parameters: (var, a=0, mode='fan_in', nonlinearity='leaky_relu')
return_statement: return gauss_(var,0, std)
docstring: Inplace initialize Jittor Var by kaiming_normal.
  
      Args:
          var (Jittor Var):
              Var to be initialized by random kaiming_normal
          a (float):
              the negative slope of the rectifier used after this layer (only used with 'leaky_relu')
          mode (string):
              mode selection, should be fan_in or fan_out.
              Choosing 'fan_in' preserves the magnitude of the variance of the weights in the forward pass. Choosing 'fan_out' preserves the magnitudes in the backwards pass.
          nonlinearity (string):
              nonlinearity used after this layer. 
              It can be one of [linear, conv*, sigmoid, tanh, relu, leaky_relu].
              leaky_relu is used by default.
  
      Example::
  
          from jittor import init
          from jittor import nn
          linear = nn.Linear(2,2)
          init.kaiming_normal_(linear.weight)
          print(linear.weight)
          linear.weight.kaiming_normal_() # This is ok too
docstring_summary: Inplace initialize Jittor Var by kaiming_normal.
docstring_tokens: Inplace initialize Jittor Var by kaiming_normal .
function: def kaiming_normal_(var, a=0, mode='fan_in', nonlinearity='leaky_relu'):
      ''' Inplace initialize Jittor Var by kaiming_normal.
  
      Args:
          var (Jittor Var):
              Var to be initialized by random kaiming_normal
          a (float):
              the negative slope of the rectifier used after this layer (only used with 'leaky_relu')
          mode (string):
              mode selection, should be fan_in or fan_out.
              Choosing 'fan_in' preserves the magnitude of the variance of the weights in the forward pass. Choosing 'fan_out' preserves the magnitudes in the backwards pass.
          nonlinearity (string):
              nonlinearity used after this layer. 
              It can be one of [linear, conv*, sigmoid, tanh, relu, leaky_relu].
              leaky_relu is used by default.
  
      Example::
  
          from jittor import init
          from jittor import nn
          linear = nn.Linear(2,2)
          init.kaiming_normal_(linear.weight)
          print(linear.weight)
          linear.weight.kaiming_normal_() # This is ok too
  
      '''
      std = calculate_std(var,mode,nonlinearity,a)
      return gauss_(var,0, std)
function_tokens: def kaiming_normal_ ( var , a = 0 , mode = 'fan_in' , nonlinearity = 'leaky_relu' ) : std = calculate_std ( var , mode , nonlinearity , a ) return gauss_ ( var , 0 , std )