class_docstr: 单独实现 train_step 和 evaluate_step；
class_docstr_tok: ["\u5355\u72ec\u5b9e\u73b0","train_step","\u548c","evaluate_step\uff1b"]
code: def forward(self, x):
      x = self.ac1(self.linear1(x))
      x = self.ac2(self.linear2(x))
      x = self.output(x)
      return x
  
file_path: fastNLP/tests/helpers/models/torch_model.py
imports: from fastNLP.envs.imports import _NEED_IMPORT_TORCH
label_desc: Use image node_id 2 for calling the TorchNormalModel_Classification_1 obj's underlying member method code with example usage: obj.forward(x) and returns: x