class_docstr: Should the kernel be computed in chunks with checkpointing or not? (Default, no)
  
  If `split_size = 0`:
      The kernel is computed explicitly. During training, the kernel matrix is
      kept in memory for the backward pass. This is the fastest option but the
      most memory intensive.
  If `split_size > 0`:
      The kernel is never fully computed or stored. Instead, the kernel is only
      accessed through matrix multiplication. The matrix multiplication is
      computed in `segments` chunks. This is slower, but requires significantly less memory.
  
  Default: 0
class_docstr_tok: ["Should","the","kernel","be","computed","in","chunks","with","checkpointing","or","not","?","(","Default",",","no",")","If","`","split_size","=","0","`",":","The","kernel","is","computed","explicitly",".","During","training",",","the","kernel","matrix","is","kept","in","memory","for","the","backward","pass",".","This","is","the","fastest","option","but","the","most","memory","intensive",".","If","`","split_size",">","0","`",":","The","kernel","is","never","fully","computed","or","stored",".","Instead",",","the","kernel","is","only","accessed","through","matrix","multiplication",".","The","matrix","multiplication","is","computed","in","`","segments","`","chunks",".","This","is","slower",",","but","requires","significantly","less","memory",".","Default",":","0"]
code: def __enter__(self, *args, **kwargs):
      warnings.warn(
          "The checkpointing feature is deprecated and will be removed in the next version. "
          "If your data cannot fit on a single GPU, we recommend using the GPyTorch KeOps integration. "
          "(The KeOps integration accomplishes the same thing that our checkpointing feature did, but better!) "
          "See the KeOps example in the GPyTorch documentation at docs.gpytorch.ai",
          DeprecationWarning,
      )
      return super().__enter__(*args, **kwargs)
  
file_path: gpytorch/gpytorch/beta_features.py
imports: import warnings
  from .settings import _feature_flag, _value_context
label_desc: Use image node_id 1 for calling the checkpoint_kernel obj's underlying member method code with example usage: obj.__enter__() and returns: super