Intuitive library to help with training neural networks in PyTorch
ignis is a high-level library that helps you write compact but full-featured training loops with metrics, early stops,
and model checkpoints for deep learning library PyTorch.
With ignis you can solve Supervised Learning and Deep Reinforcement Learning problems.
You can extend ignis according to your own needs. You can implement custom functionalities by extending simple
abstract classes.
Deep Reinforcement Learning algorithms
- Deep Q Network (DQN)
- Deep Deterministic Policy Gradients (DDPG)
Installation
- Install PyTorch. You can find it here: PyTorch
pip install ignis
Examples
You can find examples in examples/ directory
You can also run examples: python examples/iris.py
You might want to export PYTHONPATH=/path/to/this/directory
Contribute
- Implement new functionalities
- Improve code design
- Improve comments and readme
- Tests
1 maintainer
Metadata
1 maintainer
Release files for ignis 0.0.10
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ignis-0.0.10.tar.gz | 6.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ignis-0.0.10-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.6 kB
Release files / ignis-0.0.10.tar.gz
| Download URL | ignis-0.0.10.tar.gz |
|---|---|
| Size | 6.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.33.0 CPython/3.6.8
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Release files / ignis-0.0.10-py3-none-any.whl
| Download URL | ignis-0.0.10-py3-none-any.whl |
|---|---|
| Size | 8.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.33.0 CPython/3.6.8
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