code: def _get_inputs(self, N, C, H, W, order):
      input_data = np.random.rand(N, C, H, W).astype(np.float32)
      if order == "NHWC":
          # Allocate in the same order as NCHW and transpose to make sure
          # the inputs are identical on freshly-seeded calls.
          input_data = utils.NCHW2NHWC(input_data)
      elif order != "NCHW":
          raise Exception("unknown order type ({})".format(order))
  
      scale_data = np.random.rand(C).astype(np.float32)
      bias_data = np.random.rand(C).astype(np.float32)
      return input_data, scale_data, bias_data
  
file_path: pytorch/caffe2/python/operator_test/instance_norm_test.py
imports: import numpy
  from hypothesis import given, assume, settings
  import hypothesis.strategies
  from caffe2.python import core, model_helper, brew, utils
  import caffe2.python.hypothesis_test_util
  import caffe2.python.serialized_test.serialized_test_util
  import unittest
label_desc: Use image node_id 1 for calling the TestInstanceNorm obj's underlying member method code with example usage: obj._get_inputs(N, C, H, W, order) and returns: input_data,  scale_data,  bias_data