import torch
import torch.nn.functional as F

import numpy as np


def load_tensor():
    coeffs = [None,None]
    coeffs[0] = torch.load('tensor1.pt')
    coeffs[1] = torch.load('tensor2.pt')
    return coeffs



def calc_preds(coeffs, indeps):
    layers,consts = coeffs
    n = len(layers)
    res = indeps
    for i,l in enumerate(layers):
        res = res@l + consts[i]
        if i!=n-1: res = F.relu(res)
    return torch.sigmoid(res)