class_docstr: Basic representation of data stored as a dense Tensor.
class_docstr_tok: ["Basic","representation","of","data","stored","as","a","dense","Tensor","."]
code: def _validate(self) -> None:
      super()._validate()
      for a, b in zip(
          reversed(self.event_shape), reversed(self.values.shape)
      ):
          if a != b:
              raise ValueError(
                  f"Shape of `values` {self.values.shape} incompatible with "
                  f"`event shape` {self.event_shape}."
              )
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from dataclasses import dataclass, fields
  from typing import Any
  from torch import device, dtype, LongTensor, Size, Tensor
label_desc: Use image node_id 6 for calling the DenseContainer obj's underlying member method code with example usage: obj._validate() without return types