 \
  --platform_chip=v100 \
  --platform_topology=4 \
  --jax_platforms=cuda \
  --alsologtostderr

You should see a log message "Joined [admin server IP:port]" from the model server to indicate it has successfully joined the admin server.

Use Sax

Sax comes with a command-line tool called saxutil for easy usage:

# From the `saxml` repo root directory:
alias saxutil='bazel run saxml/bin:saxutil -- --sax_root=gs://${GSBUCKET}/sax-root'

saxutil supports the following commands:

  • saxutil help: Show general help or help about a particular command.
  • saxutil ls: List all cells, all models in a cell, or a particular model.
  • saxutil publish: Publish a model.
  • saxutil unpublish: Unpublish a model.
  • saxutil update: Update a model.
  • saxutil lm.generate: Use a language model generate suffixes from a prefix.
  • saxutil lm.score: Use a language model to score a prefix and suffix.
  • saxutil lm.embed: Use a language model to embed text into a vector.
  • saxutil vm.generate: Use a vision model to generate images from text.
  • saxutil vm.classify: Use a vision model to classify an image.
  • saxutil vm.embed: Use a vision model to embed an image into a vector.

As an example, Sax comes with a Pax language model servable on a Cloud TPU VM v4-8 instance. You can use it to verify Sax is correctly set up by publishing and using the model with a dummy checkpoint.

saxutil publish \
  /sax/test/lm2b \
  saxml.server.pax.lm.params.lm_cloud.LmCloudSpmd2BTest \
  None \
  1

Check if the model is loaded by looking at the "selected replica address" column of this command's output:

saxutil ls /sax/test/lm2b

When the model is loaded, issue a query:

saxutil lm.generate /sax/test/lm2b "Q: Who is Harry Porter's mother? A: "

The result will be printed in the terminal.

To use a real checkpoint with the model, follow the Paxml tutorial to generate a checkpoint. The model can then be published in Sax like this:

saxutil publish \
  /sax/test/lm2b \
  saxml.server.pax.lm.params.lm_cloud.LmCloudSpmd2B \
  gs://${GSBUCKET}/checkpoints/checkpoint_00000000 \
  1

Use the same saxutil lm.generate command as above to query the model.

Use Sax to load LLaMA 7B model:

First get LLaMA pytorch_vars from Meta, then run the following script to convert the LLaMA PyTorch checkpoint to SAX format

python3 -m saxml/tools/convert_llama_ckpt --base llama_7b --pax pax_7b

Then start the GPU server

SAX_ROOT=gs://${GSBUCKET}/sax-root \
bazel run saxml/server:server -- \
  --sax_cell=/sax/test \
  --port=10001 \
  --platform_chip=a100 \
  --platform_topology=1 \
  --jax_platforms=cuda \
  --alsologtostderr

Finally move the converted ckpt to your google cloud data bucket and publish the model

saxutil publish \
  /sax/test/llama-7b \
  saxml.server.pax.lm.params.lm_cloud.LLaMA7BFP16 \
  gs://sax-data/pax-llama/7B \
  1