class_docstr: Applies a multi-layer long short-term memory (LSTM) RNN to an input
  sequence.
code: def __init__(self, *args, **kwargs):
      super(QuantLSTM, self).__init__("LSTM", *args, **kwargs)
  
imports: import math
  import torch
  import warnings
  import itertools
  import numbers
  from torch import nn
  from torch.nn import Parameter
  from torch.nn.utils.rnn import PackedSequence
  from csrc.pytorch.pytorch_quantization import tensor_quant
  from csrc.pytorch.pytorch_quantization.nn._functions import quant_rnn
  from .None import _utils
label_desc: Use image node_id 1 to create a new QuantLSTM object from inherited base classes: QuantRNNBase with example: obj = QuantLSTM()