code: def from_float(cls, mod: _nn.Module):
      if isinstance(mod.conv, cls.qat_mod):
          conv = mod.conv
  
      else:
          assert isinstance(mod.conv, cls.root_mod), (
              f"Failed to convert module for QAT. "
              f"Expected module type {cls.root_mod}, "
              f"received type {type(mod.conv)}."
          )
          conv = cls.qat_mod.from_float(mod.conv)
  
      conv.activation_post_process = None
      return cls(conv, mod.act, mod.qconfig)
  
imports: from collections import OrderedDict
  from typing import Type
  from typing import Union
  import torch
  import torch.ao.nn.intrinsic
  import torch.ao.nn.qat
  import torch.ao.quantization
  import torch.nn
  import torch.nn.intrinsic.qat
  import coremltools.optimize.torch.quantization.modules.fused_modules
label_desc: Use image node_id 5 for calling the _ConvAct obj's underlying member method code with example usage: obj.from_float(cls, mod) and returns: cls