Marcelle - Python Package
A python package for interacting with a Marcelle backend from python.
See: http://marcelle.dev
Status ⚠️
Marcelle is still experimental and is currently under active development. Breaking changes are expected.
Installing
pip install .Basic Usage
Keras Callback
from marcelle import MarcelleCallback
mrc_callback = KerasCallback(
backend_root="http://localhost:3030",
disk_save_formats=["h5", "tfjs"],
remote_save_format="tfjs",
model_checkpoint_freq=None,
base_log_dir="marcelle-logs",
run_params={},
)
model.fit(
# ...
callbacks = [
mrc_callback,
# other callbacks
]
)Writer (for custom training loops)
from marcelle import Writer
writer = Writer(
backend_root="http://localhost:3030",
disk_save_formats=["h5", "tfjs"],
remote_save_format="tfjs",
base_log_dir="marcelle-logs",
source="keras",
)
writer.create_run(model, params, loss.name)
writer.train_begin(epochs)
for epoch in range(epochs):
# ...
logs = {
"loss": 1.3,
"accuracy": 0.7,
"val_loss": 2.3,
"val_accuracy": 0.52,
}
assets = ["path/to/asset1.wav", "path/to/asset2.wav"]
self.writer.save_epoch(epoch, logs=logs, save_checkpoint=True, assets=assets)
writer.train_end(save_checkpoint=True)Batch upload
Useful when training was done offline or connection to server failed during the training.
from glob import glob
import os
from marcelle import MarcelleRemote, MarcelleUploader
if __name__ == "__main__":
LOG_DIR = "marcelle-logs"
uploader = MarcelleUploader(
MarcelleRemote(
backend_root="http://localhost:3030",
save_format="tfjs",
source="keras",
)
)
runs = [d for d in glob(os.path.join(LOG_DIR, "*")) if os.path.isdir(d)]
for run in runs:
uploader.upload(run)
