class_docstr: A fully connected network that takes FloatFeatures input
  and supports distributional prediction.
code: def input_prototype(self):
      return rlt.FeatureData(self.fc.input_prototype())
  
imports: import logging
  import math
  from typing import List, Optional
  import torch
  import torch.nn
  import torch.nn.init
  from reagent.core import types
  from reagent.models.base import ModelBase
  from reagent.models.residual_wrapper import ResidualWrapper
label_desc: Use image node_id 2 for calling the FloatFeatureFullyConnected obj's underlying member method code with example usage: obj.input_prototype() and returns: rlt