class_docstr: C++ implementation to populate the attention atoms for the blocked attention
  kernel.
docstr: Triggers compilation of the C++ implementation.
docstr_tok: ["Triggers","compilation","of","the","C++","implementation","."]
code: def __init__(self) -> None:
      """
      Triggers compilation of the C++ implementation.
      """
      inf_module = RaggedOpsBuilder().load()
      self.kernel = inf_module.build_atoms
  
file_path: deepspeed/deepspeed/inference/v2/kernels/ragged_ops/atom_builder/atom_builder.py
imports: from typing import Tuple
  import torch
  from ...None import DSKernelBase
  from deepspeed.ops.op_builder import RaggedOpsBuilder
  from ....ragged import RaggedBatchWrapper
label_desc: Use image node_id 1 to create a new AtomBuilder object from inherited base classes: DSKernelBase with example: obj = AtomBuilder()