fix!: make learning rate a one-of

docs: A few small updates
feat: Add `learning_rate_multiplier` to tuning `Hyperparameters`

PiperOrigin-RevId: 616144364

google/ai/generativelanguage/v1beta/BUILD.bazel

@@ -345,6 +345,7 @@ load(
 
 csharp_proto_library(
     name = "generativelanguage_csharp_proto",
+    extra_opts = [],
     deps = [":generativelanguage_proto"],
 )
 

google/ai/generativelanguage/v1beta/generative_service.proto

@@ -42,6 +42,10 @@ service GenerativeService {
     option (google.api.http) = {
       post: "/v1beta/{model=models/*}:generateContent"
       body: "*"
+      additional_bindings {
+        post: "/v1beta/{model=tunedModels/*}:generateContent"
+        body: "*"
+      }
     };
     option (google.api.method_signature) = "model,contents";
   }
@@ -185,18 +189,16 @@ message GenerationConfig {
 
   // Optional. The maximum number of tokens to include in a candidate.
   //
-  // If unset, this will default to output_token_limit specified in the `Model`
-  // specification.
+  // Note: The default value varies by model, see the `Model.output_token_limit`
+  // attribute of the `Model` returned from the `getModel` function.
   optional int32 max_output_tokens = 4 [(google.api.field_behavior) = OPTIONAL];
 
   // Optional. Controls the randomness of the output.
+  //
   // Note: The default value varies by model, see the `Model.temperature`
-  // attribute of the `Model` returned the `getModel` function.
+  // attribute of the `Model` returned from the `getModel` function.
   //
-  // Values can range from [0.0,1.0],
-  // inclusive. A value closer to 1.0 will produce responses that are more
-  // varied and creative, while a value closer to 0.0 will typically result in
-  // more straightforward responses from the model.
+  // Values can range from [0.0, infinity).
   optional float temperature = 5 [(google.api.field_behavior) = OPTIONAL];
 
   // Optional. The maximum cumulative probability of tokens to consider when
@@ -210,18 +212,17 @@ message GenerationConfig {
   // of tokens based on the cumulative probability.
   //
   // Note: The default value varies by model, see the `Model.top_p`
-  // attribute of the `Model` returned the `getModel` function.
+  // attribute of the `Model` returned from the `getModel` function.
   optional float top_p = 6 [(google.api.field_behavior) = OPTIONAL];
 
   // Optional. The maximum number of tokens to consider when sampling.
   //
   // The model uses combined Top-k and nucleus sampling.
   //
   // Top-k sampling considers the set of `top_k` most probable tokens.
-  // Defaults to 40.
   //
   // Note: The default value varies by model, see the `Model.top_k`
-  // attribute of the `Model` returned the `getModel` function.
+  // attribute of the `Model` returned from the `getModel` function.
   optional int32 top_k = 7 [(google.api.field_behavior) = OPTIONAL];
 }
 
@@ -457,7 +458,9 @@ message GenerateAnswerRequest {
   // overrides the default settings for each `SafetyCategory` specified in the
   // safety_settings. If there is no `SafetySetting` for a given
   // `SafetyCategory` provided in the list, the API will use the default safety
-  // setting for that category.
+  // setting for that category. Harm categories HARM_CATEGORY_HATE_SPEECH,
+  // HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
+  // HARM_CATEGORY_HARASSMENT are supported.
   repeated SafetySetting safety_settings = 3
       [(google.api.field_behavior) = OPTIONAL];
 

google/ai/generativelanguage/v1beta/safety.proto

@@ -34,10 +34,10 @@ enum HarmCategory {
   // Negative or harmful comments targeting identity and/or protected attribute.
   HARM_CATEGORY_DEROGATORY = 1;
 
-  // Content that is rude, disrepspectful, or profane.
+  // Content that is rude, disrespectful, or profane.
   HARM_CATEGORY_TOXICITY = 2;
 
-  // Describes scenarios depictng violence against an individual or group, or
+  // Describes scenarios depicting violence against an individual or group, or
   // general descriptions of gore.
   HARM_CATEGORY_VIOLENCE = 3;
 

google/ai/generativelanguage/v1beta/tuned_model.proto

@@ -174,21 +174,38 @@ message TuningTask {
   Hyperparameters hyperparameters = 5 [(google.api.field_behavior) = IMMUTABLE];
 }
 
-// Hyperparameters controlling the tuning process.
+// Hyperparameters controlling the tuning process. Read more at
+// https://ai.google.dev/docs/model_tuning_guidance
 message Hyperparameters {
+  // Options for specifying learning rate during tuning.
+  oneof learning_rate_option {
+    // Optional. Immutable. The learning rate hyperparameter for tuning.
+    // If not set, a default of 0.001 or 0.0002 will be calculated based on the
+    // number of training examples.
+    float learning_rate = 16 [
+      (google.api.field_behavior) = IMMUTABLE,
+      (google.api.field_behavior) = OPTIONAL
+    ];
+
+    // Optional. Immutable. The learning rate multiplier is used to calculate a
+    // final learning_rate based on the default (recommended) value. Actual
+    // learning rate := learning_rate_multiplier * default learning rate Default
+    // learning rate is dependent on base model and dataset size. If not set, a
+    // default of 1.0 will be used.
+    float learning_rate_multiplier = 17 [
+      (google.api.field_behavior) = IMMUTABLE,
+      (google.api.field_behavior) = OPTIONAL
+    ];
+  }
+
   // Immutable. The number of training epochs. An epoch is one pass through the
-  // training data. If not set, a default of 10 will be used.
+  // training data. If not set, a default of 5 will be used.
   optional int32 epoch_count = 14 [(google.api.field_behavior) = IMMUTABLE];
 
   // Immutable. The batch size hyperparameter for tuning.
-  // If not set, a default of 16 or 64 will be used based on the number of
+  // If not set, a default of 4 or 16 will be used based on the number of
   // training examples.
   optional int32 batch_size = 15 [(google.api.field_behavior) = IMMUTABLE];
-
-  // Immutable. The learning rate hyperparameter for tuning.
-  // If not set, a default of 0.0002 or 0.002 will be calculated based on the
-  // number of training examples.
-  optional float learning_rate = 16 [(google.api.field_behavior) = IMMUTABLE];
 }
 
 // Dataset for training or validation.