Merge pull request #60553 from tensorflow/anirudh161-patch-1

Minor fixes for RELEASE.md

RELEASE.md

@@ -10,21 +10,21 @@
 
 *   `tf.lite`
 
-    *   Add 16-bit and 64-bit float type support for built-in op `cast`.
+    *   Added 16-bit and 64-bit float type support for built-in op `cast`.
     *   The Python TF Lite Interpreter bindings now have an option `experimental_disable_delegate_clustering` to turn-off delegate clustering.
-    *   Add int16x8 support for the built-in op `exp`
-    *   Add int16x8 support for the built-in op `mirror_pad`
-    *   Add int16x8 support for the built-in ops `space_to_batch_nd` and `batch_to_space_nd`
-    *   Add 16-bit int type support for built-in op `less`, `greater_than`, `equal`
-    *   Add 8-bit and 16-bit support for `floor_div` and `floor_mod`.
-    *   Add 16-bit and 32-bit int support for the built-in op `bitcast`.
-    *   Add 8-bit/16-bit/32-bit int/uint support for the built-in op `bitwise_xor`
-    *   Add int16 indices support for built-in op `gather` and `gather_nd`.
-    *   Add 8-bit/16-bit/32-bit int/uint support for the built-in op `right_shift`
-    *   Add reference implementation for 16-bit int unquantized `add`.
-    *   Add reference implementation for 16-bit int and 32-bit unsigned int unquantized `mul`.
+    *   Added int16x8 support for the built-in op `exp`
+    *   Added int16x8 support for the built-in op `mirror_pad`
+    *   Added int16x8 support for the built-in ops `space_to_batch_nd` and `batch_to_space_nd`
+    *   Added 16-bit int type support for built-in op `less`, `greater_than`, `equal`
+    *   Added 8-bit and 16-bit support for `floor_div` and `floor_mod`.
+    *   Added 16-bit and 32-bit int support for the built-in op `bitcast`.
+    *   Added 8-bit/16-bit/32-bit int/uint support for the built-in op `bitwise_xor`
+    *   Added int16 indices support for built-in op `gather` and `gather_nd`.
+    *   Added 8-bit/16-bit/32-bit int/uint support for the built-in op `right_shift`
+    *   Added reference implementation for 16-bit int unquantized `add`.
+    *   Added reference implementation for 16-bit int and 32-bit unsigned int unquantized `mul`.
     *   `add_op` supports broadcasting up to 6 dimensions.
-    *   Add 16-bit support for `top_k`.
+    *   Added 16-bit support for `top_k`.
 
 *   `tf.function`
 
@@ -38,16 +38,16 @@
 *   `tf.data`
 
     *   `tf.data.Dataset.zip` now supports Python-style zipping, i.e. `Dataset.zip(a, b, c)`.
-    *   `tf.data.Dataset.shuffle` now supports full shuffling. To specify that data should be fully shuffled, use `dataset = dataset.shuffle(dataset.cardinality())`. This will load the full dataset into memory so that it can be shuffled, so make sure to only use this with datasets of filenames or other small datasets.
+    * `tf.data.Dataset.shuffle` now supports `tf.data.UNKNOWN_CARDINALITY` When doing a "full shuffle" using  `dataset = dataset.shuffle(dataset.cardinality())`. But remember, a "full shuffle" will load the full dataset into memory so that it can be shuffled, so make sure to only use this with small datasets or datasets of small objects (like filenames).
 
 *   `tf.math`
 
     * `tf.nn.top_k` now supports specifying the output index type via parameter `index_type`.  Supported types are `tf.int16`, `tf.int32` (default), and `tf.int64`.
 
 *   `tf.SavedModel`
 
-    *   Introduce class method `tf.saved_model.experimental.Fingerprint.from_proto(proto)`, which can be used to construct a `Fingerprint` object directly from a protobuf.
-    *   Introduce member method `tf.saved_model.experimental.Fingerprint.singleprint()`, which provides a convenient way to uniquely identify a SavedModel.
+    *   Introduced class method `tf.saved_model.experimental.Fingerprint.from_proto(proto)`, which can be used to construct a `Fingerprint` object directly from a protobuf.
+    *   Introduced member method `tf.saved_model.experimental.Fingerprint.singleprint()`, which provides a convenient way to uniquely identify a SavedModel.
 
 ### Bug Fixes and Other Changes
 
@@ -62,7 +62,7 @@
 *   `tf.experimental.dtensor`
 
     *   Deprecated `dtensor.run_on` in favor of `dtensor.default_mesh` to correctly indicate that the context does not override the mesh that the ops and functions will run on, it only sets a fallback default mesh.
-    *   List of members of dtensor.Layout and dtensor.Mesh have slightly changed as part of efforts to consolidate the C++ and Python source code with pybind11. Most notably, Layout.serialized_string is removed.
+    *   List of members of `dtensor.Layout` and `dtensor.Mesh` have slightly changed as part of efforts to consolidate the C++ and Python source code with pybind11. Most notably, `dtensor.Layout.serialized_string` is removed.
     *   Minor API changes to represent Single Device Layout for non-distributed Tensors inside DTensor functions. Runtime support will be added soon.
 
 *   `tf.experimental.ExtensionType`