Dainik
Dainik is a client library for NimbleBox.ai LMAO (Logging, Monitoring, Alerts and Observability) service.
Usage
from dainik import Dainik
# initialise the client object
dk = Dainik()
# initialise the run
dk.init(
"california",
config = {
"model_name": "qual",
"config": {
"batch_size": 32,
"n_steps": n_steps,
"optimizer": "adam",
}
},
)
for epoch in range(10):
log = {
"loss": 1 / epoch,
"accuracy": epoch,
}
dk.log(log, step = epoch)
# optionally log metrics directly
dk.metrics.f1_score(
x = [[1, 2, 3]],
y = [[1, 2, 1]],
step = epoch
)
# log files for tracking as well, wildcards work as well!
dk.save_files([f"./checkpoint-{epoch}/*"])
dk.end() # send signal to sleep
Dev
Due to the current structure the source code for this is only available for NimbleBox.ai engineers. This is spun out of a much larger monorepo which contains the logic for server and client together which helps us work on this faster.
Metadata
Release files for dainik 1.20
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| dainik-1.20.tar.gz | 25.2 kB | Without provenance | Details for dainik-1.20.tar.gz |
Release files / dainik-1.20.tar.gz
| Download URL | dainik-1.20.tar.gz |
|---|---|
| Size | 25.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
266f6c3dfb3d75c114d0aa7ac37a0c7f4d077c584dd5dea6fde1f421521d32cb
|
|
BLAKE2b-256 checksum How to use checksums |
da2374b0281a939d4e45ab1b973b10a839fcded47d9d703681de0db33f27436b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.12
|
Security for dainik 1.20
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