code: def forward(self, x):
      if x.dim() == 2:
          return self._forward_sparse(x)
      elif x.dim() == 3:
          return self._forward_dense(x)
      else:
          raise ValueError(
              "Non supported number of dimensions {}".format(x.dim())
          )
  
imports: import numpy
  import torch
  from torch import nn
  from torch.nn.parameter import Parameter
label_desc: Use image node_id 4 for calling the FastBatchNorm1d obj's underlying member method code with example usage: obj.forward(x) and returns: self, self