code: def forward(self, x):
      return self.linear(x)
  
imports: from torch.testing._internal.common_utils import run_tests
  import copy
  import numpy
  import io
  import logging
  from itertools import product
  import torch
  import torch.ao.quantization
  from torch import nn
  from torch.ao.pruning.sparsifier.utils import fqn_to_module
  from torch.testing._internal.common_utils import TestCase, skipIfTorchDynamo
  from torch.testing._internal.common_quantized import override_cpu_allocator_for_qnnpack, override_qengines, qengine_is_qnnpack, qengine_is_fbgemm, qengine_is_onednn, qengine_is_x86
label_desc: Use image node_id 2 for calling the SparseQuantizedModel obj's underlying member method code with example usage: obj.forward(x) and returns: self