code: def calibrate_dataset():
      val_data, batch_fn = get_val_data()
      val_data.reset()
      for i, batch in enumerate(val_data):
          if i * batch_size >= calibration_samples:
              break
          data, _ = batch_fn(batch)
          yield {"data": data}
  
file_path: tvm/gallery/how_to/deploy_models/deploy_quantized.py
imports: import tvm
  from tvm import te
  from tvm import relay
  import mxnet
  from tvm.contrib.download import download_testdata
  from mxnet import gluon
  import logging
  import os
label_desc: Use image node_id 2 for calling a global function with example usage: calibrate_dataset() without return types