"""
Threshold Network for Full Adder

Adds three 1-bit inputs (a, b, cin), producing sum and carry outputs.
Built from two half adders and an OR gate.
"""

import torch
from safetensors.torch import load_file


def heaviside(x):
    return (x >= 0).float()


class ThresholdFullAdder:
    """
    Full adder: sum = a XOR b XOR cin, cout = (a AND b) OR ((a XOR b) AND cin)
    """

    def __init__(self, weights_dict):
        self.weights = weights_dict

    def half_adder(self, prefix, a, b):
        inputs = torch.tensor([float(a), float(b)])

        # XOR for sum
        or_out = heaviside((inputs * self.weights[f'{prefix}.sum.layer1.or.weight']).sum() +
                           self.weights[f'{prefix}.sum.layer1.or.bias'])
        nand_out = heaviside((inputs * self.weights[f'{prefix}.sum.layer1.nand.weight']).sum() +
                             self.weights[f'{prefix}.sum.layer1.nand.bias'])
        layer1 = torch.tensor([or_out, nand_out])
        sum_out = heaviside((layer1 * self.weights[f'{prefix}.sum.layer2.weight']).sum() +
                            self.weights[f'{prefix}.sum.layer2.bias'])

        # AND for carry
        carry_out = heaviside((inputs * self.weights[f'{prefix}.carry.weight']).sum() +
                              self.weights[f'{prefix}.carry.bias'])

        return int(sum_out.item()), int(carry_out.item())

    def __call__(self, a, b, cin):
        # First half adder: a + b
        s1, c1 = self.half_adder('ha1', a, b)

        # Second half adder: s1 + cin
        sum_out, c2 = self.half_adder('ha2', s1, cin)

        # Carry out = c1 OR c2
        carry_inputs = torch.tensor([float(c1), float(c2)])
        cout = heaviside((carry_inputs * self.weights['carry_or.weight']).sum() +
                         self.weights['carry_or.bias'])

        return int(sum_out), int(cout.item())

    @classmethod
    def from_safetensors(cls, path="model.safetensors"):
        return cls(load_file(path))


if __name__ == "__main__":
    model = ThresholdFullAdder.from_safetensors("model.safetensors")

    print("Full Adder Truth Table:")
    print("-" * 40)
    print("a | b | cin | sum | cout")
    print("-" * 40)
    for a in [0, 1]:
        for b in [0, 1]:
            for cin in [0, 1]:
                s, cout = model(a, b, cin)
                expected_sum = (a + b + cin) % 2
                expected_cout = (a + b + cin) // 2
                status = "OK" if (s == expected_sum and cout == expected_cout) else "FAIL"
                print(f"{a} | {b} |  {cin}  |  {s}  |  {cout}    [{status}]")