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site/en/guide/migrate/saved_model.ipynb

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"### Save and export a SavedModel defined with tf.Module\n",
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"To export your model in TensorFlow 2, you must define a `tf.Module` or a `tf.keras.Model` to hold all of your model's variables and functions. Then, you can call `tf.saved_model.save` to create a SavedModel. Refer to [Saving a custom model](../../guide/saved_model#saving_a_custom_model) in the [Using the SavedModel format](../../guide/saved_model) guide to learn more."
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"To export your model in TensorFlow 2, you must define a `tf.Module` or a `tf.keras.Model` to hold all of your model's variables and functions. Then, you can call `tf.saved_model.save` to create a SavedModel. Refer to [Saving a custom model](../../guide/saved_model#saving_a_custom_model) in the [Using the SavedModel format](https://www.tensorflow.org/guide/saved_model) guide to learn more."
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"Signatures are the endpoints of a SavedModel—they tell the user how to run the model and what inputs are needed.\n",
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"In TensorFlow 1, signatures are created by listing the input and output tensors. In TensorFlow 2, signatures are generated by passing in *concrete functions*. (Read more about TensorFlow functions in the [Introduction to graphs and tf.function](../guide/intro_to_graphs) guide.) In short, [a concrete function is generated](../guide/intro_to_graphs#polymorphism_one_function_many_graphs) from a `tf.function`:\n",
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"In TensorFlow 1, signatures are created by listing the input and output tensors. In TensorFlow 2, signatures are generated by passing in *concrete functions*. (Read more about TensorFlow functions in the [Introduction to graphs and tf.function](https://www.tensorflow.org/guide/intro_to_graphs) guide.) In short, [a concrete function is generated](https://www.tensorflow.org/guide/intro_to_graphs#polymorphism_one_function_many_graphs) from a `tf.function`:\n",
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"```python\n",
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"# Option 1: Specify an input signature.\n",

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