code: def load_embeddings(params: Dict[str, Any]) -> Embeddings:
      cls_name = params.pop("__cls__")
      cls = EMBEDDING_CLASSES[cls_name]
      return cls.load_embedding(params)
  
imports: import inspect
  import logging
  from abc import abstractmethod
  from typing import Any, Dict, Generic, List, Sequence, Type, Union
  import torch
  from torch.nn import Parameter, ParameterList
  import flair
  from flair.data import DT, Sentence
label_desc: Use image node_id 2 for calling a global function with example usage: load_embeddings(params) and returns: cls