Experiments logging & visualization

Project manifest. Part of Catalyst Ecosystem:

• Alchemy - Experiments logging & visualization
• Catalyst - Accelerated Deep Learning Research and Development
• Reaction - Convenient Deep Learning models serving

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Installation

Common installation:

pip install -U alchemy

Previous name alchemy-catalyst

Getting started

1. Goto Alchemy and get your personal token.

2. Run following example.py:

   importrandomfromalchemyimportLogger# insert your personal token heretoken="..."project="default"forgidinrange(1):
   group=f"group_{gid}"foreidinrange(2):
   experiment=f"experiment_{eid}"logger=Logger(
   token=token,
   experiment=experiment,
   group=group,
   project=project,
   )
   formidinrange(4):
   metric=f"metric_{mid}"# let's sample some random datan=300x=random.randint(-10, 10)
   foriinrange(n):
   logger.log_scalar(metric, x)
   x+=random.randint(-1, 1)
   logger.close()

3. Now you should see your metrics on Alchemy.

Catalyst.Ecosystem

1. Goto Alchemy and get your personal token.

2. Log your Catalyst experiment with AlchemyLogger:

   fromcatalyst.dlimportSupervisedRunner, AlchemyLoggerrunner=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 tokenproject="your_project_name",
   experiment="your_experiment_name",
   group="your_experiment_group_name",
   )
   }
   )

3. Now you should see your metrics on Alchemy.

Examples

For mode detailed tutorials, please follow Catalyst examples.