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533 × Eureka!As a part of a repo
I just tried setting the conf in the section Martin said, it works perfectly
The scenario I'm going for is never to run on the dev machine, so all I'll need to do once the server + agents are up is to add task.execute_remotely... after the Task.init line and after the execution of the script is called on the dev machine, it won't actually run but rather enqueue itself for the agent to run it?
I want to get the instances of the tasks executed by this controller task
SuccessfulKoala55 , I get a list of 1 value. This value is a dictionary which has the keys type header and cells . cells is a dictionary in itself which has the keys height values align line font
I mean if I continue and build on the example in the docs, what will happen if the training task is completed, and then I get it and log to it? Will it be defined as running again?
DangerousDragonfly8 but would this work if they are not concurrent but sequential?
Anyway I checked the base task, and this is what it has in installed packages (seems like it doesn't list all the real packages in the environment)
actually i was thinking about model that werent trained uaing clearml, like pretrained models etc
` name: XXXXXXXXXX
on:
workflow_dispatch
jobs:
test-monthly-predictions:
runs-on: self-hosted
env:
DATA_DIR: ${{ secrets.RUNNER_DATA_DIR }}
GOOGLE_APPLICATION_CREDENTIALS: ${{ secrets.RUNNER_CREDS }}
steps:
# Checkout
- name: Check out repository code
uses: actions/checkout@v2
# Setup python environment
- name: Setup up python environment using Poetry
run: |
/home/elior/.poetry/bin/poetry env use python3.9
...
SuccessfulKoala55 here it is
To be clearer - how to I refrain from using the built in file-server altogether - and use MINIO for any storage need?
So once I enqueue it is up? Docs says I can configure the queues that the auto scaler listens to in order to spin up instances, inside the auto scale task - I wanted to make sure that this config has nothing to do to where the auto scale task was enqueued to
