| // Copyright 2023 Google LLC |
| // |
| // Licensed under the Apache License, Version 2.0 (the "License"); |
| // you may not use this file except in compliance with the License. |
| // You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, software |
| // distributed under the License is distributed on an "AS IS" BASIS, |
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| // See the License for the specific language governing permissions and |
| // limitations under the License. |
| |
| // Code generated by protoc-gen-go. DO NOT EDIT. |
| // versions: |
| // protoc-gen-go v1.33.0 |
| // protoc v4.25.3 |
| // source: google/ai/generativelanguage/v1beta/tuned_model.proto |
| |
| package generativelanguagepb |
| |
| import ( |
| reflect "reflect" |
| sync "sync" |
| |
| _ "google.golang.org/genproto/googleapis/api/annotations" |
| protoreflect "google.golang.org/protobuf/reflect/protoreflect" |
| protoimpl "google.golang.org/protobuf/runtime/protoimpl" |
| timestamppb "google.golang.org/protobuf/types/known/timestamppb" |
| ) |
| |
| const ( |
| // Verify that this generated code is sufficiently up-to-date. |
| _ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion) |
| // Verify that runtime/protoimpl is sufficiently up-to-date. |
| _ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20) |
| ) |
| |
| // The state of the tuned model. |
| type TunedModel_State int32 |
| |
| const ( |
| // The default value. This value is unused. |
| TunedModel_STATE_UNSPECIFIED TunedModel_State = 0 |
| // The model is being created. |
| TunedModel_CREATING TunedModel_State = 1 |
| // The model is ready to be used. |
| TunedModel_ACTIVE TunedModel_State = 2 |
| // The model failed to be created. |
| TunedModel_FAILED TunedModel_State = 3 |
| ) |
| |
| // Enum value maps for TunedModel_State. |
| var ( |
| TunedModel_State_name = map[int32]string{ |
| 0: "STATE_UNSPECIFIED", |
| 1: "CREATING", |
| 2: "ACTIVE", |
| 3: "FAILED", |
| } |
| TunedModel_State_value = map[string]int32{ |
| "STATE_UNSPECIFIED": 0, |
| "CREATING": 1, |
| "ACTIVE": 2, |
| "FAILED": 3, |
| } |
| ) |
| |
| func (x TunedModel_State) Enum() *TunedModel_State { |
| p := new(TunedModel_State) |
| *p = x |
| return p |
| } |
| |
| func (x TunedModel_State) String() string { |
| return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x)) |
| } |
| |
| func (TunedModel_State) Descriptor() protoreflect.EnumDescriptor { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_enumTypes[0].Descriptor() |
| } |
| |
| func (TunedModel_State) Type() protoreflect.EnumType { |
| return &file_google_ai_generativelanguage_v1beta_tuned_model_proto_enumTypes[0] |
| } |
| |
| func (x TunedModel_State) Number() protoreflect.EnumNumber { |
| return protoreflect.EnumNumber(x) |
| } |
| |
| // Deprecated: Use TunedModel_State.Descriptor instead. |
| func (TunedModel_State) EnumDescriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{0, 0} |
| } |
| |
| // A fine-tuned model created using ModelService.CreateTunedModel. |
| type TunedModel struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // The model used as the starting point for tuning. |
| // |
| // Types that are assignable to SourceModel: |
| // |
| // *TunedModel_TunedModelSource |
| // *TunedModel_BaseModel |
| SourceModel isTunedModel_SourceModel `protobuf_oneof:"source_model"` |
| // Output only. The tuned model name. A unique name will be generated on |
| // create. Example: `tunedModels/az2mb0bpw6i` If display_name is set on |
| // create, the id portion of the name will be set by concatenating the words |
| // of the display_name with hyphens and adding a random portion for |
| // uniqueness. Example: |
| // |
| // display_name = "Sentence Translator" |
| // name = "tunedModels/sentence-translator-u3b7m" |
| Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"` |
| // Optional. The name to display for this model in user interfaces. |
| // The display name must be up to 40 characters including spaces. |
| DisplayName string `protobuf:"bytes,5,opt,name=display_name,json=displayName,proto3" json:"display_name,omitempty"` |
| // Optional. A short description of this model. |
| Description string `protobuf:"bytes,6,opt,name=description,proto3" json:"description,omitempty"` |
| // Optional. Controls the randomness of the output. |
| // |
| // Values can range over `[0.0,1.0]`, inclusive. A value closer to `1.0` will |
| // produce responses that are more varied, while a value closer to `0.0` will |
| // typically result in less surprising responses from the model. |
| // |
| // This value specifies default to be the one used by the base model while |
| // creating the model. |
| Temperature *float32 `protobuf:"fixed32,11,opt,name=temperature,proto3,oneof" json:"temperature,omitempty"` |
| // Optional. For Nucleus sampling. |
| // |
| // Nucleus sampling considers the smallest set of tokens whose probability |
| // sum is at least `top_p`. |
| // |
| // This value specifies default to be the one used by the base model while |
| // creating the model. |
| TopP *float32 `protobuf:"fixed32,12,opt,name=top_p,json=topP,proto3,oneof" json:"top_p,omitempty"` |
| // Optional. For Top-k sampling. |
| // |
| // Top-k sampling considers the set of `top_k` most probable tokens. |
| // This value specifies default to be used by the backend while making the |
| // call to the model. |
| // |
| // This value specifies default to be the one used by the base model while |
| // creating the model. |
| TopK *int32 `protobuf:"varint,13,opt,name=top_k,json=topK,proto3,oneof" json:"top_k,omitempty"` |
| // Output only. The state of the tuned model. |
| State TunedModel_State `protobuf:"varint,7,opt,name=state,proto3,enum=google.ai.generativelanguage.v1beta.TunedModel_State" json:"state,omitempty"` |
| // Output only. The timestamp when this model was created. |
| CreateTime *timestamppb.Timestamp `protobuf:"bytes,8,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"` |
| // Output only. The timestamp when this model was updated. |
| UpdateTime *timestamppb.Timestamp `protobuf:"bytes,9,opt,name=update_time,json=updateTime,proto3" json:"update_time,omitempty"` |
| // Required. The tuning task that creates the tuned model. |
| TuningTask *TuningTask `protobuf:"bytes,10,opt,name=tuning_task,json=tuningTask,proto3" json:"tuning_task,omitempty"` |
| } |
| |
| func (x *TunedModel) Reset() { |
| *x = TunedModel{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[0] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *TunedModel) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*TunedModel) ProtoMessage() {} |
| |
| func (x *TunedModel) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[0] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use TunedModel.ProtoReflect.Descriptor instead. |
| func (*TunedModel) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{0} |
| } |
| |
| func (m *TunedModel) GetSourceModel() isTunedModel_SourceModel { |
| if m != nil { |
| return m.SourceModel |
| } |
| return nil |
| } |
| |
| func (x *TunedModel) GetTunedModelSource() *TunedModelSource { |
| if x, ok := x.GetSourceModel().(*TunedModel_TunedModelSource); ok { |
| return x.TunedModelSource |
| } |
| return nil |
| } |
| |
| func (x *TunedModel) GetBaseModel() string { |
| if x, ok := x.GetSourceModel().(*TunedModel_BaseModel); ok { |
| return x.BaseModel |
| } |
| return "" |
| } |
| |
| func (x *TunedModel) GetName() string { |
| if x != nil { |
| return x.Name |
| } |
| return "" |
| } |
| |
| func (x *TunedModel) GetDisplayName() string { |
| if x != nil { |
| return x.DisplayName |
| } |
| return "" |
| } |
| |
| func (x *TunedModel) GetDescription() string { |
| if x != nil { |
| return x.Description |
| } |
| return "" |
| } |
| |
| func (x *TunedModel) GetTemperature() float32 { |
| if x != nil && x.Temperature != nil { |
| return *x.Temperature |
| } |
| return 0 |
| } |
| |
| func (x *TunedModel) GetTopP() float32 { |
| if x != nil && x.TopP != nil { |
| return *x.TopP |
| } |
| return 0 |
| } |
| |
| func (x *TunedModel) GetTopK() int32 { |
| if x != nil && x.TopK != nil { |
| return *x.TopK |
| } |
| return 0 |
| } |
| |
| func (x *TunedModel) GetState() TunedModel_State { |
| if x != nil { |
| return x.State |
| } |
| return TunedModel_STATE_UNSPECIFIED |
| } |
| |
| func (x *TunedModel) GetCreateTime() *timestamppb.Timestamp { |
| if x != nil { |
| return x.CreateTime |
| } |
| return nil |
| } |
| |
| func (x *TunedModel) GetUpdateTime() *timestamppb.Timestamp { |
| if x != nil { |
| return x.UpdateTime |
| } |
| return nil |
| } |
| |
| func (x *TunedModel) GetTuningTask() *TuningTask { |
| if x != nil { |
| return x.TuningTask |
| } |
| return nil |
| } |
| |
| type isTunedModel_SourceModel interface { |
| isTunedModel_SourceModel() |
| } |
| |
| type TunedModel_TunedModelSource struct { |
| // Optional. TunedModel to use as the starting point for training the new |
| // model. |
| TunedModelSource *TunedModelSource `protobuf:"bytes,3,opt,name=tuned_model_source,json=tunedModelSource,proto3,oneof"` |
| } |
| |
| type TunedModel_BaseModel struct { |
| // Immutable. The name of the `Model` to tune. |
| // Example: `models/text-bison-001` |
| BaseModel string `protobuf:"bytes,4,opt,name=base_model,json=baseModel,proto3,oneof"` |
| } |
| |
| func (*TunedModel_TunedModelSource) isTunedModel_SourceModel() {} |
| |
| func (*TunedModel_BaseModel) isTunedModel_SourceModel() {} |
| |
| // Tuned model as a source for training a new model. |
| type TunedModelSource struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Immutable. The name of the `TunedModel` to use as the starting point for |
| // training the new model. |
| // Example: `tunedModels/my-tuned-model` |
| TunedModel string `protobuf:"bytes,1,opt,name=tuned_model,json=tunedModel,proto3" json:"tuned_model,omitempty"` |
| // Output only. The name of the base `Model` this `TunedModel` was tuned from. |
| // Example: `models/text-bison-001` |
| BaseModel string `protobuf:"bytes,2,opt,name=base_model,json=baseModel,proto3" json:"base_model,omitempty"` |
| } |
| |
| func (x *TunedModelSource) Reset() { |
| *x = TunedModelSource{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[1] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *TunedModelSource) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*TunedModelSource) ProtoMessage() {} |
| |
| func (x *TunedModelSource) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[1] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use TunedModelSource.ProtoReflect.Descriptor instead. |
| func (*TunedModelSource) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{1} |
| } |
| |
| func (x *TunedModelSource) GetTunedModel() string { |
| if x != nil { |
| return x.TunedModel |
| } |
| return "" |
| } |
| |
| func (x *TunedModelSource) GetBaseModel() string { |
| if x != nil { |
| return x.BaseModel |
| } |
| return "" |
| } |
| |
| // Tuning tasks that create tuned models. |
| type TuningTask struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Output only. The timestamp when tuning this model started. |
| StartTime *timestamppb.Timestamp `protobuf:"bytes,1,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"` |
| // Output only. The timestamp when tuning this model completed. |
| CompleteTime *timestamppb.Timestamp `protobuf:"bytes,2,opt,name=complete_time,json=completeTime,proto3" json:"complete_time,omitempty"` |
| // Output only. Metrics collected during tuning. |
| Snapshots []*TuningSnapshot `protobuf:"bytes,3,rep,name=snapshots,proto3" json:"snapshots,omitempty"` |
| // Required. Input only. Immutable. The model training data. |
| TrainingData *Dataset `protobuf:"bytes,4,opt,name=training_data,json=trainingData,proto3" json:"training_data,omitempty"` |
| // Immutable. Hyperparameters controlling the tuning process. If not provided, |
| // default values will be used. |
| Hyperparameters *Hyperparameters `protobuf:"bytes,5,opt,name=hyperparameters,proto3" json:"hyperparameters,omitempty"` |
| } |
| |
| func (x *TuningTask) Reset() { |
| *x = TuningTask{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[2] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *TuningTask) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*TuningTask) ProtoMessage() {} |
| |
| func (x *TuningTask) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[2] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use TuningTask.ProtoReflect.Descriptor instead. |
| func (*TuningTask) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{2} |
| } |
| |
| func (x *TuningTask) GetStartTime() *timestamppb.Timestamp { |
| if x != nil { |
| return x.StartTime |
| } |
| return nil |
| } |
| |
| func (x *TuningTask) GetCompleteTime() *timestamppb.Timestamp { |
| if x != nil { |
| return x.CompleteTime |
| } |
| return nil |
| } |
| |
| func (x *TuningTask) GetSnapshots() []*TuningSnapshot { |
| if x != nil { |
| return x.Snapshots |
| } |
| return nil |
| } |
| |
| func (x *TuningTask) GetTrainingData() *Dataset { |
| if x != nil { |
| return x.TrainingData |
| } |
| return nil |
| } |
| |
| func (x *TuningTask) GetHyperparameters() *Hyperparameters { |
| if x != nil { |
| return x.Hyperparameters |
| } |
| return nil |
| } |
| |
| // Hyperparameters controlling the tuning process. Read more at |
| // https://ai.google.dev/docs/model_tuning_guidance |
| type Hyperparameters struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Options for specifying learning rate during tuning. |
| // |
| // Types that are assignable to LearningRateOption: |
| // |
| // *Hyperparameters_LearningRate |
| // *Hyperparameters_LearningRateMultiplier |
| LearningRateOption isHyperparameters_LearningRateOption `protobuf_oneof:"learning_rate_option"` |
| // Immutable. The number of training epochs. An epoch is one pass through the |
| // training data. If not set, a default of 5 will be used. |
| EpochCount *int32 `protobuf:"varint,14,opt,name=epoch_count,json=epochCount,proto3,oneof" json:"epoch_count,omitempty"` |
| // Immutable. The batch size hyperparameter for tuning. |
| // If not set, a default of 4 or 16 will be used based on the number of |
| // training examples. |
| BatchSize *int32 `protobuf:"varint,15,opt,name=batch_size,json=batchSize,proto3,oneof" json:"batch_size,omitempty"` |
| } |
| |
| func (x *Hyperparameters) Reset() { |
| *x = Hyperparameters{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[3] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *Hyperparameters) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*Hyperparameters) ProtoMessage() {} |
| |
| func (x *Hyperparameters) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[3] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use Hyperparameters.ProtoReflect.Descriptor instead. |
| func (*Hyperparameters) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{3} |
| } |
| |
| func (m *Hyperparameters) GetLearningRateOption() isHyperparameters_LearningRateOption { |
| if m != nil { |
| return m.LearningRateOption |
| } |
| return nil |
| } |
| |
| func (x *Hyperparameters) GetLearningRate() float32 { |
| if x, ok := x.GetLearningRateOption().(*Hyperparameters_LearningRate); ok { |
| return x.LearningRate |
| } |
| return 0 |
| } |
| |
| func (x *Hyperparameters) GetLearningRateMultiplier() float32 { |
| if x, ok := x.GetLearningRateOption().(*Hyperparameters_LearningRateMultiplier); ok { |
| return x.LearningRateMultiplier |
| } |
| return 0 |
| } |
| |
| func (x *Hyperparameters) GetEpochCount() int32 { |
| if x != nil && x.EpochCount != nil { |
| return *x.EpochCount |
| } |
| return 0 |
| } |
| |
| func (x *Hyperparameters) GetBatchSize() int32 { |
| if x != nil && x.BatchSize != nil { |
| return *x.BatchSize |
| } |
| return 0 |
| } |
| |
| type isHyperparameters_LearningRateOption interface { |
| isHyperparameters_LearningRateOption() |
| } |
| |
| type Hyperparameters_LearningRate struct { |
| // 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. |
| LearningRate float32 `protobuf:"fixed32,16,opt,name=learning_rate,json=learningRate,proto3,oneof"` |
| } |
| |
| type Hyperparameters_LearningRateMultiplier struct { |
| // 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. |
| LearningRateMultiplier float32 `protobuf:"fixed32,17,opt,name=learning_rate_multiplier,json=learningRateMultiplier,proto3,oneof"` |
| } |
| |
| func (*Hyperparameters_LearningRate) isHyperparameters_LearningRateOption() {} |
| |
| func (*Hyperparameters_LearningRateMultiplier) isHyperparameters_LearningRateOption() {} |
| |
| // Dataset for training or validation. |
| type Dataset struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Inline data or a reference to the data. |
| // |
| // Types that are assignable to Dataset: |
| // |
| // *Dataset_Examples |
| Dataset isDataset_Dataset `protobuf_oneof:"dataset"` |
| } |
| |
| func (x *Dataset) Reset() { |
| *x = Dataset{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[4] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *Dataset) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*Dataset) ProtoMessage() {} |
| |
| func (x *Dataset) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[4] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use Dataset.ProtoReflect.Descriptor instead. |
| func (*Dataset) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{4} |
| } |
| |
| func (m *Dataset) GetDataset() isDataset_Dataset { |
| if m != nil { |
| return m.Dataset |
| } |
| return nil |
| } |
| |
| func (x *Dataset) GetExamples() *TuningExamples { |
| if x, ok := x.GetDataset().(*Dataset_Examples); ok { |
| return x.Examples |
| } |
| return nil |
| } |
| |
| type isDataset_Dataset interface { |
| isDataset_Dataset() |
| } |
| |
| type Dataset_Examples struct { |
| // Optional. Inline examples. |
| Examples *TuningExamples `protobuf:"bytes,1,opt,name=examples,proto3,oneof"` |
| } |
| |
| func (*Dataset_Examples) isDataset_Dataset() {} |
| |
| // A set of tuning examples. Can be training or validation data. |
| type TuningExamples struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Required. The examples. Example input can be for text or discuss, but all |
| // examples in a set must be of the same type. |
| Examples []*TuningExample `protobuf:"bytes,1,rep,name=examples,proto3" json:"examples,omitempty"` |
| } |
| |
| func (x *TuningExamples) Reset() { |
| *x = TuningExamples{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[5] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *TuningExamples) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*TuningExamples) ProtoMessage() {} |
| |
| func (x *TuningExamples) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[5] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use TuningExamples.ProtoReflect.Descriptor instead. |
| func (*TuningExamples) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{5} |
| } |
| |
| func (x *TuningExamples) GetExamples() []*TuningExample { |
| if x != nil { |
| return x.Examples |
| } |
| return nil |
| } |
| |
| // A single example for tuning. |
| type TuningExample struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // The input to the model for this example. |
| // |
| // Types that are assignable to ModelInput: |
| // |
| // *TuningExample_TextInput |
| ModelInput isTuningExample_ModelInput `protobuf_oneof:"model_input"` |
| // Required. The expected model output. |
| Output string `protobuf:"bytes,3,opt,name=output,proto3" json:"output,omitempty"` |
| } |
| |
| func (x *TuningExample) Reset() { |
| *x = TuningExample{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[6] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *TuningExample) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*TuningExample) ProtoMessage() {} |
| |
| func (x *TuningExample) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[6] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use TuningExample.ProtoReflect.Descriptor instead. |
| func (*TuningExample) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{6} |
| } |
| |
| func (m *TuningExample) GetModelInput() isTuningExample_ModelInput { |
| if m != nil { |
| return m.ModelInput |
| } |
| return nil |
| } |
| |
| func (x *TuningExample) GetTextInput() string { |
| if x, ok := x.GetModelInput().(*TuningExample_TextInput); ok { |
| return x.TextInput |
| } |
| return "" |
| } |
| |
| func (x *TuningExample) GetOutput() string { |
| if x != nil { |
| return x.Output |
| } |
| return "" |
| } |
| |
| type isTuningExample_ModelInput interface { |
| isTuningExample_ModelInput() |
| } |
| |
| type TuningExample_TextInput struct { |
| // Optional. Text model input. |
| TextInput string `protobuf:"bytes,1,opt,name=text_input,json=textInput,proto3,oneof"` |
| } |
| |
| func (*TuningExample_TextInput) isTuningExample_ModelInput() {} |
| |
| // Record for a single tuning step. |
| type TuningSnapshot struct { |
| state protoimpl.MessageState |
| sizeCache protoimpl.SizeCache |
| unknownFields protoimpl.UnknownFields |
| |
| // Output only. The tuning step. |
| Step int32 `protobuf:"varint,1,opt,name=step,proto3" json:"step,omitempty"` |
| // Output only. The epoch this step was part of. |
| Epoch int32 `protobuf:"varint,2,opt,name=epoch,proto3" json:"epoch,omitempty"` |
| // Output only. The mean loss of the training examples for this step. |
| MeanLoss float32 `protobuf:"fixed32,3,opt,name=mean_loss,json=meanLoss,proto3" json:"mean_loss,omitempty"` |
| // Output only. The timestamp when this metric was computed. |
| ComputeTime *timestamppb.Timestamp `protobuf:"bytes,4,opt,name=compute_time,json=computeTime,proto3" json:"compute_time,omitempty"` |
| } |
| |
| func (x *TuningSnapshot) Reset() { |
| *x = TuningSnapshot{} |
| if protoimpl.UnsafeEnabled { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[7] |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| ms.StoreMessageInfo(mi) |
| } |
| } |
| |
| func (x *TuningSnapshot) String() string { |
| return protoimpl.X.MessageStringOf(x) |
| } |
| |
| func (*TuningSnapshot) ProtoMessage() {} |
| |
| func (x *TuningSnapshot) ProtoReflect() protoreflect.Message { |
| mi := &file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[7] |
| if protoimpl.UnsafeEnabled && x != nil { |
| ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x)) |
| if ms.LoadMessageInfo() == nil { |
| ms.StoreMessageInfo(mi) |
| } |
| return ms |
| } |
| return mi.MessageOf(x) |
| } |
| |
| // Deprecated: Use TuningSnapshot.ProtoReflect.Descriptor instead. |
| func (*TuningSnapshot) Descriptor() ([]byte, []int) { |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP(), []int{7} |
| } |
| |
| func (x *TuningSnapshot) GetStep() int32 { |
| if x != nil { |
| return x.Step |
| } |
| return 0 |
| } |
| |
| func (x *TuningSnapshot) GetEpoch() int32 { |
| if x != nil { |
| return x.Epoch |
| } |
| return 0 |
| } |
| |
| func (x *TuningSnapshot) GetMeanLoss() float32 { |
| if x != nil { |
| return x.MeanLoss |
| } |
| return 0 |
| } |
| |
| func (x *TuningSnapshot) GetComputeTime() *timestamppb.Timestamp { |
| if x != nil { |
| return x.ComputeTime |
| } |
| return nil |
| } |
| |
| var File_google_ai_generativelanguage_v1beta_tuned_model_proto protoreflect.FileDescriptor |
| |
| var file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDesc = []byte{ |
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| } |
| |
| var ( |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescOnce sync.Once |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescData = file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDesc |
| ) |
| |
| func file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescGZIP() []byte { |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescOnce.Do(func() { |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescData) |
| }) |
| return file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDescData |
| } |
| |
| var file_google_ai_generativelanguage_v1beta_tuned_model_proto_enumTypes = make([]protoimpl.EnumInfo, 1) |
| var file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes = make([]protoimpl.MessageInfo, 8) |
| var file_google_ai_generativelanguage_v1beta_tuned_model_proto_goTypes = []interface{}{ |
| (TunedModel_State)(0), // 0: google.ai.generativelanguage.v1beta.TunedModel.State |
| (*TunedModel)(nil), // 1: google.ai.generativelanguage.v1beta.TunedModel |
| (*TunedModelSource)(nil), // 2: google.ai.generativelanguage.v1beta.TunedModelSource |
| (*TuningTask)(nil), // 3: google.ai.generativelanguage.v1beta.TuningTask |
| (*Hyperparameters)(nil), // 4: google.ai.generativelanguage.v1beta.Hyperparameters |
| (*Dataset)(nil), // 5: google.ai.generativelanguage.v1beta.Dataset |
| (*TuningExamples)(nil), // 6: google.ai.generativelanguage.v1beta.TuningExamples |
| (*TuningExample)(nil), // 7: google.ai.generativelanguage.v1beta.TuningExample |
| (*TuningSnapshot)(nil), // 8: google.ai.generativelanguage.v1beta.TuningSnapshot |
| (*timestamppb.Timestamp)(nil), // 9: google.protobuf.Timestamp |
| } |
| var file_google_ai_generativelanguage_v1beta_tuned_model_proto_depIdxs = []int32{ |
| 2, // 0: google.ai.generativelanguage.v1beta.TunedModel.tuned_model_source:type_name -> google.ai.generativelanguage.v1beta.TunedModelSource |
| 0, // 1: google.ai.generativelanguage.v1beta.TunedModel.state:type_name -> google.ai.generativelanguage.v1beta.TunedModel.State |
| 9, // 2: google.ai.generativelanguage.v1beta.TunedModel.create_time:type_name -> google.protobuf.Timestamp |
| 9, // 3: google.ai.generativelanguage.v1beta.TunedModel.update_time:type_name -> google.protobuf.Timestamp |
| 3, // 4: google.ai.generativelanguage.v1beta.TunedModel.tuning_task:type_name -> google.ai.generativelanguage.v1beta.TuningTask |
| 9, // 5: google.ai.generativelanguage.v1beta.TuningTask.start_time:type_name -> google.protobuf.Timestamp |
| 9, // 6: google.ai.generativelanguage.v1beta.TuningTask.complete_time:type_name -> google.protobuf.Timestamp |
| 8, // 7: google.ai.generativelanguage.v1beta.TuningTask.snapshots:type_name -> google.ai.generativelanguage.v1beta.TuningSnapshot |
| 5, // 8: google.ai.generativelanguage.v1beta.TuningTask.training_data:type_name -> google.ai.generativelanguage.v1beta.Dataset |
| 4, // 9: google.ai.generativelanguage.v1beta.TuningTask.hyperparameters:type_name -> google.ai.generativelanguage.v1beta.Hyperparameters |
| 6, // 10: google.ai.generativelanguage.v1beta.Dataset.examples:type_name -> google.ai.generativelanguage.v1beta.TuningExamples |
| 7, // 11: google.ai.generativelanguage.v1beta.TuningExamples.examples:type_name -> google.ai.generativelanguage.v1beta.TuningExample |
| 9, // 12: google.ai.generativelanguage.v1beta.TuningSnapshot.compute_time:type_name -> google.protobuf.Timestamp |
| 13, // [13:13] is the sub-list for method output_type |
| 13, // [13:13] is the sub-list for method input_type |
| 13, // [13:13] is the sub-list for extension type_name |
| 13, // [13:13] is the sub-list for extension extendee |
| 0, // [0:13] is the sub-list for field type_name |
| } |
| |
| func init() { file_google_ai_generativelanguage_v1beta_tuned_model_proto_init() } |
| func file_google_ai_generativelanguage_v1beta_tuned_model_proto_init() { |
| if File_google_ai_generativelanguage_v1beta_tuned_model_proto != nil { |
| return |
| } |
| if !protoimpl.UnsafeEnabled { |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*TunedModel); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*TunedModelSource); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*TuningTask); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*Hyperparameters); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*Dataset); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*TuningExamples); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*TuningExample); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[7].Exporter = func(v interface{}, i int) interface{} { |
| switch v := v.(*TuningSnapshot); i { |
| case 0: |
| return &v.state |
| case 1: |
| return &v.sizeCache |
| case 2: |
| return &v.unknownFields |
| default: |
| return nil |
| } |
| } |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[0].OneofWrappers = []interface{}{ |
| (*TunedModel_TunedModelSource)(nil), |
| (*TunedModel_BaseModel)(nil), |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[3].OneofWrappers = []interface{}{ |
| (*Hyperparameters_LearningRate)(nil), |
| (*Hyperparameters_LearningRateMultiplier)(nil), |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[4].OneofWrappers = []interface{}{ |
| (*Dataset_Examples)(nil), |
| } |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes[6].OneofWrappers = []interface{}{ |
| (*TuningExample_TextInput)(nil), |
| } |
| type x struct{} |
| out := protoimpl.TypeBuilder{ |
| File: protoimpl.DescBuilder{ |
| GoPackagePath: reflect.TypeOf(x{}).PkgPath(), |
| RawDescriptor: file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDesc, |
| NumEnums: 1, |
| NumMessages: 8, |
| NumExtensions: 0, |
| NumServices: 0, |
| }, |
| GoTypes: file_google_ai_generativelanguage_v1beta_tuned_model_proto_goTypes, |
| DependencyIndexes: file_google_ai_generativelanguage_v1beta_tuned_model_proto_depIdxs, |
| EnumInfos: file_google_ai_generativelanguage_v1beta_tuned_model_proto_enumTypes, |
| MessageInfos: file_google_ai_generativelanguage_v1beta_tuned_model_proto_msgTypes, |
| }.Build() |
| File_google_ai_generativelanguage_v1beta_tuned_model_proto = out.File |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_rawDesc = nil |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_goTypes = nil |
| file_google_ai_generativelanguage_v1beta_tuned_model_proto_depIdxs = nil |
| } |