code: def __init__(self):
      super().__init__()
      self.linear = nn.Linear(5, 3, bias=False)
      self.bn = nn.BatchNorm1d(3)
      nn.init.ones_(self.linear.weight)
  
imports: import math
  from pathlib import Path
  import numpy
  import pytest
  import torch
  import torch.nn
  from torch.nn import AvgPool1d, AvgPool2d, MaxPool1d, MaxPool2d
  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 SqueezeModel object from inherited base classes: nn with example: obj = SqueezeModel()