class_docstr: A BNReLU2d module is a fused module of BatchNorm2d and ReLU
  
  We adopt the same interface as :class:`torch.ao.nn.quantized.BatchNorm2d`.
  
  Attributes:
      Same as torch.ao.nn.quantized.BatchNorm2d
class_docstr_tok: ["A","BNReLU2d","module","is","a","fused","module","of","BatchNorm2d","and","ReLU","We","adopt","the","same","interface","as",":","class",":","`","torch.ao.nn.quantized.BatchNorm2d","`",".","Attributes",":","Same","as","torch.ao.nn.quantized.BatchNorm2d"]
code: def from_float(cls, mod):
      # TODO: Add qat support for BNReLU2d
      return super().from_float(mod)
  
file_path: pytorch/torch/ao/nn/intrinsic/quantized/modules/bn_relu.py
imports: import torch
  import torch.ao.nn.intrinsic
  import torch.ao.nn.intrinsic.qat
  import torch.ao.nn.quantized
label_desc: Use image node_id 4 for calling the BNReLU2d obj's underlying member method code with example usage: obj.from_float(cls, mod) and returns: super