Update links for TF2

PiperOrigin-RevId: 272326185

tensorflow/lite/g3doc/convert/concrete_function.md

@@ -13,7 +13,7 @@ execution is an imperative programming environment that evaluates operations
 immediately, without building graphs. Operations return concrete values instead
 of constructing a computational graph to run later. A detailed guide on eager
 execution is available
-[here](https://github.com/tensorflow/docs/blob/r2.0rc/site/en/r2/guide/eager.ipynb).
+[here](https://www.tensorflow.org/guide/eager).
 
 While running imperatively with eager execution makes development and debugging
 more interactive, it doesn't allow for deploying on-device. The `tf.function`
@@ -171,7 +171,7 @@ tf.saved_model.save(root, export_dir, concrete_func)
 ```
 
 Reference the
-[SavedModel guide](https://github.com/tensorflow/docs/blob/r2.0rc/site/en/r2/guide/saved_model.ipynb)
+[SavedModel guide](https://www.tensorflow.org/guide/saved_model)
 for detailed instructions on using SavedModels.
 
 ### How do I get a concrete function from the SavedModel?

tensorflow/lite/g3doc/convert/index.md

@@ -3,8 +3,8 @@
 The TensorFlow Lite converter takes a TensorFlow model and generates a
 TensorFlow Lite [`FlatBuffer`](https://google.github.io/flatbuffers/) file
 (`.tflite`). The converter supports
-[SavedModel directories](https://www.tensorflow.org/alpha/guide/saved_model),
-[`tf.keras` models](https://www.tensorflow.org/alpha/guide/keras/overview), and
+[SavedModel directories](https://www.tensorflow.org/guide/saved_model),
+[`tf.keras` models](https://www.tensorflow.org/guide/keras/overview), and
 [concrete functions](concrete_function.md).
 
 Note: This page contains documentation on the converter API for TensorFlow 2.0.

tensorflow/lite/g3doc/convert/python_api.md

@@ -12,13 +12,13 @@ The Python API for converting TensorFlow models to TensorFlow Lite in TensorFlow
 classmethods to convert a model based on the original model format:
 
 *   `TFLiteConverter.from_saved_model()`: Converts
-    [SavedModel directories](https://www.tensorflow.org/alpha/guide/saved_model).
+    [SavedModel directories](https://www.tensorflow.org/guide/saved_model).
 *   `TFLiteConverter.from_keras_model()`: Converts
-    [`tf.keras` models](https://www.tensorflow.org/alpha/guide/keras/overview).
+    [`tf.keras` models](https://www.tensorflow.org/guide/keras/overview).
 *   `TFLiteConverter.from_concrete_functions()`: Converts
     [concrete functions](concrete_function.md).
 
-Note: The TensorFlow Lite 2.0 alpha had a different version of the
+Note: TensorFlow Lite 2.0 had a different version of the
 `TFLiteConverter` API which only contained the classmethod
 [`from_concrete_function`](https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/lite/TFLiteConverter#from_concrete_function).
 The API detailed in this document can be installed using the
@@ -33,7 +33,7 @@ of [changes in the API between 1.X and 2.0](#differences), and
 ### Converting a SavedModel <a name="saved_model"></a>
 
 The following example shows how to convert a
-[SavedModel](https://www.tensorflow.org/alpha/guide/saved_model) into a
+[SavedModel](https://www.tensorflow.org/guide/saved_model) into a
 TensorFlow Lite [`FlatBuffer`](https://google.github.io/flatbuffers/).
 
 ```python
@@ -72,7 +72,7 @@ converter = TFLiteConverter.from_concrete_functions([concrete_func])
 ### Converting a Keras model <a name="keras"></a>
 
 The following example shows how to convert a
-[`tf.keras` model](https://www.tensorflow.org/alpha/guide/keras/overview) into a
+[`tf.keras` model](https://www.tensorflow.org/guide/keras/overview) into a
 TensorFlow Lite [`FlatBuffer`](https://google.github.io/flatbuffers/).
 
 ```python

tensorflow/lite/g3doc/guide/get_started.md

@@ -106,28 +106,28 @@ tflite_model = converter.convert()
 open("converted_model.tflite", "wb").write(tflite_model)
 ```
 
-You can [convert TensorFlow 2.0 models](../r2/convert) in a similar way.
+You can [convert TensorFlow 2.0 models](../convert/index.md) in a similar way.
 
 The converter can also be used from the
-[command line](../convert/cmdline_examples), but the Python API is recommended.
+[command line](../convert/cmdline.md), but the Python API is recommended.
 
 ### Options
 
 The converter can convert from a variety of input types.
 
-When [converting TensorFlow 1.x models](../convert/python_api), these are:
+When [converting TensorFlow 1.x models](../convert/python_api.md), these are:
 
-*   [SavedModel directories](https://www.tensorflow.org/alpha/guide/saved_model)
+*   [SavedModel directories](https://www.tensorflow.org/guide/saved_model)
 *   Frozen GraphDef (models generated by
     [freeze_graph.py](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py))
 *   [Keras](https://keras.io) HDF5 models
 *   Models taken from a `tf.Session`
 
-When [converting TensorFlow 2.x models](../r2/convert/python_api), these are:
+When [converting TensorFlow 2.x models](../convert/python_api.md), these are:
 
-*   [SavedModel directories](https://www.tensorflow.org/alpha/guide/saved_model)
-*   [`tf.keras` models](https://www.tensorflow.org/alpha/guide/keras/overview)
-*   [Concrete functions](../r2/convert/concrete_function.md)
+*   [SavedModel directories](https://www.tensorflow.org/guide/saved_model)
+*   [`tf.keras` models](https://www.tensorflow.org/guide/keras/overview)
+*   [Concrete functions](../convert/concrete_function.md)
 
 The converter can be configured to apply various optimizations that can improve
 performance or reduce file size. This is covered in section 4,

tensorflow/lite/g3doc/r1/convert/index.md

@@ -6,7 +6,7 @@ they can be used by the TensorFlow Lite interpreter.
 
 Note: This page contains documentation on the converter API for TensorFlow 1.x.
 The API for TensorFlow 2.0 is available
-[here](https://www.tensorflow.org/lite/r2/convert/).
+[here](https://www.tensorflow.org/lite/convert/).
 
 ## FlatBuffers