docstr: x should have shape (N, embedding_size)
docstr_tok: ["x","should","have","shape","(","N",",","embedding_size",")"]
code: def forward(self, x):
      """
      x should have shape (N, embedding_size)
      """
      self.reset_stats()
      loss_dict = self.compute_loss(x)
      return self.reducer(loss_dict, x, c_f.torch_arange_from_size(x))
  
imports: from ..utils import common_functions
  from ..utils.module_with_records_and_reducer import ModuleWithRecordsReducerAndDistance
label_desc: Use image node_id 2 for calling the BaseRegularizer obj's underlying member method code with example usage: obj.forward(x) and returns: self