code: def softmax(self, dim, **kwargs):
      r"""Compute the softmax of a tensor's elements along a given dimension"""
      # 0-d case
      if self.dim() == 0:
          assert dim == 0, "Improper dim argument"
          return self.new(torch.ones_like((self.data)))
  
      if self.size(dim) == 1:
          return self.new(torch.ones_like(self.data))
  
      maximum_value = self.max(dim, keepdim=True)[0]
      logits = self - maximum_value
      numerator = logits.exp()
      with cfg.temp_override({"functions.reciprocal_all_pos": True}):
          inv_denominator = numerator.sum(
              dim, keepdim=True
          ).reciprocal()
      return numerator * inv_denominator
  
file_path: CrypTen/crypten/common/functions/approximations.py
imports: import math
  import crypten
  import torch
  from crypten.config import cfg
label_desc: Use image node_id 14 for calling a global function with example usage: softmax(dim) and returns: unknown, self, self