def load_metaparameters(param_dict=None):
    """
    Parameters for bayesian optimizer. Default dictionary listed and updated by param_dict.
    """
    metaparams = {
        'conv_units': 3,
        'filters': 80,
        'filters_roc': 0.,
        'kernel_size': 100,
        'kernel_roc': -1.,
        'stride': 5,
        'stride_roc': -0.5,
        'conv_dropout': 0.3,
        'pool_size': 3,
        'pool_roc': 0.,
        'dense_units': 2,
        'nodes': 2300,
        'nodes_roc': -1.,
        'dense_dropout': 0.5,
        'log_lr': -3,
        'log_beta_1': -1,
        'log_beta_2': -3
    }
    if param_dict: metaparams.update(param_dict)
    metaparams['conv_units'] = int(metaparams['conv_units'])
    metaparams['dense_units'] = int(metaparams['dense_units'])
    return metaparams