class_docstr: Softmax on multiple dimensions
  
  Parameters
  ----------
  axis : the axis for softmax normalization
class_docstr_tok: ["Softmax","on","multiple","dimensions","Parameters","--","--","--","--","--","axis",":","the","axis","for","softmax","normalization"]
code: def hybrid_forward(self, F, x):
      x_max = F.max(x, axis=self.axis, keepdims=True)
      x_exp = F.exp(F.broadcast_minus(x, x_max))
      norm = F.sum(x_exp, axis=self.axis, keepdims=True)
      res = F.broadcast_div(x_exp, norm)
      return res
  
imports: from __future__ import absolute_import
  from mxnet import initializer
  from mxnet.gluon import nn, contrib
  from mxnet.gluon.nn import BatchNorm, HybridBlock
label_desc: Use image node_id 2 for calling the SoftmaxHD obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: res