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41 × Eureka!I’m going to give QEMU a try and see if it performs well enough for me
With only those docker containers running I’m having this issue. In a few hours I’m going to test on a additional machine to confirm
As I’ve used it, rsync is akin to scp, but provides more control.
There are two things I want to accomplish with this:
- I want a reliable location to store my tasks without needing to worry about running out of space.
- I want to be able to access these stored tasks in the clearml ui when they are in this storage
While rsync would let me backup the file server contents, like cp’ing them into a rclone of onedrive. I don’t think it would let me view tasks that I have put on onedrive.
For clarification, I want to store artifacts and models (maybe tasks too) like how the webui lets you specify a external storage s3 bucket when you make a folder, but with onedrive.
I.e in such a way I can still see them on the ui, but don’t necessarily have them stored on the server
If a external storage is not specified it will use internal correct?
So if I give up on having specific folder paths for each project within onedrive I could just treat it as a alternative path for internal artifact storage.
Thank you!
I wasn’t getting my hopes up on storing tasks elsewhere :)
For the models & artifacts is there a parameter to change the default directory of saving and loading to something else?
This answered my question, I ended up setting up minio running off of a external hard drive which backups to onedrive.
Though I am still having some problems getting the client to connect to minio (see recent thread)
Sorry for the delay on responding to this, I had some family craziness.
And I’m still having my other issues I mentioned. I’m just ignoring the unreachable machines for the moment.
clearml-init
ClearML SDK setup process
Please create new clearml credentials through the settings page in your clearml-server
web app (e.g. None )
Or create a free account at None
In settings page, press "Create new credentials", then press "Copy to clipboard".
Paste copied configuration here:
api {
web_server: http://:8080
api_server: http://:8008
file...
From running it with the credentials I got with the non-self-hosted clearml instance
clearml-init
ClearML SDK setup process
Please create new clearml credentials through the settings page in your clearml-server
web app (e.g. None )
Or create a free account at None
In settings page, press "Create new credentials", then press "Copy to clipboard".
Paste copied configuratio...
@<1523701070390366208:profile|CostlyOstrich36> , anything I missed?
Found the problem. Some port rules between my server and client was blocking it. Some autossh forwarding solved my problem
None of the default ports are changed and in my firewalld I have ports 8080, 8081, and 8008 open to tcp
I discovered part of the problem. I did not have boto3 installed on this conda env.
No error, just failure to upload it seems
I am able to capture clearml experiments on the clearml server running on the same machine as the minio.
I’ll put in the actual copy paste later tonight thank you for the help
Hold on should host be
` s3://ipaddr:9000?
This error is thrown by a failed .get()
function call on the StorageHandler
object I looked at the ._ _ dict _ _.keys() parameter list of the StorageHandler, and I don't see anyway to access the dictionary directly.
I placed the same key and secret in the global locations under s3{ } and this did not change anything
@<1523701205467926528:profile|AgitatedDove14>
clearml python version: 1.91
python version: 3.9.15
the server is running the docker-compose on RHEL
Minio is on the same server and the 9000 and 9001 ports are open for tcp
I changed the default address space from 172.xxx.xxx.xx for docker to another space. This is not the issue as I can replicate this issue without this modified address space.
See configuration file below, I'm running the global section test now
aws {
s3 {...
Bare with the spacing, I ocr’d this. The quotes and spacing is right