I created a diagram for my neural network. This is the NN I created using pytorch

class MLP(nn.Module):
    def __init__(self):
        super().__init__()
        self.layers = nn.Sequential(
            nn.Linear(2830, 1024),
            nn.ReLU(),
            nn.BatchNorm1d(1024),
            nn.Dropout(0.2),
            
            nn.Linear(1024, 512),
            nn.ReLU(),
            nn.BatchNorm1d(512),
            nn.Dropout(0.2),
            
            nn.Linear(512, 1),
        )
        
    def forward(self, x):
        return self.layers(x)

And this is the diagram I created using this script, where gray stands for hidden nodes and black for input/output.

I am afraid that this representation is partly unclear because of the multiple layers of the same size, that in reality are simple ReLu, BatchNorm and Dropout layers. I also noted that sometimes these types of layers are not shown in diagrams, but since my model is simple and I think they are relevant for its correct functioning I would like to show them.

Do you think this diagram is correct? Can you understand the structure of the network looking at the image? What would you do differently?