code: def generate_embedding_table(vocab_size, embedding_size):
      log.info(
          "Generating embedding table with dimensions {}".format(
              [vocab_size, embedding_size]
          )
      )
  
      generate_table_net = core.Net("generate_table")
      table = generate_table_net.GaussianFill(
          [],
          ["embedding_table"],
          shape=[vocab_size, embedding_size],
      )
  
      workspace.RunNetOnce(generate_table_net)
      return table
  
file_path: pytorch/caffe2/python/embedding_generation_benchmark.py
imports: from caffe2.proto import caffe2_pb2
  from caffe2.python import workspace, core, utils, model_helper
  import argparse
  import numpy
  import time
  import logging
label_desc: Use image node_id 2 for calling a global function with example usage: generate_embedding_table(vocab_size, embedding_size) and returns: table