code: def forward(self, inputs):
      x = torch.nn.functional.relu(self.input_layer(inputs))
      x = torch.nn.functional.relu(self.mid_layer(x))
      return torch.nn.functional.softmax(self.output_layer(x), dim=-1)
  
file_path: quanto/test/test_serialization.py
imports: import io
  import pytest
  import torch
  from helpers import random_qtensor, random_tensor
  from quanto import Calibration, QTensor, absmax_scale, freeze, quantize
  from quanto.nn import QLinear, QModuleMixin
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.forward(inputs) and returns: torch