code: def test_instance_norm_device_check(
      self,
      gc,
      dc,
      N,
      C,
      H,
      W,
      order,
      store_mean,
      store_inv_stdev,
      epsilon,
      seed,
  ):
      np.random.seed(seed)
  
      # force store_inv_stdev if store_mean to match existing forward pass
      # implementation
      store_inv_stdev |= store_mean
  
      inputs = self._get_inputs(N, C, H, W, order)
      op = self._get_op(
          device_option=gc,
          store_mean=store_mean,
          store_inv_stdev=store_inv_stdev,
          epsilon=epsilon,
          order=order,
      )
  
      self.assertDeviceChecks(dc, op, inputs, [0])
  
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 7 for calling the TestInstanceNorm obj's underlying member method code with example usage: obj.test_instance_norm_device_check(gc, dc, N, C, H, W, order, store_mean, store_inv_stdev, epsilon, seed) without return types