code: def forward(self, x):
      x = x.reshape(x.shape[0], self.num_input, -1)
      output = self.tcn(x)
      output = self.linear(output[:, :, -1])
      return output.squeeze()
  
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 .pytorch_utils import count_parameters
  from ...model.base import Model
  from ...data.dataset import DatasetH
  from ...data.dataset.handler import DataHandlerLP
  from .tcn import TemporalConvNet
label_desc: Use image node_id 2 for calling the TCNModel obj's underlying member method code with example usage: obj.forward(x) and returns: output