parameters: (t)
docstring: Initialize the matrix parameter follow a Guassian distribution with
      mean = 0, std = math.sqrt(2.0 / nb_row).
  
      Ref [He, Zhang, Ren and Sun 2015]: Specifically accounts for ReLU
      nonlinearities.
  
      Args:
          t (Tensor): the parater tensor
docstring_summary: Initialize the matrix parameter follow a Guassian distribution with
      mean = 0, std = math.sqrt(2.0 / nb_row).
docstring_tokens: Initialize the matrix parameter follow a Guassian distribution with mean = 0 std = math . sqrt ( 2 . 0 / nb_row ) .
function: def msra(t):
      '''Initialize the matrix parameter follow a Guassian distribution with
      mean = 0, std = math.sqrt(2.0 / nb_row).
  
      Ref [He, Zhang, Ren and Sun 2015]: Specifically accounts for ReLU
      nonlinearities.
  
      Args:
          t (Tensor): the parater tensor
      '''
      t.gaussian(0, math.sqrt(2.0 / t.shape[0]))
function_tokens: def msra ( t ) : t . gaussian ( 0 , math . sqrt ( 2.0 / t . shape [ 0 ] ) )