Two potential issues regarding preprocess_data.py.

[SophiaConner]

First, I would like to express my gratitude to you and your organization for the continuous and outstanding contributions to the autonomous driving community.
While replicating the results of this project, I found two minor issues with the preprocess_data.py file. I have already resolved them personally, but for the convenience of new researchers, I would like to point them out here and hope that the author will consider making the necessary modifications.
The first potential issue:
The preprocess_data.py file does not define am, causing the system to fail to recognize the variable am. It is necessary to declare am = ArgoverseMap() in the global variable section of the code, for example:

import zlib
import pickle
from argoverse.map_representation.map_api import ArgoverseMap
am= ArgoverseMap()
codeEnd

The second potential issue:
The calc_ex_list function should be placed above the create_dataset function, not inside it. Otherwise, it will cause an error (AttributeError: Can't pickle local object 'create_dataset..calc_ex_list').

def calc_ex_list(queue, queue_res, args):
res = []
while True:
file = queue.get()
if file is None:
break
if file.endswith("csv"):
with open(file, "r", encoding='utf-8') as fin:
lines = fin.readlines()[1:]
instance = argoverse_get_instance(
args, lines, file)
if instance is not None:
data_compress = zlib.compress(
pickle.dumps(instance))
res.append(data_compress)
queue_res.put(data_compress)
else:
queue_res.put(None)

def create_dataset(args):
global am
am = ArgoverseMap()
files = []
for each_dir in args.data_dir:
root, dirs, cur_files = os.walk(each_dir).next()
files.extend([os.path.join(each_dir, file) for file in cur_files if
file.endswith("csv") and not file.startswith('.')])
print(files[:5], files[-5:])

pbar = tqdm(total=len(files))
queue = multiprocessing.Queue(args.core_num)
queue_res = multiprocessing.Queue()
processes = [Process(target=calc_ex_list, args=(
    queue, queue_res, args,)) for _ in range(args.core_num)]
for each in processes:
    each.start()

for file in files:
    assert file is not None
    queue.put(file)
    pbar.update(1)

while not queue.empty():
    pass

pbar.close()
ex_list = []

pbar = tqdm(total=len(files))
for i in range(len(files)):
    t = queue_res.get()
    if t is not None:
        ex_list.append(t)
    pbar.update(1)
pbar.close()

for i in range(args.core_num):
    queue.put(None)
for each in processes:
    each.join()

if args.test:
    ex_file_name = "test.ex_list"
elif args.validation:
    ex_file_name = "eval.ex_list"
else:
    ex_file_name = "ex_list"
pickle_file = open(os.path.join(
    args.output_dir, ex_file_name), 'wb')
pickle.dump(ex_list, pickle_file)
pickle_file.close()
assert len(ex_list) > 0
print("valid data size is", len(ex_list))