docstr: Fuse conv/bn/relu modules in googlenet model
  
  Fuse conv+bn+relu/ conv+relu/conv+bn modules to prepare for quantization.
  Model is modified in place.  Note that this operation does not change numerics
  and the model after modification is in floating point
docstr_tok: ["Fuse","conv\/bn\/relu","modules","in","googlenet","model","Fuse","conv+bn+relu\/","conv+relu\/conv+bn","modules","to","prepare","for","quantization",".","Model","is","modified","in","place",".","Note","that","this","operation","does","not","change","numerics","and","the","model","after","modification","is","in","floating","point"]
code: def fuse_model(self, is_qat: Optional[bool] = None) -> None:
      r"""Fuse conv/bn/relu modules in googlenet model
  
      Fuse conv+bn+relu/ conv+relu/conv+bn modules to prepare for quantization.
      Model is modified in place.  Note that this operation does not change numerics
      and the model after modification is in floating point
      """
  
      for m in self.modules():
          if type(m) is QuantizableBasicConv2d:
              m.fuse_model(is_qat)
  
imports: import warnings
  from functools import partial
  from typing import Any, Optional, Union
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import functional
  from ...transforms._presets import ImageClassification
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _IMAGENET_CATEGORIES
  from .._utils import _ovewrite_named_param, handle_legacy_interface
  from ..googlenet import BasicConv2d, GoogLeNet, GoogLeNet_Weights, GoogLeNetOutputs, Inception, InceptionAux
  from .utils import _fuse_modules, _replace_relu, quantize_model
label_desc: Use image node_id 3 for calling the QuantizableGoogLeNet obj's underlying member method code with example usage: obj.fuse_model(is_qat) without return types