Metadata-Version: 2.1
Name: keras-toolkit
Version: 0.1.0rc3
Summary: A collection of functions to help you easily train and run Tensorflow Keras
Home-page: https://github.com/xhlulu/dl-translate
Author: Xing Han Lu
Author-email: github@xinghanlu.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: tensorflow
Provides-Extra: dev
Requires-Dist: pytest ; extra == 'dev'
Requires-Dist: black ; extra == 'dev'
Requires-Dist: jinja2 ; extra == 'dev'

# Keras Toolkit

*A collection of functions to help you easily train and run Tensorflow Keras*

## Quickstart

Install the library:

```
pip install keras-toolkit
```

You can now use it:
```python
import keras_toolkit as kt

# kt reduces the number of lines from ~100 to ~3
strategy = kt.accelerator.auto_select(verbose=True)
decoder = kt.image.build_decoder(with_labels=True, target_size=(300, 300))
dtrain = kt.image.build_dataset(paths, labels, bsize=BATCH_SIZE, decode_fn=decoder)

with strategy.scope():
    model = tf.keras.Sequential([...])
    model.compile(...)

model.fit(...)
```

### API References

Get the complete [API reference here](https://github.com/xhlulu/keras-toolkit/blob/master/docs/REFERENCES.md).


## Acknowledgement

The `auto_select_accelerator` was inspired by [Martin Gorner's Kaggle notebook](https://www.kaggle.com/mgornergoogle/getting-started-with-100-flowers-on-tpu).

