class_docstr: A LinearBn1d module is a module fused from Linear and BatchNorm1d, attached
  with FakeQuantize modules for weight, used in quantization aware training.
  
  We combined the interface of :class:`torch.nn.Linear` and
  :class:torch.nn.BatchNorm1d`.
  
  Similar to :class:`torch.nn.Linear`, with FakeQuantize modules initialized
  to default.
  
  Attributes:
      freeze_bn:
      weight_fake_quant: fake quant module for weight
class_docstr_tok: ["A","LinearBn1d","module","is","a","module","fused","from","Linear","and","BatchNorm1d",",","attached","with","FakeQuantize","modules","for","weight",",","used","in","quantization","aware","training",".","We","combined","the","interface","of",":","class",":","`","torch.nn.Linear","`","and",":","class",":","torch.nn.BatchNorm1d","`",".","Similar","to",":","class",":","`","torch.nn.Linear","`",",","with","FakeQuantize","modules","initialized","to","default",".","Attributes",":","freeze_bn",":","weight_fake_quant",":","fake","quant","module","for","weight"]
docstr: Batchnorm's training behavior is using the self.training flag. Prevent
  changing it if BN is frozen. This makes sure that calling `model.train()`
  on a model with a frozen BN will behave properly.
docstr_tok: ["Batchnorm","'s","training","behavior","is","using","the","self.training","flag",".","Prevent","changing","it","if","BN","is","frozen",".","This","makes","sure","that","calling","`","model.train","(",")","`","on","a","model","with","a","frozen","BN","will","behave","properly","."]
code: def train(self, mode=True):
      """
      Batchnorm's training behavior is using the self.training flag. Prevent
      changing it if BN is frozen. This makes sure that calling `model.train()`
      on a model with a frozen BN will behave properly.
      """
      self.training = mode
      if not self.freeze_bn:
          for module in self.children():
              module.train(mode)
      return self
  
file_path: pytorch/torch/ao/nn/intrinsic/qat/modules/linear_fused.py
imports: import torch
  import torch.nn
  import torch.ao.nn.intrinsic
  import torch.nn.functional
  from torch.nn import init
  from torch.nn.parameter import Parameter
  from torch.nn.utils.fusion import fuse_linear_bn_weights
label_desc: Use image node_id 8 for calling the LinearBn1d obj's underlying member method code with example usage: obj.train(mode) and returns: self