backend/lsquant/fast_math/tensor_init.py

import torch as tr
import numpy as np

def init_v0(dim):
    v=np.zeroes(dim, dtype=tr.complex128)
    return v


def init_vrand(dim):
    mean_real = 0  # Mean of the real part
    std_dev_real = 1  # Standard deviation of the real part
    mean_imag = 0  # Mean of the imaginary part
    std_dev_imag = 1  # Standard deviation of the imaginary part

    # Generate real and imaginary parts
    real_part = np.random.normal(mean_real, std_dev_real, dim)
    imaginary_part = np.random.normal(mean_imag, std_dev_imag, dim)

    # Create complex numbers
    v = real_part + 1j * imaginary_part
    v=tr.from_numpy(v)

    return v