class_docstr: A ConvReLU2d module is a fused module of Conv2d and ReLU
  
  We adopt the same interface as :class:`torch.ao.nn.quantized.Conv2d`.
  
  Attributes:
      Same as torch.ao.nn.quantized.Conv2d
class_docstr_tok: ["A","ConvReLU2d","module","is","a","fused","module","of","Conv2d","and","ReLU","We","adopt","the","same","interface","as",":","class",":","`","torch.ao.nn.quantized.Conv2d","`",".","Attributes",":","Same","as","torch.ao.nn.quantized.Conv2d"]
code: def from_reference(cls, ref_qconv, output_scale, output_zero_point):
      assert (
          type(ref_qconv) != torch.ao.nn.intrinsic.ConvBnReLU2d
      ), "BatchNorm2d should be fused into Conv2d before converting to reference module"
      return super().from_reference(
          ref_qconv[0], output_scale, output_zero_point
      )
  
imports: import torch
  import torch.ao.nn.intrinsic
  import torch.ao.nn.intrinsic.qat
  import torch.nn.functional
  import torch.ao.nn.quantized
  from torch.nn.utils import fuse_conv_bn_weights
label_desc: Use image node_id 5 for calling the ConvReLU2d obj's underlying member method code with example usage: obj.from_reference(cls, ref_qconv, output_scale, output_zero_point) and returns: super