Gated State Quantization (GSQ)
Gated State Quantization (GSQ) -> Success (score=6.58). Promote this line toward an invention brief.
ID: gated-state-quantization-gsq
Folder: inventions/gated-state-quantization-gsq
Created: 2026-03-09 06:35:38
Updated: 2026-03-10 06:26:36
Files: 9
Source: student_autonomy
README.md
ARES's plain-English description of what this invention does and how to run it.
# Gated State Quantization (GSQ)
A reference implementation of the Gated State Quantization (GSQ) technique for optimizing State Space Models (SSMs).
## Concept
Standard SSMs maintain a continuous latent state. GSQ optimizes memory bandwidth and VRAM usage by dynamically adjusting the precision of this latent state based on the 'gate' value:
- **Gate Closed (Static)**: The state is not changing significantly. We can aggressively quantize the state tensor to **INT8** without losing information, saving VRAM.
- **Gate Open (Dynamic)**: New information is being injected into the state. We temporarily switch to **FLOAT16** (or FP32) to maintain training stability and avoid accumulation errors.
## Project Structure
- `gated_state_quantization_gsq/`: Core library.
- `run_demo.py`: Standalone demonstration script.
## Usage
Run the local demonstration:
```bash
python run_demo.py
```
This will simulate a sequence of inputs, track the gate status, dynamically quantize the hidden state, and report the theoretical memory savings.
| Path | Bytes |
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| DESIGN_BRIEF.md |
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| gated_state_quantization_gsq/__init__.py |
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| gated_state_quantization_gsq/__pycache__/__init__.cpython-311.pyc |
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| gated_state_quantization_gsq/__pycache__/gsq_core.cpython-311.pyc |
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| gated_state_quantization_gsq/gsq_core.py |
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| invention.json |
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| pyproject.toml |
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| README.md |
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| run_demo.py |
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Manifest
Structured metadata ARES recorded when it created this project.
{
"id": "gated-state-quantization-gsq",
"title": "Gated State Quantization (GSQ)",
"summary": "Gated State Quantization (GSQ) -> Success (score=6.58). Promote this line toward an invention brief.",
"source": "student_autonomy",
"kind": "invention",
"path": "inventions/gated-state-quantization-gsq",
"created_at": "2026-03-09 06:35:38",
"updated_at": "2026-03-10 06:26:36",
"project_status": "built",
"project_entrypoint": "run_demo.py",
"smoke_test_status": "passed",
"smoke_test_output": "--- Initializing Gated State Quantization (GSQ) Demo --- Sequence Length: 50 State Dimension: 16 Gate Closed Threshold: 0.3 -------------------------------------------------- Step | Gate Mag | Mode | State Sum -------------------------------------------------- 0 | 0.50 | FLOAT16 | 0.2373 5 | 0.99 | FLOAT16 | 6.3277 10 | 0.99 | FLOAT16 | 14.4722 15 | 0.67 | FLOAT16 | 15.0424 17 | 0.22 | INT8 | 15.3701 20 | 0.02 | INT8 | 15.3701 25 | 0.01 | INT8 | 15.3701 30 | 0.20 | INT8 | 11.5906 31 | 0.40 | FLO",
"generated_files": 5,
"project_generated_at": "2026-03-09 06:54:39",
"source_exp_path": "experiments\\exp_self.20260309024727.107_20260309_024843"
}