class_docstr: Abstract class of monotonic attentions
class_docstr_tok: ["Abstract","class","of","monotonic","attentions"]
code: def _set_monotonic_buffer(
      self,
      incremental_state: Optional[
          Dict[str, Dict[str, Optional[Tensor]]]
      ],
      buffer: Dict[str, Optional[Tensor]],
  ):
      self.set_incremental_state(
          incremental_state,
          "monotonic",
          buffer,
      )
  
imports: import math
  import torch
  from torch import Tensor
  import torch.nn
  from examples.simultaneous_translation.utils.p_choose_strategy import learnable_p_choose, waitk_p_choose
  from examples.simultaneous_translation.utils.monotonic_attention import expected_alignment_from_p_choose, expected_soft_attention, mass_preservation
  from fairseq.modules import MultiheadAttention
  from .None import register_monotonic_attention
  from typing import Dict, Optional
label_desc: Use image node_id 10 for calling the MonotonicAttention obj's underlying member method code with example usage: obj._set_monotonic_buffer(incremental_state, buffer) without return types