ml

type CancelJobRequest struct {

	// Required. The name of the job to cancel.
	//
	// Authorization: requires `Editor` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type CreateJobRequest struct {

	// Required. The project name.
	//
	// Authorization: requires `Editor` role on the specified project.
	Parent string `protobuf:"bytes,1,opt,name=parent,proto3" json:"parent,omitempty"`
	// Required. The job to create.
	Job *Job `protobuf:"bytes,2,opt,name=job,proto3" json:"job,omitempty"`
	// contains filtered or unexported fields
}

type CreateModelRequest struct {

	// Required. The project name.
	//
	// Authorization: requires `Editor` role on the specified project.
	Parent string `protobuf:"bytes,1,opt,name=parent,proto3" json:"parent,omitempty"`
	// Required. The model to create.
	Model *Model `protobuf:"bytes,2,opt,name=model,proto3" json:"model,omitempty"`
	// contains filtered or unexported fields
}

type CreateVersionRequest struct {

	// Required. The name of the model.
	//
	// Authorization: requires `Editor` role on the parent project.
	Parent string `protobuf:"bytes,1,opt,name=parent,proto3" json:"parent,omitempty"`
	// Required. The version details.
	Version *Version `protobuf:"bytes,2,opt,name=version,proto3" json:"version,omitempty"`
	// contains filtered or unexported fields
}

type DeleteModelRequest struct {

	// Required. The name of the model.
	//
	// Authorization: requires `Editor` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type DeleteVersionRequest struct {

	// Required. The name of the version. You can get the names of all the
	// versions of a model by calling
	// [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
	//
	// Authorization: requires `Editor` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type GetConfigRequest struct {

	// Required. The project name.
	//
	// Authorization: requires `Viewer` role on the specified project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type GetConfigResponse struct {

	// The service account Cloud ML uses to access resources in the project.
	ServiceAccount string `protobuf:"bytes,1,opt,name=service_account,json=serviceAccount,proto3" json:"service_account,omitempty"`
	// The project number for `service_account`.
	ServiceAccountProject int64 `` /* 127-byte string literal not displayed */
	// contains filtered or unexported fields
}

type GetJobRequest struct {

	// Required. The name of the job to get the description of.
	//
	// Authorization: requires `Viewer` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type GetModelRequest struct {

	// Required. The name of the model.
	//
	// Authorization: requires `Viewer` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type GetVersionRequest struct {

	// Required. The name of the version.
	//
	// Authorization: requires `Viewer` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type HyperparameterOutput struct {

	// The trial id for these results.
	TrialId string `protobuf:"bytes,1,opt,name=trial_id,json=trialId,proto3" json:"trial_id,omitempty"`
	// The hyperparameters given to this trial.
	Hyperparameters map[string]string `` /* 171-byte string literal not displayed */
	// The final objective metric seen for this trial.
	FinalMetric *HyperparameterOutput_HyperparameterMetric `protobuf:"bytes,3,opt,name=final_metric,json=finalMetric,proto3" json:"final_metric,omitempty"`
	// All recorded object metrics for this trial.
	AllMetrics []*HyperparameterOutput_HyperparameterMetric `protobuf:"bytes,4,rep,name=all_metrics,json=allMetrics,proto3" json:"all_metrics,omitempty"`
	// contains filtered or unexported fields
}

type HyperparameterOutput_HyperparameterMetric struct {

	// The global training step for this metric.
	TrainingStep int64 `protobuf:"varint,1,opt,name=training_step,json=trainingStep,proto3" json:"training_step,omitempty"`
	// The objective value at this training step.
	ObjectiveValue float64 `protobuf:"fixed64,2,opt,name=objective_value,json=objectiveValue,proto3" json:"objective_value,omitempty"`
	// contains filtered or unexported fields
}

type HyperparameterSpec struct {

	// Required. The type of goal to use for tuning. Available types are
	// `MAXIMIZE` and `MINIMIZE`.
	//
	// Defaults to `MAXIMIZE`.
	Goal HyperparameterSpec_GoalType `protobuf:"varint,1,opt,name=goal,proto3,enum=google.cloud.ml.v1.HyperparameterSpec_GoalType" json:"goal,omitempty"`
	// Required. The set of parameters to tune.
	Params []*ParameterSpec `protobuf:"bytes,2,rep,name=params,proto3" json:"params,omitempty"`
	// Optional. How many training trials should be attempted to optimize
	// the specified hyperparameters.
	//
	// Defaults to one.
	MaxTrials int32 `protobuf:"varint,3,opt,name=max_trials,json=maxTrials,proto3" json:"max_trials,omitempty"`
	// Optional. The number of training trials to run concurrently.
	// You can reduce the time it takes to perform hyperparameter tuning by adding
	// trials in parallel. However, each trail only benefits from the information
	// gained in completed trials. That means that a trial does not get access to
	// the results of trials running at the same time, which could reduce the
	// quality of the overall optimization.
	//
	// Each trial will use the same scale tier and machine types.
	//
	// Defaults to one.
	MaxParallelTrials int32 `protobuf:"varint,4,opt,name=max_parallel_trials,json=maxParallelTrials,proto3" json:"max_parallel_trials,omitempty"`
	// Optional. The Tensorflow summary tag name to use for optimizing trials. For
	// current versions of Tensorflow, this tag name should exactly match what is
	// shown in Tensorboard, including all scopes.  For versions of Tensorflow
	// prior to 0.12, this should be only the tag passed to tf.Summary.
	// By default, "training/hptuning/metric" will be used.
	HyperparameterMetricTag string `` /* 132-byte string literal not displayed */
	// contains filtered or unexported fields
}

type HyperparameterSpec_GoalType int32

type Job struct {

	// Required. The user-specified id of the job.
	JobId string `protobuf:"bytes,1,opt,name=job_id,json=jobId,proto3" json:"job_id,omitempty"`
	// Required. Parameters to create a job.
	//
	// Types that are assignable to Input:
	//	*Job_TrainingInput
	//	*Job_PredictionInput
	Input isJob_Input `protobuf_oneof:"input"`
	// Output only. When the job was created.
	CreateTime *timestamppb.Timestamp `protobuf:"bytes,4,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
	// Output only. When the job processing was started.
	StartTime *timestamppb.Timestamp `protobuf:"bytes,5,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
	// Output only. When the job processing was completed.
	EndTime *timestamppb.Timestamp `protobuf:"bytes,6,opt,name=end_time,json=endTime,proto3" json:"end_time,omitempty"`
	// Output only. The detailed state of a job.
	State Job_State `protobuf:"varint,7,opt,name=state,proto3,enum=google.cloud.ml.v1.Job_State" json:"state,omitempty"`
	// Output only. The details of a failure or a cancellation.
	ErrorMessage string `protobuf:"bytes,8,opt,name=error_message,json=errorMessage,proto3" json:"error_message,omitempty"`
	// Output only. The current result of the job.
	//
	// Types that are assignable to Output:
	//	*Job_TrainingOutput
	//	*Job_PredictionOutput
	Output isJob_Output `protobuf_oneof:"output"`
	// contains filtered or unexported fields
}

type JobServiceClient interface {
	// Creates a training or a batch prediction job.
	CreateJob(ctx context.Context, in *CreateJobRequest, opts ...grpc.CallOption) (*Job, error)
	// Lists the jobs in the project.
	ListJobs(ctx context.Context, in *ListJobsRequest, opts ...grpc.CallOption) (*ListJobsResponse, error)
	// Describes a job.
	GetJob(ctx context.Context, in *GetJobRequest, opts ...grpc.CallOption) (*Job, error)
	// Cancels a running job.
	CancelJob(ctx context.Context, in *CancelJobRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
}

type JobServiceServer interface {
	// Creates a training or a batch prediction job.
	CreateJob(context.Context, *CreateJobRequest) (*Job, error)
	// Lists the jobs in the project.
	ListJobs(context.Context, *ListJobsRequest) (*ListJobsResponse, error)
	// Describes a job.
	GetJob(context.Context, *GetJobRequest) (*Job, error)
	// Cancels a running job.
	CancelJob(context.Context, *CancelJobRequest) (*emptypb.Empty, error)
}

type Job_PredictionInput struct {
	// Input parameters to create a prediction job.
	PredictionInput *PredictionInput `protobuf:"bytes,3,opt,name=prediction_input,json=predictionInput,proto3,oneof"`
}

type Job_PredictionOutput struct {
	// The current prediction job result.
	PredictionOutput *PredictionOutput `protobuf:"bytes,10,opt,name=prediction_output,json=predictionOutput,proto3,oneof"`
}

type Job_State int32

type Job_TrainingInput struct {
	// Input parameters to create a training job.
	TrainingInput *TrainingInput `protobuf:"bytes,2,opt,name=training_input,json=trainingInput,proto3,oneof"`
}

type Job_TrainingOutput struct {
	// The current training job result.
	TrainingOutput *TrainingOutput `protobuf:"bytes,9,opt,name=training_output,json=trainingOutput,proto3,oneof"`
}

type ListJobsRequest struct {

	// Required. The name of the project for which to list jobs.
	//
	// Authorization: requires `Viewer` role on the specified project.
	Parent string `protobuf:"bytes,1,opt,name=parent,proto3" json:"parent,omitempty"`
	// Optional. Specifies the subset of jobs to retrieve.
	Filter string `protobuf:"bytes,2,opt,name=filter,proto3" json:"filter,omitempty"`
	// Optional. A page token to request the next page of results.
	//
	// You get the token from the `next_page_token` field of the response from
	// the previous call.
	PageToken string `protobuf:"bytes,4,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"`
	// Optional. The number of jobs to retrieve per "page" of results. If there
	// are more remaining results than this number, the response message will
	// contain a valid value in the `next_page_token` field.
	//
	// The default value is 20, and the maximum page size is 100.
	PageSize int32 `protobuf:"varint,5,opt,name=page_size,json=pageSize,proto3" json:"page_size,omitempty"`
	// contains filtered or unexported fields
}

type ListJobsResponse struct {

	// The list of jobs.
	Jobs []*Job `protobuf:"bytes,1,rep,name=jobs,proto3" json:"jobs,omitempty"`
	// Optional. Pass this token as the `page_token` field of the request for a
	// subsequent call.
	NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"`
	// contains filtered or unexported fields
}

type ListModelsRequest struct {

	// Required. The name of the project whose models are to be listed.
	//
	// Authorization: requires `Viewer` role on the specified project.
	Parent string `protobuf:"bytes,1,opt,name=parent,proto3" json:"parent,omitempty"`
	// Optional. A page token to request the next page of results.
	//
	// You get the token from the `next_page_token` field of the response from
	// the previous call.
	PageToken string `protobuf:"bytes,4,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"`
	// Optional. The number of models to retrieve per "page" of results. If there
	// are more remaining results than this number, the response message will
	// contain a valid value in the `next_page_token` field.
	//
	// The default value is 20, and the maximum page size is 100.
	PageSize int32 `protobuf:"varint,5,opt,name=page_size,json=pageSize,proto3" json:"page_size,omitempty"`
	// contains filtered or unexported fields
}

type ListModelsResponse struct {

	// The list of models.
	Models []*Model `protobuf:"bytes,1,rep,name=models,proto3" json:"models,omitempty"`
	// Optional. Pass this token as the `page_token` field of the request for a
	// subsequent call.
	NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"`
	// contains filtered or unexported fields
}

type ListVersionsRequest struct {

	// Required. The name of the model for which to list the version.
	//
	// Authorization: requires `Viewer` role on the parent project.
	Parent string `protobuf:"bytes,1,opt,name=parent,proto3" json:"parent,omitempty"`
	// Optional. A page token to request the next page of results.
	//
	// You get the token from the `next_page_token` field of the response from
	// the previous call.
	PageToken string `protobuf:"bytes,4,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"`
	// Optional. The number of versions to retrieve per "page" of results. If
	// there are more remaining results than this number, the response message
	// will contain a valid value in the `next_page_token` field.
	//
	// The default value is 20, and the maximum page size is 100.
	PageSize int32 `protobuf:"varint,5,opt,name=page_size,json=pageSize,proto3" json:"page_size,omitempty"`
	// contains filtered or unexported fields
}

type ListVersionsResponse struct {

	// The list of versions.
	Versions []*Version `protobuf:"bytes,1,rep,name=versions,proto3" json:"versions,omitempty"`
	// Optional. Pass this token as the `page_token` field of the request for a
	// subsequent call.
	NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"`
	// contains filtered or unexported fields
}

type ManualScaling struct {

	// The number of nodes to allocate for this model. These nodes are always up,
	// starting from the time the model is deployed, so the cost of operating
	// this model will be proportional to nodes * number of hours since
	// deployment.
	Nodes int32 `protobuf:"varint,1,opt,name=nodes,proto3" json:"nodes,omitempty"`
	// contains filtered or unexported fields
}

type Model struct {

	// Required. The name specified for the model when it was created.
	//
	// The model name must be unique within the project it is created in.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// Optional. The description specified for the model when it was created.
	Description string `protobuf:"bytes,2,opt,name=description,proto3" json:"description,omitempty"`
	// Output only. The default version of the model. This version will be used to
	// handle prediction requests that do not specify a version.
	//
	// You can change the default version by calling
	// [projects.methods.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
	DefaultVersion *Version `protobuf:"bytes,3,opt,name=default_version,json=defaultVersion,proto3" json:"default_version,omitempty"`
	// Optional. The list of regions where the model is going to be deployed.
	// Currently only one region per model is supported.
	// Defaults to 'us-central1' if nothing is set.
	Regions []string `protobuf:"bytes,4,rep,name=regions,proto3" json:"regions,omitempty"`
	// Optional. If true, enables StackDriver Logging for online prediction.
	// Default is false.
	OnlinePredictionLogging bool `` /* 133-byte string literal not displayed */
	// contains filtered or unexported fields
}

type ModelServiceClient interface {
	// Creates a model which will later contain one or more versions.
	//
	// You must add at least one version before you can request predictions from
	// the model. Add versions by calling
	// [projects.models.versions.create](/ml/reference/rest/v1/projects.models.versions/create).
	CreateModel(ctx context.Context, in *CreateModelRequest, opts ...grpc.CallOption) (*Model, error)
	// Lists the models in a project.
	//
	// Each project can contain multiple models, and each model can have multiple
	// versions.
	ListModels(ctx context.Context, in *ListModelsRequest, opts ...grpc.CallOption) (*ListModelsResponse, error)
	// Gets information about a model, including its name, the description (if
	// set), and the default version (if at least one version of the model has
	// been deployed).
	GetModel(ctx context.Context, in *GetModelRequest, opts ...grpc.CallOption) (*Model, error)
	// Deletes a model.
	//
	// You can only delete a model if there are no versions in it. You can delete
	// versions by calling
	// [projects.models.versions.delete](/ml/reference/rest/v1/projects.models.versions/delete).
	DeleteModel(ctx context.Context, in *DeleteModelRequest, opts ...grpc.CallOption) (*longrunning.Operation, error)
	// Creates a new version of a model from a trained TensorFlow model.
	//
	// If the version created in the cloud by this call is the first deployed
	// version of the specified model, it will be made the default version of the
	// model. When you add a version to a model that already has one or more
	// versions, the default version does not automatically change. If you want a
	// new version to be the default, you must call
	// [projects.models.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
	CreateVersion(ctx context.Context, in *CreateVersionRequest, opts ...grpc.CallOption) (*longrunning.Operation, error)
	// Gets basic information about all the versions of a model.
	//
	// If you expect that a model has a lot of versions, or if you need to handle
	// only a limited number of results at a time, you can request that the list
	// be retrieved in batches (called pages):
	ListVersions(ctx context.Context, in *ListVersionsRequest, opts ...grpc.CallOption) (*ListVersionsResponse, error)
	// Gets information about a model version.
	//
	// Models can have multiple versions. You can call
	// [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list)
	// to get the same information that this method returns for all of the
	// versions of a model.
	GetVersion(ctx context.Context, in *GetVersionRequest, opts ...grpc.CallOption) (*Version, error)
	// Deletes a model version.
	//
	// Each model can have multiple versions deployed and in use at any given
	// time. Use this method to remove a single version.
	//
	// Note: You cannot delete the version that is set as the default version
	// of the model unless it is the only remaining version.
	DeleteVersion(ctx context.Context, in *DeleteVersionRequest, opts ...grpc.CallOption) (*longrunning.Operation, error)
	// Designates a version to be the default for the model.
	//
	// The default version is used for prediction requests made against the model
	// that don't specify a version.
	//
	// The first version to be created for a model is automatically set as the
	// default. You must make any subsequent changes to the default version
	// setting manually using this method.
	SetDefaultVersion(ctx context.Context, in *SetDefaultVersionRequest, opts ...grpc.CallOption) (*Version, error)
}

type ModelServiceServer interface {
	// Creates a model which will later contain one or more versions.
	//
	// You must add at least one version before you can request predictions from
	// the model. Add versions by calling
	// [projects.models.versions.create](/ml/reference/rest/v1/projects.models.versions/create).
	CreateModel(context.Context, *CreateModelRequest) (*Model, error)
	// Lists the models in a project.
	//
	// Each project can contain multiple models, and each model can have multiple
	// versions.
	ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error)
	// Gets information about a model, including its name, the description (if
	// set), and the default version (if at least one version of the model has
	// been deployed).
	GetModel(context.Context, *GetModelRequest) (*Model, error)
	// Deletes a model.
	//
	// You can only delete a model if there are no versions in it. You can delete
	// versions by calling
	// [projects.models.versions.delete](/ml/reference/rest/v1/projects.models.versions/delete).
	DeleteModel(context.Context, *DeleteModelRequest) (*longrunning.Operation, error)
	// Creates a new version of a model from a trained TensorFlow model.
	//
	// If the version created in the cloud by this call is the first deployed
	// version of the specified model, it will be made the default version of the
	// model. When you add a version to a model that already has one or more
	// versions, the default version does not automatically change. If you want a
	// new version to be the default, you must call
	// [projects.models.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
	CreateVersion(context.Context, *CreateVersionRequest) (*longrunning.Operation, error)
	// Gets basic information about all the versions of a model.
	//
	// If you expect that a model has a lot of versions, or if you need to handle
	// only a limited number of results at a time, you can request that the list
	// be retrieved in batches (called pages):
	ListVersions(context.Context, *ListVersionsRequest) (*ListVersionsResponse, error)
	// Gets information about a model version.
	//
	// Models can have multiple versions. You can call
	// [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list)
	// to get the same information that this method returns for all of the
	// versions of a model.
	GetVersion(context.Context, *GetVersionRequest) (*Version, error)
	// Deletes a model version.
	//
	// Each model can have multiple versions deployed and in use at any given
	// time. Use this method to remove a single version.
	//
	// Note: You cannot delete the version that is set as the default version
	// of the model unless it is the only remaining version.
	DeleteVersion(context.Context, *DeleteVersionRequest) (*longrunning.Operation, error)
	// Designates a version to be the default for the model.
	//
	// The default version is used for prediction requests made against the model
	// that don't specify a version.
	//
	// The first version to be created for a model is automatically set as the
	// default. You must make any subsequent changes to the default version
	// setting manually using this method.
	SetDefaultVersion(context.Context, *SetDefaultVersionRequest) (*Version, error)
}

type OnlinePredictionServiceClient interface {
	// Performs prediction on the data in the request.
	//
	// **** REMOVE FROM GENERATED DOCUMENTATION
	Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*httpbody.HttpBody, error)
}

type OnlinePredictionServiceServer interface {
	// Performs prediction on the data in the request.
	//
	// **** REMOVE FROM GENERATED DOCUMENTATION
	Predict(context.Context, *PredictRequest) (*httpbody.HttpBody, error)
}

type OperationMetadata struct {

	// The time the operation was submitted.
	CreateTime *timestamppb.Timestamp `protobuf:"bytes,1,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
	// The time operation processing started.
	StartTime *timestamppb.Timestamp `protobuf:"bytes,2,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
	// The time operation processing completed.
	EndTime *timestamppb.Timestamp `protobuf:"bytes,3,opt,name=end_time,json=endTime,proto3" json:"end_time,omitempty"`
	// Indicates whether a request to cancel this operation has been made.
	IsCancellationRequested bool `` /* 133-byte string literal not displayed */
	// The operation type.
	OperationType OperationMetadata_OperationType `` /* 157-byte string literal not displayed */
	// Contains the name of the model associated with the operation.
	ModelName string `protobuf:"bytes,6,opt,name=model_name,json=modelName,proto3" json:"model_name,omitempty"`
	// Contains the version associated with the operation.
	Version *Version `protobuf:"bytes,7,opt,name=version,proto3" json:"version,omitempty"`
	// contains filtered or unexported fields
}

type OperationMetadata_OperationType int32

type ParameterSpec struct {

	// Required. The parameter name must be unique amongst all ParameterConfigs in
	// a HyperparameterSpec message. E.g., "learning_rate".
	ParameterName string `protobuf:"bytes,1,opt,name=parameter_name,json=parameterName,proto3" json:"parameter_name,omitempty"`
	// Required. The type of the parameter.
	Type ParameterSpec_ParameterType `protobuf:"varint,4,opt,name=type,proto3,enum=google.cloud.ml.v1.ParameterSpec_ParameterType" json:"type,omitempty"`
	// Required if type is `DOUBLE` or `INTEGER`. This field
	// should be unset if type is `CATEGORICAL`. This value should be integers if
	// type is INTEGER.
	MinValue float64 `protobuf:"fixed64,2,opt,name=min_value,json=minValue,proto3" json:"min_value,omitempty"`
	// Required if typeis `DOUBLE` or `INTEGER`. This field
	// should be unset if type is `CATEGORICAL`. This value should be integers if
	// type is `INTEGER`.
	MaxValue float64 `protobuf:"fixed64,3,opt,name=max_value,json=maxValue,proto3" json:"max_value,omitempty"`
	// Required if type is `CATEGORICAL`. The list of possible categories.
	CategoricalValues []string `protobuf:"bytes,5,rep,name=categorical_values,json=categoricalValues,proto3" json:"categorical_values,omitempty"`
	// Required if type is `DISCRETE`.
	// A list of feasible points.
	// The list should be in strictly increasing order. For instance, this
	// parameter might have possible settings of 1.5, 2.5, and 4.0. This list
	// should not contain more than 1,000 values.
	DiscreteValues []float64 `protobuf:"fixed64,6,rep,packed,name=discrete_values,json=discreteValues,proto3" json:"discrete_values,omitempty"`
	// Optional. How the parameter should be scaled to the hypercube.
	// Leave unset for categorical parameters.
	// Some kind of scaling is strongly recommended for real or integral
	// parameters (e.g., `UNIT_LINEAR_SCALE`).
	ScaleType ParameterSpec_ScaleType `` /* 137-byte string literal not displayed */
	// contains filtered or unexported fields
}

type ParameterSpec_ParameterType int32

type ParameterSpec_ScaleType int32

type PredictRequest struct {

	// Required. The resource name of a model or a version.
	//
	// Authorization: requires `Viewer` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	//
	// Required. The prediction request body.
	HttpBody *httpbody.HttpBody `protobuf:"bytes,2,opt,name=http_body,json=httpBody,proto3" json:"http_body,omitempty"`
	// contains filtered or unexported fields
}

type PredictionInput struct {

	// Required. The model or the version to use for prediction.
	//
	// Types that are assignable to ModelVersion:
	//	*PredictionInput_ModelName
	//	*PredictionInput_VersionName
	//	*PredictionInput_Uri
	ModelVersion isPredictionInput_ModelVersion `protobuf_oneof:"model_version"`
	// Required. The format of the input data files.
	DataFormat PredictionInput_DataFormat `` /* 143-byte string literal not displayed */
	// Required. The Google Cloud Storage location of the input data files.
	// May contain wildcards.
	InputPaths []string `protobuf:"bytes,4,rep,name=input_paths,json=inputPaths,proto3" json:"input_paths,omitempty"`
	// Required. The output Google Cloud Storage location.
	OutputPath string `protobuf:"bytes,5,opt,name=output_path,json=outputPath,proto3" json:"output_path,omitempty"`
	// Optional. The maximum number of workers to be used for parallel processing.
	// Defaults to 10 if not specified.
	MaxWorkerCount int64 `protobuf:"varint,6,opt,name=max_worker_count,json=maxWorkerCount,proto3" json:"max_worker_count,omitempty"`
	// Required. The Google Compute Engine region to run the prediction job in.
	Region string `protobuf:"bytes,7,opt,name=region,proto3" json:"region,omitempty"`
	// Optional. The Google Cloud ML runtime version to use for this batch
	// prediction. If not set, Google Cloud ML will pick the runtime version used
	// during the CreateVersion request for this model version, or choose the
	// latest stable version when model version information is not available
	// such as when the model is specified by uri.
	RuntimeVersion string `protobuf:"bytes,8,opt,name=runtime_version,json=runtimeVersion,proto3" json:"runtime_version,omitempty"`
	// contains filtered or unexported fields
}

type PredictionInput_DataFormat int32

type PredictionInput_ModelName struct {
	// Use this field if you want to use the default version for the specified
	// model. The string must use the following format:
	//
	// `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
	ModelName string `protobuf:"bytes,1,opt,name=model_name,json=modelName,proto3,oneof"`
}

type PredictionInput_Uri struct {
	// Use this field if you want to specify a Google Cloud Storage path for
	// the model to use.
	Uri string `protobuf:"bytes,9,opt,name=uri,proto3,oneof"`
}

type PredictionInput_VersionName struct {
	// Use this field if you want to specify a version of the model to use. The
	// string is formatted the same way as `model_version`, with the addition
	// of the version information:
	//
	// `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
	VersionName string `protobuf:"bytes,2,opt,name=version_name,json=versionName,proto3,oneof"`
}

type PredictionOutput struct {

	// The output Google Cloud Storage location provided at the job creation time.
	OutputPath string `protobuf:"bytes,1,opt,name=output_path,json=outputPath,proto3" json:"output_path,omitempty"`
	// The number of generated predictions.
	PredictionCount int64 `protobuf:"varint,2,opt,name=prediction_count,json=predictionCount,proto3" json:"prediction_count,omitempty"`
	// The number of data instances which resulted in errors.
	ErrorCount int64 `protobuf:"varint,3,opt,name=error_count,json=errorCount,proto3" json:"error_count,omitempty"`
	// Node hours used by the batch prediction job.
	NodeHours float64 `protobuf:"fixed64,4,opt,name=node_hours,json=nodeHours,proto3" json:"node_hours,omitempty"`
	// contains filtered or unexported fields
}

type ProjectManagementServiceClient interface {
	// Get the service account information associated with your project. You need
	// this information in order to grant the service account persmissions for
	// the Google Cloud Storage location where you put your model training code
	// for training the model with Google Cloud Machine Learning.
	GetConfig(ctx context.Context, in *GetConfigRequest, opts ...grpc.CallOption) (*GetConfigResponse, error)
}

type ProjectManagementServiceServer interface {
	// Get the service account information associated with your project. You need
	// this information in order to grant the service account persmissions for
	// the Google Cloud Storage location where you put your model training code
	// for training the model with Google Cloud Machine Learning.
	GetConfig(context.Context, *GetConfigRequest) (*GetConfigResponse, error)
}

type SetDefaultVersionRequest struct {

	// Required. The name of the version to make the default for the model. You
	// can get the names of all the versions of a model by calling
	// [projects.models.versions.list](/ml/reference/rest/v1/projects.models.versions/list).
	//
	// Authorization: requires `Editor` role on the parent project.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// contains filtered or unexported fields
}

type TrainingInput struct {

	// Required. Specifies the machine types, the number of replicas for workers
	// and parameter servers.
	ScaleTier TrainingInput_ScaleTier `` /* 137-byte string literal not displayed */
	// Optional. Specifies the type of virtual machine to use for your training
	// job's master worker.
	//
	// The following types are supported:
	//
	// <dl>
	//   <dt>standard</dt>
	//   <dd>
	//   A basic machine configuration suitable for training simple models with
	//   small to moderate datasets.
	//   </dd>
	//   <dt>large_model</dt>
	//   <dd>
	//   A machine with a lot of memory, specially suited for parameter servers
	//   when your model is large (having many hidden layers or layers with very
	//   large numbers of nodes).
	//   </dd>
	//   <dt>complex_model_s</dt>
	//   <dd>
	//   A machine suitable for the master and workers of the cluster when your
	//   model requires more computation than the standard machine can handle
	//   satisfactorily.
	//   </dd>
	//   <dt>complex_model_m</dt>
	//   <dd>
	//   A machine with roughly twice the number of cores and roughly double the
	//   memory of <code suppresswarning="true">complex_model_s</code>.
	//   </dd>
	//   <dt>complex_model_l</dt>
	//   <dd>
	//   A machine with roughly twice the number of cores and roughly double the
	//   memory of <code suppresswarning="true">complex_model_m</code>.
	//   </dd>
	//   <dt>standard_gpu</dt>
	//   <dd>
	//   A machine equivalent to <code suppresswarning="true">standard</code> that
	//   also includes a
	//   <a href="ml/docs/how-tos/using-gpus">
	//   GPU that you can use in your trainer</a>.
	//   </dd>
	//   <dt>complex_model_m_gpu</dt>
	//   <dd>
	//   A machine equivalent to
	//   <code suppresswarning="true">coplex_model_m</code> that also includes
	//   four GPUs.
	//   </dd>
	// </dl>
	//
	// You must set this value when `scaleTier` is set to `CUSTOM`.
	MasterType string `protobuf:"bytes,2,opt,name=master_type,json=masterType,proto3" json:"master_type,omitempty"`
	// Optional. Specifies the type of virtual machine to use for your training
	// job's worker nodes.
	//
	// The supported values are the same as those described in the entry for
	// `masterType`.
	//
	// This value must be present when `scaleTier` is set to `CUSTOM` and
	// `workerCount` is greater than zero.
	WorkerType string `protobuf:"bytes,3,opt,name=worker_type,json=workerType,proto3" json:"worker_type,omitempty"`
	// Optional. Specifies the type of virtual machine to use for your training
	// job's parameter server.
	//
	// The supported values are the same as those described in the entry for
	// `master_type`.
	//
	// This value must be present when `scaleTier` is set to `CUSTOM` and
	// `parameter_server_count` is greater than zero.
	ParameterServerType string `protobuf:"bytes,4,opt,name=parameter_server_type,json=parameterServerType,proto3" json:"parameter_server_type,omitempty"`
	// Optional. The number of worker replicas to use for the training job. Each
	// replica in the cluster will be of the type specified in `worker_type`.
	//
	// This value can only be used when `scale_tier` is set to `CUSTOM`. If you
	// set this value, you must also set `worker_type`.
	WorkerCount int64 `protobuf:"varint,5,opt,name=worker_count,json=workerCount,proto3" json:"worker_count,omitempty"`
	// Optional. The number of parameter server replicas to use for the training
	// job. Each replica in the cluster will be of the type specified in
	// `parameter_server_type`.
	//
	// This value can only be used when `scale_tier` is set to `CUSTOM`.If you
	// set this value, you must also set `parameter_server_type`.
	ParameterServerCount int64 `protobuf:"varint,6,opt,name=parameter_server_count,json=parameterServerCount,proto3" json:"parameter_server_count,omitempty"`
	// Required. The Google Cloud Storage location of the packages with
	// the training program and any additional dependencies.
	PackageUris []string `protobuf:"bytes,7,rep,name=package_uris,json=packageUris,proto3" json:"package_uris,omitempty"`
	// Required. The Python module name to run after installing the packages.
	PythonModule string `protobuf:"bytes,8,opt,name=python_module,json=pythonModule,proto3" json:"python_module,omitempty"`
	// Optional. Command line arguments to pass to the program.
	Args []string `protobuf:"bytes,10,rep,name=args,proto3" json:"args,omitempty"`
	// Optional. The set of Hyperparameters to tune.
	Hyperparameters *HyperparameterSpec `protobuf:"bytes,12,opt,name=hyperparameters,proto3" json:"hyperparameters,omitempty"`
	// Required. The Google Compute Engine region to run the training job in.
	Region string `protobuf:"bytes,14,opt,name=region,proto3" json:"region,omitempty"`
	// Optional. A Google Cloud Storage path in which to store training outputs
	// and other data needed for training. This path is passed to your TensorFlow
	// program as the 'job_dir' command-line argument. The benefit of specifying
	// this field is that Cloud ML validates the path for use in training.
	JobDir string `protobuf:"bytes,16,opt,name=job_dir,json=jobDir,proto3" json:"job_dir,omitempty"`
	// Optional. The Google Cloud ML runtime version to use for training.  If not
	// set, Google Cloud ML will choose the latest stable version.
	RuntimeVersion string `protobuf:"bytes,15,opt,name=runtime_version,json=runtimeVersion,proto3" json:"runtime_version,omitempty"`
	// contains filtered or unexported fields
}

type TrainingInput_ScaleTier int32

type TrainingOutput struct {

	// The number of hyperparameter tuning trials that completed successfully.
	// Only set for hyperparameter tuning jobs.
	CompletedTrialCount int64 `protobuf:"varint,1,opt,name=completed_trial_count,json=completedTrialCount,proto3" json:"completed_trial_count,omitempty"`
	// Results for individual Hyperparameter trials.
	// Only set for hyperparameter tuning jobs.
	Trials []*HyperparameterOutput `protobuf:"bytes,2,rep,name=trials,proto3" json:"trials,omitempty"`
	// The amount of ML units consumed by the job.
	ConsumedMlUnits float64 `protobuf:"fixed64,3,opt,name=consumed_ml_units,json=consumedMlUnits,proto3" json:"consumed_ml_units,omitempty"`
	// Whether this job is a hyperparameter tuning job.
	IsHyperparameterTuningJob bool `` /* 141-byte string literal not displayed */
	// contains filtered or unexported fields
}

type UnimplementedJobServiceServer struct {
}

type UnimplementedModelServiceServer struct {
}

type UnimplementedOnlinePredictionServiceServer struct {
}

type UnimplementedProjectManagementServiceServer struct {
}

type Version struct {

	// Required.The name specified for the version when it was created.
	//
	// The version name must be unique within the model it is created in.
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
	// Optional. The description specified for the version when it was created.
	Description string `protobuf:"bytes,2,opt,name=description,proto3" json:"description,omitempty"`
	// Output only. If true, this version will be used to handle prediction
	// requests that do not specify a version.
	//
	// You can change the default version by calling
	// [projects.methods.versions.setDefault](/ml/reference/rest/v1/projects.models.versions/setDefault).
	IsDefault bool `protobuf:"varint,3,opt,name=is_default,json=isDefault,proto3" json:"is_default,omitempty"`
	// Required. The Google Cloud Storage location of the trained model used to
	// create the version. See the
	// [overview of model deployment](/ml/docs/concepts/deployment-overview) for
	// more informaiton.
	//
	// When passing Version to
	// [projects.models.versions.create](/ml/reference/rest/v1/projects.models.versions/create)
	// the model service uses the specified location as the source of the model.
	// Once deployed, the model version is hosted by the prediction service, so
	// this location is useful only as a historical record.
	DeploymentUri string `protobuf:"bytes,4,opt,name=deployment_uri,json=deploymentUri,proto3" json:"deployment_uri,omitempty"`
	// Output only. The time the version was created.
	CreateTime *timestamppb.Timestamp `protobuf:"bytes,5,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
	// Output only. The time the version was last used for prediction.
	LastUseTime *timestamppb.Timestamp `protobuf:"bytes,6,opt,name=last_use_time,json=lastUseTime,proto3" json:"last_use_time,omitempty"`
	// Optional. The Google Cloud ML runtime version to use for this deployment.
	// If not set, Google Cloud ML will choose a version.
	RuntimeVersion string `protobuf:"bytes,8,opt,name=runtime_version,json=runtimeVersion,proto3" json:"runtime_version,omitempty"`
	// Optional. Manually select the number of nodes to use for serving the
	// model. If unset (i.e., by default), the number of nodes used to serve
	// the model automatically scales with traffic. However, care should be
	// taken to ramp up traffic according to the model's ability to scale. If
	// your model needs to handle bursts of traffic beyond it's ability to
	// scale, it is recommended you set this field appropriately.
	ManualScaling *ManualScaling `protobuf:"bytes,9,opt,name=manual_scaling,json=manualScaling,proto3" json:"manual_scaling,omitempty"`
	// contains filtered or unexported fields
}