code: def _initialize_triton_ops(self):
      block_size = self.__values.shape[-1]
      self.__sparse_dot_sdd = blocksparse_matmul(
          self.__layout,
          block_size,
          "sdd",
          trans_a=False,
          trans_b=True,
          device=self.__layout.device,
      )
      self.__sparse_dot_dsd = blocksparse_matmul(
          self.__layout,
          block_size,
          "dsd",
          trans_a=False,
          trans_b=False,
          device=self.__layout.device,
      )
      self.__sparse_softmax = blocksparse_softmax(
          self.__layout, block_size, device=self.__layout.device
      )
  
imports: import logging
  import torch
  from xformers import _is_triton_available
  from xformers.ops import masked_matmul
label_desc: Use image node_id 3 for calling the BlockSparseTensor obj's underlying member method code with example usage: obj._initialize_triton_ops() without return types