code: def mean_grad(grad_out, outputs, inputs):
      return np.repeat(
          np.expand_dims(grad_out / inputs[0].shape[0], 0),
          inputs[0].shape[0],
          axis=0,
      )
  
imports: from functools import partial
  from hypothesis import given, settings
  import numpy
  import unittest
  import hypothesis.strategies
  from caffe2.python import core, workspace
  import caffe2.python.hypothesis_test_util
  import caffe2.python.serialized_test.serialized_test_util
label_desc: Use image node_id 8 for calling a global function with example usage: mean_grad(grad_out, outputs, inputs) and returns: np