import torch
import torch.nn as nn
from transformers import AutoModel

class EmotionClassifier(nn.Module):
    def __init__(self, model_name, num_labels=5):
        super().__init__()
        self.transformer = AutoModel.from_pretrained(model_name)
        hidden_size = self.transformer.config.hidden_size
        self.classifier = nn.Linear(hidden_size, num_labels)

    def forward(self, input_ids, attention_mask):
        outputs = self.transformer(
            input_ids=input_ids,
            attention_mask=attention_mask
        )
        cls_embeddings = outputs.last_hidden_state[:, 0, :]
        logits = self.classifier(cls_embeddings)
        return logits