extempauto.py

import torch.nn as nn


class ExTempAuto(nn.Module):
    def __init__(self):
        super().__init__()

        self.encoder = nn.Sequential(
            nn.Linear(1440, 1024),
            nn.LeakyReLU(),
            nn.Linear(1024, 512),
            nn.LeakyReLU(),
            nn.Linear(512, 256),
            nn.LeakyReLU(),
        )

        self.classifier = nn.Sequential(
            nn.Linear(256, 128),
            nn.LeakyReLU(),
            nn.Linear(128, 64),
            nn.LeakyReLU(),
            nn.Linear(64, 32),
            nn.LeakyReLU(),
            nn.Linear(32, 16),
            nn.LeakyReLU(),
            nn.Linear(16, 8),
            nn.LeakyReLU(),
            nn.Linear(8, 4),
            nn.Softmax(1),
        )

        self.decoder = nn.Sequential(
            nn.Linear(256, 512),
            nn.LeakyReLU(),
            nn.Linear(512, 1024),
            nn.LeakyReLU(),
            nn.Linear(1024, 1440),
            nn.Sigmoid(),
        )

    def forward(self, x):
        encoded = self.encoder(x)
        softmax = self.classifier(encoded)
        decoded = self.decoder(encoded)
        return softmax, decoded