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
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