class_docstr: PalettizationCustomConversionBase is the base class for palettized model conversion. It implements the
  get_finalized_weights method which returns the palettized weights from ``LUT`` and ``indices``
  post-palettization.
code: def do_attribute_assertions(cls, observed_module: _nn.Module):
      assert hasattr(
          observed_module, "qconfig"
      ), f"Module {type(observed_module)} has no attribute qconfig"
      assert hasattr(observed_module, "activation_post_process"), (
          f"Module {type(observed_module)} has no "
          f"attribute activation_post_process "
      )
      assert hasattr(observed_module, "weight_fake_quant"), (
          f"Module {type(observed_module)} has no attribute "
          f"weight_fake_quant "
      )
  
imports: import torch.nn
  import torch.nn.qat
  from ._supported_modules import Conv1d, Embedding, LayerNorm, MultiheadAttention
label_desc: Use image node_id 2 for calling the PalettizationCustomConversionBase obj's underlying member method code with example usage: obj.do_attribute_assertions(cls, observed_module) without return types