import torch
from safetensors.torch import load_file

def load_model(path='model.safetensors'):
    return load_file(path)

def majority7(a, b, c, d, e, f, g, weights):
    inp = torch.tensor([float(a), float(b), float(c), float(d), float(e), float(f), float(g)])
    return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())

if __name__ == '__main__':
    w = load_model()
    print('majority7 sample outputs:')
    print(f'  0000000 -> {majority7(0,0,0,0,0,0,0,w)}')
    print(f'  0000111 -> {majority7(0,0,0,0,1,1,1,w)}')
    print(f'  0001111 -> {majority7(0,0,0,1,1,1,1,w)}')
    print(f'  1111111 -> {majority7(1,1,1,1,1,1,1,w)}')