Hi. I am experimenting with clearml.Dataset and encountering an error.

LockException: [Errno 11] Resource temporarily unavailable

In my experiment, I make a chain of datasets where each new dataset adds new files to an existing (finalized parent) dataset.

Here is code I use to make the chain of datasets:
` from clearml import Dataset
import os
from pathlib import Path

def make_batch(i_batch, files_per_batch=10):
"""make a batch of mock data files in a folder"""
batch_path = Path(f"./batch_{i_batch}")
os.makedirs(batch_path, exist_ok=True)
for i in range(files_per_batch):
with open(batch_path / f"file_{i_batch}{i}.txt", "w") as fp:
fp.write(f"file{i_batch}_{i} contents\n")
return batch_path

def make_dataset_chain(num_datasets=3):
"""make a set of chained datasets"""
project = "testing-datasets"
parent_datasets = None
for i_batch in range(num_datasets):
batch_path = make_batch(i_batch)

    new_dataset_name = f"chained_dataset_{i_batch}"
    the_dataset = Dataset.create(
        dataset_name=new_dataset_name,
        dataset_project=project,
        parent_datasets=parent_datasets,
    )
    the_dataset.add_files(batch_path)
    the_dataset.upload()
    the_dataset.finalize()
    parent_datasets = [the_dataset.id]

make_dataset_chain() If I then try to download dataset_1 or dataset_2 : the_dataset = Dataset.get(dataset_project="testing-datasets", dataset_name="dataset_1")
ds_path = the_dataset.get_local_copy() The get_local_copy() waits 300 seconds and then throws that error LockException `

If I try to get a local copy of dataset_0 :
the_dataset = Dataset.get(dataset_project="testing-datasets", dataset_name="dataset_1") ds_path = the_dataset.get_local_copy()The dataset_0 is downloaded without issue

Attaching an image of what dataset_2 looks like in the dataset viewer for clarity.

Am I doing something wrong? Is there some other way of making new datasets by adding to older (finalized) ones?