class_docstr: Basic class representing data in Compressed Sparse Column (CSC) format.
  
  Examples
  --------
  >>> indptr = torch.tensor([0, 1, 3])
  >>> indices = torch.tensor([1, 4, 2])
  >>> csc_foramt_base = CSCFormatBase(indptr=indptr, indices=indices)
  >>> print(csc_format_base.indptr)
  ... torch.tensor([0, 1, 3])
  >>> print(csc_foramt_base)
  ... torch.tensor([1, 4, 2])
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code: def __init__(self, indptr: torch.Tensor, indices: torch.Tensor):
      self.indptr = indptr
      self.indices = indices
      if not indptr.is_cuda:
          assert self.indptr[-1] == len(
              self.indices
          ), "The last element of indptr should be the same as the length of indices."
  
file_path: dgl/python/dgl/graphbolt/base.py
imports: from dataclasses import dataclass
  import torch
  from torch.utils.data import functional_datapipe
  from torchdata.datapipes.iter import IterDataPipe
  from ..utils import recursive_apply
label_desc: Use image node_id 1 to create a new CSCFormatBase object  with example: obj = CSCFormatBase(indptr, indices)