class_docstr: Pytorch version >= 1.10 and <1.12, bfloat16 precision is supported.
  But there is no optimization on bfloat16.
code: def test_bf16_pytorch_1_11(self):
      model = resnet18(num_classes=10)
      x = torch.rand((10, 3, 256, 256))
      with pytest.raises(
          RuntimeError,
          match="Require torch>=1.12 to obtain bfloat16 acceleration.",
      ):
          bf16_model = InferenceOptimizer.quantize(
              model, precision="bf16"
          )
  
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_11 obj's underlying member method code with example usage: obj.test_bf16_pytorch_1_11() without return types