Reputation
Badges 1
27 × Eureka!Am I missing anything? because I can clearly see the usage of --config-file using clearml-agent --help
Thanks a lot @<1523701435869433856:profile|SmugDolphin23>
will go through this one.
your quick reply really means a lot. Thanks again!!
clearml-data create --storage "
" --project dummyproject --name testingds1
clearml-data - Dataset Management & Versioning CLI
Creating a new dataset:
Error: Insufficient permissions (write failed) for ostore.xyz.tech
it is picking http, it should https?
Thanks a lot @<1523701070390366208:profile|CostlyOstrich36> 🙏
Everytime I start training; first download dataset using minio client and then do further operations.
Can we integrate minio easily with clearML?
Also tried changing files_server in config but didn’t work
Hi @<1523701435869433856:profile|SmugDolphin23>
This is follow up question from my side.
Is it efficient to use clearML data for hundred of thousands of image dataset. I’ve a concern about performance.
So basically I’m training a transformers classifier. which need at least 300-400K images.
And just FYI: one dataset size can beyond 80GB.
Hi @<1523701070390366208:profile|CostlyOstrich36>
FYI: I’m not using docker agent.
I set the env vars as you mentioned above in config. And I can see the those while starting agent using command: clearml-agent daemon --queue default
While running below code locally eg: python test.py
I’m loading the env vars that is working fine.
But my question is when we clone the same task from clearml UI and send it to default queue; So can below piece of code can use those envs?
I tried sendi...
Yes, this is what I’m doing currently. But strugginling to manage the versions and all.
Yes, I tried with default port of minio (9000). didn’t work either.
@<1590514584836378624:profile|AmiableSeaturtle81>
Yes, I can also feel that slowness.
But what about if we have millions of pdfs and we need to generate a image dataset along with their bounding boxes. We cannot generate it on the fly while training the model as it will very very very slow.
So I’m doing all preprocessing the upload preprocessed data back to storage.
And while training again pulling preprocessed dataset from storage. 😄
Well I can understand well your problem. @<1590514584836378624:profile|AmiableSeaturtle81>
Please let me know if you have answers for my problem. 😄
And what I feel; pulling data by using some client eg: minio-client for minio is faster than clearml
For below config and command it worked
command: clearml-data create --storage "
None " --project dummyproject --name testingds2
raise ValueError(“Insufficient permissions (delete failed) for {}“.format(base_url))
ValueError: Insufficient permissions (delete failed) for None
Though I’m able to connect using minio client with the same creds without any issues.
Removed port and set secure as true.
Am I missing anything in config?
Again throwing Insufficient permissions.
Hi @<1523701070390366208:profile|CostlyOstrich36>
After removing the port number from command given by you.
Re: your message
with the combination of None :port/bucket
for --storage
?
botocore.exceptions.EndpointConnectionError: Could not connect to the endpoint URL: “ None ”