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533 × Eureka!cool, didn't know about the PAT
So regarding 1, I'm not really sure what is the difference
When running in docker mode what is different the the regular mode? No where in the instructions is nvidia docker a prerequisite, so how exacly will tasks on GPU get executed?
I feel I don't underatand enough of the mechanism to (1) understand the difference between docker mode and not and (2) what is the use casr for each
a machine that had previous installation, but I deleted the /opt/trains
directory beforehand
I followed the upgrading still nothing
I manually deleted the allegroai/trains:latest
image, that didn't help either
sudo curl
https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose.yml -o /opt/trains/docker-compose.yml
but shouldn't the :lastest
make it redownload the right image?
Why would I have 0.15.1 if I followed the instructions of the docs?
but I can't seem to run docker-compose down
Config == conf_obj
no?
inference table is a pandas dataframe
Well done to you!
looks like it did pull the right image
but the task pending says its in the queue
it's double weird, because also a task that the pipeline says is "in progress" is actually completed
Okay so at the first part of the code, we define some kind of callback that we add to our steps, so later we can collect them and attach the results to the pipeline task. It looks something like this
` class MedianPredictionCollector:
_tasks_to_collect = list()
@classmethod
def collect_description_tables(cls, pipeline: clearml.PipelineController, node: clearml.PipelineController.Node):
# Collect tasks
cls._tasks_to_collect.append(node.executed)
@classmethod...
can't remember, I just restarted everything so I don't have this info now
you can use pgrep -af "trains-agent"
AgitatedDove14 worked like a charm, thanks a lot!
Cool - what kind of objects are returned by .artifacts.
getitem
? I want to check their docs