def update_config_with_model_dims(data_loader, config):
    """Updates options by adding the dimension of input features as the dimension of first hidden layer of the model"""
    # Get the first batch (data is in dictionary format)
    x, y = next(iter(data_loader.train_loader))
    # Get the features and turn them into numpy.
    xi = x.cpu().numpy()
    # Get the number of features
    dim = xi.shape[-1]
    # Update the dims of model architecture by adding the number of features as the first dimension
    config["dims"].insert(0, dim)
    return config