code: def _get_stacked_convs_model(self):
      i = tf.keras.Input(shape=(64, 64, 3))
      x = tf.keras.layers.Conv2D(
          10, kernel_size=(3, 3), strides=(1, 1), activation="relu"
      )(i)
      x = tf.keras.layers.Conv2D(
          # Setting strides to (1, 1) passes test, (2, 2) fails test?
          # Somehow one value is at border.
          # Train over 100 epochs, and issue goes away.
          # Why are all the first values zero?
          10,
          kernel_size=(3, 3),
          strides=(2, 2),
          activation="relu",
      )(x)
      x = tf.keras.layers.Conv2D(
          10, kernel_size=(3, 3), strides=(2, 2), activation="relu"
      )(x)
      x = tf.keras.layers.Conv2D(
          5, kernel_size=(3, 3), strides=(2, 2), activation="relu"
      )(x)
      x = tf.keras.layers.Conv2D(
          2, kernel_size=(3, 3), strides=(2, 2), activation="relu"
      )(x)
      return tf.keras.Model(i, x)
  
imports: import tempfile
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras import quantize
  from tensorflow_model_optimization.python.core.quantization.keras import utils
label_desc: Use image node_id 7 for calling the QuantizeNumericalTest obj's underlying member method code with example usage: obj._get_stacked_convs_model() and returns: tf