code: def pytorch_model():
      class PytorchModel(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.hidden_layer = torch.nn.Linear(1, 1)
              self.hidden_layer.weight = torch.nn.Parameter(
                  torch.tensor([[1.58]])
              )
              self.hidden_layer.bias = torch.nn.Parameter(
                  torch.tensor([-0.14])
              )
  
              self.output_layer = torch.nn.Linear(1, 1)
              self.output_layer.weight = torch.nn.Parameter(
                  torch.tensor([[2.45]])
              )
              self.output_layer.bias = torch.nn.Parameter(
                  torch.tensor([-0.11])
              )
  
          def forward(self, x):
              x = torch.sigmoid(self.hidden_layer(x))
              x = torch.sigmoid(self.output_layer(x))
              return x
  
      return PytorchModel()
  
imports: import pytest
label_desc: Use image node_id 2 for calling a global function with example usage: pytorch_model() and returns: PytorchModel, x