code: def get_lrs(optimizer):
      lrs = []
      for pgs in optimizer.state_dict()["param_groups"]:
          lrs.append(pgs["lr"])
      lrs = ["{:.6f}".format(x) for x in lrs]
      return lrs
  
imports: import os
  import argparse
  import time
  import torch
  import torch.nn
  import torch.optim
  import torch.nn.functional
  from torch.optim.lr_scheduler import CosineAnnealingLR, ReduceLROnPlateau
  from loader import get_train_loaders, add_depth_channel
  from models import UNetResNetV4, UNetResNetV5, UNetResNetV6
  from lovasz_losses import lovasz_hinge
  from focal_loss import FocalLoss2d
  from postprocessing import binarize, crop_image, resize_image
  from metrics import intersection_over_union, intersection_over_union_thresholds
  import settings
label_desc: Use image node_id 3 for calling a global function with example usage: get_lrs(optimizer) and returns: lrs