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Vanilla-split-learning

This is an implementation of vanilla split learning considering LeNet5 architecture over the FMNIST dataset. The program can handle multiple clients. The clients have uniformly, identically, and independently distributed FMNIST dataset. The client programs and the server program run separately, and socket programming is used to handle the communication between the server and the clients.

The PyTorch implementation is coming shortly!

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This is an implementation of vanilla split learning.

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