From 50b886ddc64403e3f08361387acd733900b1632e Mon Sep 17 00:00:00 2001 From: tcmyxc <1282494272@qq.com> Date: Tue, 31 May 2022 15:53:36 +0800 Subject: [PATCH] `.detach()` on bias init (#8044) make init bias better, I think `detach` is more safer than `data` --- models/yolo.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/models/yolo.py b/models/yolo.py index c7674a5..02660e6 100644 --- a/models/yolo.py +++ b/models/yolo.py @@ -207,9 +207,9 @@ class Model(nn.Module): # cf = torch.bincount(torch.tensor(np.concatenate(dataset.labels, 0)[:, 0]).long(), minlength=nc) + 1. m = self.model[-1] # Detect() module for mi, s in zip(m.m, m.stride): # from - b = mi.bias.view(m.na, -1) # conv.bias(255) to (3,85) - b.data[:, 4] += math.log(8 / (640 / s) ** 2) # obj (8 objects per 640 image) - b.data[:, 5:] += math.log(0.6 / (m.nc - 0.999999)) if cf is None else torch.log(cf / cf.sum()) # cls + b = mi.bias.view(m.na, -1).detach() # conv.bias(255) to (3,85) + b[:, 4] += math.log(8 / (640 / s) ** 2) # obj (8 objects per 640 image) + b[:, 5:] += math.log(0.6 / (m.nc - 0.999999)) if cf is None else torch.log(cf / cf.sum()) # cls mi.bias = torch.nn.Parameter(b.view(-1), requires_grad=True) def _print_biases(self):