# models.py
import torch.nn as nn

class DistilBERTClassifier(nn.Module):
    def __init__(self, num_classes):
        super(DistilBERTClassifier, self).__init__()
        self.dropout = nn.Dropout(0.1)
        self.classifier = nn.Linear(768, num_classes)

    def forward(self, x):
        # forward pass here
        pass

class EmotionClassifier(nn.Module):
    def __init__(self, input_size, hidden_size, num_classes):
        super(EmotionClassifier, self).__init__()
        self.fc1 = nn.Linear(input_size, hidden_size)
        self.relu = nn.ReLU()
        self.fc2 = nn.Linear(hidden_size, num_classes)

    def forward(self, x):
        out = self.fc1(x)
        out = self.relu(out)
        return self.fc2(out)