code: def build(self, config):
      # check config and update
      self._check_config(**config)
      self.config = config
      # build model
      if "selected_features" in config:
          config["input_feature_num"] = (
              len(config["selected_features"])
              + config["output_feature_num"]
          )
      self.model = self.model_creator(config)
      if not isinstance(self.model, torch.nn.Module):
          raise ValueError(
              "You must create a torch model in model_creator"
          )
      self.model_built = True
      self._create_loss()
      self._create_optimizer()
  
imports: import torch
  from torch.utils.data import TensorDataset, DataLoader
  import types
  import numpy
  import math
  import pandas
  import tempfile
  import os
  from zoo.orca.automl.model.abstract import BaseModel, ModelBuilder
  from zoo.orca.automl.metrics import Evaluator
  from zoo.orca.automl.pytorch_utils import LR_NAME, DEFAULT_LR
label_desc: Use image node_id 4 for calling the PytorchBaseModel obj's underlying member method code with example usage: obj.build(config) without return types