Added polynomial lr scheduler for training

train.py

@@ -15,6 +15,24 @@
 from ptsemseg.loss import cross_entropy2d
 from ptsemseg.metrics import scores
 
+
+def poly_lr_scheduler(optimizer, init_lr, iter, lr_decay_iter=1, max_iter=30000, power=0.9,):
+    """Polynomial decay of learning rate
+        :param init_lr is base learning rate
+        :param iter is a current iteration
+        :param lr_decay_iter how frequently decay occurs, default is 1
+        :param max_iter is number of maximum iterations
+        :param power is a polymomial power
+
+    """
+    if iter % lr_decay_iter or iter > max_iter:
+        return optimizer
+
+    for param_group in optimizer.param_groups:
+        param_group['lr'] = init_lr*(1 - iter/max_iter)**power
+    return optimizer
+
+
 def train(args):
 
     # Setup Dataloader