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41 × Eureka!The exact error I am getting is:
line 1095, in output_uri
raise ValueError("Could not get access credentials for '{}' "
Is that being used as a dictionary key?
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?
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
No error, just failure to upload it seems
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
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
I’ll put in the actual copy paste later tonight thank you for the help
Hold on should host be
` s3://ipaddr:9000?
I am able to capture clearml experiments on the clearml server running on the same machine as the minio.
I discovered part of the problem. I did not have boto3 installed on this conda env.
Found the problem. Some port rules between my server and client was blocking it. Some autossh forwarding solved my problem
This is post script completion on the client end
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
Bare with the spacing, I ocr’d this. The quotes and spacing is right
>>> 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":...
I’m going to give QEMU a try and see if it performs well enough for me
Yes I will give it a try and get back to you.
And again thank you for the help with this.
with the filepath leading to /clearml/task.py
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.
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...