Demetric
Dead simple standard for metric logging
Logging
import demetric as dm
metrics = dm.Metrics.new('metrics/gpt2-3')
metrics.log('loss', value=loss, step=step)
metrics.log('accuracy', value=acc, step=step)
# ...
Creates:
runs/
gpt2-3/
loss.csv
accuracy.csv
Reading
# single metrics
metrics = dm.Metrics('metrics/run1.0')
metrics.read('loss') # pd.DataFrame
# all metrics
metrics.read() # pd.DataFrame with a column per metric
# comparing runs
runs = { run: dm.Metrics(run) for run in ['metrics/version1', 'metrics/version2'] }
df = dm.compare(runs, 'loss') # pd.DataFrame with columns ("loss_run1.0", "loss_run1.1", ...)
# concatenating runs (i.e. they're the same experiment but trained by steps or something)
runs = [dm.Metrics(run) for run in ['metrics/part1', 'metrics/part2']]
df = dm.concat(runs, 'loss') # pd.DataFrame with cumulative step indices
1 maintainer
Metadata
1 maintainer
Release files for demetric 0.1.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| demetric-0.1.13.tar.gz | 3.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| demetric-0.1.13-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.1 kB
Release files / demetric-0.1.13.tar.gz
| Download URL | demetric-0.1.13.tar.gz |
|---|---|
| Size | 3.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/5.1.0 CPython/3.11.6
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Release files / demetric-0.1.13-py3-none-any.whl
| Download URL | demetric-0.1.13-py3-none-any.whl |
|---|---|
| Size | 3.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.0 CPython/3.11.6
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