IoT_Multiclass_Model.py

# Build model
class IoTMultiClassModel(nn.Module):
    def __init__(self, input_features=91, output_features=4, hidden_units=128, dropout=0.0):
        super().__init__()
        
        self.input_features = input_features
        self.output_features = output_features
        self.hidden_units = hidden_units
        
        self.linear_layer_stack = nn.Sequential(
            # 1
            nn.Linear(in_features=input_features, out_features=hidden_units),
            nn.LeakyReLU(), # LeakyReLU
            nn.Dropout(dropout),
            # 2
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.LeakyReLU(), # LeakyReLU
            nn.Dropout(dropout),
            # 3
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.RReLU(), 
            nn.Dropout(dropout),
            # 4
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.RReLU(), 
            nn.Dropout(dropout),
            # 5
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.RReLU(), 
            nn.Dropout(dropout),
            # 6
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.RReLU(), 
            nn.Dropout(dropout),
            # 7
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.RReLU(), 
            nn.Dropout(dropout),
            # 8
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.RReLU(), 
            nn.Dropout(dropout),
            # 9
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.RReLU(), # RReLU
            nn.Dropout(dropout),
            # 10
            nn.Linear(in_features=hidden_units, out_features=hidden_units),
            nn.LeakyReLU(), # RReLU
            nn.Dropout(dropout),
            # final
            nn.Linear(in_features=hidden_units, out_features=output_features), 
        )
    
    def forward(self, x):
        return self.linear_layer_stack(x)