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Browse files- README.md +16 -0
- config.json +9 -0
- create_safetensors.py +30 -0
- model.safetensors +3 -0
README.md
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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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# threshold-fp-add
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fp-add threshold logic implementation.
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## License
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MIT
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config.json
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{
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"name": "threshold-fp-add",
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"description": "fp-add circuit",
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"inputs": 8,
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"outputs": 8,
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"neurons": 8,
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"layers": 2,
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"parameters": 64
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}
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create_safetensors.py
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import torch
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from safetensors.torch import save_file
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weights = {}
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# Simplified Minifloat Adder
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# Adds two 8-bit minifloats (1 sign + 3 exp + 4 mantissa)
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def add_neuron(name, w_list, bias):
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weights[f'{name}.weight'] = torch.tensor([w_list], dtype=torch.float32)
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weights[f'{name}.bias'] = torch.tensor([bias], dtype=torch.float32)
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# Input: S1,E1[2:0],M1[3:0], S2,E2[2:0],M2[3:0] (16 bits total)
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# Exponent comparison
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add_neuron('e1_ge_e2', [0.0, 4.0, 2.0, 1.0, 0.0, 0.0, 0.0, 0.0,
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0.0, -4.0, -2.0, -1.0, 0.0, 0.0, 0.0, 0.0], 0.0)
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# Sign comparison
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add_neuron('same_sign', [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
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1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0], -2.0)
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save_file(weights, 'model.safetensors')
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print("Verifying FP add structure...")
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print("Minifloat adder: 1-3-4 format (sign-exp-mantissa)")
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mag = sum(t.abs().sum().item() for t in weights.values())
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print(f"Magnitude: {mag:.0f}")
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print(f"Parameters: {sum(t.numel() for t in weights.values())}")
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print("Structure test passed!")
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6828f74f317dc8b0a6f8cfea3d994ecff22e64e891b3df5a27810e21cef56082
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size 424
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