just reran and got the same results with the flag for force_analyze_entire_repo set to false 😞 still has the following import error:
ImportError: cannot import name 'bigquery' from 'google.cloud' (unknown location)

AgitatedDove14 Thanks- just got the pipeline to run 🙂 Just one final question- on the documentation, it says not to queue any training/inference tasks into the services queue, so should I be creating a different queue for training tasks or is using the default queue okay?

AgitatedDove14 thanks, I'm new to Allegro here so just trying to figure everything out. When you say trains agent, are you referring to the trains agent command(so in this case , would it be trains-agent execute ?). Is it sufficient to queue the experiments(using execute_remotely ) or do I need to clone them as well?

task = Task.init(...) if task.running_locally(): # wait for the repo detection and requirements update task._wait_for_repo_detection() # reset requirements task._update_requirements(None)Regarding this, does this work if the task is not running locally and is being executed by the trains agent?

AgitatedDove14 I tried your code snippet, something like this:
task = Task.init(...) if task.running_locally(): # wait for the repo detection and requirements update task._wait_for_repo_detection() # reset requirements task._update_requirements(None) task.execute_remotely(queue="default") ... rest of task here ...It’s able to create a draft successfully with no items in the installed packages section, but it only installed Cython and began the execution immediately....

The default GKE OS is container optimized os so some directories(i.e. opt) are read only. I solved the problem by mounting it in var/libs. In the future, is allegro considering including deployment of trains-server on GKE?

SuccessfulKoala55 Getting an error with mounting on a read-only file system(Error response from daemon: error while creating mount source path '/opt/trains/logs': mkdir /opt/trains: read-only file system: RunContainerError), is there any workaround for this?

This line: “if task.running_locally():” makes sure that when the code is executed by the agent it will not reset it’s own requirements (the agent updates the requirements/installed_packages after it installs them from the requiremenst.txt, so that later you know exactly which packages/versions were used)

got it! Thanks for explaining

SuccessfulKoala55 I looked back into my configuration settings for the VM(I already created a VM instance from the custom image yesterday) and thats where I got my external IP from. I checked "Allow HTTP access" but it's giving me a gateway timeout error now and telling me that the server at the IP is unreachable at the moment.

SuccessfulKoala55 At the time, yes it was v0.15.1. How do I actually launch trains server from the custom image? Do I use the external IP associated with the VM or are there any other steps I have to take?

The path for setting up trains-server on GCP is deploying the server, and then configuring the trains server, from my understanding. I'm unable to run trains-init to setup, as it tells me the command isn't found.

Regarding the trains server SDK, the end of the documentation for GCP says 'Next step, configuring trains for trains server' where the first step is running trains-init setup wizard

AgitatedDove14 Yes, I understand that, but as I mentioned earlier, I don't want to have to edit installed_packages manually, as others will also be running the same scripts from their own local development machines. This is why I was inquiring about the requirements.txt file, so that this manual editing would not have to be done by each person running the same scripts.

Additionally, since I'm running a pipeline, would I have to execute each task in the pipeline locally(but still...

AgitatedDove14 Thanks! That resolved a lot of my questions.

Which would mean 

trains

` will update the installed packages, no?

Can you explain what is meant by this?
I think what you're trying to say is that in the UI the installed packages will be determined through the code via the imports as usual and the users will have to manually clear the installed packages so that the requirements.txt is used instead.

Since I'm running a pipeline, does this mean I have to execute each task of the pipeline individually and manually? Then uncomment task.execute_remotely() from each task and then run via trains-agent ?

If there a way to do this without manually editing installed packages? I'm trying to create a setup in which others can utilize the same repo and have their venvs be built similarly without having to do much work on their end (i.e. editing the installed packages). As for why it's failing to detect, I'm not sure.
from google.cloud import bigquery ImportError: cannot import name 'bigquery' from 'google.cloud' (unknown location)That's the error I get after the task makes use of the function ...

Since the package requirements vary from task to task, setting it up in trains.conf might be a little tedious to go back and change. Most of the time, the package analysis has worked very well, but in this particular use case it failed to detect. I think task.init flag would be great!

I was thinking more along the lines of a draft task that has yet to be enqueued(so it can still be edited). The installed packages grabs most packages except for a few, which is why I am resorting to clearing the packages so that requirements.txt is used. I’ve been using the UI so far to do it, but would like to move the process to a script

If you have a few lines for resetting, I would love to have that as an option as well!

SuccessfulKoala55 Actually- just resolved this. I had to allow access from all ports(not secure but will fix that asap) but everything seems to be running now, thanks for the help!

TimelyPenguin76 thanks! Do you know when the next version will be released?

I didn't execute the code manually, I executed it from trains-agent to begin with. So to conclude: it has to be executed manually first, then with trains agent?

i ran ping <IP HERE>:8008 , it returns
ping: <ip-here>:8008: Name or service not known

Yeah, I’m trying to connect to my own server, and I installed trains-agent on a vm. How could I diagnose the issue?

The VM ip is 153.73.X.Y and the trains-server IP is 34.74.X.Y

Yeah, the command is executed and nothing is returned.

Yes, I did both

I also tried detection with pip freeze and that didn’t work

No response is returned

Let me experiment with force_analyze_entire_repo and I’ll get back to you! It was missing google-cloud-bigquery , an import from a separate file in the repository. Hopefully that should resolve the problem. A flag would be really cool, just in case if theres any problem with the package analysis.