When you want to connect your parameters and other objects. Please take as look here:
https://clear.ml/docs/latest/docs/references/sdk/task#connect
You can find a usage example in
https://github.com/allegroai/clearml/blob/master/examples/reporting/hyper_parameters.py
Hi @<1806135344731525120:profile|GrumpyDog7> , it shows the reason in the log:
Python executable with version '3.9' requested by the Task, not found in path, using '/usr/bin/python3' (v3.12.3) instead
You either need a container with the relevant python version available or have it installed using the bash script section.
Makes sense?
Hi @<1576381444509405184:profile|ManiacalLizard2> , is there a specific reason you're running the agent inside a docker container instead of running the agent in docker mode which would make it spin up a container?
The AMI you used, does it have python preinstalled?
Please do 🙂
SuccessfulKoala55 , is this hack applicable for most API calls in ClearML?
ShallowGoldfish8 , I think the best would be storing them as separate datasets per day and then having a "grand" dataset that includes all days and new days are being added as you go.
What do you think?
HI SubstantialElk6 ,
If I'm not mistaken the order is as goes:output_uri
(Both code and CLI) Configurations vault default_output_uri
in clearml.conf
but you can use it with or without K8s
It means you can run your code on a different machine very very easily using ClearML 🙂
It can run dockers and it can run over K8s
clearml-agent
is for orchestration - remote execution. clearml
is the python package you need to install and add the magic lines of code:
https://github.com/allegroai/clearml
Hi @<1582179661935284224:profile|AbruptJellyfish92> , connectivity issues should not affect training and should cache everything until connection is restored and everything should be sent to the server. Did you encounter a different behavior?
Hi,
From the looks of it, it always returns a string. What is your use case for this? Do you have some conditionality on the type of variable the parameters are?
Also please note that your path is wrong
I am not very familiar with KubeFlow but as far as I know it is mainly for orchestration whereas ClearML offers a full E2E solution 🙂
run on dockers - i.e. execute your code inside of a docker image
@<1681111528419364864:profile|SmoothGoldfish52> , it will be saved to a cache folder. Take a look at what @<1576381444509405184:profile|ManiacalLizard2> wrote. I think tar files might work already. Give it a test
It depends on what you use K8s for
Just adding this here for easier readability
` ClearML results page: https:/xxxxt/projects/xxx/experimentsxxx
2022-11-21 11:02:07.590338: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2022-11-21 11:02:07.733169: I tensor...
You're gettingSyncing scheduler Failed deserializing configuration: the JSON object must be str, bytes or bytearray, not NoneType
Like before? Are all the symptoms the same as above?
Hi AbruptHedgehog21 , it looks like you need to parameters.dataset_id
on step data_creation
You must perform Task.init()
to have something reported 🙂
I think it tries to get the latest one. Are you using the agent in docker mode? you can also control this via clearml.conf
with agent.cuda_version
Hi @<1760474471606521856:profile|UptightMoth89> , I'm not sure that Task.get_task is related to the cache. Also the cache should be auto cleared by the SDK. Can you provide the full log of the experiment? What exactly are you trying to do in the code?
Hi @<1736194481398484992:profile|MoodySeaurchin62> , how are you currently reporting it? Are you reporting iterations?
BitterLeopard33 , ReassuredTiger98 , my bad. I just dug a bit in slack history, I think I got the issue mixed up with long file names 😞
Regarding http/chunking issue/solution - I can't find anything either. Maybe open a github issue / github feature request (for chunking files)
Yeah, but how are iterations marked in the script?