Downloads · 30 days
0
BDA-Botanical-Dormancy
ay933/BDA-Botanical-Dormancy
BDA-Botanical-Dormancy is a machine learning model from ay933. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as mit.
BDA is a novel neural network architecture where each neuron independently learns when to enter a "dormant" state, inspired by selective plant cell dormancy during winter. This per-neuron adaptive sparsity mechanism a…
Access
Public
Updated Mar 12, 2026
Repo size
488 KB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pdf488 KB · 97%
At a glance
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Mar 12, 2026
- Updated
- Mar 12, 2026
- SHA
- eee18168
Model card
From the Hugging Face model README
🌿 BDA - Botanical Dormancy Architecture
Model Description
BDA is a novel neural network architecture where each neuron independently learns when to enter a "dormant" state, inspired by selective plant cell dormancy during winter. This per-neuron adaptive sparsity mechanism achieves 55-84% neuron dormancy with minimal inference overhead (2.5-8%).
Key Features
- 🧠 Per-neuron learnable thresholds
- ⚡ Minimal overhead (2.5-8%)
- 💾 96% cache hit rate
- 🔧 Hardware agnostic (P100, T4, A100)
Performance Results
A100 GPU (FP16)
| Batch Size | Standard (ms) | BDA (ms) | Overhead | Dormancy |
|---|---|---|---|---|
| 1 | 0.594 | 0.701 | +18.0% | 55% |
| 8 | 0.847 | 0.917 | +8.3% | 55% |
| 32 | 2.906 | 3.252 | +11.9% | 55% |
Other GPUs (Batch=8)
| GPU | Standard (ms) | BDA (ms) | Overhead | Dormancy |
|---|---|---|---|---|
| T4 | 7.23 | 7.89 | +9.1% | 82% |
| P100 | 9.43 | 9.67 | +2.5% | 84% |
How It Works
Each BDA layer has a learnable threshold θ = sigmoid(φ) × 0.5. During inference:
- Neuron enters dormant state when activation < threshold
- Dormant neurons output zero, reducing computation
- Cache mechanism reuses previous decisions (96% hit rate)
Installation
pip install torch torchvision numpy
- Library
- pytorch
- License
- mit
- Languages
- en
- Created
- Mar 12, 2026
- Updated
- Mar 12, 2026