code: def compute_amax(model, **kwargs):
      """Loads statistics of data and calculates quantization parameters in whole network"""
      for name, module in model.named_modules():
          if (
              isinstance(module, quant_nn.TensorQuantizer)
              and module._calibrator is not None
          ):
              if isinstance(module._calibrator, calib.MaxCalibrator):
                  module.load_calib_amax()
              else:
                  module.load_calib_amax(**kwargs)
      model.cuda()
  
file_path: DALI/docs/examples/use_cases/pytorch/efficientnet/image_classification/quantization.py
imports: from tqdm import tqdm
  import torch
  import contextlib
  import time
  import logging
  from pytorch_quantization import quant_modules
  from pytorch_quantization import nn
  from pytorch_quantization import calib
  from pytorch_quantization.tensor_quant import QuantDescriptor
  from .None import logger
  from .utils import calc_ips
  import dllogger
label_desc: Use image node_id 5 for calling a global function with example usage: compute_amax(model) without return types