class_docstr: A subclass of ``BoxMode``.
  
  Also represented as "xxyy" or "xxyyzz", with format of
  [xmin, xmax, ymin, ymax] or [xmin, xmax, ymin, ymax, zmin, zmax].
  
  Example:
      .. code-block:: python
  
          CornerCornerModeTypeB.get_name(spatial_dims=2) # will return "xxyy"
          CornerCornerModeTypeB.get_name(spatial_dims=3) # will return "xxyyzz"
class_docstr_tok: ["A","subclass","of","``","BoxMode","``",".","Also","represented","as","``","xxyy","''","or","``","xxyyzz","''",",","with","format","of","[","xmin",",","xmax",",","ymin",",","ymax","]","or","[","xmin",",","xmax",",","ymin",",","ymax",",","zmin",",","zmax","]",".","Example",":","..","code-block",":",":","python","CornerCornerModeTypeB.get_name","(","spatial_dims=2",")","#","will","return","``","xxyy","''","CornerCornerModeTypeB.get_name","(","spatial_dims=3",")","#","will","return","``","xxyyzz","''"]
code: def boxes_to_corners(self, boxes: torch.Tensor) -> tuple:
      corners: tuple
      spatial_dims = get_spatial_dims(boxes=boxes)
      if spatial_dims == 3:
          xmin, xmax, ymin, ymax, zmin, zmax = boxes.split(1, dim=-1)
          corners = xmin, ymin, zmin, xmax, ymax, zmax
      elif spatial_dims == 2:
          xmin, xmax, ymin, ymax = boxes.split(1, dim=-1)
          corners = xmin, ymin, xmax, ymax
      return corners
  
imports: from __future__ import annotations
  import inspect
  import warnings
  from abc import ABC, abstractmethod
  from collections.abc import Callable, Sequence
  from copy import deepcopy
  import numpy
  import torch
  from monai.config.type_definitions import NdarrayOrTensor, NdarrayTensor
  from monai.utils import look_up_option
  from monai.utils.enums import BoxModeName
  from monai.utils.type_conversion import convert_data_type, convert_to_dst_type
label_desc: Use image node_id 1 for calling the CornerCornerModeTypeB obj's underlying member method code with example usage: obj.boxes_to_corners(boxes) and returns: corners