code: def __init__(
      self, batch_size: int, input_data: List[Tuple[np.ndarray, ...]]
  ):
      super(TensorRTCalibrator, self).__init__()
      self._bs = batch_size
      self.batches = (x for x in input_data)
  
file_path: nebuly/optimization/nebullvm/nebullvm/operations/optimizations/compilers/quantizations/tensor_rt.py
imports: from typing import List, Tuple
  import numpy
  from nebullvm.core.models import QuantizationType, ModelParams
  from nebullvm.optional_modules.tensor_rt import tensorrt, IInt8EntropyCalibrator2, polygraphy
  from nebullvm.tools.transformations import MultiStageTransformation
label_desc: Use image node_id 1 to create a new TensorRTCalibrator object from inherited base classes: IInt8EntropyCalibrator2 with example: obj = TensorRTCalibrator(batch_size, input_data)