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8-bit zero detector, magnitude 8

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Files changed (5) hide show
  1. README.md +37 -0
  2. config.json +9 -0
  3. create_safetensors.py +24 -0
  4. model.py +16 -0
  5. model.safetensors +0 -0
README.md ADDED
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+ ---
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+ license: mit
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+ tags:
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+ - pytorch
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+ - safetensors
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+ - threshold-logic
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+ - neuromorphic
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+ ---
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+
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+ # threshold-iszero8
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+
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+ 8-bit zero detector. Outputs 1 if all 8 input bits are zero.
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+
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+ ## Function
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+
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+ iszero8(b0..b7) = 1 if all bits are 0, else 0
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+
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+ Equivalent to 8-input NOR gate.
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+
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+ ## Architecture
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+
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+ Single neuron: weights [-1, -1, -1, -1, -1, -1, -1, -1], bias 0
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+
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+ ## Parameters
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+
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+ | | |
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+ |---|---|
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+ | Inputs | 8 |
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+ | Outputs | 1 |
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+ | Neurons | 1 |
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+ | Layers | 1 |
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+ | Parameters | 9 |
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+ | Magnitude | 8 |
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+
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+ ## License
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+
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+ MIT
config.json ADDED
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+ {
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+ "name": "threshold-iszero8",
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+ "description": "8-bit zero detector",
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+ "inputs": 8,
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+ "outputs": 1,
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+ "neurons": 1,
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+ "layers": 1,
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+ "parameters": 9
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+ }
create_safetensors.py ADDED
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+ import torch
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+ from safetensors.torch import save_file
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+
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+ weights = {
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+ 'neuron.weight': torch.tensor([[-1.0] * 8], dtype=torch.float32),
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+ 'neuron.bias': torch.tensor([0.0], dtype=torch.float32)
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+ }
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+ save_file(weights, 'model.safetensors')
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+
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+ def iszero8(bits):
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+ inp = torch.tensor([float(b) for b in bits])
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+ return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())
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+
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+ print("Verifying iszero8...")
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+ errors = 0
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+ for i in range(256):
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+ bits = [(i >> j) & 1 for j in range(8)]
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+ result = iszero8(bits)
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+ expected = 1 if i == 0 else 0
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+ if result != expected:
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+ errors += 1
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+ if errors == 0:
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+ print("All 256 test cases passed!")
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+ print(f"Magnitude: {sum(t.abs().sum().item() for t in weights.values()):.0f}")
model.py ADDED
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+ import torch
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+ from safetensors.torch import load_file
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+
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+ def load_model(path='model.safetensors'):
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+ return load_file(path)
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+
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+ def iszero8(bits, weights):
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+ inp = torch.tensor([float(b) for b in bits])
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+ return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())
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+
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+ if __name__ == '__main__':
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+ w = load_model()
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+ print('iszero8: outputs 1 only for input 00000000')
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+ for i in [0, 1, 128, 255]:
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+ bits = [(i >> j) & 1 for j in range(8)]
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+ print(f' {i:08b} -> {iszero8(bits, w)}')
model.safetensors ADDED
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