code: def download_model(model_name, dst_dir="./", meta_info=None):
      """Download a model from data.mxnet.io
  
      Parameters
      ----------
      model_name : str
          Model name to download
      dst_dir : str
          Destination Directory to download the model
      meta_info : dict of dict
          Mapping from model_name to dict of the following structure:
          {'symbol': url, 'params': url}
  
      Returns
      -------
      Two element tuple containing model_name and epoch for the params saved
      """
      _base_model_url = "http://data.mxnet.io/models/"
      _default_model_info = {
          "imagenet1k-inception-bn": {
              "symbol": _base_model_url
              + "imagenet/inception-bn/Inception-BN-symbol.json",
              "params": _base_model_url
              + "imagenet/inception-bn/Inception-BN-0126.params",
          },
          "imagenet1k-resnet-18": {
              "symbol": _base_model_url
              + "imagenet/resnet/18-layers/resnet-18-symbol.json",
              "params": _base_model_url
              + "imagenet/resnet/18-layers/resnet-18-0000.params",
          },
          "imagenet1k-resnet-34": {
              "symbol": _base_model_url
              + "imagenet/resnet/34-layers/resnet-34-symbol.json",
              "params": _base_model_url
              + "imagenet/resnet/34-layers/resnet-34-0000.params",
          },
          "imagenet1k-resnet-50": {
              "symbol": _base_model_url
              + "imagenet/resnet/50-layers/resnet-50-symbol.json",
              "params": _base_model_url
              + "imagenet/resnet/50-layers/resnet-50-0000.params",
          },
          "imagenet1k-resnet-101": {
              "symbol": _base_model_url
              + "imagenet/resnet/101-layers/resnet-101-symbol.json",
              "params": _base_model_url
              + "imagenet/resnet/101-layers/resnet-101-0000.params",
          },
          "imagenet1k-resnet-152": {
              "symbol": _base_model_url
              + "imagenet/resnet/152-layers/resnet-152-symbol.json",
              "params": _base_model_url
              + "imagenet/resnet/152-layers/resnet-152-0000.params",
          },
          "imagenet1k-resnext-50": {
              "symbol": _base_model_url
              + "imagenet/resnext/50-layers/resnext-50-symbol.json",
              "params": _base_model_url
              + "imagenet/resnext/50-layers/resnext-50-0000.params",
          },
          "imagenet1k-resnext-101": {
              "symbol": _base_model_url
              + "imagenet/resnext/101-layers/resnext-101-symbol.json",
              "params": _base_model_url
              + "imagenet/resnext/101-layers/resnext-101-0000.params",
          },
          "imagenet1k-resnext-101-64x4d": {
              "symbol": _base_model_url
              + "imagenet/resnext/101-layers/resnext-101-64x4d-symbol.json",
              "params": _base_model_url
              + "imagenet/resnext/101-layers/resnext-101-64x4d-0000.params",
          },
          "imagenet11k-resnet-152": {
              "symbol": _base_model_url
              + "imagenet-11k/resnet-152/resnet-152-symbol.json",
              "params": _base_model_url
              + "imagenet-11k/resnet-152/resnet-152-0000.params",
          },
          "imagenet11k-place365ch-resnet-152": {
              "symbol": _base_model_url
              + "imagenet-11k-place365-ch/resnet-152-symbol.json",
              "params": _base_model_url
              + "imagenet-11k-place365-ch/resnet-152-0000.params",
          },
          "imagenet11k-place365ch-resnet-50": {
              "symbol": _base_model_url
              + "imagenet-11k-place365-ch/resnet-50-symbol.json",
              "params": _base_model_url
              + "imagenet-11k-place365-ch/resnet-50-0000.params",
          },
      }
  
      if meta_info is None:
          meta_info = _default_model_info
      meta_info = dict(meta_info)
      if model_name not in meta_info:
          return (None, 0)
      if not os.path.isdir(dst_dir):
          os.mkdir(dst_dir)
      meta = dict(meta_info[model_name])
      assert "symbol" in meta, "missing symbol url"
      model_name = os.path.join(dst_dir, model_name)
      download(meta["symbol"], model_name + "-symbol.json")
      assert "params" in meta, "mssing parameter file url"
      download(meta["params"], model_name + "-0000.params")
      download(_base_model_url + "imagenet/synset.txt")
      return (model_name, 0)
  
imports: import logging
  import argparse
  import requests
  import errno
  import os
label_desc: Use image node_id 2 for calling a global function with example usage: download_model(model_name, dst_dir, meta_info) and returns: model_name,  int, None,  int