code: def __init__(self):
      super().__init__()
      self.layer = nn.Sequential(
          OrderedDict(
              [
                  ("conv_1", nn.Conv2d(1, 20, 5)),
                  ("relu_1", nn.ReLU()),
                  ("conv_2", nn.Conv2d(20, 64, 5)),
                  ("relu_2", nn.ReLU()),
              ]
          )
      )
  
file_path: hls4ml/test/pytest/test_sequential_parsing_pytorch.py
imports: from collections import OrderedDict
  from pathlib import Path
  import pytest
  import torch.nn
  from hls4ml.converters import convert_from_pytorch_model
  from hls4ml.utils.config import config_from_pytorch_model
label_desc: Use image node_id 1 to create a new SeqModelNamedLayers object from inherited base classes: nn with example: obj = SeqModelNamedLayers()