class_docstr: A model that maps a feature array to a D-sized representation (embedding) using a single linear layer.
class_docstr_tok: ["A","model","that","maps","a","feature","array","to","a","D-sized","representation","(","embedding",")","using","a","single","linear","layer","."]
code: def tensorize(self, datapoint: np.ndarray) -> np.ndarray:
      return datapoint
  
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 6 for calling the FeatureRepresentationModel obj's underlying member method code with example usage: obj.tensorize(datapoint) and returns: datapoint