I'm working on a face classifier using YOLO, but for the classification step, we are using a neural network with the following architecture:

self.fc = nn.Sequential(
        nn.Linear(input_dim, 256),
        nn.ReLU(),
        nn.Dropout(0.3),
        nn.Linear(256, 128),
        nn.ReLU(),
        nn.Dropout(0.3),
        nn.Linear(128, num_classes)
    )

I'm training the network with N classes of 200 embeddings each, which means I have 200*N inputs to the neural network. I want to see if there is way to estimate the time complexity of the training phase of the neural network in function of the number of classes.

Thank you!