Project manifest. Part of Catalyst Ecosystem:

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

Common installation:

pip install -U alchemy

Previous name alchemy-catalyst

1. Goto Alchemy and get your personal token.

2. 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()

3. Now you should see your metrics on Alchemy.

1. Goto Alchemy and get your personal token.

2. 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",
           )
       }
   )

3. Now you should see your metrics on Alchemy.

For mode detailed tutorials, please follow Catalyst examples.