code: def __init__(
      self,
      d_feat=6,
      hidden_size=64,
      num_layers=2,
      dropout=0.0,
      rnn_type="GRU",
  ):
      super().__init__()
      self.hid_size = hidden_size
      self.input_size = d_feat
      self.dropout = dropout
      self.rnn_type = rnn_type
      self.rnn_layer = num_layers
      self._build_model()
  
imports: from __future__ import division
  from __future__ import print_function
  import numpy
  import pandas
  from typing import Text, Union
  import copy
  from ...utils import get_or_create_path
  from ...log import get_module_logger
  import torch
  import torch.nn
  import torch.optim
  from torch.utils.data import DataLoader
  from .pytorch_utils import count_parameters
  from ...model.base import Model
  from ...data.dataset import DatasetH
  from ...data.dataset.handler import DataHandlerLP
  from ...model.utils import ConcatDataset
  from ...data.dataset.weight import Reweighter
label_desc: Use image node_id 1 to create a new ALSTMModel object from inherited base classes: nn with example: obj = ALSTMModel(d_feat, hidden_size, num_layers, dropout, rnn_type)