| license: mit | |
| tags: | |
| - pytorch | |
| - safetensors | |
| - threshold-logic | |
| - neuromorphic | |
| # threshold-gray2binary | |
| 4-bit Gray code to binary converter. | |
| ## Function | |
| gray2binary(G3, G2, G1, G0) -> (B3, B2, B1, B0) | |
| Conversion formulas: | |
| - B3 = G3 | |
| - B2 = G3 XOR G2 | |
| - B1 = G3 XOR G2 XOR G1 | |
| - B0 = G3 XOR G2 XOR G1 XOR G0 | |
| ## Example Conversions | |
| | Gray | Binary | | |
| |------|--------| | |
| | 0000 | 0000 (0) | | |
| | 0001 | 0001 (1) | | |
| | 0011 | 0010 (2) | | |
| | 0010 | 0011 (3) | | |
| | 0110 | 0100 (4) | | |
| | 0111 | 0101 (5) | | |
| | 0101 | 0110 (6) | | |
| | 0100 | 0111 (7) | | |
| ## Architecture | |
| Cascade XOR structure with shared intermediate results: | |
| ``` | |
| G3 ──────────────────────────────────────────► B3 | |
| G3,G2 ─► [XOR] ─► X1 ────────────────────────► B2 | |
| X1,G1 ─► [XOR] ─► X2 ──────────► B1 | |
| X2,G0 ─► [XOR] ──► B0 | |
| ``` | |
| Each XOR uses 3 neurons (OR, NAND, AND) with mag-7 weights. | |
| ## Parameters | |
| | | | | |
| |---|---| | |
| | Inputs | 4 | | |
| | Outputs | 4 | | |
| | Neurons | 10 | | |
| | Layers | 6 | | |
| | Parameters | 46 | | |
| | Magnitude | 33 | | |
| ## Usage | |
| ```python | |
| from safetensors.torch import load_file | |
| import torch | |
| w = load_file('model.safetensors') | |
| # Convert gray code 0110 (which is binary 4) | |
| # Full implementation in model.py | |
| ``` | |
| ## License | |
| MIT | |