import torch.nn as nn
import torch.nn.functional as F


# Declare 3-layer MLP for MNIST dataset
class MLP(nn.Module):
    def __init__(self, input_size=28 * 28, output_size=10, layers=[120, 84]):
        super(MLP, self).__init__()
        self.fc1 = nn.Linear(input_size, layers[0])
        self.fc2 = nn.Linear(layers[0], layers[1])
        self.fc3 = nn.Linear(layers[1], output_size)

    def forward(self, x):
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return F.log_softmax(x, dim=1)