Reputation
Badges 1
109 × Eureka!and then it works
mmm..I'm having the same issue:
in my GCP agent:
base) root@gst-cv-glema3-final-tf2-cu101:~# clearml-agent daemon --queue redness
Current configuration (clearml_agent v0.17.1, location: /root/clearml.conf):
sdk.storage.cache.default_base_dir = ~/.clearml/cache
sdk.development.default_output_uri =
if I launch the same script in GCP, (I don't run it as a clearml-agent), then everything works fine
so with these two configurations, and no output_uri in the task creation in the script:
I get model saved model in tl2 and in GCP (when run as agent):
/home/tglema/git_repo/~/clearml/
let me know if you need any help/ have issues trying to reproduce...thanks!
Did you put anything insideΒ
init.py
?
nope
I understand that it uses time in seconds when there is no report being logged..but, it has already logged three times..
yes, that works..but wasn't the issue with logging tensors?
<tf.Tensor 'Loss/RPNLoss/localization_loss:0' shape=() dtype=float32
This is what is being logged as scalar in the OD API
I'll need to see how to extract only the part that we care about
It's kind of a pain to setup Tensorflow Object Detection API
whereas this is what is being logged in your toy example: tf.Tensor(1742.0144, shape=(), dtype=float32)
I don't think so..I had a problem before 0.17.5
and is this image just a VM with a docker?
This is only with Detect API ?
I only tested it with the Detect API
clearml == 0.17.5rc5
google_cloud_storage == 1.36.1
joblib == 1.0.1
matplotlib == 3.3.4
numpy == 1.20.0
object_detection == 0.1
opencv_python_headless == 4.5.1.48
pandas == 1.2.3
scikit_learn == 0.24.1
tensorflow == 2.4.0
@ https://app.slack.com/team/U01J3C692M8 where you able to come up with a solution?
Hi AgitatedDove14 ! Were you able to reproduce this?
great, let me know if I can help you in any way. Thanks!
very possible yes..but doesn't it fallback to iteration =epoch then after?
so I have a couple of questions regarding setup.py.
If I add the requirement '.' as the last entry, does that mean that it will install my package lastly? Can I do in setup.py the modifications to the tensorflow code?I need to see how I can change the tensoflow code after it was installed and prevent other tensorflow installation to overwrite it..is it clear?