A wrapper to run and monitor absl app.
Project description
ABSL-Extra
A collection of utils I commonly use for running my experiments. It will:
- Notify on execution start, finish or failed.
- By default, Notifier will just log those out to
stdout
. - I prefer receiving those in Slack, though (see example below).
- By default, Notifier will just log those out to
- Log parsed CLI flags from
absl.flags.FLAGS
and config values fromconfig_file:get_config()
- Select registered task to run based on --task= CLI argument.
Minimal example
import os
from absl import logging
import tensorflow as tf
from absl_extra import tf_utils, tasks, notifier
@tasks.register_task(
notifier=notifier.SlackNotifier(slack_token=os.environ["SLACK_BOT_TOKEN"], channel_id=os.environ["CHANNEL_ID"])
)
@tf_utils.requires_gpu
def main() -> None:
if tf_utils.supports_mixed_precision():
tf.keras.mixed_precision.set_global_policy("mixed_float16")
with tf_utils.make_gpu_strategy().scope():
logging.info("Doing some heavy lifting...")
if __name__ == "__main__":
tasks.run()
flax_utils.py
- Common utilities used for training flax models, which I got tired of copy-pasting in every project.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
absl_extra-0.1.3.tar.gz
(13.7 kB
view hashes)
Built Distribution
absl_extra-0.1.3-py3-none-any.whl
(16.5 kB
view hashes)
Close
Hashes for absl_extra-0.1.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ab974a2ba40a9a515b8f20ba14955e5bda38ee55655b23e5ad6cf2ed2a562358 |
|
MD5 | bd301903732c83afbe49d9d6a8bd3e9e |
|
BLAKE2b-256 | e613eec46f949977dcf25dcb5d67c594bf01af0d1a4881ae7f70fbff2353b43c |