import torch
import torch.nn as nn

class EridaModel(nn.Module):
    def __init__(self, input_dim, hidden_dim):
        super().__init__()
        self.encoder = nn.Sequential(
            nn.Linear(input_dim, hidden_dim),
            nn.GELU(),
            nn.Dropout(0.1)
        )
        self.attention = nn.MultiheadAttention(hidden_dim, 8)
        
    def forward(self, x):
        features = self.encoder(x)
        attended, _ = self.attention(features, features, features)
        return attended