Update protos to match tensorflow 2.10.0rc0

tensorboard/compat/proto/config.proto

@@ -123,6 +123,12 @@ message GPUOptions {
       // created with the default. If this field has values set, then the size
       // of this must match with the above memory_limit_mb.
       repeated int32 priority = 2;
+
+      // Virtual Device ordinal number determines the device ID of the device.
+      // A Virtual device with a lower ordinal number always receives the a
+      // smaller device id. The phyiscal device id and location in the
+      // virtual device list is used to break ties.
+      repeated int32 device_ordinal = 3;
     }
 
     // The multi virtual device settings. If empty (not set), it will create
@@ -132,15 +138,30 @@ message GPUOptions {
     // "visible_device_list" filtering if it is set), and the string represented
     // device names (e.g. /device:GPU:<id>) will refer to the virtual
     // devices and have the <id> field assigned sequentially starting from 0,
-    // according to the order they appear in this list and the "memory_limit"
-    // list inside each element. For example,
+    // according to the order of the virtual devices determined by
+    // device_ordinal and the location in the virtual device list.
+    //
+    // For example,
     //   visible_device_list = "1,0"
     //   virtual_devices { memory_limit: 1GB memory_limit: 2GB }
-    //   virtual_devices {}
-    // will create three virtual devices as:
+    //   virtual_devices { memory_limit: 3GB memory_limit: 4GB }
+    // will create 4 virtual devices as:
     //   /device:GPU:0 -> visible GPU 1 with 1GB memory
     //   /device:GPU:1 -> visible GPU 1 with 2GB memory
-    //   /device:GPU:2 -> visible GPU 0 with all available memory
+    //   /device:GPU:2 -> visible GPU 0 with 3GB memory
+    //   /device:GPU:3 -> visible GPU 0 with 4GB memory
+    //
+    // but
+    //   visible_device_list = "1,0"
+    //   virtual_devices { memory_limit: 1GB memory_limit: 2GB
+    //                     device_ordinal: 10 device_ordinal: 20}
+    //   virtual_devices { memory_limit: 3GB memory_limit: 4GB
+    //                     device_ordinal: 10 device_ordinal: 20}
+    // will create 4 virtual devices as:
+    //   /device:GPU:0 -> visible GPU 1 with 1GB memory  (ordinal 10)
+    //   /device:GPU:1 -> visible GPU 0 with 3GB memory  (ordinal 10)
+    //   /device:GPU:2 -> visible GPU 1 with 2GB memory  (ordinal 20)
+    //   /device:GPU:3 -> visible GPU 0 with 4GB memory  (ordinal 20)
     //
     // NOTE:
     // 1. It's invalid to set both this and "per_process_gpu_memory_fraction"
@@ -798,6 +819,9 @@ message RunMetadata {
   // level idea of what the built graph looks like (since the various graph
   // optimization passes might change the structure of the graph significantly).
   repeated FunctionGraphs function_graphs = 4;
+
+  // Metadata about the session.
+  SessionMetadata session_metadata = 5;
 }
 
 // Defines a connection between two tensors in a `GraphDef`.

tensorboard/compat/proto/full_type.proto

@@ -174,6 +174,18 @@ enum FullTypeId {
   //   TFT_LITERAL[TFT_INT32]{1} is the compile-time constant 1.
   TFT_LITERAL = 1003;
 
+  // Encoding types describe a value of a certain type, encoded as a different
+  // type.
+  //
+  // Parametrization:
+  //   TFT_ENCODED[<encoded type>, <encoding type>]
+  //   * <encoded type> may be any type
+  //   * <encoding type> may be any type
+  //
+  // Examples:
+  //   TFT_ENCODING[TFT_INT32, TFT_STRING] is an integer encoded as string.
+  TFT_ENCODED = 1004;
+
   // Type attributes. These always appear in the parametrization of a type,
   // never alone. For example, there is no such thing as a "bool" TensorFlow
   // object (for now).
@@ -217,7 +229,7 @@ enum FullTypeId {
   // is expressed using TFT_PRODUCT.
   //
   //
-  // Parametrization: TFT_ARRAY[<element type>].
+  // Parametrization: TFT_DATASET[<element type>].
   //   * <element type> may be a concrete type or a type symbol. It represents
   //     the data type of the elements produced by the dataset.
   //
@@ -235,6 +247,15 @@ enum FullTypeId {
   // Parametrization: TFT_RAGGED[<element_type>].
   TFT_RAGGED = 10103;
 
+  // Iterators created by tf.data ops and APIs. Very similar to Datasets, except
+  // they are mutable.
+  //
+  //
+  // Parametrization: TFT_ITERATOR[<element type>].
+  //   * <element type> may be a concrete type or a type symbol. It represents
+  //     the data type of the elements produced by the dataset.
+  TFT_ITERATOR = 10104;
+
   // A mutex lock tensor, produced by tf.raw_ops.MutexLock.
   // Unlike strict execution models, where ownership of a lock is denoted by
   // "running after the lock has been acquired", in non-strict mode, lock
@@ -265,7 +286,7 @@ message FullTypeDef {
 
   repeated FullTypeDef args = 2;
 
-  // Literal values of this type object, if the the type admits one.
+  // Literal values of this type object, if the type admits one.
   // For example, a type variable admits a string attribute - its name.
   // Shape-related types may admit int attributes - their static shape values.
   // Fields for more data types to be added as needed.

tensorboard/compat/proto/meta_graph.proto

@@ -17,9 +17,6 @@ option java_multiple_files = true;
 option java_package = "org.tensorflow.framework";
 option go_package = "github.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto";
 
-// NOTE: This protocol buffer is evolving, and will go through revisions in the
-// coming months.
-//
 // Protocol buffer containing the following which are necessary to restart
 // training, run inference. It can be used to serialize/de-serialize memory
 // objects necessary for running computation in a graph when crossing the

tensorboard/compat/proto/rewriter_config.proto

@@ -107,10 +107,17 @@ message RewriterConfig {
   // Note that this can change the numerical stability of the graph and may
   // require the use of loss scaling to maintain model convergence.
   Toggle auto_mixed_precision = 23;
-  // Optimize data types for MKL (default is OFF).
+  // Optimize data types for oneDNN (default is OFF).
   // This will try to use bfloat16 on CPUs, which is faster.
   // Note that this can change the numerical stability of the graph.
+  // Note: this is deprecated.
+  // It is replaced by auto_mixed_precision_onednn_bfloat16
   Toggle auto_mixed_precision_mkl = 25;
+  // Optimize data types for oneDNN (default is OFF).
+  // This will try to use bfloat16 on CPUs, which is faster.
+  // Note that this can change the numerical stability of the graph.
+  // Note: this is equivalent to the deprecated option auto_mixed_precision_mkl
+  Toggle auto_mixed_precision_onednn_bfloat16 = 31;
   // Emulate a model using data type float16 on CPU (default is OFF).
   // This will try to emulate the float16 inputs and outputs of an operator
   // on CPU to have better correlation with float16 on GPU; however the
@@ -121,6 +128,8 @@ message RewriterConfig {
   bool disable_meta_optimizer = 19;
   // Optimizers registered by plugin (default is ON)
   Toggle use_plugin_optimizers = 28;
+  // Conditional code motion (default is ON).
+  Toggle experimental_conditional_code_motion = 30;
 
   // Controls how many times we run the optimizers in meta optimizer (default
   // is once).

tensorboard/compat/proto/types.proto

@@ -75,3 +75,8 @@ enum DataType {
 //    https://www.tensorflow.org/code/tensorboard/compat/proto/types.cc,
 //    https://www.tensorflow.org/code/tensorboard/compat/proto/dtypes.py,
 //    https://www.tensorflow.org/code/tensorboard/compat/proto/function.py)
+
+// Represents a serialized tf.dtypes.Dtype
+message SerializedDType {
+  DataType datatype = 1;
+}