code: def prepare_embedding(
      embedding_file,
      word_index=None,
      randomize_unknown=False,
      normalize=False,
  ):
      """
      Prepare embedding weights from embedding_file given word_index.
  
      # Arguments
      embedding_file and word_index: See WordEmbedding.
      randomize_unknown: Boolean. Whether to randomly initialize words that don't exist in
                         embedding_file. Default is False and in this case corresponding entries
                         to unknown words will be zero vectors.
      normalize: Boolean. Whether to normalize word vectors. Default is False.
  
      # Return
      Pretrained embedding weights as a numpy array.
      """
      return callZooFunc(
          "float",
          "prepareEmbedding",
          embedding_file,
          word_index,
          randomize_unknown,
          normalize,
      ).to_ndarray()
  
file_path: BigDL/python/dllib/src/bigdl/dllib/keras/layers/embeddings.py
imports: import sys
  from bigdl.dllib.utils.common import JTensor
  from bigdl.dllib.utils.file_utils import callZooFunc
  from ..engine.topology import ZooKerasLayer
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_embedding(embedding_file, word_index, randomize_unknown, normalize) and returns: callZooFunc