#tied-weights

This autoencoder ties its decoder weights to the transpose of its encoder weights. How many trainable parameters does it have?

import torch
import torch.nn as nn

class TiedAutoencoder(nn.Module):
    def __init__(self):
        super().__init__()
        self.encoder = nn.Linear(784, 128)
        self.decoder_bias = nn.Parameter(torch.zeros(784))

    def forward(self, x):
        codings = torch.relu(self.encoder(x))
        return torch.sigmoid(codings @ self.encoder.weight + self.decoder_bias)

print(sum(p.numel() for p in TiedAutoencoder().parameters()))