docstr: This function is used to define the way of feeding calibrating data each batch.
  
  Parameters
  ----------
  names : str
       The names of the network inputs for each object in the bindings array
  
  Returns
  -------
  list
      A list of device memory pointers set to the memory containing each network
      input data, or an empty list if there are no more batches for calibration.
      You can allocate these device buffers with pycuda, for example, and then
      cast them to int to retrieve the pointer
code: def get_batch(self, names):
      """
      This function is used to define the way of feeding calibrating data each batch.
  
      Parameters
      ----------
      names : str
           The names of the network inputs for each object in the bindings array
  
      Returns
      -------
      list
          A list of device memory pointers set to the memory containing each network
          input data, or an empty list if there are no more batches for calibration.
          You can allocate these device buffers with pycuda, for example, and then
          cast them to int to retrieve the pointer
      """
      if self.current_index + self.batch_size > self.data.shape[0]:
          return None
  
      current_batch = int(self.current_index / self.batch_size)
      if current_batch % 10 == 0:
          logger.info(
              "Calibrating batch %d, containing %d images",
              current_batch,
              self.batch_size,
          )
  
      batch = self.data[
          self.current_index : self.current_index + self.batch_size
      ].ravel()
      cuda.memcpy_htod(self.device_input, batch)
      self.current_index += self.batch_size
      memory_pointers = [self.device_input]
      return memory_pointers
  
file_path: nni/nni/compression/quantization_speedup/calibrator.py
imports: import os
  import logging
  import tensorrt
  import pycuda.driver
label_desc: Use image node_id 4 for calling the Calibrator obj's underlying member method code with example usage: obj.get_batch(names) and returns: memory_pointers, None