| ---
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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
|
| ---
|
|
|
| # threshold-2to4decoder
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|
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| 2-to-4 binary decoder. Converts 2-bit input to one-hot 4-bit output.
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|
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| ## Function
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| decode(A1, A0) -> [Y0, Y1, Y2, Y3]
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|
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| Yi = 1 iff input = i
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|
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| ## Truth Table
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|
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| | A1 | A0 | Y0 | Y1 | Y2 | Y3 |
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| |----|----|----|----|----|-----|
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| | 0 | 0 | 1 | 0 | 0 | 0 |
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| | 0 | 1 | 0 | 1 | 0 | 0 |
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| | 1 | 0 | 0 | 0 | 1 | 0 |
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| | 1 | 1 | 0 | 0 | 0 | 1 |
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|
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| ## Architecture
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| Single layer with 4 neurons. Each Yi matches pattern i.
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|
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| | Output | Weights [A1, A0] | Bias |
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| |--------|------------------|------|
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| | Y0 | [-1, -1] | 0 |
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| | Y1 | [-1, +1] | -1 |
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| | Y2 | [+1, -1] | -1 |
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| | Y3 | [+1, +1] | -2 |
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|
|
| ## Parameters
|
|
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| | | |
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| |---|---|
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| | Inputs | 2 |
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| | Outputs | 4 |
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| | Neurons | 4 |
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| | Layers | 1 |
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| | Parameters | 12 |
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| | Magnitude | 12 |
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|
|
| ## Usage
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|
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| ```python
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| from safetensors.torch import load_file
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| import torch
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|
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| w = load_file('model.safetensors')
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|
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| def decode2to4(a1, a0):
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| inp = torch.tensor([float(a1), float(a0)])
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| return [int((inp * w[f'y{i}.weight']).sum() + w[f'y{i}.bias'] >= 0) for i in range(4)]
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|
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| print(decode2to4(1, 0)) # [0, 0, 1, 0] - input 2
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| ```
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|
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| ## License
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|
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| MIT
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|
