code: def glorot(shape, name=None):
      """Glorot & Bengio (AISTATS 2010) initialization."""
      init_range = np.sqrt(6.0 / (shape[0] + shape[1]))
      initial = tf.random_uniform(
          shape,
          minval=-init_range,
          maxval=init_range,
          dtype=tf.float32,
          name=name,
      )
      return initial
  
file_path: neural-structured-learning/research/gam/gam/models/models_base.py
imports: import abc
  import logging
  import numpy
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: glorot(shape, name) and returns: initial