code: def word_list_to_embedding(words, embeddings, embedding_dimension=50):
      """
      :param words: an n x (2*window_size + 1) matrix from data_to_mat
      :param embeddings: an embedding dictionary where keys are strings and values
      are embeddings; the output from embeddings_to_dict
      :param embedding_dimension: the dimension of the values in embeddings; in this
      assignment, embedding_dimension=50
      :return: an n x ((2*window_size + 1)*embedding_dimension) matrix where each entry of the
      words matrix is replaced with its embedding
      """
      m, n = words.shape
      words = words.reshape((-1))
  
      return np.array(
          [embeddings[w] for w in words], dtype=np.float32
      ).reshape(m, n * embedding_dimension)
  
file_path: smooth-gelu/twitter_pos.py
imports: import numpy
  import tensorflow
  import pickle
  import sys
  import io
  import os
label_desc: Use image node_id 3 for calling a global function with example usage: word_list_to_embedding(words, embeddings, embedding_dimension) and returns: np