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


class FeedForwardClassifier(nn.Module):

    def __init__(self, input_size):
        super(FeedForwardClassifier, self).__init__()

        self.fc1 = nn.Linear(in_features=input_size, out_features=600)
        self.drop1 = nn.Dropout(0.25)
        self.fc2 = nn.Linear(in_features=600, out_features=120)
        self.drop2 = nn.Dropout(0.25)
        self.fc3 = nn.Linear(in_features=120, out_features=10)

    def forward(self, x):
        x = x.view(x.size(0), -1)  # Flatten the input
        x = F.relu(self.fc1(x))
        x = self.drop1(x)
        x = F.relu(self.fc2(x))
        x = self.drop2(x)
        x = self.fc3(x)
        return x