Ayoub Benaissa youben11

## keygen_log_reg.py
ctx = h.create_context()
keys = ctx.keygen()

## run_plain_log_reg.py
print(f"Simulation result: {h.simulate(x)}")
print(f"Plain NumPy result: {func(x)}")

## rand_input.py
x = np.random.uniform(-1, 1, 5)

## compile_log_reg.py
h = hnp.compile_fhe(
    func,
    {
        'x': hnp.encrypted_ndarray(bounds=(-1, 1), shape=(5,)),
    }
)

## log_reg.py
weights = np.array([0.1, 0.2, 0.3, 0.4, 0.5])
bias = np.array([0.1])


def sigmoid(x):
    return 1 / (1 + np.exp(-x))


def func(x):
    return sigmoid(np.dot(x, weights) + bias)

## import_hnp.py
import hnumpy as hnp
import numpy as np
	print(f"Simulation result: {h.simulate(x)}")
	print(f"Plain NumPy result: {func(x)}")
	h = hnp.compile_fhe(
	func,
	{
	'x': hnp.encrypted_ndarray(bounds=(-1, 1), shape=(5,)),
	}
	)
	weights = np.array([0.1, 0.2, 0.3, 0.4, 0.5])
	bias = np.array([0.1])


	def sigmoid(x):
	return 1 / (1 + np.exp(-x))


	def func(x):
	return sigmoid(np.dot(x, weights) + bias)