code: def _layernorm_transform(self, X):
      mean = np.mean(X, axis=1)
      mean_exp = np.outer(mean, np.ones(X.shape[1]))
      std = np.std(X, axis=1)
      std_exp = np.outer(std, np.ones(X.shape[1]))
      Y = (X - mean_exp) / std_exp
      return Y
  
file_path: pytorch/caffe2/contrib/fakelowp/test/test_layernorm_nnpi_fp16.py
imports: import numpy
  import caffe2.python.fakelowp.init_shared_libs
  from caffe2.proto import caffe2_pb2
  from caffe2.python import core
  from caffe2.python import workspace
  from caffe2.python.onnx.onnxifi import onnxifi_caffe2_net
  from caffe2.python.fakelowp.test_utils import print_test_debug_info
  from hypothesis import given, settings
  from hypothesis import strategies
  import caffe2.python.serialized_test.serialized_test_util
  import datetime
label_desc: Use image node_id 3 for calling the LayerNorm obj's underlying member method code with example usage: obj._layernorm_transform(X) and returns: Y