code: def test_quantized_matmul(self, quant_dtype):
      class Model(torch.nn.Module):
          def __init__(self):
              super().__init__()
              self.weight = torch.nn.parameter.Parameter(
                  torch.rand(5, 4)
              )
  
          def forward(self, x):
              return torch.ops.quantized.matmul(x, self.weight, 0, 0)
  
      model = Model()
      model = _force_quantize_model(model, q_dtype=quant_dtype)
      input_shape = [(3, 5)]
      self.run_compare_torch(input_shape, model)
  
imports: import itertools
  from typing import Optional
  import numpy
  import pytest
  import torch
  import torchvision
  import coremltools
  from coremltools import TensorType
  from coremltools._deps import _HAS_TORCH, _HAS_TORCH_VISION, MSG_TORCH_NOT_FOUND, MSG_TORCH_VISION_NOT_FOUND
  from coremltools.converters.mil.testing_utils import get_op_types_in_program
  from .testing_utils import TorchBaseTest
label_desc: Use image node_id 5 for calling the TestPytorchQuantizedOps obj's underlying member method code with example usage: obj.test_quantized_matmul(quant_dtype) and returns: torch