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):
      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)
  
imports: import torch
  from torch.nn import Linear, BatchNorm1d, ReLU
  import numpy
  from pytorch_tabnet import sparsemax
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