Metadata-Version: 2.4
Name: axiomos
Version: 0.1.9
Summary: A lightweight AXIR playground to run numerical kernels across CPU and OpenCL
Author: Axiomos
License: MIT
Project-URL: Homepage, https://github.com/Aidenkuro10/axiomos-vitrine
Project-URL: Documentation, https://github.com/Aidenkuro10/axiomos-vitrine#readme
Project-URL: Repository, https://github.com/Aidenkuro10/axiomos-vitrine
Keywords: opencl,kernels,gemm,axir,numpy,runtime,AI
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.23
Requires-Dist: jsonschema>=4.21
Requires-Dist: tqdm>=4.0
Provides-Extra: opencl
Requires-Dist: pyopencl>=2022.3; extra == "opencl"
Dynamic: license-file

[![PyPI version](https://img.shields.io/pypi/v/axiomos.svg?logo=pypi)](https://pypi.org/project/axiomos/)

# AXIOMOS – Minimal Public Showcase

This repository is a **public showcase** proving that **AXIR** – the universal AI runtime IR – works **without exposing any proprietary core code**.  
It relies on the public PyPI package **`axiomos`** (CPU + OpenCL), already published.

> ✨ Goal: let anyone (YC, investors, reviewers) **test in 2 minutes** that the IR executes correctly and results are verifiable across backends.

---

## ⚡️ Quickstart

### 1) Environment setup
```bash
python -m venv .venv
# Windows
.\.venv\Scripts\activate
# macOS/Linux
# source .venv/bin/activate

2) Install the public runtime

CPU only:

python -m pip install axiomos

With OpenCL (if GPU/drivers are available):

python -m pip install "axiomos[opencl]"

3) Generate two example fixtures
python make_fixtures.py


This creates:

examples/
 ├─ vector_add_small.axir.json
 └─ softmax2d_small.axir.json

✅ Demo 1 — Environment check
axiomos-doctor


If OpenCL is not available, you can still use --backend-a cpu --backend-b cpu.

✅ Demo 2 — “Hello AXIR” (vector add)

Compare CPU vs CPU on a simple vector:

axiomos-verify examples/vector_add_small.axir.json --buffer hC --backend-a cpu --backend-b cpu


Expected output: RESULT: PASS.

✅ Demo 3 — Softmax2D (8×8)

Without GPU (CPU vs CPU):

axiomos-verify examples/softmax2d_small.axir.json --buffer hY --backend-a cpu --backend-b cpu


With GPU (CPU vs OpenCL):

# Windows PowerShell
$env:AXIOMOS_OCL_REAL="1"
# macOS/Linux
# export AXIOMOS_OCL_REAL=1

axiomos-verify examples/softmax2d_small.axir.json --buffer hY --backend-a cpu --backend-b opencl


Expected output:

SHAPES     : CPU(8, 8) vs OPENCL(8, 8)
max_abs_err: 0.0
ALLCLOSE   : True (atol=1e-06, rtol=1e-05)
[SMOKE] RESULT: PASS

🔥 Demo 4 — Small benchmark (optional)
axiomos-smoke --axir examples/softmax2d_small.axir.json --buffer hY --backend-a opencl --backend-b cpu --inproc --time --warmup 3 --repeat 10


Produces an OpenCL vs CPU latency comparison.
If no GPU is present, use --backend-a cpu --backend-b cpu.

🧩 What this showcase proves

Portability – the same .axir.json runs on both CPU and OpenCL.

Verifiability – axiomos-verify checks numerical equality with strict tolerance (allclose).

Simplicity – 2 fixtures, 3 commands, no access to proprietary code needed.

The full runtime (optimizations, advanced kernels, Ed25519 signature, etc.) remains private.
This showcase demonstrates only the critical path: IR → execution → verification.

🪪 License

MIT (for this public showcase only). The full runtime remains proprietary.
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