code: def he_uniform(t):
      """Initialize the values of the input tensor following a uniform
      distribution with specific bounds.
  
      It draws samples from a uniform distribution within [-limit, limit]
      where `limit` is `sqrt(6 / fan_in)`
      where `fan_in` is the number of input units in the weight tensor.
  
      # Arguments
          t(Tensor): the tensor to be filled in.
  
      # References
          - [Delving Deep into Rectifiers: Surpassing Human-Level Performance on
             ImageNet Classification](http://arxiv.org/abs/1502.01852)
      """
      _random_fill(t, scale=2.0, mode="fan_in", 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 8 for calling a global function with example usage: he_uniform(t) without return types