class_docstr: An abstract class representing a Dataset.
  
  All other datasets should subclass it. All subclasses should override
  ``__len__``, that provides the size of the dataset, and ``__getitem__``,
  supporting integer indexing in range from 0 to len(self) exclusive.
class_docstr_tok: ["An","abstract","class","representing","a","Dataset",".","All","other","datasets","should","subclass","it",".","All","subclasses","should","override","``","__len__","``",",","that","provides","the","size","of","the","dataset",",","and","``","__getitem__","``",",","supporting","integer","indexing","in","range","from","0","to","len","(","self",")","exclusive","."]
code: def __len__(self):
      return (
          len(self.inputs)
          if not isinstance(self.inputs, (tuple, list))
          else len(self.inputs[0])
      )
  
file_path: pywick/pywick/datasets/BaseDataset.py
imports: import numpy
  import torch
  from torchvision import transforms
  from .data_utils import is_tuple_or_list
label_desc: Use image node_id 1 for calling the BaseDataset obj's underlying member method code with example usage: obj.__len__() and returns: unknown