class_docstr: Abstract class for attention modules
code: def forward(
      self,
      query,
      key,
      value,
      mask_future_timesteps=False,
      key_padding_mask=None,
      incremental_state=None,
      need_weights=True,
      static_kv=False,
  ):
      raise NotImplementedError()
  
imports: import torch
  import torch.nn.functional
  from fairseq import utils
  from fairseq.incremental_decoding_utils import with_incremental_state
  from torch import nn
label_desc: Use image node_id 2 for calling the AttentionAbstract obj's underlying member method code with example usage: obj.forward(query, key, value, mask_future_timesteps, key_padding_mask, incremental_state, need_weights, static_kv) without return types