A simple tool for opendilab.
Project description
DI-toolkit
A simple toolkit package for opendilab, including the following utilities:
ditk.logging
, a easy-to-use logger systemditk.annonated
, an annotated documentation generation scriptditk.tensorboard
, a utility for extract data from tensorboard log fileditk.tensorboard.plot
, plot utilities for plotting data extracted from tensorboard log file
Installation
You can simply install it with pip
command line from the official PyPI site.
pip install DI-toolkit
Or installing from the latest source code as follows:
git clone https://github.com/opendilab/DI-toolkit.git
cd di-toolkit
pip install . --user
Quick Start
Example of ditk.logging
Here is an example of logging.
from ditk import logging
if __name__ == '__main__':
logging.try_init_root(logging.INFO)
logging.info('This is info')
logging.warning('This is warning with integer 233')
logging.error('This is a error with string \'233\'.')
try:
_ = 1 / 0
except ZeroDivisionError as err:
logging.exception(err)
ditk.logging
has almost the same interface as native logging
module. You can directly replace import logging
in the
code with from ditk import logging
.
ditk.annonated
Python annotated documentation generation script like the following
Usage
python -m ditk.doc.annotated create -i ditk/doc/annotated/ppo.py -o my_doc/index.html -L zh
You will get
my_doc
├── assets
│ ├── pylit.css
│ └── solarized.css
└── index.html
Help Information
python -m ditk.doc.annotated --help
Usage: python -m ditk.doc.annotated [OPTIONS] COMMAND [ARGS]...
Utils for creating annotation documentation.
Options:
-v, --version Show version information.
-h, --help Show this message and exit.
Commands:
create Utils for creating annotation documentation from local code.
python -m ditk.doc.annotated create --help
Usage: python -m ditk.doc.annotated create [OPTIONS]
Utils for creating annotation documentation from local code.
Options:
-i, --input_file FILE Input source code. [required]
-o, --output_file FILE Output annotated documentation code. [required]
-A, --assets_dir DIRECTORY Directory for assets file of this documentation.
-L, --language [zh|en] Language for documentation. [default: en]
-T, --title TEXT Title of the documentation. [default: <Untitled
Documentation>]
-h, --help Show this message and exit.
Related Library
Create Multi-Seed Multi-Algorithm Benchmark Plots
import matplotlib.pyplot as plt
import seaborn as sns
from ditk.tensorboard.plots import tb_create_range_plots
sns.set()
tb_create_range_plots(
'test/testfile/pong_tb', # directory of tensorboard log
xname='step',
yname='evaluator_step/reward_mean',
)
plt.show()
Contributing
We appreciate all contributions to improve DI-toolkit
, both logic and system designs. Please refer to CONTRIBUTING.md
for more guides.
License
DI-toolkit
released under the Apache 2.0 license.
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