class_docstr: Calibrates a floating point model and then quantizes it.
  
  This is an internal class, not a public interface.
class_docstr_tok: ["Calibrates","a","floating","point","model","and","then","quantizes","it",".","This","is","an","internal","class",",","not","a","public","interface","."]
docstr: Calibrates the model with specified generator.
  
  Returns:
    A model with min and max calibration stats.
  
  Args:
    dataset_gen: A generator that generates calibration samples.
docstr_tok: ["Calibrates","the","model","with","specified","generator",".","Returns",":","A","model","with","min","and","max","calibration","stats",".","Args",":","dataset_gen",":","A","generator","that","generates","calibration","samples","."]
code: def calibrate(self, dataset_gen):
      """Calibrates the model with specified generator.
  
      Returns:
        A model with min and max calibration stats.
  
      Args:
        dataset_gen: A generator that generates calibration samples.
      """
      self._feed_tensors(dataset_gen, resize_input=True)
      return self._calibrator.Calibrate()
  
file_path: tensorflow/tensorflow/lite/python/optimize/calibrator.py
imports: import numpy
  from tensorflow.lite.python.convert_phase import Component
  from tensorflow.lite.python.convert_phase import convert_phase
  from tensorflow.lite.python.convert_phase import SubComponent
  from tensorflow.lite.python.interpreter import Interpreter
  from tensorflow.python.framework import dtypes
  from tensorflow.python.util.lazy_loader import LazyLoader
label_desc: Use image node_id 6 for calling the Calibrator obj's underlying member method code with example usage: obj.calibrate(dataset_gen) and returns: self