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.FLAGSand 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.
1 maintainer
Release files for absl-extra 0.1.3
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Source distribution (sdist)
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| absl_extra-0.1.3.tar.gz | 13.7 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| absl_extra-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 30.2 kB
Release files / absl_extra-0.1.3.tar.gz
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| Size | 13.7 kB |
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