class_docstr: it is a dummy feature engineer , which directly returns identical data
code: def _transform(self, data):
      if "x" in data:
          data.x = torch.ones((data.x.shape[0], 1))
      else:
          data.x = torch.ones(
              (torch.unique(data.edge_index).shape[0], 1)
          )
      return data
  
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 2 for calling the Onlyconst obj's underlying member method code with example usage: obj._transform(data) and returns: data