code: def _load_memory_mapped_array(file_name):
      # Due to a legacy problem related to memory alignment in joblib [1], the
      # data provided in the example may not be byte-aligned. This can be risky
      # when loading with mmap_mode. To fix the issue, load and re-dump the data.
      # [1] https://joblib.readthedocs.io/en/latest/developing.html#release-1-2-0
      dump(load(file_name), file_name)
      return load(file_name, mmap_mode="r")
  
file_path: dgl/examples/pytorch/eeg-gcnn/main.py
imports: import argparse
  import numpy
  import pandas
  import torch
  import torch.nn
  from dgl.dataloading import GraphDataLoader
  from EEGGraphDataset import EEGGraphDataset
  from joblib import dump, load
  from sklearn import preprocessing
  from sklearn.metrics import balanced_accuracy_score, roc_auc_score
  from sklearn.model_selection import train_test_split
  from torch.utils.data import WeightedRandomSampler
label_desc: Use image node_id 1 for calling a global function with example usage: _load_memory_mapped_array(file_name) and returns: load