SteadyFox10 AgitatedDove14 Thanks, I really did change the name.

AgitatedDove14 Yes.

SteadyFox10 ModelCheckpoint is not for pytorch I think, couldn't find anything like it.

AgitatedDove14 Thanks Martin, I know that. I just say it's a bug.

TimelyPenguin76 I see it in the web-app under the model.

AgitatedDove14 You were right. I can get them as system tags.
I've wrote a class that wraps an training session and interaction with trains as upon loading/saving the experiment I need more than just the 'model.bin'
So I use these tags to match a specific aux files that were saved with their model.

TimelyPenguin76 the tags names are 'Epoch 1', 'Step 5705'
the return value of the InputModel(<Put a string copy from the UI with the tag id>).tags is an empty array.

I've solved the first part by importing trains after parsing the arguments. Still not sure about the second part of my question.

AgitatedDove14 yes, exactly.

AgitatedDove14
I think exclusion of arguments from the arg praser is a good idea.
Regarding the other parameters such as the working directory and script path. I just want to automate it as when running the script from my local machine for the "template" of the experiment it gets values that won't work when running in the worker. I just thought it can be automated from the code.

AgitatedDove14 I can't try the new agent at the moment, the OS is Ubuntu 18.04 more specifically: amazon/Deep Learning Base AMI (Ubuntu 18.04) Version 22.0 and no docker. Running on the machine.

AgitatedDove14 I'm using that code in the meanwhile
` ### This script checks the number of GPUs, create a list like 0,1,2...

Then adds '--gpus' before that list of GPUs

NUM_GPUS=nvidia-smi -L | wc -l
NUM_GPUS=$(($NUM_GPUS-1))
OUT=()
if [ $NUM_GPUS -ge 0 ]
then
for i in $(seq 0 $NUM_GPUS); do OUT+=( "$i" ); done
echo ${OUT[*]// /|} | tr ' ' ',' | awk '{print "--gpus "$1}'
else
echo ""
fi `

AgitatedDove14 yes, you're right. it was 10.2 or 10.1 if I recall.

SuccessfulKoala55 No, that's not what I mean.
Take a look at the process in the machine:
/home/ubuntu/.trains/venvs-builds/3.6/bin/python -u path/to/script/my_script.py
That's how the process starts. Therefore, when I try to get sys.argv all I get is path/to/script/my_script.py .
I'm talking about allowing to have arguments that are not being injected to the argparse. So it will look like:
` /home/ubuntu/.trains/venvs-builds/3.6/bin/python -u path/to/script/my_script.py --...

AgitatedDove14 thanks, I'll check it out.

I created a wrapper to work like executing python -m torch.distributed.launch --nproc_per_node 2 ./my_script.py but from my script. I do call trains.init in the subprocesses, I the actually difference between the subproceses supposed to be, in terms or arguments, local_rank that's all.It may be possible and that I'm not distributing the model between the GPUs in an optimal way or at least in a way that matches your framework.
If you have an example it would be great.

AgitatedDove14 Hi, So I solve that by passing to the created processes the arguments injected into the argprase as part of the commandline. The examples helped.

AgitatedDove14 It will take me probably a few days but I'll let you know.

AgitatedDove14 Well, after starting a new project it works. I guess it's a bug.

AgitatedDove14 yes, it's the same.

AgitatedDove14 Yes, I can. I didn't delete the previous project yet.

AgitatedDove14 My solution actually works better when I want to copy the model + aux to a different s3 folder for deployment as the aux is very light and I can copy the model without downloading it. But thanks for the suggestion.

Yeah, I thought to use artifact, wondered if I can avoid using it or on the other hand, use only it just to define the "the model" as a folder.
Thanks.

I actually tried to print the logging.getLogger("trains.frameworks").level and it was ERROR as expected. Therefore I'm not quite sure that's the problem... next I thought to patch your functions.

the solution that worked: [logging.getLogger(name).setLevel(logging.ERROR) for name in logging.root.manager.loggerDict if "trains" in name]

AgitatedDove14 It didn't help 😕

AgitatedDove14 thanks, I'll try

AgitatedDove14
These were the loggers names I can see locally running the code, it might differ running remotely.
['trains.utilities.pyhocon.config_parser', 'trains.utilities.pyhocon', 'trains.utilities', 'trains', 'trains.config', 'trains.storage', 'trains.metrics', 'trains.Repository Detection']
regarding repreduce it, have a long data processing after initializing the task and before setting the input model/output model.

AgitatedDove14 I've tried the drastic measure suggested above as I had a log file of 1gb filled with the trains.frameworks - WARNING - Could not retrieve model location, skipping auto model logging
It didn't work :S

AgitatedDove14 Drastic indeed, I belive I will lose all the trains logs that way. In that case I prefer to keep the redundant logs.
If you'll find a more specific solution I'll love to know what it is 🙂