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')
Hello TSL team,
Is it possible to add the functionality of specifying the save directory of a dataset? Such as:
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:
gives the error:
which seems to be: "Segmentation fault" means that you tried to access memory that you do not have access to".
Thanks in advance!