def init_weights(self):
for module_list in [
self.reg_cls_fcs, self.reg_offset_fcs, self.cls_fcs
]:
for m in module_list.modules():
if isinstance(m, nn.Linear):
xavier_init(m, distribution='uniform')
if self.reg_feat_up_ratio > 1:
kaiming_init(self.upsample_x, distribution='normal')
kaiming_init(self.upsample_y, distribution='normal')
normal_init(self.reg_conv_att_x, 0, 0.01)
normal_init(self.reg_conv_att_y, 0, 0.01)
normal_init(self.fc_reg_offset, 0, 0.001)
normal_init(self.fc_reg_cls, 0, 0.01)
normal_init(self.fc_cls, 0, 0.01)
def init_weights(self):
"""Initialize weights of the head."""
for m in self.modules():
if isinstance(m, nn.Conv2d):
xavier_init(m, distribution='uniform', bias=0)