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nvidia--tensorrt/tools/tensorflow-quantization/docs/source/qmodel.rst
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.. _qmodel_api:
**tensorflow_quantization.quantize_model**
============================================
.. automodule:: tensorflow_quantization.quantize
:members: quantize_model
.. note:: Currently only Functional and Sequential models are supported.
Examples
.. code:: python
import tensorflow as tf
from tensorflow_quantization.quantize import quantize_model
# Simple full model quantization.
# 1. Create a simple network
input_img = tf.keras.layers.Input(shape=(28, 28))
r = tf.keras.layers.Reshape(target_shape=(28, 28, 1))(input_img)
x = tf.keras.layers.Conv2D(filters=2, kernel_size=(3, 3))(r)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Conv2D(filters=2, kernel_size=(3, 3))(x)
x = tf.keras.layers.ReLU()(x)
x = tf.keras.layers.Flatten()(x)
model = tf.keras.Model(input_img, x)
print(model.summary())
# 2. Quantize the network
q_model = quantize_model(model)
print(q_model.summary())