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5.1.0

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agi-transformer

AGi Transformer v5.1 Advanced — FP4-E2M1, Parallel Blocks, Mamba, Double Buffering

Published17 May 2026

Direct dependencies9

Transitive dependenciesNot calculated

README

Version 5.1.0 documentation

AGi Transformer v5.1 — Advanced Core

High-performance transformer library with FP4-E2M1 quantization, Parallel Blocks, Mamba layers, and Triton double-buffering kernels.

Features

FP4-E2M1 Format: 1 sign + 2 exponent + 1 mantissa (superior to NF4 for Gaussian weights)
Parallel Block Architecture: PaLM-style simultaneous Attention + FFN (15% speedup)
Mamba/TTT Hybrid: Replace middle attention with O(L) linear recurrent layers
Double Buffering: Triton kernel preloads Block K+1 while computing Block K
Matrix Swizzling: XOR-based shared memory indexing eliminates bank conflicts
Dynamic Scaled Clamping: Per-row adaptive bounds based on block maxima
Vector SmoothAlpha: Per-channel 4096-parameter scaling (not scalar)
AdaRound + KLD: Learnable rounding with distribution-preserving loss

Quick Start

pip install -e .
python scripts/train.py --steps 5000 --d-model 512 --n-layers 8

Project Structure

src/agi_core/
├── kernels/      # Triton AOT kernels (FP4, Double Buffer, Swizzle)
├── layers/       # Quantized Linear, Mamba, Parallel Block
├── model/        # AGiParallelTransformer
├── ops/csrc/     # C++/CUDA extensions (optional AOT)
└── utils/        # Quantization helpers, logging

License

MIT

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Declared dependencies 9

Native requirements

9 direct targetsNot calculated transitive count

Package / target	Requirement	Relationship
torch Environment { "extras": "", "marker": null, "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`torch>=2.1.0`	runtime
triton Environment { "extras": "", "marker": null, "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`triton>=3.0.0`	runtime
numpy Environment { "extras": "", "marker": null, "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`numpy>=1.24.0`	runtime
matplotlib Environment { "extras": "", "marker": null, "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`matplotlib>=3.7.0`	runtime
tqdm Environment { "extras": "", "marker": null, "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`tqdm>=4.65.0`	runtime
pytest Environment { "extras": "", "marker": "extra == \"dev\"", "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`pytest>=7.0; extra == "dev"`	runtime
black Environment { "extras": "", "marker": "extra == \"dev\"", "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`black; extra == "dev"`	runtime
ruff Environment { "extras": "", "marker": "extra == \"dev\"", "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`ruff; extra == "dev"`	runtime
mypy Environment { "extras": "", "marker": "extra == \"dev\"", "requires_python": ">=3.9", "evaluation": "NOT_EVALUATED" }	`mypy; extra == "dev"`	runtime