Remove the input range.


model = keras.Sequential([
    layers.Dense(10, activation='relu', input_shape=(100,)),
    quantize_annotate_layer(layers.Dense(2, activation='sigmoid'))
with quantize.quantize_scope():
  model = quantize_annotate_model(model)
  model = quantize_apply(model)
  model = remove_input_range(model)

In certain cases, a desired input range is not required if the model itself is internally used.

model A tf.keras Sequential or Functional model which has been quantized.

Returns a new tf.keras model removed input range.