class_docstr: Ghost Batch Normalization
  https://arxiv.org/abs/1705.08741
class_docstr_tok: ["Ghost","Batch","Normalization","https",":","\/\/arxiv.org\/abs\/1705.08741"]
code: def forward(self, x):
      if self.training:
          chunks = x.chunk(
              int(np.ceil(x.shape[0] / self.virtual_batch_size)), 0
          )
          res = [self.bn(x_) for x_ in chunks]
          return torch.cat(res, dim=0)
      else:
          return self.bn(x)
  
file_path: pytorch_tabular/src/pytorch_tabular/models/common/layers/batch_norm.py
imports: import numpy
  import torch
  from torch import nn
label_desc: Use image node_id 2 for calling the GBN obj's underlying member method code with example usage: obj.forward(x) and returns: torch, self