57591a23e73d3b2ca8132589e68c8a480f1686f5,baseline/tf/lm/model.py,LanguageModelBase,load,#Any#Any#,225

Before Change

            embeddings = {}
            embeddings_dict = _state.pop("embeddings")

            for key, class_name in embeddings_dict.items():
                md = read_json("{}-{}-md.json".format(basename, key))
                embed_args = dict({"vsz": md["vsz"], "dsz": md["dsz"]})
                Constructor = eval(class_name)
                embeddings[key] = Constructor(key, **embed_args)

            model = cls.create(embeddings, **_state)
            model._state = _state

            do_init = kwargs.get("init", True)

After Change

            _state["sess"] = kwargs.pop("sess", create_session())
            embeddings_info = _state.pop("embeddings")

            with _state["sess"].graph.as_default():
                embeddings = reload_embeddings(embeddings_info, basename)
                for k in embeddings_info:
                    if k in kwargs:

Instances