class_docstr: it is a dummy feature engineer , which directly returns identical data
code: def __init__(self, *args, **kwargs):
      super(FeIdentity, self).__init__(multigraph=True, *args, **kwargs)
  
imports: from sklearn import preprocessing
  import numpy
  from sklearn.metrics.pairwise import cosine_similarity
  import copy
  from tqdm import tqdm
  from tabulate import tabulate
  import time
  from .base import BaseFeature, BaseFeatureEngineer
  from .selectors import SeGBDT
  from .None import register_feature
  from ...utils import get_logger
  import torch
label_desc: Use image node_id 1 to create a new FeIdentity object from inherited base classes: BaseFeatureEngineer with example: obj = FeIdentity()