class_docstr: Log-space in and out
code: def input_prototype(self):
      # Sample config for input
      batch_size = 2
      state_dim = 5
      num_docs = 3
      candidate_dim = 4
      return rlt.FeatureData(
          float_features=torch.randn((batch_size, state_dim)),
          candidate_docs=rlt.DocList(
              float_features=torch.randn(
                  batch_size, num_docs, candidate_dim
              )
          ),
      )
  
file_path: ReAgent/reagent/models/mlp_scorer.py
imports: import reagent.core.types
  import torch
  from reagent.models.base import ModelBase
label_desc: Use image node_id 3 for calling the MLPScorer obj's underlying member method code with example usage: obj.input_prototype() and returns: rlt