Hydra Callbacks
A collection of usefulls and simple to use callbacks for the https://hydra.cc/ configuration framework.
Installation
pip install hydra-callbacks
Development version
pip install git+https://github.com/paquiteau/hydra-callbacks
Usage
In your hydra root config file add the following, or analoguous:
hydra:
callbacks:
git_infos:
_target_: hydra_callbacks.GitInfo
clean: true
latest_run:
_target_: hydra_callbacks.LatestRunLink
resource_monitor:
_target_: hydra_callbacks.ResourceMonitor
sample_interval: 0.5
runtime_perf:
_target_: hydra_callbacks.RuntimePerformance
This will enrich your script output with:
paquiteau@laptop$ python my_app.py
[hydra] Git sha: 844b9ca1a74d8307ef5331351897cebb18f71b88, dirty: False
## All your app log and outputs ##
[hydra][INFO] - Total runtime: 0.51 seconds
[hydra][INFO] - Writing monitoring data to [...]/outputs/2023-04-06/16-02-46/resource_monitoring.csv
[hydra][INFO] - Latest run is at: [...]/outputs/latest
Detailled configuration for each callback is available in the tests/test_app/ folder.
Available Callbacks
| Name | Action |
|---|---|
| GitInfo | Check status of Repository |
| LatestRunLink | Get a link to the latest run |
| MultiRunGatherer | Gather results json file in a single table |
| RuntimePerformance | Get Execution time for each run |
| ResourceMonitor | Monitor resources of running jobs (CPU and Memory) |
And more to come !
Also Available
PerfLogger: A simple to use performance logger
from hydra_callbacks import PerfLogger
import logging
log = logging.getLogger(__name__)
def main_app(cfg):
with PerfLogger(log, "step1"):
sleep(1)
with PerfLogger(log, "step2"):
sleep(2)
PerfLogger.recap(log)
RessourceMonitorService: A simple CPU and GPU usage and memory sampler. It launches an extra process to monitor everything.
from hydra_callbacks.monitor import RessourceMonitorService
import os
monitor = RessourceMonitorService(interval=0.2, gpu_monit=True)
monitor.start()
# Launch heavy stuff
metrics = monitor.stop()
# Or use it as a context manager
with RessourceMonitorService(interval=0.2, gpu_monit=True) as monitor:
# launch heavy stuff
metrics_values = monitor.get_values()
You too, have cool Callbacks, or idea for one ?
Open a PR or an issue !
Possible Ideas
- A callback that summarize log from multiple runs
- Monitoring of GPU using nvitop
:star2: If you like this work, don't forget to star it and share it 🌟
Metadata
Release files for hydra-callbacks 0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| hydra_callbacks-0.6.1.tar.gz | 18.5 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hydra_callbacks-0.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 30.4 kB
Release files / hydra_callbacks-0.6.1.tar.gz
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