def eval(model: RNDNetwork, obs: Tensor) -> float:
    """
     **Overview**:
        Testing function for the RND model.
    """
    # The evaluation is done with no gradients computed
    with torch.no_grad():
        # Forward pass
        target_feature, pred_feature = model(obs)

        # Compute the loss as the MSE between the target and predicted features
        loss = ((target_feature - pred_feature) ** 2).mean()

    # Return the evaluation loss
    return loss.item()

     **Overview**:
        Testing function for the RND model.
    
chapter4_reward/curiosity_rnd.py