class_docstr: Implemented LipSwish activation, i.e. LipSwish(z) := Swish(z)/ 1.1 with a
  learnable parameter beta.
class_docstr_tok: ["Implemented","LipSwish","activation",",","i.e",".","LipSwish","(","z",")",":","=","Swish","(","z",")","\/","1.1","with","a","learnable","parameter","beta","."]
docstr: Parameters
  ----------
  F
      A module that can either refer to the Symbol API or the NDArray
      API in MXNet.
  x
      Input tensor
  beta
      beta parameter of activation
  
  Returns
  -------
  Tensor
      output of forward
docstr_tok: ["Parameters","--","--","--","--","--","F","A","module","that","can","either","refer","to","the","Symbol","API","or","the","NDArray","API","in","MXNet",".","x","Input","tensor","beta","beta","parameter","of","activation","Returns","--","--","--","-","Tensor","output","of","forward"]
code: def hybrid_forward(self, F, x: Tensor, beta: Tensor) -> Tensor:
      """
  
      Parameters
      ----------
      F
          A module that can either refer to the Symbol API or the NDArray
          API in MXNet.
      x
          Input tensor
      beta
          beta parameter of activation
  
      Returns
      -------
      Tensor
          output of forward
  
      """
      return x * F.sigmoid(beta * x, name="fwd") / 1.1
  
file_path: gluonts/src/gluonts/mx/activation.py
imports: from functools import partial
  from typing import Callable
  import mxnet
  import mxnet.gluon.nn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
label_desc: Use image node_id 2 for calling the LipSwish obj's underlying member method code with example usage: obj.hybrid_forward(F, x, beta) and returns: unknown