'Creates a model from previously saved checkpoint.
Parameters
prefix : str
path prefix of saved model files. You should have
"prefix-symbol.json", "prefix-xxxx.params", and
optionally "prefix-xxxx.states", where xxxx is the
epoch number.
epoch : int
epoch to load.
load_optimizer_states : bool
whether to load optimizer states. Checkpoint needs
to have been made with save_optimizer_states=True.
data_names : list of str
Default is `(\'data\')` for a typical model used in image classification.
label_names : list of str
Default is `(\'softmax_label\')` for a typical model used in image
classification.
logger : Logger
Default is `logging`.
context : Context or list of Context
Default is ``cpu()``.
work_load_list : list of number
Default ``None``, indicating uniform workload.
fixed_param_names: list of str
Default ``None``, indicating no network parameters are fixed.'

@staticmethod
def load(prefix, epoch, load_optimizer_states=False, **kwargs):

    (sym, args, auxs) = load_checkpoint(prefix, epoch)
    mod = Module(symbol=sym, **kwargs)
    mod._arg_params = args
    mod._aux_params = auxs
    mod.params_initialized = True
    if load_optimizer_states:
        mod._preload_opt_states = ('%s-%04d.states' % (prefix, epoch))
    return mod
