bastionai 0.2.1

Client SDK for BastionAI Confidential AI Training.

BastionAI Client

BastionAI Client is a python library to create client applications for BastionAI Server (Mithril Security's confidential training server).

If you wish to know more about BastionAI, please have a look to the project Github repository.

Installation

Using pip

$ pip install bastionai

Local installation

Note: It is preferrable to install BastionAI package in a virtual environment.

Execute the following command to install BastionAI locally.

pip install -e .

Usage

Uploading a model and datasets to BastionAI

The snippet below sets up a very simple linear regression model and dataset to train the model with.

import torch
from bastionai.utils import TensorDataset  
from torch.nn import Module
from bastionai.psg.nn import Linear  
from torch.utils.data import DataLoader

class LReg(Module):
    def __init__(self) -> None:
        super().__init__()
        self.fc1 = Linear(1, 1, 2)

    def forward(self, x: Tensor) -> Tensor:
        return self.fc1(x)

lreg_model = LReg()

X = torch.tensor([[0.0], [1.0], [0.5], [0.2]])
Y = torch.tensor([[0.0], [2.0], [1.0], [0.4]])
train_dataset = TensorDataset([X], Y)
train_dataloader = DataLoader(train_dataset, batch_size=2)

X = torch.tensor([[0.1], [-1.0]])
Y = torch.tensor([[0.2], [-2.0]])
test_dataset = TensorDataset([X], Y)
test_dataloader = DataLoader(test_dataset, batch_size=2)

Training a model on BastionAI

With this snippet below, BastionAI is used to securely and remotely train the model.

The model, along with the training and testing datasets are uploaded to BastionAI through the client API.

from bastionai.client import Connection, SGD  


with Connection("localhost", 50051, default_secret=b"") as client:
    remote_dataloader = client.RemoteDataLoader(
        train_dataloader,
        test_dataloader,
        "Dummy 1D Linear Regression Dataset (param is 2)",
    )
    remote_learner = client.RemoteLearner(
        lreg_model,
        remote_dataloader,
        metric="l2",
        optimizer=SGD(lr=0.1),
        model_description="1D Linear Regression Model",
        expand=False,
    )

    remote_learner.fit(nb_epochs=100, eps=100.0)

    lreg_model = remote_learner.get_model() # Gets trained model from BastionAI server.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under Apache 2.0 License.