code: def forward(self, features):
      mapped_features = self.__linear_map(features)
      if self.__activation is not None:
          mapped_features = self.__activation(mapped_features)
      return mapped_features
  
imports: from typing_extensions import Final
  import numpy
  import torch
  from torch import nn
  from typing import Any, Dict, Optional, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel
  from ptgnn.baseneuralmodel.utils.data import enforce_not_None
  from ptgnn.neuralmodels.gnn.structs import AbstractNodeEmbedder
label_desc: Use image node_id 2 for calling the LinearFeatureEmbedder obj's underlying member method code with example usage: obj.forward(features) and returns: mapped_features