code: def __init__(
      self,
      in_size: int = -1,
      out_size: int = 1,
      hidden_size: int = 256,
      num_layers: int = 3,
      bias: bool = False,
  ):
      super(DotPredictor, self).__init__()
      lins_list = []
      for _ in range(num_layers - 2):
          lins_list.append(nn.Linear(in_size, hidden_size, bias=bias))
          lins_list.append(nn.ReLU())
      lins_list.append(nn.Linear(hidden_size, out_size, bias=bias))
      self.linear = nn.Sequential(*lins_list)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new DotPredictor object from inherited base classes: nn with example: obj = DotPredictor(in_size, out_size, hidden_size, num_layers, bias)