how you solved it?? i am getting this error till now and don’t really know how to solve it
can you provide me with any code or something…bcoz i am still getting this error.
np.random.seed(2)
pat = r’/([^/]+)_\d+.jpg$’
ds_tfms=get_transforms()
data = ImageDataBunch.from_name_re(path_img, fnames, pat, size=224, bs=bs).normalize(imagenet_stats)
data.show_batch(rows=3, figsize=(7,6))
it is working fine for from_name_re but the problem is with from_folder.
This is the command I use to install Pytorch, all I did was add the version number to the command.
conda config --set ssl_verify no && conda install -y -c pytorch pytorch=1.4.0 torchvision cuda92
torch version 1.4.0 requires torchvision version 0.5.0
Therefore, if you install using pip, the command should be:
pip install "torch==1.4" "torchvision==0.5.0"
Thank you so much @mattbriancon. I was stuck with this issue for a day or two and finally focused and found your advice. It worked out great.
I use Google Colab and have the same error. Adding this in the begining fix the problem for me, thank you.
Best Reply, thank you
i am using kaggle kernel. what can i do in kaggle or in colab?
FWIW, your code only “fixes” it because you’ve stopped passing the transforms to ImageDataBunch.from_name_re
. I suspect that if you start passing it again, you’ll still get the error.
data = ImageDataBunch.from_name_re(
path_img,
fnames,
pat,
size=224,
bs=bs,
ds_tfms=ds_tfms, # <------
).normalize(imagenet_stats)
Admittedly, I have no idea what transforms are returned from get_transforms()
or what they do but I’m guessing they’re important enough that you don’t want to leave them out.
You Sir, are a star!! Thank you.
My Colab training now uses image augmentation - yaaaaay!
Thank you very much.
Is this because there is a change in fastai repo?
https://anaconda.org/pytorch/pytorch had a new release on 2020-04-22 that was impacting me because I was just taking the latest version.
I am sure once the new version of fastai is out the requirement of using PyTorch 1.4.0 will be no longer needed.
there are no torch==1.4 version
no torch==1.4
You may need to add the ‘0’ at the end.
For example:
pip install torch==1.0.0 torchvision==0.2.1
I have never used the Kaggle or Colab systems.
I use g4n.xlarge instances from AWS on spot pricing for $0.1588 an hour and only run them for when I’m working on the model.
All other time I spend on my localhost with writing code and collecting datasets.
how much it cost you(average) for a month?
I’m spending about USD $10 or so a month.
I spend about 5 hours each time I spin an instance and do this 2-3 times a week.
So about 15 hours a week, and than data transfer and what not, gets me to about that USD $10.
I also use S3 for backups of my computers so there’s a bunch of that in there as well.
Looking up my current bill for May 2020 here are my details:
g4dn.xlarge Linux/UNIX Spot Instance-hour in US East (N. Virginia) in VPC Zone #7 - 33.591 Hrs - $5.30
There is also some EBS but it’s less than a dollar.