Metadata-Version: 2.1
Name: gradsflow
Version: 0.0.1a0
Summary: Democratising AI
Home-page: https://docs.gradsflow.com
Author: Aniket Maurya
Author-email: hello@gradsflow.com
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Information Technology
Classifier: Operating System :: OS Independent
Classifier: Typing :: Typed
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Dist: optuna == 2.9.1
Requires-Dist: smart_open == 5.1.0
Requires-Dist: lightning-flash[image] == 0.4.0
Requires-Dist: loguru
Requires-Dist: pytest ; extra == "test"
Requires-Dist: coverage ; extra == "test"
Provides-Extra: test

# Gradsflow

An AutoML Library made with Optuna and PyTorch Lightning

[![CodeFactor](https://www.codefactor.io/repository/github/gradsflow/gradsflow/badge)](https://www.codefactor.io/repository/github/gradsflow/gradsflow)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/gradsflow/gradsflow/main.svg)](https://results.pre-commit.ci/latest/github/gradsflow/gradsflow/main)
[![Documentation Status](https://readthedocs.org/projects/gradsflow/badge/?version=latest)](https://gradsflow.readthedocs.io/en/latest/?badge=latest)


## Image Classification

```python
from flash.core.data.utils import download_data
from flash.image import ImageClassificationData

from gradsflow.autoclassifier import AutoImageClassifier

# 1. Create the DataModule
download_data("https://pl-flash-data.s3.amazonaws.com/hymenoptera_data.zip", "./data")

datamodule = ImageClassificationData.from_folders(
    train_folder="data/hymenoptera_data/train/",
    val_folder="data/hymenoptera_data/val/",
)

model = AutoImageClassifier(
    datamodule, max_epochs=2, optimization_metric="val_accuracy"
)
print("AutoImageClassifier initialised!")

model.fit()
```

