class_docstr: Pytorch version >= 1.10 and <1.12, bfloat16 precision is supported.
  But there is no optimization on bfloat16.
code: def test_unsupported_HW_or_OS(self, mocked_has_bf16_isa):
      mocked_has_bf16_isa.return_value = False
      model = resnet18(num_classes=10)
  
      x = torch.rand((10, 3, 256, 256))
      y = torch.ones((10,), dtype=torch.long)
      bf16_model = InferenceOptimizer.quantize(model, precision="bf16")
      with InferenceOptimizer.get_context(bf16_model):
          y_hat = bf16_model(x)
  
imports: from unittest import TestCase
  import pytest
  import torch
  from bigdl.nano.pytorch import InferenceOptimizer
  from torchvision.models.resnet import resnet18
  from unittest.mock import MagicMock, PropertyMock, patch
  from bigdl.nano.utils.pytorch import TORCH_VERSION_LESS_1_12
  import tempfile
label_desc: Use image node_id 1 for calling the Pytorch1_12 obj's underlying member method code with example usage: obj.test_unsupported_HW_or_OS(mocked_has_bf16_isa) without return types