class_docstr: AugmentationBase3D base class for customized augmentation implementations.
  
  Args:
      p: probability for applying an augmentation. This param controls the augmentation probabilities
        element-wise for a batch.
      p_batch: probability for applying an augmentation to a batch. This param controls the augmentation
        probabilities batch-wise.
      same_on_batch: apply the same transformation across the batch.
docstr: Check if the input tensor is formatted as expected.
docstr_tok: ["Check","if","the","input","tensor","is","formatted","as","expected","."]
code: def validate_tensor(self, input: Tensor) -> None:
      """Check if the input tensor is formatted as expected."""
      _validate_input_dtype(
          input, accepted_dtypes=[float16, float32, float64]
      )
      if len(input.shape) != 5:
          raise RuntimeError(
              f"Expect (B, C, D, H, W). Got {input.shape}."
          )
  
imports: from typing import Any, Dict, Optional
  from torch import float16, float32, float64
  import kornia
  from kornia.augmentation.base import _AugmentationBase
  from kornia.augmentation.utils import _transform_input3d, _validate_input_dtype
  from kornia.core import Tensor
  from kornia.geometry.boxes import Boxes3D
  from kornia.geometry.keypoints import Keypoints3D
label_desc: Use image node_id 1 for calling the AugmentationBase3D obj's underlying member method code with example usage: obj.validate_tensor(input) without return types