code: def glorot_uniform(t):
      """Glorot uniform initializer, also called Xavier uniform initializer.
  
      It draws samples from a uniform distribution within [-limit, limit]
      where `limit` is `sqrt(6 / (fan_in + fan_out))`
      where `fan_in` is the number of input units in the weight tensor
      and `fan_out` is the number of output units in the weight tensor.
  
      # Arguments
          t(Tensor):the tensor to be filled in.
      # References
          - [Understanding the difficulty of training deep feedforward neural
             networks](http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf)
      """
      _random_fill(t, scale=1.0, mode="fan_avg", distribution="uniform")
  
file_path: singa/python/singa/initializer.py
imports: from __future__ import division
  import math
  import numpy
  from deprecated import deprecated
label_desc: Use image node_id 5 for calling a global function with example usage: glorot_uniform(t) without return types