class_docstr: `ConcatedEncodedDs` abstracts over multiple encoded datasources (`EncodedDs`) as if they were a single entity.
class_docstr_tok: ["`","ConcatedEncodedDs","`","abstracts","over","multiple","encoded","datasources","(","`","EncodedDs","`",")","as","if","they","were","a","single","entity","."]
docstr: See `lightwood.data.encoded_ds.EncodedDs.__len__()`.
docstr_tok: ["See","`","lightwood.data.encoded_ds.EncodedDs.__len__","(",")","`","."]
code: def __len__(self):
      """
      See `lightwood.data.encoded_ds.EncodedDs.__len__()`.
      """
      # @TODO: behavior here is not intuitive
      return max(0, np.sum(self.encoded_ds_lengths) - 2)
  
imports: import inspect
  from typing import List, Tuple, Dict
  import torch
  import numpy
  import pandas
  from torch.utils.data import Dataset
  from lightwood.encoder.base import BaseEncoder
label_desc: Use image node_id 2 for calling the ConcatedEncodedDs obj's underlying member method code with example usage: obj.__len__() and returns: max