code: def __call__(self, df):
      genres = set(g for col in df.values for g in col.split(self.sep))
      mapping = {genre: i for i, genre in enumerate(genres)}
  
      x = torch.zeros(len(df), len(mapping))
      for i, col in enumerate(df.values):
          for genre in col.split(self.sep):
              x[i, mapping[genre]] = 1
      return x
  
file_path: pytorch_geometric/examples/hetero/load_csv.py
imports: import os.path
  import pandas
  import torch
  from sentence_transformers import SentenceTransformer
  from torch_geometric.data import HeteroData, download_url, extract_zip
  from torch_geometric.transforms import RandomLinkSplit, ToUndirected
label_desc: Use image node_id 2 for calling the GenresEncoder obj's underlying member method code with example usage: obj.__call__(df) and returns: x