code: def forward(cls, ctx, X, target, n_iter=50):
      return super().forward(
          ctx, X, target, alpha=2, proj_args=dict(n_iter=n_iter)
      )
  
imports: import torch
  import torch.nn
  from torch.autograd import Function
  from ludwig.constants import IGNORE_INDEX_TOKEN_ID
  from ludwig.utils.entmax.activations import entmax15, sparsemax
  from ludwig.utils.entmax.root_finding import entmax_bisect, sparsemax_bisect
label_desc: Use image node_id 3 for calling the SparsemaxBisectLossFunction obj's underlying member method code with example usage: obj.forward(cls, ctx, X, target, n_iter) and returns: super