code: def __init__(self):
      super().__init__()
      setattr(self, "layer_0", nn.Linear(16, 64))
      setattr(self, "layer_0a", torch.nn.ReLU())
      for i in range(1, 3):
          setattr(self, f"layer_{i}", nn.Linear(64, 64))
          setattr(self, f"layer_{i}a", torch.nn.ReLU())
      setattr(self, "layer_end", nn.Linear(64, 1))
  
      self.train_mse = MeanSquaredError()
      self.valid_mse = MeanSquaredError()
      self.test_mse = MeanSquaredError()
  
imports: import operator
  import torch
  import torch.nn.functional
  from lightning.pytorch import LightningModule
  from lightning_utilities.core.imports import compare_version
  from torch import nn
  from torchmetrics import Accuracy, MeanSquaredError
label_desc: Use image node_id 1 to create a new RegressionModel object from inherited base classes: LightningModule with example: obj = RegressionModel()