Upload folder using huggingface_hub

README.md

@@ -0,0 +1,50 @@
+---
+license: mit
+tags:
+- pytorch
+- safetensors
+- threshold-logic
+- neuromorphic
+- arithmetic
+- multiplier
+---
+
+# threshold-dadda-tree
+
+2x2 Dadda tree multiplier. Uses height-reduction algorithm to minimize adder stages.
+
+## Circuit
+
+```
+Inputs: A[1:0], B[1:0] (4 inputs)
+Outputs: P[3:0] (4 outputs)
+
+P = A × B (unsigned)
+```
+
+## Dadda Algorithm
+
+Reduces partial product columns to heights in sequence: 2, 3, 4, 6, 9, 13...
+For 2x2, columns are already within limits, so minimal reduction needed.
+
+```
+        A1·B0  A0·B0
+  A1·B1 A0·B1
+  ─────────────────
+    P3   P2   P1   P0
+```
+
+## Parameters
+
+| | |
+|---|---|
+| Inputs | 4 |
+| Outputs | 4 |
+| Neurons | 10 |
+| Layers | 3 |
+| Parameters | 44 |
+| Magnitude | 44 |
+
+## License
+
+MIT

config.json

@@ -0,0 +1,9 @@
+{
+  "name": "threshold-dadda-tree",
+  "description": "2x2 Dadda tree multiplier",
+  "inputs": 4,
+  "outputs": 4,
+  "neurons": 10,
+  "layers": 3,
+  "parameters": 44
+}

create_safetensors.py

@@ -0,0 +1,94 @@
+import torch
+from safetensors.torch import save_file
+
+weights = {}
+
+# 2x2 Dadda Tree Multiplier
+# Inputs: A1,A0, B1,B0 (4 inputs)
+# Outputs: P3,P2,P1,P0 (4 outputs)
+#
+# Partial products:
+#       A1B0  A0B0
+#  A1B1 A0B1
+# ----------------
+#  P3   P2   P1   P0
+#
+# Dadda reduces column heights to specific sequence: 2,2,3,4,6,9,13...
+# For 2x2, columns are already height 1 or 2, so minimal reduction needed.
+
+# Input indices: A1=0, A0=1, B1=2, B0=3
+
+def add_and(name, idx_a, idx_b, n_inputs):
+    w = [0.0] * n_inputs
+    w[idx_a] = 1.0
+    w[idx_b] = 1.0
+    weights[f'{name}.weight'] = torch.tensor([w], dtype=torch.float32)
+    weights[f'{name}.bias'] = torch.tensor([-2.0], dtype=torch.float32)
+
+def add_xor_direct(name, n_prev):
+    weights[f'{name}.or.weight'] = torch.tensor([[1.0, 1.0]], dtype=torch.float32)
+    weights[f'{name}.or.bias'] = torch.tensor([-1.0], dtype=torch.float32)
+    weights[f'{name}.nand.weight'] = torch.tensor([[-1.0, -1.0]], dtype=torch.float32)
+    weights[f'{name}.nand.bias'] = torch.tensor([1.0], dtype=torch.float32)
+    weights[f'{name}.and.weight'] = torch.tensor([[1.0, 1.0]], dtype=torch.float32)
+    weights[f'{name}.and.bias'] = torch.tensor([-2.0], dtype=torch.float32)
+
+# Partial products (AND gates)
+add_and('pp00', 1, 3, 4)  # A0 * B0 -> P0
+add_and('pp01', 1, 2, 4)  # A0 * B1
+add_and('pp10', 0, 3, 4)  # A1 * B0
+add_and('pp11', 0, 2, 4)  # A1 * B1
+
+# Column 1 (weight 2): pp01 + pp10 -> half adder
+add_xor_direct('ha1_sum', 2)
+weights['ha1_carry.weight'] = torch.tensor([[1.0, 1.0]], dtype=torch.float32)
+weights['ha1_carry.bias'] = torch.tensor([-2.0], dtype=torch.float32)
+
+# Column 2 (weight 4): pp11 + carry from column 1 -> half adder
+add_xor_direct('ha2_sum', 2)
+weights['ha2_carry.weight'] = torch.tensor([[1.0, 1.0]], dtype=torch.float32)
+weights['ha2_carry.bias'] = torch.tensor([-2.0], dtype=torch.float32)
+
+save_file(weights, 'model.safetensors')
+
+def dadda_mult(a1, a0, b1, b0):
+    pp00 = a0 & b0
+    pp01 = a0 & b1
+    pp10 = a1 & b0
+    pp11 = a1 & b1
+
+    p0 = pp00
+
+    # Half adder for column 1
+    p1 = pp01 ^ pp10
+    c1 = pp01 & pp10
+
+    # Half adder for column 2
+    p2 = pp11 ^ c1
+    c2 = pp11 & c1
+
+    p3 = c2
+
+    return p3, p2, p1, p0
+
+print("Verifying 2x2 Dadda tree multiplier...")
+errors = 0
+for a in range(4):
+    for b in range(4):
+        a1, a0 = (a >> 1) & 1, a & 1
+        b1, b0 = (b >> 1) & 1, b & 1
+        p3, p2, p1, p0 = dadda_mult(a1, a0, b1, b0)
+        result = p3*8 + p2*4 + p1*2 + p0
+        expected = a * b
+        if result != expected:
+            errors += 1
+            print(f"ERROR: {a}*{b} = {result}, expected {expected}")
+
+if errors == 0:
+    print("All 16 test cases passed!")
+else:
+    print(f"FAILED: {errors} errors")
+
+mag = sum(t.abs().sum().item() for t in weights.values())
+print(f"Magnitude: {mag:.0f}")
+print(f"Parameters: {sum(t.numel() for t in weights.values())}")

model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:190502e4d427546b55862398447302774edfa455b6f96b24931d25603b3b4e0d
+size 1864