| Name | absl-extra JSON |
| Version |
0.1.3
JSON |
| download |
| home_page | |
| Summary | A wrapper to run and monitor absl app. |
| upload_time | 2023-10-20 13:46:39 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | |
| keywords |
|
| VCS |
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| bugtrack_url |
|
| requirements |
No requirements were recorded.
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### 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).
- Log parsed CLI flags from `absl.flags.FLAGS` and config values from `config_file:get_config()`
- Select registered task to run based on --task= CLI argument.
Minimal example
```python
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.
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