Mathesis Wiki

class Netzwerk(nn.Module):
    def __init__(self):
        super(Netzwerk, self).__init__()
        self.conv1 = nn.Conv1d(12, 24, kernel_size=15, stride=1, padding=1)
        self.pool1 = nn.MaxPool1d(kernel_size=3, stride=2, padding=1)
        self.conv2 = nn.Conv1d(24, 32, kernel_size=10, padding=1)
        self.pool2 = nn.MaxPool1d(2, stride=2, padding=1)
        self.conv3 = nn.Conv1d(32, 24, kernel_size=5, padding=1)
        self.pool3 = nn.MaxPool1d(3, stride=2, padding=1)
        self.conv4 = nn.Conv1d(24, 12, kernel_size=3, padding=1)
        self.pool4 = nn.MaxPool1d(3, stride=2, padding=1)

        self.lin1 = nn.Linear(12*61, 40)
        self.lin2 = nn.Linear(40, 10)
        self.lin3 = nn.Linear(10, 2)

        self.history_loss = []
        self.history_eval = []
        self.classific_accuracy_training = []
        self.current_epoch = 0

    def forward(self, x):
        x = self.pool1(F.relu(self.conv1(x)))
        x = self.pool2(F.relu(self.conv2(x)))
        x = self.pool3(F.relu(self.conv3(x)))
        x = self.pool4(F.relu(self.conv4(x)))
        
        x = x.view(-1, 12*61)       
        x = F.relu(self.lin1(x))
        x = F.relu(self.lin2(x))
        x = self.lin3(x)
        return x