code: def __init__(
      self,
      F=F,
      in_joints=IN_JOINTS,
      out_joints=OUT_JOINTS,
      regularization=0.0,
      max_norm=True,
      residual=True,
      mask_type="locally_connected",
      neighbour_matrix=neighbour_matrix,
      init_type="ones",
      in_F=IN_F,
  ):
      super().__init__()
      self.F = F
      self.in_joints = in_joints
      self.regularizers = []
      self.regularization = regularization
      self.max_norm = max_norm
      self.out_joints = out_joints
      self.residual = residual
      self.mask_type = mask_type
  
      self.init_type = init_type
      self.in_F = in_F
  
      assert neighbour_matrix.shape[0] == neighbour_matrix.shape[1]
      assert neighbour_matrix.shape[0] == in_joints
      self.neighbour_matrix = neighbour_matrix
  
      self._initialize_mask()
  
imports: import numpy
  import tensorflow
  from tensorlayer.layers import Layer, Dropout, Dense, Input, BatchNorm, Reshape, Elementwise
  from tensorlayer.models import Model
  from tensorlayer import logging
  from .common import mask_weight, neighbour_matrix
label_desc: Use image node_id 1 to create a new Base_layer object from inherited base classes: Layer with example: obj = Base_layer(F, in_joints, out_joints, regularization, max_norm, residual, mask_type, neighbour_matrix, init_type, in_F)