Then I tried to extract this in collab using: // mount google driveĭrive.mount('gdrive', force_remount=True) I tried to extract using cloud converter but it is paid, if your file size is bigger than 1GB I have a very big file in google drive around (6 GB) (upload file to google drive) And finally I am able to resolve this (with just one line of code). !rm /gdrive/My\ Drive/Temp/ML/Final/dataset/ import osĭrive.mount('/gdrive', force_remount = True)ĭir_path = "/gdrive/My Drive/Temp/ML/Final/dataset/"įor block in r.iter_content(chunk_size = 4096):įor member in tqdm(iterable = tar.getmembers(), total = len(tar.getmembers())): I'm using this fairly simple piece of code. Is this some kind of bug in the Google Drive's sync process that is causing this? Or am I doing something in an incorrect way? Any help or advice would be appreciated. Running a couple of lines of code reveal that only 10-12 directories have been updated correctly (out of 36) and the rest are empty. But even after waiting for quite a while (almost a day) the Google Drive is not getting updated properly. I understand that syncing the Colab's Virtual Machine memory with the Google Drive needs some time.
#COLLABORATORY GOOGLE DRIVE ARCHIVE#
After executing the code snippet attached below, I can see that the archive has been extracted correctly and I can see all the files in the Virtual Machine disk (needless to say, there are 100K+ files as expected). The Tar archive is fairly large, but from an ML dataset POV it's pretty small.
I'm trying to download and extract the Google Speech Commands Dataset using a Google Colab notebook.
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