2. Setup Environment

Before installing and configuring Cifer's FHE, it's important to properly prepare your environment. Follow these steps to ensure a smooth setup process:

Update Python

Cifer requires Python 3.8 or later. To check your Python version:

bash

python --version

If Python is not installed or you need to upgrade, download and install the latest version from python.org.

Set Up a Virtual Environment

It's recommended to use a virtual environment to avoid conflicts with other Python projects:

bash

python -m venv cifer_env

Activate the virtual environment:

• On Linux or macOS:

bash

source cifer_env/bin/activate

• On Windows:

bash

cifer_env\Scripts\activate

Upgrade pip

Ensure you have the latest version of pip:

bash

pip install --upgrade pip

Check GPU/TPU Availability (Optional)

If you plan to use GPU or TPU acceleration:

For NVIDIA GPUs:

bash

nvidia-smi

For TPUs (on Google Cloud):

bash

gcloud compute tpus list

Set Up Cloud Environment (for Collaboration Mode)

If you're planning to contribute your encrypted data as part of a collaborative Federated Learning.

1. Ensure you have access to a cloud platform (e.g., AWS, Google Cloud, Azure).

2. Set up firewall rules to allow communication on the required ports.

3. Prepare a shared storage solution for model checkpoints (e.g., S3, Google Cloud Storage).

Prepare Your Dataset / Model

Organize your dataset or model as follows:

• Split the data into appropriate training and validation sets as needed.

• Store the raw files in a directory accessible to your local environment or the FHE client.

Important: The data must be preprocessed and converted into numerical array format prior to encryption. Cifer's FHE uses .npz as the standard input format. You will find detailed .npz preparation steps in the Configuration section.

Review System Requirements

Double-check that your system meets all the requirements listed in the previous section, including RAM, storage, and any specific hardware needs.