code: def __init__(
      self,
      embed_dim: int,
      num_heads: int,
      scaling: float = 0.125,
      dropout: float = 0.1,
      compress_layer=None,
      bias: bool = True,
  ):
      super().__init__(
          embed_dim=embed_dim,
          num_heads=num_heads,
          scaling=scaling,
          dropout=dropout,
          compress_layer=compress_layer,
          bias=bias,
      )
      log_class_usage(__class__)
  
file_path: pytext/pytext/models/representations/transformer/multihead_linear_attention.py
imports: from typing import List, Tuple
  import numpy
  import torch
  from pytext.utils.usage import log_class_usage
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 1 to create a new QuantizedMultiheadLinearAttention object from inherited base classes: MultiheadLinearAttention with example: obj = QuantizedMultiheadLinearAttention(embed_dim, num_heads, scaling, dropout, compress_layer, bias)