docstr: Define an integer post-training quantized model from saved model.
docstr_tok: ["Define","an","integer","post-training","quantized","model","from","saved","model","."]
code: def _generate_integer_tflite_model_from_saved_model(self):
      """Define an integer post-training quantized model from saved model."""
  
      saved_model_dir = os.path.join(
          self.get_temp_dir(), "simple_savedmodel"
      )
      return _generate_integer_tflite_model(
          use_saved_model=True,
          saved_model_dir=saved_model_dir,
          add_unquantizable_layer=True,
      )
  
imports: import os
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.lite.python import util
  from tensorflow.lite.tools.flatbuffer_utils import read_model
  from tensorflow.python.client import session
  from tensorflow.python.framework import convert_to_constants
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the UtilModifyIntegerQuantizedModelIOTypeSignatureDefTest obj's underlying member method code with example usage: obj._generate_integer_tflite_model_from_saved_model() and returns: _generate_integer_tflite_model