| 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) | |