code: def load_1d_1ch_conv_model():
      """Load a pre-trained 1d-convolutional classification model (architecture at quantus/helpers/models)."""
      model = ConvNet1D(n_channels=1, n_classes=10)
      model.eval()
      # TODO: add trained model weights
      # model.load_state_dict(
      #    torch.load("tests/assets/mnist", map_location="cpu", pickle_module=pickle)
      # )
      return model
  
imports: import pytest
  import pickle
  import torch
  import numpy
  from keras.datasets import cifar10
  import pandas
  from sklearn.model_selection import train_test_split
  import os
  from quantus.helpers.model.models import LeNet, LeNetTF, CifarCNNModel, ConvNet1D, ConvNet1DTF, TitanicSimpleTFModel, TitanicSimpleTorchModel
label_desc: Use image node_id 4 for calling a global function with example usage: load_1d_1ch_conv_model() and returns: model