class_docstr: Protocol definition of a Dataset that has a tensors field (like
  TensorDataset).
  
  A TensorDataset can be easily converted to a :class:`IDatasetWithTargets`
  by using one of the provided tensors (usually the second, which commonly
  contains the "y" values).
class_docstr_tok: ["Protocol","definition","of","a","Dataset","that","has","a","tensors","field","(","like","TensorDataset",")",".","A","TensorDataset","can","be","easily","converted","to","a",":","class",":","`","IDatasetWithTargets","`","by","using","one","of","the","provided","tensors","(","usually","the","second",",","which","commonly","contains","the","``","y","''","values",")","."]
docstr: A sequence of PyTorch Tensors describing the contents of the Dataset.
docstr_tok: ["A","sequence","of","PyTorch","Tensors","describing","the","contents","of","the","Dataset","."]
code: def tensors(self) -> Sequence[T_co]:
      """
      A sequence of PyTorch Tensors describing the contents of the Dataset.
      """
      ...
  
imports: from typing import TypeVar, SupportsInt, Sequence
  from torch.utils.data.dataset import Dataset
  from typing_extensions import Protocol
label_desc: Use image node_id 1 for calling the ITensorDataset obj's underlying member method code with example usage: obj.tensors() without return types