code: def amp_scaler(config):
      if "AMP" in config and config["AMP"]["use_amp"] is True:
          AMP_RELATED_FLAGS_SETTING = {
              "FLAGS_cudnn_batchnorm_spatial_persistent": 1,
              "FLAGS_max_inplace_grad_add": 8,
          }
          paddle.set_flags(AMP_RELATED_FLAGS_SETTING)
          scale_loss = config["AMP"].get("scale_loss", 1.0)
          use_dynamic_loss_scaling = config["AMP"].get(
              "use_dynamic_loss_scaling", False
          )
          scaler = paddle.amp.GradScaler(
              init_loss_scaling=scale_loss,
              use_dynamic_loss_scaling=use_dynamic_loss_scaling,
          )
          return scaler
      else:
          return None
  
imports: import paddle
  import numpy
  import os
  import paddle.nn
  import paddle.distributed
  from loss import build_loss, LossDistill, DMLLoss, KLJSLoss
  from optimizer import create_optimizer
  from data_loader import build_dataloader
  from metric import create_metric
  from mv3 import MobileNetV3_large_x0_5, distillmv3_large_x0_5, build_model
  from config import preprocess
  import time
  from paddleslim.dygraph.quant import QAT
  from slim.slim_quant import PACT, quant_config
  from slim.slim_fpgm import prune_model
  from utils import load_model
label_desc: Use image node_id 3 for calling a global function with example usage: amp_scaler(config) and returns: scaler, None