| Name | pynajax JSON |
| Version |
0.2.0
JSON |
| download |
| home_page | None |
| Summary | A JAX backend for pynapple. |
| upload_time | 2024-09-16 19:31:31 |
| maintainer | None |
| docs_url | None |
| author | pynajax authors |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2024 pynapple-org Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
neuroscience
jax-backend
pynapple
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# pynajax
[](https://github.com/pynapple-org/pynajax/blob/main/LICENSE)
[](https://www.repostatus.org/#active)
[](https://github.com/pynapple-org/pynajax/actions/workflows/ci.yml)
[](https://coveralls.io/github/pynapple-org/pynajax)
Welcome to `pynajax`, a GPU accelerated backend for [pynapple](https://github.com/pynapple-org/pynapple) built on top on [jax](https://github.com/google/jax). It offers a fast acceleration for the core pynapple functions using GPU.
> **Warning**
> ⚠️ This package is not meant to be used on its own. It should only be used through the pynapple API.
## Installation
Run the following `pip` command in your virtual environment.
**For macOS/Linux users:**
```bash
pip install pynajax
```
**For Windows users:**
```
python -m pip install pynajax
```
Alternatively, you can install pynapple and pynajax together.
```bash
pip install pynapple[jax]
```
## Basic usage
To use pynajax, you need to change the pynapple backend using `nap.nap_config.set_backend`. See the example below :
```python
import pynapple as nap
import numpy as np
nap.nap_config.set_backend("jax")
tsd = nap.Tsd(t=np.arange(100), d=np.random.randn(100))
# This will run on GPU or CPU depending on the jax installation
tsd.convolve(np.ones(11))
```
## Benchmark
This benchmark for the `convolve` function was run on a GPU.
See the documentation for others benchmarks.
Raw data
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