` [package_manager.force_repo_requirements_txt=true] Skipping requirements, using repository "requirements.txt"
Using base prefix '/opt/conda'
New python executable in /home/ramon/.clearml/venvs-builds/3.7/bin/python3.7
Also creating executable in /home/ramon/.clearml/venvs-builds/3.7/bin/python
Installing setuptools, pip, wheel...
2021-06-10 09:57:56
done.
Collecting pip<20.2
Using cached pip-20.1.1-py2.py3-none-any.whl (1.5 MB)
Installing collected packages: pip
Attempting uninstall: p...

Yes! How can I help? AgitatedDove14

` File "/home/ramon/.trains/venvs-builds/3.7/lib/python3.7/site-packages/trains/backend_api/session/token_manager.py", line 72, in _get_token_exp
return jwt.decode(token, verify=False).get('exp', sys.maxsize)
File "/home/ramon/.trains/venvs-builds/3.7/lib/python3.7/site-packages/jwt/api_jwt.py", line 113, in decode
decoded = self.decode_complete(jwt, key, algorithms, options, **kwargs)
File "/home/ramon/.trains/venvs-builds/3.7/lib/python3.7/site-packages/jwt/api_jwt.py", line 80, in decode_c...

Not yet AgitatedDove14 , does the agent use by default the python version the command is run with? I installed conda and tried using package_manager.type=conda but then get an error:
clearml_agent: ERROR: 'NoneType' object has no attribute 'lower'

With pip I get the first error I showed, I tried conda and it starts running but at some point crashes with:
clearml_agent: ERROR: 'NoneType' object has no attribute 'lower'

My bad :man-facepalming: It was just specifying weights_path=dirpath since the first argument is weights_filename

Managed to get:

clearml_agent: ERROR: Command '['/home/ramon/.clearml/venvs-builds/3.9/bin/python', '-m', 'pip', '--disable-pip-version-check', 'install', '-r', '/var/tmp/requirements_tb0x2i3j.txt', '--extra-index-url', '

 died with <Signals.SIGKILL: 9>.

while building the task with the id on the agent

Yes AgitatedDove14 , I am not sure what they use by default. Here is a simple working example:
` from typing import Optional

import torch
from clearml import Task
from pytorch_lightning import LightningDataModule, LightningModule
from pytorch_lightning.utilities.cli import LightningCLI
from torch.utils.data import DataLoader, Dataset, Subset

class RandomDataset(Dataset):
def init(self, size, length):
self.len = length
self.data = torch.randn(length, size)

def ...

There are also ways to override the parameters as stated https://pytorch-lightning.readthedocs.io/en/latest/common/lightning_cli.html#use-of-command-line-arguments .

Works like a charm 👌 thanks!

Thats really cool! But I would still prefer avoid using pip_freeze, is there a way?

I configured a firewall rule that opened the ports for the instance (not 100% sure if this is the right way) using network tags. Yes, the whole screen is black and no trains logo show up: Safari can’t open the page because the server where this page is located isn’t responding.

I enabled both https and http

Also, should I allow 8080 , 8008 , and 8081 on ingress and egress on GCP or is only egress enough?

Sure! I enqueue the experiment from my local machine:
python -m src.train model=my_model loss=my_loss dataset=my_dataset

Then I go to the server and run the experiment and create a copy to run with a new model. On the copy, I go to the script path and modify it to be:
-m src.train model=my_other_model loss=my_loss dataset=my_dataset

The new experiment, even though the script path has my_new_model default, starts training using my_model .

I can also see ...

Thanks TimelyPenguin76 , the example works fine! I’ll debug further on my side!

I’ll open the PR!

Thanks AgitatedDove14 !

AgitatedDove14 its on the checkpoint

Thanks Martin! I’ll keep checking 👌

AgitatedDove14 Thanks! Im trying to figure out how to create a minimum working example! I am also working with Hydra so that may be a thing. The extension is whats causing it to fail (haven’t figured out why).

The plot is generated and added to tensorboard but seems clearml is not catching it.

Thanks SuccessfulKoala55 !

Let me work on it 👌

Sure! For torch I have:

torch==2.0.1
    # via
    #   monai
    #   pytorch-lightning
    #   torchio
    #   torchmetrics

AgitatedDove14 from this thread I understand hydra is not supported and therefore overriding the parameters from the UI wont work, but is there still a way to track and add the parameters to the experiment? Will task.connect_configuration work with the yaml files?

AgitatedDove14 Well I have a loss function which is something like:
class MyLoss(...): def forward(...): weights = self.compute_weights(...) return (weights * (target-preds)).mean()There seems to be a problem on certain batch when computing the weights. What would be the best way to log the batch that causes the problem, along with the weights being computed.

@<1523701070390366208:profile|CostlyOstrich36> Thanks for the help! It ended being a mistake on my side. Misconfigured the VM's memory and it had only 3.75 G. Failed when installing torch.

Hey AgitatedDove14 does this work for you?
` from argparse import ArgumentParser
from tensorflow.keras import utils as np_utils
from tensorflow.keras.datasets import mnist
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.callbacks import ModelCheckpoint

import tensorflow as tf
from clearml import Task

class Linear(tf.keras.Model):
def init(self, in_shape=(784,), num_classes=10):
super().init()
self.l...

It is the latest RC, I get the following:
` Executing Conda: /opt/conda/bin/conda install -p /home/ramon/.clearml/venvs-builds/3.8 -c pytorch -c conda-forge -c defaults 'pip<20.2' --quiet --json
Pass
Trying pip install: /home/ramon/.clearml/venvs-builds/3.8/task_repository/my-rep.git/requirements.txt
Executing Conda: /opt/conda/bin/conda install -p /home/ramon/.clearml/venvs-builds/3.8 -c pytorch -c conda-forge -c defaults numpy==1.20.3 --quiet --json
Pass
Warning, could not locate PyTorch to...