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37 × Eureka!Oh my word 🙈 Yes, I just saw this just and came back to reply on here. Thank you!
Following up, I found this in the code on Github: None
A taskid
is required though - to get this id would we run the pipeline manually as it then shows up in the Web UI and then just use the id of the task that we can get from the UI by clicking on the pipeline run info?
Thanks, @<1523701070390366208:profile|CostlyOstrich36> .
If I use Task.current_task()
, I then get a task object back that looks like <clearml.task.Task object at 0x7f7723b90a00>
. How does one get the url from this?
For reference for anyone else, this is what I did:
current_task = Task.current_task()
model_run_url = Task.get_task_output_log_web_page(
task_id=current_task.id,
project_id="abc")
Thanks @<1523701070390366208:profile|CostlyOstrich36> , that does sound like an option. Can you point me to the documentation for this API call as I haven't been able to find anything?
Ok, so the image needs ssh in order to clone the repo, not just the server.
This is my dockerfile:
# Use a slim Python image as the base image
FROM python:3.9.9-slim as builder
ARG CODEARTIFACT_AUTH_TOKEN
ARG POETRY_HTTP_BASIC_ARTIFACT_USERNAME
ARG POETRY_HTTP_BASIC_ARTIFACT_PASSWORD
# Set environment variables for Poetry
ENV POETRY_HOME=/opt/poetry \
POETRY_NO_INTERACTION=1 \
POETRY_VIRTUALENVS_CREATE=false \
PATH="/opt/poetry/bin:$PATH"\
PYTHONPATH="/ml_pipeline:${...
Yes, I started the agent in docker mode with clearml-agent daemon --queue direct-relief-forecasting --docker directrelief_ml_clearml --cpu-only -d
Hi @<1523701205467926528:profile|AgitatedDove14> , thanks for your reply. We want to use the Scheduler
but to run a pipeline. Looking at this example here, it looks like it only works with tasks: None
So, in my code example above, where I have executing_pipeline
as the pipeline function created with the decorator, can this be scheduled to run with the TaskScheduler
, ie. used as the function...
I think I found it: None
Will this work for pipelines too, which are also Tasks, right?
I've tried changing the clearml.conf
file to specify the python_binary
with:
python_binary: "usr/bin/python3"
But, still getting the same error.