Open Luismbpr opened 7 months ago
————— Python == 3.9.18 -> Seems to be working
mlflow == 2.10.2 mlserver == 1.5.0 mlserver-mlflow == 1.5.0 MarkupSafe == 2.1.5 numpy == 1.26.4 pandas == 2.2.1 scikit-learn == 1.4.1.post1 tqdm == 4.66.2 zenml == 0.55.5
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1.1) I did try to install those versions (first by bash pip install -r requirements.txt
) and did not work.
1.2) Then tried installing one by one and also could not do it. Pip installer did not let me install those versions
2) I did the zenml disconnect, zenml down, zenml up many times and never got it to work.
3) Tried creating different stacks, experiment-trackers, model-deployers and set them up to be the ones working. Tried this many times
4) Something that seemed to work but not entirely sure was using those two pieces of code on the https://stackoverflow.com/questions/52671926/rails-may-have-been-in-progress-in-another-thread-when-fork-was-called
Was appending these two lines of code on the .zshrc file
% vim ~/.zshrc
appending those two lines of code:
## for MLOPS deployment
export DISABLE_SPRING=true
export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES
% source ~/.zshrc
Then creating a new stack, experiment-tracker, model-deployer and setting them.
I am still not sure what was the piece that made it work. I have not finished the course (almost done now) but so far it seems to be working, or at least not displaying any errors.
Note: I found that stackoverflow post since the zenml logs were giving me a similar error to what one of the users from that post was having
This was a copy from that Stack Overflow post:
bjc[81924]: +[__NSPlaceholderDictionary initialize] may have been in progress in another thread when fork() was called.
objc[81924]: +[__NSPlaceholderDictionary initialize] may have been in progress in another thread when fork() was called.
Side Note:
————— Python == 3.11.8
mlflow == 2.10.2 mlserver == 1.5.0 mlserver-mlflow == 1.5.0 MarkupSafe == 2.1.5 numpy == 1.26.4 pandas == 2.2.1 scikit-learn == 1.4.1.post1 tqdm == 4.66.2 zenml == 0.55.5 ————— I have been following the code of the video lecture. The previous versions of the pipeline ran well. That was until trying to deploy the model. I have made several virtual environments and used different stacks (deleted one stack and created another one and set that up (The latest stack used was:
mlflow_customer_02
. I still cannot make the deployment work.This is the main error:
Tried to do this as well and did not work:
————— A summary of the steps retrieved to show that the pipeline works until the deployment phase:
————— Below is more stack information —————
'mlflow_stack_customer_02' stack (ACTIVE)
Stack 'mlflow_stack_customer_02' with id 'c314644e-6abc-45a8-b8fa-271fff858b6c' is owned by user default. Dashboard URL: http://127.0.0.1:8237/workspaces/default/stacks/c314644e-6abc-45a8-b8fa-271fff858b 6c/configuration
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-----ZenML Server Status----- Connected to a ZenML server: 'http://127.0.0.1:8237' The active user is: 'default' The active workspace is: 'default' (repository) The active stack is: 'mlflow_stack_customer_02' (repository) Active repository root: /Users/luis/Documents/.../venv_0754_FCC_MLOPS_MLProd_Projects_311_02 Using configuration from: '/Users/luis/Library/Application Support/zenml' Local store files are located at: '/Users/luis/Library/Application Support/zenml/local_stores' The status of the local dashboard:
| ZenML server 'local' | | | URL | http://127.0.0.1:8237 | | STATUS | ✅ | | STATUS_MESSAGE | | | CONNECTED | ✅ |
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