class_docstr: Simple CategoricalMLPModel for testing.
  
  Args:
      output_dim (int): Dimension of the network output.
      name (str): Policy name, also the variable scope.
      args: Extra arguments which are not used.
      kwargs: Extra keyword arguments which are not used.
class_docstr_tok: ["Simple","CategoricalMLPModel","for","testing",".","Args",":","output_dim","(","int",")",":","Dimension","of","the","network","output",".","name","(","str",")",":","Policy","name",",","also","the","variable","scope",".","args",":","Extra","arguments","which","are","not","used",".","kwargs",":","Extra","keyword","arguments","which","are","not","used","."]
docstr: Network output spec.
  
  Returns:
      list[str]: Name of the model outputs, in order.
docstr_tok: ["Network","output","spec",".","Returns",":","list","[","str","]",":","Name","of","the","model","outputs",",","in","order","."]
code: def network_output_spec(self):
      """Network output spec.
  
      Returns:
          list[str]: Name of the model outputs, in order.
  
      """
      return ["prob", "dist"]
  
imports: import tensorflow_probability
  from tests.fixtures.models.simple_mlp_model import SimpleMLPModel
label_desc: Use image node_id 2 for calling the SimpleCategoricalMLPModel obj's underlying member method code with example usage: obj.network_output_spec() and returns: list