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Update TensorFlow protos to 2.1.0rc0
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tensorboard/compat/proto/config.proto

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@@ -540,6 +540,33 @@ message ConfigProto {
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// GraphDef must be passed in a single call to Session::Create(), and
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// Session::Extend() may not be supported.
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bool optimize_for_static_graph = 12;
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// Whether to enable the MLIR-based TF->XLA bridge.
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//
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// This is a replacement to the existing bridge, and not ready for
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// production usage yet.
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// If this option is set to true when a session is created, MLIR is used to
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// perform the set of graph transformations to put the graph in a form that
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// can be executed with delegation of some computations to an accelerator.
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// This builds on the model of XLA where a subset of the graph is
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// encapsulated and attached to a "compile" operation, whose result is fed
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// to an "execute" operation. The kernel for these operations is responsible
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// to lower the encapsulated graph to a particular device.
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bool enable_mlir_bridge = 13;
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// If true, the session will not store an additional copy of the graph for
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// each subgraph.
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//
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// If this option is set to true when a session is created, the
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// `RunOptions.output_partition_graphs` options must not be set.
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bool disable_output_partition_graphs = 14;
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// Minimum number of batches run through the XLA graph before XLA fusion
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// autotuner is enabled. Default value of zero disables the autotuner.
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//
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// The XLA fusion autotuner can improve performance by executing a heuristic
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// search on the compiler parameters.
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int64 xla_fusion_autotuner_thresh = 15;
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};
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Experimental experimental = 16;

tensorboard/compat/proto/event.proto

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@@ -106,9 +106,14 @@ message WatchdogConfig {
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int64 timeout_ms = 1;
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}
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message RequestedExitCode {
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int32 exit_code = 1;
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}
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message WorkerHeartbeatRequest {
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WorkerShutdownMode shutdown_mode = 1;
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WatchdogConfig watchdog_config = 2;
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RequestedExitCode exit_code = 3;
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}
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message WorkerHeartbeatResponse {

tensorboard/compat/proto/struct.proto

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syntax = "proto3";
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package tensorboard;
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import "tensorboard/compat/proto/tensor_shape.proto";
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import "tensorboard/compat/proto/types.proto";
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package tensorboard;
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// `StructuredValue` represents a dynamically typed value representing various
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// data structures that are inspired by Python data structures typically used in
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// TensorFlow functions as inputs and outputs.
@@ -120,6 +120,7 @@ message TypeSpecProto {
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DATA_ITERATOR_SPEC = 6; // IteratorSpec from data/ops/iterator_ops.py
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OPTIONAL_SPEC = 7; // tf.OptionalSpec
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PER_REPLICA_SPEC = 8; // PerReplicaSpec from distribute/values.py
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VARIABLE_SPEC = 9; // tf.VariableSpec
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}
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TypeSpecClass type_spec_class = 1;
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