Updates compat proto copies by running our script to sync with TF protos.

Author: arcra

tensorboard/compat/proto/BUILD

@@ -238,7 +238,6 @@ tb_proto_library(
 tb_proto_library(
     name = "summary",
     srcs = ["summary.proto"],
-    exports = [":histogram"],
     deps = [
         ":histogram",
         ":tensor",

tensorboard/compat/proto/config.proto

@@ -18,9 +18,9 @@ option java_package = "org.tensorflow.framework";
 option go_package = "github.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto";
 
 message GPUOptions {
-  // Fraction of the available GPU memory to allocate for each process.
+  // Fraction of the total GPU memory to allocate for each process.
   // 1 means to allocate all of the GPU memory, 0.5 means the process
-  // allocates up to ~50% of the available GPU memory.
+  // allocates up to ~50% of the total GPU memory.
   //
   // GPU memory is pre-allocated unless the allow_growth option is enabled.
   //
@@ -239,6 +239,19 @@ message GPUOptions {
     // hopes that another thread will free up memory in the meantime.  Setting
     // this to true disables the sleep; instead we'll OOM immediately.
     bool disallow_retry_on_allocation_failure = 12;
+
+    // Memory limit for "GPU host allocator", aka pinned memory allocator.  This
+    // can also be set via the envvar TF_GPU_HOST_MEM_LIMIT_IN_MB.
+    float gpu_host_mem_limit_in_mb = 13;
+
+    // If true, then the host allocator allocates its max memory all upfront and
+    // never grows.  This can be useful for latency-sensitive systems, because
+    // growing the GPU host memory pool can be expensive.
+    //
+    // You probably only want to use this in combination with
+    // gpu_host_mem_limit_in_mb, because the default GPU host memory limit is
+    // quite high.
+    bool gpu_host_mem_disallow_growth = 14;
   }
 
   // Everything inside experimental is subject to change and is not subject
@@ -582,7 +595,8 @@ message ConfigProto {
     // If set, this can be used by the runtime and the Ops for debugging,
     // monitoring, etc.
     //
-    // NOTE: This is currently used and propagated only by the direct session.
+    // NOTE: This is currently used and propagated only by the direct session
+    // and EagerContext.
     SessionMetadata session_metadata = 11;
 
     // If true, the session may treat the graph as being static for optimization
@@ -615,18 +629,9 @@ message ConfigProto {
       MLIR_BRIDGE_ROLLOUT_ENABLED = 1;
       // Disabling the MLIR bridge disables it for all graphs in this session.
       MLIR_BRIDGE_ROLLOUT_DISABLED = 2;
-      // Enable the MLIR bridge on a per graph basis based on an analysis of
-      // the features used in the graph. If the features used by the graph are
-      // supported by the MLIR bridge, the MLIR bridge will be used to run the
-      // graph.
-      MLIR_BRIDGE_ROLLOUT_SAFE_MODE_ENABLED = 3;
-      // Enable the MLIR bridge in a fallback mode on a per graph basis based
-      // on an analysis of the features used in the graph.
-      // Running the MLIR bridge in the fallback mode means that it is
-      // executed and it commits all the changes to the TF graph in case
-      // of success. And it does not in case of failures and let the old bridge
-      // to process the TF graph.
-      MLIR_BRIDGE_ROLLOUT_SAFE_MODE_FALLBACK_ENABLED = 4;
+      reserved 3, 4;
+      reserved "MLIR_BRIDGE_ROLLOUT_SAFE_MODE_ENABLED",
+          "MLIR_BRIDGE_ROLLOUT_SAFE_MODE_FALLBACK_ENABLED";
     }
     // Whether to enable the MLIR-based TF->XLA bridge.
     MlirBridgeRollout mlir_bridge_rollout = 17;
@@ -675,7 +680,18 @@ message ConfigProto {
     // Distributed coordination service configurations.
     CoordinationServiceConfig coordination_config = 23;
 
-    // Next: 24
+    // If true, the session will treat the graph as being non-static for
+    // optimization purposes.
+    //
+    // If this option is set to true when a session is created, the full
+    // GraphDef will be retained to enable calls to Session::Extend().
+    // Calling Extend() without setting this flag will result in errors.
+    //
+    // This option is meant to replace `optimize_for_static_graph` and it
+    // aims to negate its value.
+    bool disable_optimize_for_static_graph = 24;
+
+    // Next: 25
   }
 
   Experimental experimental = 16;

tensorboard/compat/proto/full_type.proto

@@ -186,6 +186,17 @@ enum FullTypeId {
   //   TFT_ENCODING[TFT_INT32, TFT_STRING] is an integer encoded as string.
   TFT_ENCODED = 1004;
 
+  // The type of "shape tensors" where the runtime value is the shape of
+  // some tensor(s), i.e. the output of tf.shape.
+  // Shape tensors have special, host-only placement, in contrast to
+  // TFT_TENSOR[TFT_INT32] which is the type of a normal numeric tensor
+  // with no special placement.
+  //
+  // Examples:
+  //   TFT_SHAPE_TENSOR[TFT_INT32] is the most common
+  //   TFT_SHAPE_TENSOR[TFT_INT64] is also allowed
+  TFT_SHAPE_TENSOR = 1005;
+
   // 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).

tensorboard/compat/proto/tensor.proto

@@ -83,6 +83,10 @@ message TensorProto {
 
   // DT_UINT64
   repeated uint64 uint64_val = 17 [packed = true];
+
+  // DT_FLOAT8_*, use variable-sized set of bytes
+  // (i.e. the equivalent of repeated uint8, if such a thing existed).
+  bytes float8_val = 18;
 }
 
 // Protocol buffer representing the serialization format of DT_VARIANT tensors.

tensorboard/compat/proto/tfprof_log.proto

@@ -1,11 +1,12 @@
 syntax = "proto3";
 
 package tensorboard;
-option go_package = "github.com/tensorflow/tensorflow/tensorflow/go/core/profiler/tfprof_log_go_proto";
 
 import "tensorboard/compat/proto/attr_value.proto";
 import "tensorboard/compat/proto/step_stats.proto";
 
+option go_package = "github.com/tensorflow/tensorflow/tensorflow/go/core/profiler/protos_all_go_proto";
+
 // It specifies the Python callstack that creates an op.
 message CodeDef {
   repeated Trace traces = 1;

tensorboard/compat/proto/types.proto

@@ -30,7 +30,7 @@ enum DataType {
   DT_QINT8 = 11;     // Quantized int8
   DT_QUINT8 = 12;    // Quantized uint8
   DT_QINT32 = 13;    // Quantized int32
-  DT_BFLOAT16 = 14;  // Float32 truncated to 16 bits.  Only for cast ops.
+  DT_BFLOAT16 = 14;  // Float32 truncated to 16 bits.
   DT_QINT16 = 15;    // Quantized int16
   DT_QUINT16 = 16;   // Quantized uint16
   DT_UINT16 = 17;
@@ -40,6 +40,9 @@ enum DataType {
   DT_VARIANT = 21;  // Arbitrary C++ data types
   DT_UINT32 = 22;
   DT_UINT64 = 23;
+  DT_FLOAT8_E5M2 = 24;    // 5 exponent bits, 2 mantissa bits.
+  DT_FLOAT8_E4M3FN = 25;  // 4 exponent bits, 3 mantissa bits, finite-only, with
+                          // 2 NaNs (0bS1111111).
 
   // Do not use!  These are only for parameters.  Every enum above
   // should have a corresponding value below (verified by types_test).
@@ -66,6 +69,8 @@ enum DataType {
   DT_VARIANT_REF = 121;
   DT_UINT32_REF = 122;
   DT_UINT64_REF = 123;
+  DT_FLOAT8_E5M2_REF = 124;
+  DT_FLOAT8_E4M3FN_REF = 125;
 }
 // DISABLED.ThenChange(
 //    https://www.tensorflow.org/code/tensorflow/c/tf_datatype.h,