About the smooth the resulting class weights

[huixiancheng]

Hi, dear sir. Look like the weight of each class of your code is not same to rangenet++.

3D-MiniNet/pytorch_code/lidar-bonnetal/train/tasks/semantic/modules/trainer.py

Lines 78 to 81 in 21a2783

	self.loss_w = 1 / (content + epsilon_w) # get weights
	power_value = 0.25
	self.loss_w = np.power(self.loss_w, power_value) * np.power(10, 1 - power_value)
	for x_cl, w in enumerate(self.loss_w): # ignore the ones necessary to ignore

Have your results show that the smooth weight is much better? Since there is not have a ablation study.
Looking forward to your reply