Awesome
<div align="center">Experiments logging & visualization
</div>Project manifest. Part of Catalyst Ecosystem:
- Alchemy - Experiments logging & visualization
- Catalyst - Accelerated Deep Learning Research and Development
- Reaction - Convenient Deep Learning models serving
Installation
Common installation:
pip install -U alchemy
Previous name alchemy-catalyst
Getting started
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Goto Alchemy and get your personal token.
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Run following example.py:
import random from alchemy import Logger # insert your personal token here token = "..." project = "default" for gid in range(1): group = f"group_{gid}" for eid in range(2): experiment = f"experiment_{eid}" logger = Logger( token=token, experiment=experiment, group=group, project=project, ) for mid in range(4): metric = f"metric_{mid}" # let's sample some random data n = 300 x = random.randint(-10, 10) for i in range(n): logger.log_scalar(metric, x) x += random.randint(-1, 1) logger.close()
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Now you should see your metrics on Alchemy.
Catalyst.Ecosystem
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Goto Alchemy and get your personal token.
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Log your Catalyst experiment with AlchemyLogger:
from catalyst.dl import SupervisedRunner, AlchemyLogger runner = SupervisedRunner() runner.train( model=model, criterion=criterion, optimizer=optimizer, loaders=loaders, logdir=logdir, num_epochs=num_epochs, verbose=True, callbacks={ "logger": AlchemyLogger( token="...", # your Alchemy token project="your_project_name", experiment="your_experiment_name", group="your_experiment_group_name", ) } )
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Now you should see your metrics on Alchemy.
Examples
For mode detailed tutorials, please follow Catalyst examples.