class_docstr: A LinearReLU module fused from Linear and ReLU modules, attached with
  FakeQuantize modules for weight, used in
  quantization aware training.
  
  We adopt the same interface as :class:`torch.nn.Linear`.
  
  Similar to `torch.ao.nn.intrinsic.LinearReLU`, with FakeQuantize modules initialized to
  default.
  
  Attributes:
      weight: fake quant module for weight
  
  Examples::
  
      >>> # xdoctest: +SKIP
      >>> m = nn.qat.LinearReLU(20, 30)
      >>> input = torch.randn(128, 20)
      >>> output = m(input)
      >>> print(output.size())
      torch.Size([128, 30])
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code: def from_float(cls, mod):
      return super().from_float(mod)
  
file_path: pytorch/torch/ao/nn/intrinsic/qat/modules/linear_relu.py
imports: import torch
  import torch.ao.nn.qat
  import torch.ao.nn.intrinsic
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the LinearReLU obj's underlying member method code with example usage: obj.from_float(cls, mod) and returns: super