class_docstr: BiLSTM with same hidden units as input dim.
      
class_docstr_tok: ["BiLSTM","with","same","hidden","units","as","input","dim","."]
code: def __init__(self, dim, layers=2):
      super().__init__()
      self.lstm = nn.LSTM(
          bidirectional=True,
          num_layers=layers,
          hidden_size=dim,
          input_size=dim,
      )
      self.linear = nn.Linear(2 * dim, dim)
  
imports: from dataclasses import dataclass
  import typing
  import torch
  from torch import nn
  from torch.nn import functional
  from audiocraft.modules.transformer import StreamingTransformer, create_sin_embedding
label_desc: Use image node_id 1 to create a new BLSTM object from inherited base classes: nn with example: obj = BLSTM(dim, layers)