code: def forward(cls, ctx, X, dim=0, k=None):
      ctx.dim = dim
  
      max_val, _ = X.max(dim=dim, keepdim=True)
      X = X - max_val  # same numerical stability trick as for softmax
      X = X / 2  # divide by 2 to solve actual Entmax
  
      tau_star, _ = _entmax_threshold_and_support(X, dim=dim, k=k)
  
      Y = torch.clamp(X - tau_star, min=0) ** 2
      ctx.save_for_backward(Y)
      return Y
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from torch.autograd import Function
  from torch.jit import script
label_desc: Use image node_id 1 for calling the Entmax15Function obj's underlying member method code with example usage: obj.forward(cls, ctx, X, dim, k) and returns: Y