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

Yes.

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.

Sorry for the delay on responding to this, I had some family craziness.

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?

I’m going to give QEMU a try and see if it performs well enough for me

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.

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.

Bare with the spacing, I ocr’d this. The quotes and spacing is right

I placed the same key and secret in the global locations under s3{ } and this did not change anything

This is post script completion on the client end

Hold on should host be
` s3://ipaddr:9000?

credentials: [

specifies key/secret credentials to use when handli$

{
＃

This will apply to all buckets in this host ($

host: "...:9000”
key: "*********"
secret: "******************"
multipart: false
secure: false
}
]
}
boto3 {
pool_connections: 512
max_ multipart_concurrency: 16

Nevermind, 😆 as you thought, seems I was just needing a few more f5s on my dashboard. Thank you very much for this

I upgraded to 1.9.3 and that didn’t change my error.

I created a new bucket with the name testbucket which didn’t change anything (I only updated this name in the output_uri parameter)

I tried curl on the minio:9000 which returns some html with AccessDenied as content

I tried curl on minio:9001 which returns the minio console html

Is that being used as a dictionary key?

I discovered part of the problem. I did not have boto3 installed on this conda env.

No error, just failure to upload it seems

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

>>> print(json.dumps(config_obj.get("sdk"), indent=2))
{
  "storage": {
    "cache": {
      "default_base_dir": "~/.clearml/cache"
    },
    "direct_access": [
      {
        "url": "file://*"
      }
    ]
  },
  "metrics": {
    "file_history_size": 100,
    "matplotlib_untitled_history_size": 100,
    "images": {
      "format": "JPEG",
      "quality": 87,
      "subsampling": 0
    },
    "tensorboard_single_series_per_graph": false
  },
  "network": {
    "file_upload_retries":...

It gave no import error, and I'm still having problems. I returned to my original script and it shows some file transfer print statements, but I don't see the files appearing in minio

Thank you

Yes I will give it a try and get back to you.

I am able to capture clearml experiments on the clearml server running on the same machine as the minio.

And I’m still having my other issues I mentioned. I’m just ignoring the unreachable machines for the moment.

@<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 {...

The exact error I am getting is:

 line 1095, in output_uri
    raise ValueError("Could not get access credentials for '{}' "

I’ll put in the actual copy paste later tonight thank you for the help

with the filepath leading to /clearml/task.py

And again thank you for the help with this.