code: def prepare_glove():
      if not (
          os.path.exists("glove.840B.300d.txt")
          and data.utils.check_sha1(
              "glove.840B.300d.txt",
              sha1_hash="294b9f37fa64cce31f9ebb409c266fc379527708",
          )
      ):
          zip_path = data.utils.download(
              "http://nlp.stanford.edu/data/glove.840B.300d.zip",
              sha1_hash="8084fbacc2dee3b1fd1ca4cc534cbfff3519ed0d",
          )
          with zipfile.ZipFile(zip_path, "r") as zf:
              zf.extractall()
          if not data.utils.check_sha1(
              "glove.840B.300d.txt",
              sha1_hash="294b9f37fa64cce31f9ebb409c266fc379527708",
          ):
              warnings.warn(
                  "The downloaded glove embedding file checksum mismatch. File content "
                  "may be corrupted."
              )
  
file_path: dgl/examples/mxnet/tree_lstm/train.py
imports: import argparse
  import collections
  import os
  import time
  import warnings
  import zipfile
  import dgl
  import dgl.data
  import mxnet
  import numpy
  from mxnet import gluon
  from tree_lstm import TreeLSTM
label_desc: Use image node_id 2 for calling a global function with example usage: prepare_glove() without return types