code: def forward(self, input: torch.Tensor) -> torch.Tensor:
      assert input.ndim == 3  # type: ignore
      return torch.mean(input, dim=2)
  
file_path: ReAgent/reagent/net_builder/quantile_dqn_net_builder.py
imports: import abc
  from typing import List
  import reagent.core.types
  import torch
  from reagent.core.fb_checker import IS_FB_ENVIRONMENT
  from reagent.core.parameters import NormalizationData
  from reagent.models import ModelBase, Sequential
  from reagent.prediction.predictor_wrapper import DiscreteDqnWithPreprocessor
  from reagent.preprocessing.normalization import get_num_output_features
  from reagent.preprocessing.preprocessor import Preprocessor
label_desc: Use image node_id 1 for calling the _Mean obj's underlying member method code with example usage: obj.forward(input) and returns: torch