Method to specify save location of a dataset

[StefanBloemheuvel]

Hello TSL team,

Is it possible to add the functionality of specifying the save directory of a dataset?
Such as:

dataset = MetrLA('current_path or folder')

because I am trying to run TSL on an external GPU cluster where I do not have root access/all permissions. Therefore, I think I am getting the following error when trying to run the MetrLA() command:

import tsl
import torch
import numpy as np
np.set_printoptions(suppress=True)
print(f"tsl version  : {tsl.__version__}")
print(f"torch version: {torch.__version__}")
from tsl.datasets import MetrLA
dataset = MetrLA(root='data')

gives the error:

tsl version  : 0.9.0
torch version: 1.10.1+cu111
Segmentation fault (core dumped)

which seems to be: "Segmentation fault" means that you tried to access memory that you do not have access to".

Thanks in advance!

[marshka]

Hi, the command

dataset = MetrLA(root='data')

is the right one to specify the correct data path and works for me. Are you sure that your error raises from that instruction?