Check if 4-bit input equals 1, magnitude 5

README.md

@@ -9,25 +9,40 @@ tags:
 
 # threshold-isone4
 
-4-bit one detector. Outputs 1 if 4-bit input equals decimal 1 (binary 0001).
+Check if 4-bit input equals 1 (binary 0001).
 
 ## Function
 
-isone4(b0, b1, b2, b3) = 1 if input == 1 (b0=1, b1=b2=b3=0), else 0
+isone4(a3, a2, a1, a0) = 1 if input == 1, else 0
+
+Where input = 8*a3 + 4*a2 + 2*a1 + a0
+
+## Truth Table
+
+| a3 | a2 | a1 | a0 | decimal | out |
+|----|----|----|----|---------| ----|
+| 0 | 0 | 0 | 0 | 0 | 0 |
+| 0 | 0 | 0 | 1 | 1 | 1 |
+| 0 | 0 | 1 | 0 | 2 | 0 |
+| 0 | 0 | 1 | 1 | 3 | 0 |
+| ... | ... | ... | ... | ... | 0 |
 
 ## Architecture
 
-Single neuron with pattern matching: weights [1, -1, -1, -1], bias -1
+Single neuron pattern matcher for binary 0001:
+
+- Weights: [-1, -1, -1, +1]
+- Bias: -1
 
-Fires when: b0 - b1 - b2 - b3 - 1 >= 0
+Fires when: -a3 - a2 - a1 + a0 - 1 >= 0
 
-Only input 0001 satisfies this: 1 - 0 - 0 - 0 - 1 = 0 >= 0
+This requires a3=0, a2=0, a1=0, a0=1 (exactly the pattern 0001).
 
 ## Parameters
 
 | | |
 |---|---|
-| Inputs | 4 (b0 LSB, b3 MSB) |
+| Inputs | 4 |
 | Outputs | 1 |
 | Neurons | 1 |
 | Layers | 1 |
@@ -42,12 +57,13 @@ import torch
 
 w = load_file('model.safetensors')
 
-def isone4(b0, b1, b2, b3):
-    inp = torch.tensor([float(b0), float(b1), float(b2), float(b3)])
+def isone4(a3, a2, a1, a0):
+    inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
     return int((inp @ w['neuron.weight'].T + w['neuron.bias'] >= 0).item())
 
-print(isone4(1, 0, 0, 0))  # 1 (equals 1)
-print(isone4(0, 1, 0, 0))  # 0 (equals 2)
+print(isone4(0, 0, 0, 1))  # 1 (input = 1)
+print(isone4(0, 0, 1, 0))  # 0 (input = 2)
+print(isone4(0, 0, 0, 0))  # 0 (input = 0)
 ```
 
 ## License

config.json

@@ -1,6 +1,6 @@
 {
   "name": "threshold-isone4",
-  "description": "4-bit one detector (equals 1)",
+  "description": "Check if 4-bit input equals 1",
   "inputs": 4,
   "outputs": 1,
   "neurons": 1,

create_safetensors.py

@@ -1,28 +1,28 @@
 import torch
 from safetensors.torch import save_file
 
-# isone4: outputs 1 if 4-bit input equals 1 (binary 0001)
-# Input order: b0 (LSB), b1, b2, b3 (MSB)
-# Need: b0=1, b1=0, b2=0, b3=0
+# Input order: a3, a2, a1, a0 (MSB to LSB)
+# Output 1 if input == 0001 (decimal 1)
 weights = {
-    'neuron.weight': torch.tensor([[1.0, -1.0, -1.0, -1.0]], dtype=torch.float32),
+    'neuron.weight': torch.tensor([[-1.0, -1.0, -1.0, 1.0]], dtype=torch.float32),
     'neuron.bias': torch.tensor([-1.0], dtype=torch.float32)
 }
 save_file(weights, 'model.safetensors')
 
-def isone4(b0, b1, b2, b3):
-    inp = torch.tensor([float(b0), float(b1), float(b2), float(b3)])
+def isone4(a3, a2, a1, a0):
+    inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
     return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())
 
 print("Verifying isone4...")
 errors = 0
 for i in range(16):
-    bits = [(i >> j) & 1 for j in range(4)]
-    result = isone4(*bits)
+    a3, a2, a1, a0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1
+    result = isone4(a3, a2, a1, a0)
     expected = 1 if i == 1 else 0
     if result != expected:
         errors += 1
-        print(f"ERROR: {i:04b} -> {result}, expected {expected}")
+        print(f"ERROR: {a3}{a2}{a1}{a0} (={i}) -> {result}, expected {expected}")
+
 if errors == 0:
     print("All 16 test cases passed!")
 print(f"Magnitude: {sum(t.abs().sum().item() for t in weights.values()):.0f}")

model.py

@@ -4,13 +4,16 @@ from safetensors.torch import load_file
 def load_model(path='model.safetensors'):
     return load_file(path)
 
-def isone4(b0, b1, b2, b3, weights):
-    inp = torch.tensor([float(b0), float(b1), float(b2), float(b3)])
+def isone4(a3, a2, a1, a0, weights):
+    """Returns 1 if 4-bit input equals 1 (0001), else 0"""
+    inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
     return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())
 
 if __name__ == '__main__':
     w = load_model()
-    print('isone4: outputs 1 only for input 0001')
-    for i in [0, 1, 2, 15]:
-        bits = [(i >> j) & 1 for j in range(4)]
-        print(f'  {i} ({i:04b}) -> {isone4(*bits, w)}')
+    print('isone4 truth table:')
+    for i in range(16):
+        a3, a2, a1, a0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1
+        result = isone4(a3, a2, a1, a0, w)
+        marker = ' <-- ONE' if result else ''
+        print(f'  {a3}{a2}{a1}{a0} (={i:2d}) -> {result}{marker}')