code: def __init__(
      self,
      actions,
      num_feat,
      num_label,
      drop_out=0.6,
      multi_label=False,
      batch_normal=True,
      state_num=5,
      residual=False,
      layers=2,
  ):
      self.residual = residual
      self.batch_normal = batch_normal
      self.layer_nums = layers
      self.multi_label = multi_label
      self.num_feat = num_feat
      self.num_label = num_label
      self.input_dim = num_feat
      self.output_dim = num_label
      self.dropout = drop_out
  
      super().__init__()
      self.build_model(
          actions,
          batch_normal,
          drop_out,
          num_feat,
          num_label,
          state_num,
      )
  
imports: import torch
  import typing
  import torch.nn
  import torch.nn.functional
  from .None import register_nas_space
  from .base import BaseSpace, map_nn
  from ...model import BaseAutoModel
  from .operation import act_map
  from ..utils import count_parameters, measure_latency
  from ..backend import *
  from operator import *
  from .operation import *
label_desc: Use image node_id 1 to create a new GraphNet object from inherited base classes: BaseSpace with example: obj = GraphNet(actions, num_feat, num_label, drop_out, multi_label, batch_normal, state_num, residual, layers)