Metadata-Version: 2.1
Name: neuraltrain
Version: 0.0.1
Summary: A lightweight deep learning library for learning on M/EEG and other neuroimaging modalities.
Author: FAIR, AI at Meta
Project-URL: Source, https://github.com/fairinternal/brainai
Project-URL: Tracker, https://github.com/fairinternal/brainai/issues
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: pandas>=2.0.1
Requires-Dist: numpy>=1.24.3
Requires-Dist: scikit-learn>=0.21.2
Requires-Dist: torch>=2.0.1
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Requires-Dist: pydantic>=2.5.0
Requires-Dist: torchmetrics>=1.1.2
Requires-Dist: braindecode@ git+https://github.com/braindecode/braindecode@master
Provides-Extra: lightning
Requires-Dist: lightning>=2.0.8; extra == "lightning"
Requires-Dist: wandb>=0.15.11; extra == "lightning"
Provides-Extra: dev
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# neuraltrain

`neuraltrain` is a lightweight library of useful classes and functions for training deep learning models with neuralset.

## Install

If you have already installed `neuralset` following its installation instructions, you can just do:

```
conda activate <your_neuralset_env>
pip install --config-settings editable_mode=strict -e .
```
*Note*: `editable_mode=strict` is required for `mypy` to pick up `neuralset` typing from within `neuraltrain` when installed as editable (`-e`).

If starting from scratch:

```
conda create -n neuraltrain python=3.10 ipython -y
conda activate neuraltrain
pip install -e .
```

To install additional `dev` or `lightning` dependencies, you can instead run: 
```
pip install -e .'[dev,lightning]'
```

## Project example

See [`project_example`](project_example/README.md) for an example project built with `neuraltrain` and `pytorch-lightning`.
