code: def _get_initializer(random_init):
      if random_init:
          kernel_initializer = keras.initializers.glorot_uniform()
      else:
          kernel_initializer = keras.initializers.glorot_uniform(seed=0)
      return kernel_initializer
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/layers/conv_batchnorm_test_utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: _get_initializer(random_init) and returns: kernel_initializer