Changing syntax of optimization_parameters.proto from proto2 to proto3. Since the lower and upper fields of ClippingLimits used non-zero defaults, they had to be converted to use the google.protobuf.FloatValue wrappers.

PiperOrigin-RevId: 206400787

1 files changed, 58 insertions, 56 deletions

diff --git a/tensorflow/contrib/tpu/proto/optimization_parameters.proto b/tensorflow/contrib/tpu/proto/optimization_parameters.proto
index 9150606f5e..2cc17d6d92 100644
--- a/tensorflow/contrib/tpu/proto/optimization_parameters.proto
+++ b/tensorflow/contrib/tpu/proto/optimization_parameters.proto
@@ -1,10 +1,12 @@
-syntax = "proto2";
+syntax = "proto3";
 
 package tensorflow.tpu;
 
+import "google/protobuf/wrappers.proto";
+
 message ClippingLimits {
-  optional float lower = 1 [default = -inf];
-  optional float upper = 2 [default = inf];
+  google.protobuf.FloatValue lower = 1;  // -inf if not set
+  google.protobuf.FloatValue upper = 2;  // +inf if not set
 }
 
 // Get the learning rate from a <yet to be determined> source that can change
@@ -21,18 +23,18 @@ message LearningRate {
 }
 
 message AdagradParameters {
-  optional float initial_accumulator = 1 [default = 0.];
+  float initial_accumulator = 1;
 }
 
 message StochasticGradientDescentParameters {
 }
 
 message FtrlParameters {
-  optional float l1 = 1 [default = 0.];
-  optional float l2 = 2 [default = 0.];
-  optional float lr_power = 3 [default = 0.];
-  optional float initial_accum = 4 [default = 0.];
-  optional float initial_linear = 5 [default = 0.];
+  float l1 = 1;
+  float l2 = 2;
+  float lr_power = 3;
+  float initial_accum = 4;
+  float initial_linear = 5;
 }
 
 // The Adam optimizer does not implement hyper-parameter update; use the dynamic
@@ -41,84 +43,84 @@ message FtrlParameters {
 // Here, t is the current timestep.
 // https://github.com/tensorflow/tensorflow/blob/ab51450c817674c8ff08a7ae4f8ac50cdc4bed8b/tensorflow/python/training/adam.py#L54
 message AdamParameters {
-  optional float beta1 = 3 [default = 0.];
-  optional float beta2 = 4 [default = 0.];
-  optional float epsilon = 5 [default = 0.];
-  optional float initial_m = 6 [default = 0.];
-  optional float initial_v = 7 [default = 0.];
+  float beta1 = 3;
+  float beta2 = 4;
+  float epsilon = 5;
+  float initial_m = 6;
+  float initial_v = 7;
 }
 
 message MomentumParameters {
-  optional float momentum = 1 [default = 0.];
-  optional bool use_nesterov = 2 [default = false];
-  optional float initial_accum = 3 [default = 0.];
+  float momentum = 1;
+  bool use_nesterov = 2;
+  float initial_accum = 3;
 }
 
 message RmsPropParameters {
-  optional float rho = 1 [default = 0.];
-  optional float momentum = 2 [default = 0.];
-  optional float epsilon = 3 [default = 0.];
-  optional float initial_ms = 4 [default = 0.];
-  optional float initial_mom = 5 [default = 0.];
+  float rho = 1;
+  float momentum = 2;
+  float epsilon = 3;
+  float initial_ms = 4;
+  float initial_mom = 5;
 }
 
 message CenteredRmsPropParameters {
-  optional float rho = 1 [default = 0.];
-  optional float momentum = 2 [default = 0.];
-  optional float epsilon = 3 [default = 0.];
-  optional float initial_ms = 4 [default = 0.];
-  optional float initial_mom = 5 [default = 0.];
-  optional float initial_mg = 6 [default = 0.];
+  float rho = 1;
+  float momentum = 2;
+  float epsilon = 3;
+  float initial_ms = 4;
+  float initial_mom = 5;
+  float initial_mg = 6;
 }
 
 message MdlAdagradLightParameters {
-  optional float l2 = 1;
-  optional float lr_power = 2;
-  optional float min_servable_mdl_benefit = 3;
-  optional float mdl_mix_in_margin = 4;
-  optional float mdl_benefit_rampup_coeff = 5;
-  optional float mdl_min_weight = 6;
-  optional float benefit_revisit_scale = 7;
-  optional float max_event_benefit = 8;
-  optional float max_total_benefit = 9;
-  optional float mdl_hard_limit = 10;
-  optional bool hard_limit_min_benefit = 11;
-  optional bool mdl_regularize = 12;
-  optional float initial_accumulator = 13;
-  optional float initial_weight = 14;
-  optional float initial_benefit = 15;
+  float l2 = 1;
+  float lr_power = 2;
+  float min_servable_mdl_benefit = 3;
+  float mdl_mix_in_margin = 4;
+  float mdl_benefit_rampup_coeff = 5;
+  float mdl_min_weight = 6;
+  float benefit_revisit_scale = 7;
+  float max_event_benefit = 8;
+  float max_total_benefit = 9;
+  float mdl_hard_limit = 10;
+  bool hard_limit_min_benefit = 11;
+  bool mdl_regularize = 12;
+  float initial_accumulator = 13;
+  float initial_weight = 14;
+  float initial_benefit = 15;
 }
 
 message AdadeltaParameters {
-  optional float rho = 1;
-  optional float epsilon = 2;
-  optional float initial_accumulator = 3 [default = 0.];
-  optional float initial_update = 4 [default = 0.];
+  float rho = 1;
+  float epsilon = 2;
+  float initial_accumulator = 3;
+  float initial_update = 4;
 }
 
 message ProximalAdagradParameters {
-  optional float l1 = 1;
-  optional float l2 = 2;
-  optional float initial_accumulator = 3;
+  float l1 = 1;
+  float l2 = 2;
+  float initial_accumulator = 3;
 }
 
 message OptimizationParameters {
   // Learning rate used for updating the embedding layer parameters.
-  optional LearningRate learning_rate = 13;
+  LearningRate learning_rate = 13;
   reserved 1;  // Old learning rate tag.
 
   // Limits to which to clip the weight values after the backward pass; not
   // present means no limits are applied.
-  optional ClippingLimits clipping_limits = 2;
+  ClippingLimits clipping_limits = 2;
 
   // Limits to which to clip the backward pass gradient before using it for
   // updates; not present means no limits are applied.
-  optional ClippingLimits gradient_clipping_limits = 7;
+  ClippingLimits gradient_clipping_limits = 7;
 
   // Whether to use gradient accumulation (do two passes over the input
   // gradients: one to accumulate them into a temporary array and another to
   // apply them using the actual optimization algorithm).
-  optional bool use_gradient_accumulation = 15 [default = false];
+  bool use_gradient_accumulation = 15;
 
   // Optimization algorithm parameters; which field is selected determines which
   // algorithm to use.
@@ -140,7 +142,7 @@ message OptimizationParameters {
 // value vector and any extra accumulators, etc.).
 message StateVariableSpecification {
   // Parameter name for the state variable.
-  optional string name = 1;
+  string name = 1;
 
   // A normal state variable that should be saved and restored in checkpoints
   // and used as an input or output to non-debug TensorFlow ops.
@@ -151,7 +153,7 @@ message StateVariableSpecification {
   // from users (used for intermediate gradients being accumulated, for
   // example).
   message FillWithConstant {
-    optional double initial_value = 1;
+    double initial_value = 1;
   }
 
   // Usage type of this state variable.