docstr: Make each layer in the MLP and add it to self.model.
code: def _make_layers(self):
      """
      Make each layer in the MLP and add it to self.model.
      """
      self.layer_weights = [0] * len(self.layer_widths[1:])
      self.layer_biases = [0] * len(self.layer_widths[1:])
      l = 1
      for width in self.layer_widths[1:]:
          if l == 1:
              if self.standard_first:
                  w_init = lambda x: np.random.normal(0, 1, x)
                  b_init = lambda x: np.zeros((x))
              else:
                  w_init = self.weight_init
                  b_init = self.bias_init
                  w_init.apply_scale = False
                  b_init.apply_scale = False
                  # w_init = create_initialiser(self.weight_init._F,
                  #        self.weight_init._expected_over_D_of_F,
                  #        apply_scale=False,
                  #        use_normal_ABCD = self.weight_init.use_normal_ABCD)
                  # b_init = create_initialiser(self.bias_init._F,
                  #        self.bias_init._expected_over_D_of_F,
                  #        apply_scale=False,
                  #        use_normal_ABCD = self.bias_init.use_normal_ABCD)
          else:
              w_init = self.weight_init
              b_init = self.bias_init
              w_init.apply_scale = True
              b_init.apply_scale = True
          if l == len(self.layer_widths):
              scale_w = 1.0 / np.sqrt(self.layer_widths[l - 1])
              w_init = lambda x: np.random.normal(0, scale_w, x)
              b_init = lambda x: np.zeros((x))
  
          # input_shape = (self.layer_widths[l-1],)
          # activation = self.layer_activations[l-1]
  
          self.layer_weights[l - 1] = w_init(
              (self.layer_widths[l], self.layer_widths[l - 1])
          )
          self.layer_biases[l - 1] = b_init((self.layer_widths[l], 1))
  
          l += 1
  
file_path: elu-gelu-kernels/code/networks/np_mlp.py
imports: import numpy
  from .np_initialisers import create_initialiser
label_desc: Use image node_id 3 for calling the Mlp obj's underlying member method code with example usage: obj._make_layers() without return types