Tensorflow implementation about polylanenet HOT 7 CLOSED

No, unfortunately.

from polylanenet.

Never mind. I knew the reasons.
Now the total loss reached around 4~5.

Anyway, Can you explain your code as below?
def forward(self, x, epoch=None, **kwargs): output, extra_outputs = self.model(x, **kwargs) for i in range(len(self.curriculum_steps)): if epoch is not None and epoch < self.curriculum_steps[i]: output[-len(self.curriculum_steps) + i] = 0 return output, extra_outputs

Particularly, why we need to zero one feature before feeding to loss function as below?
output[-len(self.curriculum_steps) + i] = 0

from polylanenet.

That's just a leftover from some experiments I did with curriculum learning. That line has no effect with the default config files used, you can ignore it (or remove).

from polylanenet.

After a few trials, I could not get lower loss value as your logs. I have reviewed your code many times but could not get it right.

Here is your loss calculation:

# applying weights to partial losses
poly_loss = poly_loss * poly_weight
lower_loss = lower_loss * lower_weight
upper_loss = upper_loss * upper_weight
cls_loss = cls_loss * cls_weight
conf_loss = bce(pred_confs, target_confs) * conf_weight

loss = conf_loss + lower_loss + upper_loss + poly_loss + cls_loss

return loss, {
            'conf': conf_loss,
            'lower': lower_loss,
            'upper': upper_loss,
            'poly': poly_loss,
            'cls_loss': cls_loss
        }

Here is your loss parameters:

loss_parameters:
conf_weight: 1
lower_weight: 1
upper_weight: 1
cls_weight: 0
poly_weight: 300

Here is your loss calculated values:
[2020-04-03 21:41:01,371] [INFO] Epoch [1/2695], Step [1/227], Loss: 105.9413 (upper: 0.8436, lower: 0.1043, poly: 104.3011, conf: 0.6923), s/iter: 0.5786, lr: 3.0e-04
[2020-04-03 21:41:01,776] [INFO] Epoch [1/2695], Step [2/227], Loss: 83.7656 (upper: 0.7416, lower: 0.0899, poly: 60.0729, conf: 0.6855), s/iter: 0.4678, lr: 3.0e-04
[2020-04-03 21:41:02,159] [INFO] Epoch [1/2695], Step [3/227], Loss: 68.2684 (upper: 0.6549, lower: 0.0667, poly: 35.8984, conf: 0.6538), s/iter: 0.4277, lr: 3.0e-04
[2020-04-03 21:41:02,516] [INFO] Epoch [1/2695], Step [4/227], Loss: 57.8521 (upper: 0.5872, lower: 0.0476, poly: 25.3292, conf: 0.6394), s/iter: 0.4079, lr: 3.0e-04

with poly_weight: 300, how did you calculate Loss as above? Should it as poly_weight: 1?

from polylanenet.

That poly loss value being printed is after multiplying it by poly_weight. If you sum all loss components (upper + lower + poly + conf) you'll see that, for the first line, it equals 105.9413, as printed. That doesn't mean that the poly_weight equals 1, it's just that the printed value is post-multiplication.

from polylanenet.

My bad. I have noticed the same thing after posting the comment.

from polylanenet.

No problem :) Feel free to ask any more questions you have.

from polylanenet.