code: def activation(self, x, f="sigmoid", der=False):
          
          if f == "sigmoid":
              if der:
                  return x * (1 - x)
              return 1. / (1 + np.exp(-x))
          elif f == "tanh":
              if der:
                  return 1 - x**2 
              return (2. / (1 + np.exp(-2*x))) - 1
docs: This function process values of layer outputs with activation function.
  
          **Args:**
  
          * `x` : array to process (1-dimensional array) 
  
          **Kwargs:**
  
          * `f` : activation function
  
          * `der` : normal output, or its derivation (bool)
  
          **Returns:**
  
          * values processed with activation function (1-dimensional array)