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Description:

alchemy 20.5

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

Installation
Common installation:
pip install -U alchemy

Previous name alchemy-catalyst
Getting started

Goto Alchemy and get your personal token.

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()

Now you should see your metrics on Alchemy.

Catalyst.Ecosystem

Goto Alchemy and get your personal token.

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",
)
}
)

Now you should see your metrics on Alchemy.

Examples
For mode detailed tutorials, please follow Catalyst examples.