code: def __init__(self):
      super(MetaModel, self).__init__()
      self.features = MetaSequential(
          OrderedDict(
              [
                  ("linear1", nn.Linear(2, 3)),
                  ("relu1", nn.ReLU()),
                  ("linear2", nn.Linear(3, 5)),
                  ("relu2", nn.ReLU()),
              ]
          )
      )
      self.classifier = MetaLinear(5, 7, bias=False)
  
file_path: pytorch-meta/torchmeta/tests/modules/test_module.py
imports: import pytest
  import torch
  import torch.nn
  from collections import OrderedDict
  from torchmeta.modules import MetaLinear, MetaModule, MetaSequential
label_desc: Use image node_id 1 to create a new MetaModel object from inherited base classes: MetaModule with example: obj = MetaModel()