class_docstr: 基础的 jittor 分类模型，只实现 execute 函数测试用户自己初始化了分布式的场景
class_docstr_tok: ["\u57fa\u7840\u7684","jittor","\u5206\u7c7b\u6a21\u578b\uff0c\u53ea\u5b9e\u73b0","execute","\u51fd\u6570\u6d4b\u8bd5\u7528\u6237\u81ea\u5df1\u521d\u59cb\u5316\u4e86\u5206\u5e03\u5f0f\u7684\u573a\u666f"]
code: def execute(self, x, y):
      x = self.ac1(self.linear1(x))
      x = self.ac2(self.linear2(x))
      x = self.output(x)
      return {
          "loss": self.loss_fn(x, y),
          "pred": x,
          "target": y.reshape((-1,)),
      }
  
file_path: fastNLP/tests/helpers/models/jittor_model.py
imports: from fastNLP.envs.imports import _NEED_IMPORT_JITTOR
label_desc: Use image node_id 2 for calling the JittorNormalModel_Classification_2 obj's underlying member method code with example usage: obj.execute(x, y) and returns: dict