code: def keras_resnet50(tmpdir_factory):
      try:
          from tensorflow.keras.applications.resnet50 import ResNet50
      except ImportError:
          # not all environments provide TensorFlow, so skip this fixture
          # if that is that case.
          return ""
  
      model_file_name = "{}/{}".format(
          tmpdir_factory.mktemp("data"), "resnet50.h5"
      )
      model = ResNet50(
          include_top=True,
          weights="imagenet",
          input_shape=(224, 224, 3),
          classes=1000,
      )
      model.save(model_file_name)
  
      return model_file_name
  
imports: import os
  import pytest
  import tarfile
  import textwrap
  import numpy
  from PIL import Image
  import tvm
  from tvm import relay
  from tvm.driver import tvmc
  from tvm.contrib.download import download_testdata
label_desc: Use image node_id 4 for calling a global function with example usage: keras_resnet50(tmpdir_factory) and returns: model_file_name, str