Upload folder using huggingface_hub

README.md

@@ -0,0 +1,121 @@
+---
+license: mit
+tags:
+- pytorch
+- safetensors
+- threshold-logic
+- neuromorphic
+---
+
+# threshold-exactly1outof8
+
+Exactly-1-out-of-8 detector. Fires when exactly one input is active.
+
+## Circuit
+
+```
+  x₀ x₁ x₂ x₃ x₄ x₅ x₆ x₇
+   │  │  │  │  │  │  │  │
+   └──┴──┴──┴──┼──┴──┴──┴──┘
+               │
+       ┌───────┴───────┐
+       ▼               ▼
+  ┌─────────┐     ┌─────────┐
+  │ AtLeast1│     │ AtMost1 │
+  │ w: +1×8 │     │ w: -1×8 │
+  │ b:  -1  │     │ b:  +1  │
+  └─────────┘     └─────────┘
+       │               │
+       └───────┬───────┘
+               ▼
+          ┌─────────┐
+          │   AND   │
+          │ w: 1, 1 │
+          │ b:  -2  │
+          └─────────┘
+               │
+               ▼
+          (HW = 1?)
+```
+
+## Mechanism
+
+The circuit uses two threshold neurons in parallel:
+
+1. **AtLeast1**: Fires when HW ≥ 1 (at least one input active)
+   - Weights: all +1
+   - Bias: -1
+
+2. **AtMost1**: Fires when HW ≤ 1 (at most one input active)
+   - Weights: all -1
+   - Bias: +1
+   - Logic: fires when -HW + 1 ≥ 0, i.e., HW ≤ 1
+
+3. **AND**: Combines the two conditions
+   - Exactly1 = AtLeast1 AND AtMost1
+
+## Truth Table
+
+| HW | AtLeast1 | AtMost1 | Exactly1 |
+|----|----------|---------|----------|
+| 0 | 0 | 1 | 0 |
+| 1 | 1 | 1 | **1** |
+| 2 | 1 | 0 | 0 |
+| 3 | 1 | 0 | 0 |
+| ... | 1 | 0 | 0 |
+| 8 | 1 | 0 | 0 |
+
+## Exactly-k Family
+
+| Circuit | AtLeast bias | AtMost bias |
+|---------|--------------|-------------|
+| **Exactly1** | -1 | +1 |
+| Exactly2 | -2 | +2 |
+| Exactly3 | -3 | +3 |
+| ... | -k | +k |
+| Exactly7 | -7 | +7 |
+
+All use the same structure: two threshold detectors + AND.
+
+## Architecture
+
+| Component | Neurons | Parameters |
+|-----------|---------|------------|
+| AtLeast1 | 1 | 9 |
+| AtMost1 | 1 | 9 |
+| AND | 1 | 3 |
+| **Total** | **3** | **21** |
+
+**Layers: 2**
+
+## Usage
+
+```python
+from safetensors.torch import load_file
+import torch
+
+w = load_file('model.safetensors')
+
+def exactly1(bits):
+    inp = torch.tensor([float(b) for b in bits])
+    atleast = int((inp * w['atleast.weight']).sum() + w['atleast.bias'] >= 0)
+    atmost = int((inp * w['atmost.weight']).sum() + w['atmost.bias'] >= 0)
+    return int((torch.tensor([float(atleast), float(atmost)]) * w['and.weight']).sum() + w['and.bias'] >= 0)
+
+bits = [0, 0, 0, 1, 0, 0, 0, 0]  # HW=1
+print(exactly1(bits))  # 1
+```
+
+## Files
+
+```
+threshold-exactly1outof8/
+├── model.safetensors
+├── model.py
+├── config.json
+└── README.md
+```
+
+## License
+
+MIT

config.json

@@ -0,0 +1,9 @@
+{
+  "name": "threshold-exactly1outof8",
+  "description": "Exactly-1-out-of-8 detector as threshold circuit",
+  "inputs": 8,
+  "outputs": 1,
+  "neurons": 3,
+  "layers": 2,
+  "parameters": 20
+}

model.py

@@ -0,0 +1,23 @@
+import torch
+from safetensors.torch import load_file
+
+def load_model(path='model.safetensors'):
+    return load_file(path)
+
+def exactly1(bits, weights):
+    """Exactly-1-out-of-8 detector.
+    bits: list of 8 binary values
+    Returns: 1 if exactly one bit is set, 0 otherwise
+    """
+    inp = torch.tensor([float(b) for b in bits])
+    atleast = int((inp * weights['atleast.weight']).sum() + weights['atleast.bias'] >= 0)
+    atmost = int((inp * weights['atmost.weight']).sum() + weights['atmost.bias'] >= 0)
+    return int((torch.tensor([float(atleast), float(atmost)]) * weights['and.weight']).sum() + weights['and.bias'] >= 0)
+
+if __name__ == '__main__':
+    w = load_model()
+    print('Exactly1OutOf8 Detector')
+    for hw in range(9):
+        bits = [1] * hw + [0] * (8 - hw)
+        result = exactly1(bits, w)
+        print(f'HW={hw}: {result}')

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3de11d8b2cd4d44e20f6a71ae67e97603b25165fa55131f9918f7c08e15f7a09
+size 484