mirror of
https://github.com/genuinetools/reg.git
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2094 lines
80 KiB
Go
2094 lines
80 KiB
Go
// Code generated by protoc-gen-go. DO NOT EDIT.
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// source: google/cloud/ml/v1/job_service.proto
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package ml // import "google.golang.org/genproto/googleapis/cloud/ml/v1"
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import proto "github.com/golang/protobuf/proto"
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import fmt "fmt"
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import math "math"
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import empty "github.com/golang/protobuf/ptypes/empty"
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import timestamp "github.com/golang/protobuf/ptypes/timestamp"
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import _ "google.golang.org/genproto/googleapis/api/annotations"
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import _ "google.golang.org/genproto/googleapis/api/serviceconfig"
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import (
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context "golang.org/x/net/context"
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grpc "google.golang.org/grpc"
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)
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// Reference imports to suppress errors if they are not otherwise used.
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var _ = proto.Marshal
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var _ = fmt.Errorf
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var _ = math.Inf
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// This is a compile-time assertion to ensure that this generated file
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// is compatible with the proto package it is being compiled against.
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// A compilation error at this line likely means your copy of the
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// proto package needs to be updated.
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const _ = proto.ProtoPackageIsVersion2 // please upgrade the proto package
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// A scale tier is an abstract representation of the resources Cloud ML
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// will allocate to a training job. When selecting a scale tier for your
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// training job, you should consider the size of your training dataset and
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// the complexity of your model. As the tiers increase, virtual machines are
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// added to handle your job, and the individual machines in the cluster
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// generally have more memory and greater processing power than they do at
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// lower tiers. The number of training units charged per hour of processing
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// increases as tiers get more advanced. Refer to the
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// [pricing guide](/ml/pricing) for more details. Note that in addition to
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// incurring costs, your use of training resources is constrained by the
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// [quota policy](/ml/quota).
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type TrainingInput_ScaleTier int32
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const (
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// A single worker instance. This tier is suitable for learning how to use
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// Cloud ML, and for experimenting with new models using small datasets.
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TrainingInput_BASIC TrainingInput_ScaleTier = 0
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// Many workers and a few parameter servers.
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TrainingInput_STANDARD_1 TrainingInput_ScaleTier = 1
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// A large number of workers with many parameter servers.
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TrainingInput_PREMIUM_1 TrainingInput_ScaleTier = 3
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// A single worker instance [with a GPU](ml/docs/how-tos/using-gpus).
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TrainingInput_BASIC_GPU TrainingInput_ScaleTier = 6
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// The CUSTOM tier is not a set tier, but rather enables you to use your
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// own cluster specification. When you use this tier, set values to
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// configure your processing cluster according to these guidelines:
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//
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// * You _must_ set `TrainingInput.masterType` to specify the type
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// of machine to use for your master node. This is the only required
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// setting.
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//
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// * You _may_ set `TrainingInput.workerCount` to specify the number of
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// workers to use. If you specify one or more workers, you _must_ also
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// set `TrainingInput.workerType` to specify the type of machine to use
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// for your worker nodes.
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//
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// * You _may_ set `TrainingInput.parameterServerCount` to specify the
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// number of parameter servers to use. If you specify one or more
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// parameter servers, you _must_ also set
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// `TrainingInput.parameterServerType` to specify the type of machine to
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// use for your parameter servers.
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//
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// Note that all of your workers must use the same machine type, which can
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// be different from your parameter server type and master type. Your
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// parameter servers must likewise use the same machine type, which can be
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// different from your worker type and master type.
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TrainingInput_CUSTOM TrainingInput_ScaleTier = 5
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)
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var TrainingInput_ScaleTier_name = map[int32]string{
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0: "BASIC",
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1: "STANDARD_1",
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3: "PREMIUM_1",
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6: "BASIC_GPU",
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5: "CUSTOM",
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}
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var TrainingInput_ScaleTier_value = map[string]int32{
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"BASIC": 0,
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"STANDARD_1": 1,
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"PREMIUM_1": 3,
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"BASIC_GPU": 6,
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"CUSTOM": 5,
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}
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func (x TrainingInput_ScaleTier) String() string {
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return proto.EnumName(TrainingInput_ScaleTier_name, int32(x))
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}
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func (TrainingInput_ScaleTier) EnumDescriptor() ([]byte, []int) {
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return fileDescriptor_job_service_fd7c04231fa00b5c, []int{0, 0}
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}
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// The available types of optimization goals.
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type HyperparameterSpec_GoalType int32
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const (
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// Goal Type will default to maximize.
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HyperparameterSpec_GOAL_TYPE_UNSPECIFIED HyperparameterSpec_GoalType = 0
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// Maximize the goal metric.
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HyperparameterSpec_MAXIMIZE HyperparameterSpec_GoalType = 1
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// Minimize the goal metric.
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HyperparameterSpec_MINIMIZE HyperparameterSpec_GoalType = 2
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)
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var HyperparameterSpec_GoalType_name = map[int32]string{
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0: "GOAL_TYPE_UNSPECIFIED",
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1: "MAXIMIZE",
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2: "MINIMIZE",
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}
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var HyperparameterSpec_GoalType_value = map[string]int32{
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"GOAL_TYPE_UNSPECIFIED": 0,
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"MAXIMIZE": 1,
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"MINIMIZE": 2,
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}
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func (x HyperparameterSpec_GoalType) String() string {
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return proto.EnumName(HyperparameterSpec_GoalType_name, int32(x))
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}
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func (HyperparameterSpec_GoalType) EnumDescriptor() ([]byte, []int) {
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return fileDescriptor_job_service_fd7c04231fa00b5c, []int{1, 0}
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}
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// The type of the parameter.
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type ParameterSpec_ParameterType int32
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const (
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// You must specify a valid type. Using this unspecified type will result in
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// an error.
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ParameterSpec_PARAMETER_TYPE_UNSPECIFIED ParameterSpec_ParameterType = 0
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// Type for real-valued parameters.
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ParameterSpec_DOUBLE ParameterSpec_ParameterType = 1
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// Type for integral parameters.
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ParameterSpec_INTEGER ParameterSpec_ParameterType = 2
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// The parameter is categorical, with a value chosen from the categories
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// field.
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ParameterSpec_CATEGORICAL ParameterSpec_ParameterType = 3
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// The parameter is real valued, with a fixed set of feasible points. If
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// `type==DISCRETE`, feasible_points must be provided, and
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// {`min_value`, `max_value`} will be ignored.
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ParameterSpec_DISCRETE ParameterSpec_ParameterType = 4
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)
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var ParameterSpec_ParameterType_name = map[int32]string{
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0: "PARAMETER_TYPE_UNSPECIFIED",
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1: "DOUBLE",
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2: "INTEGER",
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3: "CATEGORICAL",
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4: "DISCRETE",
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}
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var ParameterSpec_ParameterType_value = map[string]int32{
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"PARAMETER_TYPE_UNSPECIFIED": 0,
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"DOUBLE": 1,
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"INTEGER": 2,
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"CATEGORICAL": 3,
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"DISCRETE": 4,
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}
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func (x ParameterSpec_ParameterType) String() string {
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return proto.EnumName(ParameterSpec_ParameterType_name, int32(x))
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}
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func (ParameterSpec_ParameterType) EnumDescriptor() ([]byte, []int) {
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return fileDescriptor_job_service_fd7c04231fa00b5c, []int{2, 0}
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}
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// The type of scaling that should be applied to this parameter.
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type ParameterSpec_ScaleType int32
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const (
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// By default, no scaling is applied.
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ParameterSpec_NONE ParameterSpec_ScaleType = 0
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// Scales the feasible space to (0, 1) linearly.
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ParameterSpec_UNIT_LINEAR_SCALE ParameterSpec_ScaleType = 1
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// Scales the feasible space logarithmically to (0, 1). The entire feasible
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// space must be strictly positive.
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ParameterSpec_UNIT_LOG_SCALE ParameterSpec_ScaleType = 2
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// Scales the feasible space "reverse" logarithmically to (0, 1). The result
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// is that values close to the top of the feasible space are spread out more
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// than points near the bottom. The entire feasible space must be strictly
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// positive.
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ParameterSpec_UNIT_REVERSE_LOG_SCALE ParameterSpec_ScaleType = 3
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)
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var ParameterSpec_ScaleType_name = map[int32]string{
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0: "NONE",
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1: "UNIT_LINEAR_SCALE",
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2: "UNIT_LOG_SCALE",
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3: "UNIT_REVERSE_LOG_SCALE",
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}
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var ParameterSpec_ScaleType_value = map[string]int32{
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"NONE": 0,
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"UNIT_LINEAR_SCALE": 1,
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"UNIT_LOG_SCALE": 2,
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"UNIT_REVERSE_LOG_SCALE": 3,
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}
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func (x ParameterSpec_ScaleType) String() string {
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return proto.EnumName(ParameterSpec_ScaleType_name, int32(x))
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}
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func (ParameterSpec_ScaleType) EnumDescriptor() ([]byte, []int) {
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return fileDescriptor_job_service_fd7c04231fa00b5c, []int{2, 1}
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}
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// The format used to separate data instances in the source files.
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type PredictionInput_DataFormat int32
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const (
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// Unspecified format.
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PredictionInput_DATA_FORMAT_UNSPECIFIED PredictionInput_DataFormat = 0
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// The source file is a text file with instances separated by the
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// new-line character.
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PredictionInput_TEXT PredictionInput_DataFormat = 1
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// The source file is a TFRecord file.
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PredictionInput_TF_RECORD PredictionInput_DataFormat = 2
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// The source file is a GZIP-compressed TFRecord file.
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PredictionInput_TF_RECORD_GZIP PredictionInput_DataFormat = 3
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)
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var PredictionInput_DataFormat_name = map[int32]string{
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0: "DATA_FORMAT_UNSPECIFIED",
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1: "TEXT",
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2: "TF_RECORD",
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3: "TF_RECORD_GZIP",
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}
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var PredictionInput_DataFormat_value = map[string]int32{
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"DATA_FORMAT_UNSPECIFIED": 0,
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"TEXT": 1,
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"TF_RECORD": 2,
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"TF_RECORD_GZIP": 3,
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}
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func (x PredictionInput_DataFormat) String() string {
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return proto.EnumName(PredictionInput_DataFormat_name, int32(x))
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}
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func (PredictionInput_DataFormat) EnumDescriptor() ([]byte, []int) {
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return fileDescriptor_job_service_fd7c04231fa00b5c, []int{5, 0}
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}
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// Describes the job state.
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type Job_State int32
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const (
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// The job state is unspecified.
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Job_STATE_UNSPECIFIED Job_State = 0
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// The job has been just created and processing has not yet begun.
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Job_QUEUED Job_State = 1
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// The service is preparing to run the job.
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Job_PREPARING Job_State = 2
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// The job is in progress.
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Job_RUNNING Job_State = 3
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// The job completed successfully.
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Job_SUCCEEDED Job_State = 4
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// The job failed.
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// `error_message` should contain the details of the failure.
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Job_FAILED Job_State = 5
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// The job is being cancelled.
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// `error_message` should describe the reason for the cancellation.
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Job_CANCELLING Job_State = 6
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// The job has been cancelled.
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// `error_message` should describe the reason for the cancellation.
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Job_CANCELLED Job_State = 7
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)
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var Job_State_name = map[int32]string{
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0: "STATE_UNSPECIFIED",
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1: "QUEUED",
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2: "PREPARING",
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3: "RUNNING",
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4: "SUCCEEDED",
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5: "FAILED",
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6: "CANCELLING",
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7: "CANCELLED",
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}
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var Job_State_value = map[string]int32{
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"STATE_UNSPECIFIED": 0,
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"QUEUED": 1,
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"PREPARING": 2,
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"RUNNING": 3,
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"SUCCEEDED": 4,
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"FAILED": 5,
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"CANCELLING": 6,
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"CANCELLED": 7,
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}
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func (x Job_State) String() string {
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return proto.EnumName(Job_State_name, int32(x))
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}
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func (Job_State) EnumDescriptor() ([]byte, []int) {
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return fileDescriptor_job_service_fd7c04231fa00b5c, []int{7, 0}
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}
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// Represents input parameters for a training job.
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type TrainingInput struct {
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// Required. Specifies the machine types, the number of replicas for workers
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// and parameter servers.
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ScaleTier TrainingInput_ScaleTier `protobuf:"varint,1,opt,name=scale_tier,json=scaleTier,proto3,enum=google.cloud.ml.v1.TrainingInput_ScaleTier" json:"scale_tier,omitempty"`
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// Optional. Specifies the type of virtual machine to use for your training
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// job's master worker.
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//
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// The following types are supported:
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//
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// <dl>
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// <dt>standard</dt>
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// <dd>
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// A basic machine configuration suitable for training simple models with
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// small to moderate datasets.
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// </dd>
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// <dt>large_model</dt>
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// <dd>
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// A machine with a lot of memory, specially suited for parameter servers
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// when your model is large (having many hidden layers or layers with very
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// large numbers of nodes).
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// </dd>
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// <dt>complex_model_s</dt>
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// <dd>
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// A machine suitable for the master and workers of the cluster when your
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// model requires more computation than the standard machine can handle
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// satisfactorily.
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// </dd>
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// <dt>complex_model_m</dt>
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// <dd>
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// A machine with roughly twice the number of cores and roughly double the
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// memory of <code suppresswarning="true">complex_model_s</code>.
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// </dd>
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// <dt>complex_model_l</dt>
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// <dd>
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// A machine with roughly twice the number of cores and roughly double the
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// memory of <code suppresswarning="true">complex_model_m</code>.
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// </dd>
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// <dt>standard_gpu</dt>
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// <dd>
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// A machine equivalent to <code suppresswarning="true">standard</code> that
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// also includes a
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// <a href="ml/docs/how-tos/using-gpus">
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// GPU that you can use in your trainer</a>.
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// </dd>
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// <dt>complex_model_m_gpu</dt>
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// <dd>
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// A machine equivalent to
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// <code suppresswarning="true">coplex_model_m</code> that also includes
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// four GPUs.
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// </dd>
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// </dl>
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//
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// You must set this value when `scaleTier` is set to `CUSTOM`.
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MasterType string `protobuf:"bytes,2,opt,name=master_type,json=masterType,proto3" json:"master_type,omitempty"`
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// Optional. Specifies the type of virtual machine to use for your training
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// job's worker nodes.
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//
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// The supported values are the same as those described in the entry for
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// `masterType`.
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//
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// This value must be present when `scaleTier` is set to `CUSTOM` and
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// `workerCount` is greater than zero.
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WorkerType string `protobuf:"bytes,3,opt,name=worker_type,json=workerType,proto3" json:"worker_type,omitempty"`
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// Optional. Specifies the type of virtual machine to use for your training
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// job's parameter server.
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//
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// The supported values are the same as those described in the entry for
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// `master_type`.
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//
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// This value must be present when `scaleTier` is set to `CUSTOM` and
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// `parameter_server_count` is greater than zero.
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ParameterServerType string `protobuf:"bytes,4,opt,name=parameter_server_type,json=parameterServerType,proto3" json:"parameter_server_type,omitempty"`
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// Optional. The number of worker replicas to use for the training job. Each
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// replica in the cluster will be of the type specified in `worker_type`.
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//
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// This value can only be used when `scale_tier` is set to `CUSTOM`. If you
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// set this value, you must also set `worker_type`.
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WorkerCount int64 `protobuf:"varint,5,opt,name=worker_count,json=workerCount,proto3" json:"worker_count,omitempty"`
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// Optional. The number of parameter server replicas to use for the training
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// job. Each replica in the cluster will be of the type specified in
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// `parameter_server_type`.
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//
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// This value can only be used when `scale_tier` is set to `CUSTOM`.If you
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// set this value, you must also set `parameter_server_type`.
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ParameterServerCount int64 `protobuf:"varint,6,opt,name=parameter_server_count,json=parameterServerCount,proto3" json:"parameter_server_count,omitempty"`
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// Required. The Google Cloud Storage location of the packages with
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// the training program and any additional dependencies.
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PackageUris []string `protobuf:"bytes,7,rep,name=package_uris,json=packageUris,proto3" json:"package_uris,omitempty"`
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// Required. The Python module name to run after installing the packages.
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PythonModule string `protobuf:"bytes,8,opt,name=python_module,json=pythonModule,proto3" json:"python_module,omitempty"`
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// Optional. Command line arguments to pass to the program.
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Args []string `protobuf:"bytes,10,rep,name=args,proto3" json:"args,omitempty"`
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// Optional. The set of Hyperparameters to tune.
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Hyperparameters *HyperparameterSpec `protobuf:"bytes,12,opt,name=hyperparameters,proto3" json:"hyperparameters,omitempty"`
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// Required. The Google Compute Engine region to run the training job in.
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Region string `protobuf:"bytes,14,opt,name=region,proto3" json:"region,omitempty"`
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// Optional. A Google Cloud Storage path in which to store training outputs
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// and other data needed for training. This path is passed to your TensorFlow
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// program as the 'job_dir' command-line argument. The benefit of specifying
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// this field is that Cloud ML validates the path for use in training.
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JobDir string `protobuf:"bytes,16,opt,name=job_dir,json=jobDir,proto3" json:"job_dir,omitempty"`
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// Optional. The Google Cloud ML runtime version to use for training. If not
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// set, Google Cloud ML will choose the latest stable version.
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RuntimeVersion string `protobuf:"bytes,15,opt,name=runtime_version,json=runtimeVersion,proto3" json:"runtime_version,omitempty"`
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XXX_NoUnkeyedLiteral struct{} `json:"-"`
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XXX_unrecognized []byte `json:"-"`
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XXX_sizecache int32 `json:"-"`
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}
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func (m *TrainingInput) Reset() { *m = TrainingInput{} }
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func (m *TrainingInput) String() string { return proto.CompactTextString(m) }
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func (*TrainingInput) ProtoMessage() {}
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func (*TrainingInput) Descriptor() ([]byte, []int) {
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return fileDescriptor_job_service_fd7c04231fa00b5c, []int{0}
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}
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func (m *TrainingInput) XXX_Unmarshal(b []byte) error {
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return xxx_messageInfo_TrainingInput.Unmarshal(m, b)
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}
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func (m *TrainingInput) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
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return xxx_messageInfo_TrainingInput.Marshal(b, m, deterministic)
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}
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func (dst *TrainingInput) XXX_Merge(src proto.Message) {
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xxx_messageInfo_TrainingInput.Merge(dst, src)
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}
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func (m *TrainingInput) XXX_Size() int {
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return xxx_messageInfo_TrainingInput.Size(m)
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}
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func (m *TrainingInput) XXX_DiscardUnknown() {
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xxx_messageInfo_TrainingInput.DiscardUnknown(m)
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}
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var xxx_messageInfo_TrainingInput proto.InternalMessageInfo
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|
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func (m *TrainingInput) GetScaleTier() TrainingInput_ScaleTier {
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if m != nil {
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return m.ScaleTier
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}
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return TrainingInput_BASIC
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}
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|
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func (m *TrainingInput) GetMasterType() string {
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if m != nil {
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return m.MasterType
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}
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return ""
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}
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|
|
func (m *TrainingInput) GetWorkerType() string {
|
|
if m != nil {
|
|
return m.WorkerType
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *TrainingInput) GetParameterServerType() string {
|
|
if m != nil {
|
|
return m.ParameterServerType
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *TrainingInput) GetWorkerCount() int64 {
|
|
if m != nil {
|
|
return m.WorkerCount
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *TrainingInput) GetParameterServerCount() int64 {
|
|
if m != nil {
|
|
return m.ParameterServerCount
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *TrainingInput) GetPackageUris() []string {
|
|
if m != nil {
|
|
return m.PackageUris
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *TrainingInput) GetPythonModule() string {
|
|
if m != nil {
|
|
return m.PythonModule
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *TrainingInput) GetArgs() []string {
|
|
if m != nil {
|
|
return m.Args
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *TrainingInput) GetHyperparameters() *HyperparameterSpec {
|
|
if m != nil {
|
|
return m.Hyperparameters
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *TrainingInput) GetRegion() string {
|
|
if m != nil {
|
|
return m.Region
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *TrainingInput) GetJobDir() string {
|
|
if m != nil {
|
|
return m.JobDir
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *TrainingInput) GetRuntimeVersion() string {
|
|
if m != nil {
|
|
return m.RuntimeVersion
|
|
}
|
|
return ""
|
|
}
|
|
|
|
// Represents a set of hyperparameters to optimize.
|
|
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 `protobuf:"bytes,5,opt,name=hyperparameter_metric_tag,json=hyperparameterMetricTag,proto3" json:"hyperparameter_metric_tag,omitempty"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *HyperparameterSpec) Reset() { *m = HyperparameterSpec{} }
|
|
func (m *HyperparameterSpec) String() string { return proto.CompactTextString(m) }
|
|
func (*HyperparameterSpec) ProtoMessage() {}
|
|
func (*HyperparameterSpec) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{1}
|
|
}
|
|
func (m *HyperparameterSpec) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_HyperparameterSpec.Unmarshal(m, b)
|
|
}
|
|
func (m *HyperparameterSpec) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_HyperparameterSpec.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *HyperparameterSpec) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_HyperparameterSpec.Merge(dst, src)
|
|
}
|
|
func (m *HyperparameterSpec) XXX_Size() int {
|
|
return xxx_messageInfo_HyperparameterSpec.Size(m)
|
|
}
|
|
func (m *HyperparameterSpec) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_HyperparameterSpec.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_HyperparameterSpec proto.InternalMessageInfo
|
|
|
|
func (m *HyperparameterSpec) GetGoal() HyperparameterSpec_GoalType {
|
|
if m != nil {
|
|
return m.Goal
|
|
}
|
|
return HyperparameterSpec_GOAL_TYPE_UNSPECIFIED
|
|
}
|
|
|
|
func (m *HyperparameterSpec) GetParams() []*ParameterSpec {
|
|
if m != nil {
|
|
return m.Params
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *HyperparameterSpec) GetMaxTrials() int32 {
|
|
if m != nil {
|
|
return m.MaxTrials
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *HyperparameterSpec) GetMaxParallelTrials() int32 {
|
|
if m != nil {
|
|
return m.MaxParallelTrials
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *HyperparameterSpec) GetHyperparameterMetricTag() string {
|
|
if m != nil {
|
|
return m.HyperparameterMetricTag
|
|
}
|
|
return ""
|
|
}
|
|
|
|
// Represents a single hyperparameter to optimize.
|
|
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 `protobuf:"varint,7,opt,name=scale_type,json=scaleType,proto3,enum=google.cloud.ml.v1.ParameterSpec_ScaleType" json:"scale_type,omitempty"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *ParameterSpec) Reset() { *m = ParameterSpec{} }
|
|
func (m *ParameterSpec) String() string { return proto.CompactTextString(m) }
|
|
func (*ParameterSpec) ProtoMessage() {}
|
|
func (*ParameterSpec) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{2}
|
|
}
|
|
func (m *ParameterSpec) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_ParameterSpec.Unmarshal(m, b)
|
|
}
|
|
func (m *ParameterSpec) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_ParameterSpec.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *ParameterSpec) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_ParameterSpec.Merge(dst, src)
|
|
}
|
|
func (m *ParameterSpec) XXX_Size() int {
|
|
return xxx_messageInfo_ParameterSpec.Size(m)
|
|
}
|
|
func (m *ParameterSpec) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_ParameterSpec.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_ParameterSpec proto.InternalMessageInfo
|
|
|
|
func (m *ParameterSpec) GetParameterName() string {
|
|
if m != nil {
|
|
return m.ParameterName
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *ParameterSpec) GetType() ParameterSpec_ParameterType {
|
|
if m != nil {
|
|
return m.Type
|
|
}
|
|
return ParameterSpec_PARAMETER_TYPE_UNSPECIFIED
|
|
}
|
|
|
|
func (m *ParameterSpec) GetMinValue() float64 {
|
|
if m != nil {
|
|
return m.MinValue
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *ParameterSpec) GetMaxValue() float64 {
|
|
if m != nil {
|
|
return m.MaxValue
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *ParameterSpec) GetCategoricalValues() []string {
|
|
if m != nil {
|
|
return m.CategoricalValues
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *ParameterSpec) GetDiscreteValues() []float64 {
|
|
if m != nil {
|
|
return m.DiscreteValues
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *ParameterSpec) GetScaleType() ParameterSpec_ScaleType {
|
|
if m != nil {
|
|
return m.ScaleType
|
|
}
|
|
return ParameterSpec_NONE
|
|
}
|
|
|
|
// Represents the result of a single hyperparameter tuning trial from a
|
|
// training job. The TrainingOutput object that is returned on successful
|
|
// completion of a training job with hyperparameter tuning includes a list
|
|
// of HyperparameterOutput objects, one for each successful trial.
|
|
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 `protobuf:"bytes,2,rep,name=hyperparameters,proto3" json:"hyperparameters,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
|
|
// 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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *HyperparameterOutput) Reset() { *m = HyperparameterOutput{} }
|
|
func (m *HyperparameterOutput) String() string { return proto.CompactTextString(m) }
|
|
func (*HyperparameterOutput) ProtoMessage() {}
|
|
func (*HyperparameterOutput) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{3}
|
|
}
|
|
func (m *HyperparameterOutput) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_HyperparameterOutput.Unmarshal(m, b)
|
|
}
|
|
func (m *HyperparameterOutput) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_HyperparameterOutput.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *HyperparameterOutput) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_HyperparameterOutput.Merge(dst, src)
|
|
}
|
|
func (m *HyperparameterOutput) XXX_Size() int {
|
|
return xxx_messageInfo_HyperparameterOutput.Size(m)
|
|
}
|
|
func (m *HyperparameterOutput) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_HyperparameterOutput.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_HyperparameterOutput proto.InternalMessageInfo
|
|
|
|
func (m *HyperparameterOutput) GetTrialId() string {
|
|
if m != nil {
|
|
return m.TrialId
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *HyperparameterOutput) GetHyperparameters() map[string]string {
|
|
if m != nil {
|
|
return m.Hyperparameters
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *HyperparameterOutput) GetFinalMetric() *HyperparameterOutput_HyperparameterMetric {
|
|
if m != nil {
|
|
return m.FinalMetric
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *HyperparameterOutput) GetAllMetrics() []*HyperparameterOutput_HyperparameterMetric {
|
|
if m != nil {
|
|
return m.AllMetrics
|
|
}
|
|
return nil
|
|
}
|
|
|
|
// An observed value of a metric.
|
|
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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *HyperparameterOutput_HyperparameterMetric) Reset() {
|
|
*m = HyperparameterOutput_HyperparameterMetric{}
|
|
}
|
|
func (m *HyperparameterOutput_HyperparameterMetric) String() string { return proto.CompactTextString(m) }
|
|
func (*HyperparameterOutput_HyperparameterMetric) ProtoMessage() {}
|
|
func (*HyperparameterOutput_HyperparameterMetric) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{3, 0}
|
|
}
|
|
func (m *HyperparameterOutput_HyperparameterMetric) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_HyperparameterOutput_HyperparameterMetric.Unmarshal(m, b)
|
|
}
|
|
func (m *HyperparameterOutput_HyperparameterMetric) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_HyperparameterOutput_HyperparameterMetric.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *HyperparameterOutput_HyperparameterMetric) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_HyperparameterOutput_HyperparameterMetric.Merge(dst, src)
|
|
}
|
|
func (m *HyperparameterOutput_HyperparameterMetric) XXX_Size() int {
|
|
return xxx_messageInfo_HyperparameterOutput_HyperparameterMetric.Size(m)
|
|
}
|
|
func (m *HyperparameterOutput_HyperparameterMetric) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_HyperparameterOutput_HyperparameterMetric.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_HyperparameterOutput_HyperparameterMetric proto.InternalMessageInfo
|
|
|
|
func (m *HyperparameterOutput_HyperparameterMetric) GetTrainingStep() int64 {
|
|
if m != nil {
|
|
return m.TrainingStep
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *HyperparameterOutput_HyperparameterMetric) GetObjectiveValue() float64 {
|
|
if m != nil {
|
|
return m.ObjectiveValue
|
|
}
|
|
return 0
|
|
}
|
|
|
|
// Represents results of a training job. Output only.
|
|
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 `protobuf:"varint,4,opt,name=is_hyperparameter_tuning_job,json=isHyperparameterTuningJob,proto3" json:"is_hyperparameter_tuning_job,omitempty"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *TrainingOutput) Reset() { *m = TrainingOutput{} }
|
|
func (m *TrainingOutput) String() string { return proto.CompactTextString(m) }
|
|
func (*TrainingOutput) ProtoMessage() {}
|
|
func (*TrainingOutput) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{4}
|
|
}
|
|
func (m *TrainingOutput) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_TrainingOutput.Unmarshal(m, b)
|
|
}
|
|
func (m *TrainingOutput) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_TrainingOutput.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *TrainingOutput) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_TrainingOutput.Merge(dst, src)
|
|
}
|
|
func (m *TrainingOutput) XXX_Size() int {
|
|
return xxx_messageInfo_TrainingOutput.Size(m)
|
|
}
|
|
func (m *TrainingOutput) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_TrainingOutput.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_TrainingOutput proto.InternalMessageInfo
|
|
|
|
func (m *TrainingOutput) GetCompletedTrialCount() int64 {
|
|
if m != nil {
|
|
return m.CompletedTrialCount
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *TrainingOutput) GetTrials() []*HyperparameterOutput {
|
|
if m != nil {
|
|
return m.Trials
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *TrainingOutput) GetConsumedMlUnits() float64 {
|
|
if m != nil {
|
|
return m.ConsumedMlUnits
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *TrainingOutput) GetIsHyperparameterTuningJob() bool {
|
|
if m != nil {
|
|
return m.IsHyperparameterTuningJob
|
|
}
|
|
return false
|
|
}
|
|
|
|
// Represents input parameters for a prediction job.
|
|
type PredictionInput struct {
|
|
// Required. The model or the version to use for prediction.
|
|
//
|
|
// Types that are valid to be assigned 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 `protobuf:"varint,3,opt,name=data_format,json=dataFormat,proto3,enum=google.cloud.ml.v1.PredictionInput_DataFormat" json:"data_format,omitempty"`
|
|
// 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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *PredictionInput) Reset() { *m = PredictionInput{} }
|
|
func (m *PredictionInput) String() string { return proto.CompactTextString(m) }
|
|
func (*PredictionInput) ProtoMessage() {}
|
|
func (*PredictionInput) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{5}
|
|
}
|
|
func (m *PredictionInput) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_PredictionInput.Unmarshal(m, b)
|
|
}
|
|
func (m *PredictionInput) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_PredictionInput.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *PredictionInput) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_PredictionInput.Merge(dst, src)
|
|
}
|
|
func (m *PredictionInput) XXX_Size() int {
|
|
return xxx_messageInfo_PredictionInput.Size(m)
|
|
}
|
|
func (m *PredictionInput) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_PredictionInput.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_PredictionInput proto.InternalMessageInfo
|
|
|
|
type isPredictionInput_ModelVersion interface {
|
|
isPredictionInput_ModelVersion()
|
|
}
|
|
|
|
type PredictionInput_ModelName struct {
|
|
ModelName string `protobuf:"bytes,1,opt,name=model_name,json=modelName,proto3,oneof"`
|
|
}
|
|
type PredictionInput_VersionName struct {
|
|
VersionName string `protobuf:"bytes,2,opt,name=version_name,json=versionName,proto3,oneof"`
|
|
}
|
|
type PredictionInput_Uri struct {
|
|
Uri string `protobuf:"bytes,9,opt,name=uri,proto3,oneof"`
|
|
}
|
|
|
|
func (*PredictionInput_ModelName) isPredictionInput_ModelVersion() {}
|
|
func (*PredictionInput_VersionName) isPredictionInput_ModelVersion() {}
|
|
func (*PredictionInput_Uri) isPredictionInput_ModelVersion() {}
|
|
|
|
func (m *PredictionInput) GetModelVersion() isPredictionInput_ModelVersion {
|
|
if m != nil {
|
|
return m.ModelVersion
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *PredictionInput) GetModelName() string {
|
|
if x, ok := m.GetModelVersion().(*PredictionInput_ModelName); ok {
|
|
return x.ModelName
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *PredictionInput) GetVersionName() string {
|
|
if x, ok := m.GetModelVersion().(*PredictionInput_VersionName); ok {
|
|
return x.VersionName
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *PredictionInput) GetUri() string {
|
|
if x, ok := m.GetModelVersion().(*PredictionInput_Uri); ok {
|
|
return x.Uri
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *PredictionInput) GetDataFormat() PredictionInput_DataFormat {
|
|
if m != nil {
|
|
return m.DataFormat
|
|
}
|
|
return PredictionInput_DATA_FORMAT_UNSPECIFIED
|
|
}
|
|
|
|
func (m *PredictionInput) GetInputPaths() []string {
|
|
if m != nil {
|
|
return m.InputPaths
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *PredictionInput) GetOutputPath() string {
|
|
if m != nil {
|
|
return m.OutputPath
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *PredictionInput) GetMaxWorkerCount() int64 {
|
|
if m != nil {
|
|
return m.MaxWorkerCount
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *PredictionInput) GetRegion() string {
|
|
if m != nil {
|
|
return m.Region
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *PredictionInput) GetRuntimeVersion() string {
|
|
if m != nil {
|
|
return m.RuntimeVersion
|
|
}
|
|
return ""
|
|
}
|
|
|
|
// XXX_OneofFuncs is for the internal use of the proto package.
|
|
func (*PredictionInput) XXX_OneofFuncs() (func(msg proto.Message, b *proto.Buffer) error, func(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error), func(msg proto.Message) (n int), []interface{}) {
|
|
return _PredictionInput_OneofMarshaler, _PredictionInput_OneofUnmarshaler, _PredictionInput_OneofSizer, []interface{}{
|
|
(*PredictionInput_ModelName)(nil),
|
|
(*PredictionInput_VersionName)(nil),
|
|
(*PredictionInput_Uri)(nil),
|
|
}
|
|
}
|
|
|
|
func _PredictionInput_OneofMarshaler(msg proto.Message, b *proto.Buffer) error {
|
|
m := msg.(*PredictionInput)
|
|
// model_version
|
|
switch x := m.ModelVersion.(type) {
|
|
case *PredictionInput_ModelName:
|
|
b.EncodeVarint(1<<3 | proto.WireBytes)
|
|
b.EncodeStringBytes(x.ModelName)
|
|
case *PredictionInput_VersionName:
|
|
b.EncodeVarint(2<<3 | proto.WireBytes)
|
|
b.EncodeStringBytes(x.VersionName)
|
|
case *PredictionInput_Uri:
|
|
b.EncodeVarint(9<<3 | proto.WireBytes)
|
|
b.EncodeStringBytes(x.Uri)
|
|
case nil:
|
|
default:
|
|
return fmt.Errorf("PredictionInput.ModelVersion has unexpected type %T", x)
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func _PredictionInput_OneofUnmarshaler(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error) {
|
|
m := msg.(*PredictionInput)
|
|
switch tag {
|
|
case 1: // model_version.model_name
|
|
if wire != proto.WireBytes {
|
|
return true, proto.ErrInternalBadWireType
|
|
}
|
|
x, err := b.DecodeStringBytes()
|
|
m.ModelVersion = &PredictionInput_ModelName{x}
|
|
return true, err
|
|
case 2: // model_version.version_name
|
|
if wire != proto.WireBytes {
|
|
return true, proto.ErrInternalBadWireType
|
|
}
|
|
x, err := b.DecodeStringBytes()
|
|
m.ModelVersion = &PredictionInput_VersionName{x}
|
|
return true, err
|
|
case 9: // model_version.uri
|
|
if wire != proto.WireBytes {
|
|
return true, proto.ErrInternalBadWireType
|
|
}
|
|
x, err := b.DecodeStringBytes()
|
|
m.ModelVersion = &PredictionInput_Uri{x}
|
|
return true, err
|
|
default:
|
|
return false, nil
|
|
}
|
|
}
|
|
|
|
func _PredictionInput_OneofSizer(msg proto.Message) (n int) {
|
|
m := msg.(*PredictionInput)
|
|
// model_version
|
|
switch x := m.ModelVersion.(type) {
|
|
case *PredictionInput_ModelName:
|
|
n += 1 // tag and wire
|
|
n += proto.SizeVarint(uint64(len(x.ModelName)))
|
|
n += len(x.ModelName)
|
|
case *PredictionInput_VersionName:
|
|
n += 1 // tag and wire
|
|
n += proto.SizeVarint(uint64(len(x.VersionName)))
|
|
n += len(x.VersionName)
|
|
case *PredictionInput_Uri:
|
|
n += 1 // tag and wire
|
|
n += proto.SizeVarint(uint64(len(x.Uri)))
|
|
n += len(x.Uri)
|
|
case nil:
|
|
default:
|
|
panic(fmt.Sprintf("proto: unexpected type %T in oneof", x))
|
|
}
|
|
return n
|
|
}
|
|
|
|
// Represents results of a prediction job.
|
|
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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *PredictionOutput) Reset() { *m = PredictionOutput{} }
|
|
func (m *PredictionOutput) String() string { return proto.CompactTextString(m) }
|
|
func (*PredictionOutput) ProtoMessage() {}
|
|
func (*PredictionOutput) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{6}
|
|
}
|
|
func (m *PredictionOutput) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_PredictionOutput.Unmarshal(m, b)
|
|
}
|
|
func (m *PredictionOutput) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_PredictionOutput.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *PredictionOutput) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_PredictionOutput.Merge(dst, src)
|
|
}
|
|
func (m *PredictionOutput) XXX_Size() int {
|
|
return xxx_messageInfo_PredictionOutput.Size(m)
|
|
}
|
|
func (m *PredictionOutput) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_PredictionOutput.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_PredictionOutput proto.InternalMessageInfo
|
|
|
|
func (m *PredictionOutput) GetOutputPath() string {
|
|
if m != nil {
|
|
return m.OutputPath
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *PredictionOutput) GetPredictionCount() int64 {
|
|
if m != nil {
|
|
return m.PredictionCount
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *PredictionOutput) GetErrorCount() int64 {
|
|
if m != nil {
|
|
return m.ErrorCount
|
|
}
|
|
return 0
|
|
}
|
|
|
|
func (m *PredictionOutput) GetNodeHours() float64 {
|
|
if m != nil {
|
|
return m.NodeHours
|
|
}
|
|
return 0
|
|
}
|
|
|
|
// Represents a training or prediction job.
|
|
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 valid to be assigned to Input:
|
|
// *Job_TrainingInput
|
|
// *Job_PredictionInput
|
|
Input isJob_Input `protobuf_oneof:"input"`
|
|
// Output only. When the job was created.
|
|
CreateTime *timestamp.Timestamp `protobuf:"bytes,4,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
|
|
// Output only. When the job processing was started.
|
|
StartTime *timestamp.Timestamp `protobuf:"bytes,5,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
|
|
// Output only. When the job processing was completed.
|
|
EndTime *timestamp.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 valid to be assigned to Output:
|
|
// *Job_TrainingOutput
|
|
// *Job_PredictionOutput
|
|
Output isJob_Output `protobuf_oneof:"output"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *Job) Reset() { *m = Job{} }
|
|
func (m *Job) String() string { return proto.CompactTextString(m) }
|
|
func (*Job) ProtoMessage() {}
|
|
func (*Job) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{7}
|
|
}
|
|
func (m *Job) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_Job.Unmarshal(m, b)
|
|
}
|
|
func (m *Job) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_Job.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *Job) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_Job.Merge(dst, src)
|
|
}
|
|
func (m *Job) XXX_Size() int {
|
|
return xxx_messageInfo_Job.Size(m)
|
|
}
|
|
func (m *Job) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_Job.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_Job proto.InternalMessageInfo
|
|
|
|
type isJob_Input interface {
|
|
isJob_Input()
|
|
}
|
|
type isJob_Output interface {
|
|
isJob_Output()
|
|
}
|
|
|
|
type Job_TrainingInput struct {
|
|
TrainingInput *TrainingInput `protobuf:"bytes,2,opt,name=training_input,json=trainingInput,proto3,oneof"`
|
|
}
|
|
type Job_PredictionInput struct {
|
|
PredictionInput *PredictionInput `protobuf:"bytes,3,opt,name=prediction_input,json=predictionInput,proto3,oneof"`
|
|
}
|
|
type Job_TrainingOutput struct {
|
|
TrainingOutput *TrainingOutput `protobuf:"bytes,9,opt,name=training_output,json=trainingOutput,proto3,oneof"`
|
|
}
|
|
type Job_PredictionOutput struct {
|
|
PredictionOutput *PredictionOutput `protobuf:"bytes,10,opt,name=prediction_output,json=predictionOutput,proto3,oneof"`
|
|
}
|
|
|
|
func (*Job_TrainingInput) isJob_Input() {}
|
|
func (*Job_PredictionInput) isJob_Input() {}
|
|
func (*Job_TrainingOutput) isJob_Output() {}
|
|
func (*Job_PredictionOutput) isJob_Output() {}
|
|
|
|
func (m *Job) GetInput() isJob_Input {
|
|
if m != nil {
|
|
return m.Input
|
|
}
|
|
return nil
|
|
}
|
|
func (m *Job) GetOutput() isJob_Output {
|
|
if m != nil {
|
|
return m.Output
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *Job) GetJobId() string {
|
|
if m != nil {
|
|
return m.JobId
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *Job) GetTrainingInput() *TrainingInput {
|
|
if x, ok := m.GetInput().(*Job_TrainingInput); ok {
|
|
return x.TrainingInput
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *Job) GetPredictionInput() *PredictionInput {
|
|
if x, ok := m.GetInput().(*Job_PredictionInput); ok {
|
|
return x.PredictionInput
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *Job) GetCreateTime() *timestamp.Timestamp {
|
|
if m != nil {
|
|
return m.CreateTime
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *Job) GetStartTime() *timestamp.Timestamp {
|
|
if m != nil {
|
|
return m.StartTime
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *Job) GetEndTime() *timestamp.Timestamp {
|
|
if m != nil {
|
|
return m.EndTime
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *Job) GetState() Job_State {
|
|
if m != nil {
|
|
return m.State
|
|
}
|
|
return Job_STATE_UNSPECIFIED
|
|
}
|
|
|
|
func (m *Job) GetErrorMessage() string {
|
|
if m != nil {
|
|
return m.ErrorMessage
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *Job) GetTrainingOutput() *TrainingOutput {
|
|
if x, ok := m.GetOutput().(*Job_TrainingOutput); ok {
|
|
return x.TrainingOutput
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *Job) GetPredictionOutput() *PredictionOutput {
|
|
if x, ok := m.GetOutput().(*Job_PredictionOutput); ok {
|
|
return x.PredictionOutput
|
|
}
|
|
return nil
|
|
}
|
|
|
|
// XXX_OneofFuncs is for the internal use of the proto package.
|
|
func (*Job) XXX_OneofFuncs() (func(msg proto.Message, b *proto.Buffer) error, func(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error), func(msg proto.Message) (n int), []interface{}) {
|
|
return _Job_OneofMarshaler, _Job_OneofUnmarshaler, _Job_OneofSizer, []interface{}{
|
|
(*Job_TrainingInput)(nil),
|
|
(*Job_PredictionInput)(nil),
|
|
(*Job_TrainingOutput)(nil),
|
|
(*Job_PredictionOutput)(nil),
|
|
}
|
|
}
|
|
|
|
func _Job_OneofMarshaler(msg proto.Message, b *proto.Buffer) error {
|
|
m := msg.(*Job)
|
|
// input
|
|
switch x := m.Input.(type) {
|
|
case *Job_TrainingInput:
|
|
b.EncodeVarint(2<<3 | proto.WireBytes)
|
|
if err := b.EncodeMessage(x.TrainingInput); err != nil {
|
|
return err
|
|
}
|
|
case *Job_PredictionInput:
|
|
b.EncodeVarint(3<<3 | proto.WireBytes)
|
|
if err := b.EncodeMessage(x.PredictionInput); err != nil {
|
|
return err
|
|
}
|
|
case nil:
|
|
default:
|
|
return fmt.Errorf("Job.Input has unexpected type %T", x)
|
|
}
|
|
// output
|
|
switch x := m.Output.(type) {
|
|
case *Job_TrainingOutput:
|
|
b.EncodeVarint(9<<3 | proto.WireBytes)
|
|
if err := b.EncodeMessage(x.TrainingOutput); err != nil {
|
|
return err
|
|
}
|
|
case *Job_PredictionOutput:
|
|
b.EncodeVarint(10<<3 | proto.WireBytes)
|
|
if err := b.EncodeMessage(x.PredictionOutput); err != nil {
|
|
return err
|
|
}
|
|
case nil:
|
|
default:
|
|
return fmt.Errorf("Job.Output has unexpected type %T", x)
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func _Job_OneofUnmarshaler(msg proto.Message, tag, wire int, b *proto.Buffer) (bool, error) {
|
|
m := msg.(*Job)
|
|
switch tag {
|
|
case 2: // input.training_input
|
|
if wire != proto.WireBytes {
|
|
return true, proto.ErrInternalBadWireType
|
|
}
|
|
msg := new(TrainingInput)
|
|
err := b.DecodeMessage(msg)
|
|
m.Input = &Job_TrainingInput{msg}
|
|
return true, err
|
|
case 3: // input.prediction_input
|
|
if wire != proto.WireBytes {
|
|
return true, proto.ErrInternalBadWireType
|
|
}
|
|
msg := new(PredictionInput)
|
|
err := b.DecodeMessage(msg)
|
|
m.Input = &Job_PredictionInput{msg}
|
|
return true, err
|
|
case 9: // output.training_output
|
|
if wire != proto.WireBytes {
|
|
return true, proto.ErrInternalBadWireType
|
|
}
|
|
msg := new(TrainingOutput)
|
|
err := b.DecodeMessage(msg)
|
|
m.Output = &Job_TrainingOutput{msg}
|
|
return true, err
|
|
case 10: // output.prediction_output
|
|
if wire != proto.WireBytes {
|
|
return true, proto.ErrInternalBadWireType
|
|
}
|
|
msg := new(PredictionOutput)
|
|
err := b.DecodeMessage(msg)
|
|
m.Output = &Job_PredictionOutput{msg}
|
|
return true, err
|
|
default:
|
|
return false, nil
|
|
}
|
|
}
|
|
|
|
func _Job_OneofSizer(msg proto.Message) (n int) {
|
|
m := msg.(*Job)
|
|
// input
|
|
switch x := m.Input.(type) {
|
|
case *Job_TrainingInput:
|
|
s := proto.Size(x.TrainingInput)
|
|
n += 1 // tag and wire
|
|
n += proto.SizeVarint(uint64(s))
|
|
n += s
|
|
case *Job_PredictionInput:
|
|
s := proto.Size(x.PredictionInput)
|
|
n += 1 // tag and wire
|
|
n += proto.SizeVarint(uint64(s))
|
|
n += s
|
|
case nil:
|
|
default:
|
|
panic(fmt.Sprintf("proto: unexpected type %T in oneof", x))
|
|
}
|
|
// output
|
|
switch x := m.Output.(type) {
|
|
case *Job_TrainingOutput:
|
|
s := proto.Size(x.TrainingOutput)
|
|
n += 1 // tag and wire
|
|
n += proto.SizeVarint(uint64(s))
|
|
n += s
|
|
case *Job_PredictionOutput:
|
|
s := proto.Size(x.PredictionOutput)
|
|
n += 1 // tag and wire
|
|
n += proto.SizeVarint(uint64(s))
|
|
n += s
|
|
case nil:
|
|
default:
|
|
panic(fmt.Sprintf("proto: unexpected type %T in oneof", x))
|
|
}
|
|
return n
|
|
}
|
|
|
|
// Request message for the CreateJob method.
|
|
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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *CreateJobRequest) Reset() { *m = CreateJobRequest{} }
|
|
func (m *CreateJobRequest) String() string { return proto.CompactTextString(m) }
|
|
func (*CreateJobRequest) ProtoMessage() {}
|
|
func (*CreateJobRequest) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{8}
|
|
}
|
|
func (m *CreateJobRequest) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_CreateJobRequest.Unmarshal(m, b)
|
|
}
|
|
func (m *CreateJobRequest) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_CreateJobRequest.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *CreateJobRequest) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_CreateJobRequest.Merge(dst, src)
|
|
}
|
|
func (m *CreateJobRequest) XXX_Size() int {
|
|
return xxx_messageInfo_CreateJobRequest.Size(m)
|
|
}
|
|
func (m *CreateJobRequest) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_CreateJobRequest.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_CreateJobRequest proto.InternalMessageInfo
|
|
|
|
func (m *CreateJobRequest) GetParent() string {
|
|
if m != nil {
|
|
return m.Parent
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *CreateJobRequest) GetJob() *Job {
|
|
if m != nil {
|
|
return m.Job
|
|
}
|
|
return nil
|
|
}
|
|
|
|
// Request message for the ListJobs method.
|
|
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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *ListJobsRequest) Reset() { *m = ListJobsRequest{} }
|
|
func (m *ListJobsRequest) String() string { return proto.CompactTextString(m) }
|
|
func (*ListJobsRequest) ProtoMessage() {}
|
|
func (*ListJobsRequest) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{9}
|
|
}
|
|
func (m *ListJobsRequest) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_ListJobsRequest.Unmarshal(m, b)
|
|
}
|
|
func (m *ListJobsRequest) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_ListJobsRequest.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *ListJobsRequest) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_ListJobsRequest.Merge(dst, src)
|
|
}
|
|
func (m *ListJobsRequest) XXX_Size() int {
|
|
return xxx_messageInfo_ListJobsRequest.Size(m)
|
|
}
|
|
func (m *ListJobsRequest) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_ListJobsRequest.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_ListJobsRequest proto.InternalMessageInfo
|
|
|
|
func (m *ListJobsRequest) GetParent() string {
|
|
if m != nil {
|
|
return m.Parent
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *ListJobsRequest) GetFilter() string {
|
|
if m != nil {
|
|
return m.Filter
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *ListJobsRequest) GetPageToken() string {
|
|
if m != nil {
|
|
return m.PageToken
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func (m *ListJobsRequest) GetPageSize() int32 {
|
|
if m != nil {
|
|
return m.PageSize
|
|
}
|
|
return 0
|
|
}
|
|
|
|
// Response message for the ListJobs method.
|
|
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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *ListJobsResponse) Reset() { *m = ListJobsResponse{} }
|
|
func (m *ListJobsResponse) String() string { return proto.CompactTextString(m) }
|
|
func (*ListJobsResponse) ProtoMessage() {}
|
|
func (*ListJobsResponse) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{10}
|
|
}
|
|
func (m *ListJobsResponse) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_ListJobsResponse.Unmarshal(m, b)
|
|
}
|
|
func (m *ListJobsResponse) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_ListJobsResponse.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *ListJobsResponse) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_ListJobsResponse.Merge(dst, src)
|
|
}
|
|
func (m *ListJobsResponse) XXX_Size() int {
|
|
return xxx_messageInfo_ListJobsResponse.Size(m)
|
|
}
|
|
func (m *ListJobsResponse) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_ListJobsResponse.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_ListJobsResponse proto.InternalMessageInfo
|
|
|
|
func (m *ListJobsResponse) GetJobs() []*Job {
|
|
if m != nil {
|
|
return m.Jobs
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func (m *ListJobsResponse) GetNextPageToken() string {
|
|
if m != nil {
|
|
return m.NextPageToken
|
|
}
|
|
return ""
|
|
}
|
|
|
|
// Request message for the GetJob method.
|
|
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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *GetJobRequest) Reset() { *m = GetJobRequest{} }
|
|
func (m *GetJobRequest) String() string { return proto.CompactTextString(m) }
|
|
func (*GetJobRequest) ProtoMessage() {}
|
|
func (*GetJobRequest) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{11}
|
|
}
|
|
func (m *GetJobRequest) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_GetJobRequest.Unmarshal(m, b)
|
|
}
|
|
func (m *GetJobRequest) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_GetJobRequest.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *GetJobRequest) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_GetJobRequest.Merge(dst, src)
|
|
}
|
|
func (m *GetJobRequest) XXX_Size() int {
|
|
return xxx_messageInfo_GetJobRequest.Size(m)
|
|
}
|
|
func (m *GetJobRequest) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_GetJobRequest.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_GetJobRequest proto.InternalMessageInfo
|
|
|
|
func (m *GetJobRequest) GetName() string {
|
|
if m != nil {
|
|
return m.Name
|
|
}
|
|
return ""
|
|
}
|
|
|
|
// Request message for the CancelJob method.
|
|
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"`
|
|
XXX_NoUnkeyedLiteral struct{} `json:"-"`
|
|
XXX_unrecognized []byte `json:"-"`
|
|
XXX_sizecache int32 `json:"-"`
|
|
}
|
|
|
|
func (m *CancelJobRequest) Reset() { *m = CancelJobRequest{} }
|
|
func (m *CancelJobRequest) String() string { return proto.CompactTextString(m) }
|
|
func (*CancelJobRequest) ProtoMessage() {}
|
|
func (*CancelJobRequest) Descriptor() ([]byte, []int) {
|
|
return fileDescriptor_job_service_fd7c04231fa00b5c, []int{12}
|
|
}
|
|
func (m *CancelJobRequest) XXX_Unmarshal(b []byte) error {
|
|
return xxx_messageInfo_CancelJobRequest.Unmarshal(m, b)
|
|
}
|
|
func (m *CancelJobRequest) XXX_Marshal(b []byte, deterministic bool) ([]byte, error) {
|
|
return xxx_messageInfo_CancelJobRequest.Marshal(b, m, deterministic)
|
|
}
|
|
func (dst *CancelJobRequest) XXX_Merge(src proto.Message) {
|
|
xxx_messageInfo_CancelJobRequest.Merge(dst, src)
|
|
}
|
|
func (m *CancelJobRequest) XXX_Size() int {
|
|
return xxx_messageInfo_CancelJobRequest.Size(m)
|
|
}
|
|
func (m *CancelJobRequest) XXX_DiscardUnknown() {
|
|
xxx_messageInfo_CancelJobRequest.DiscardUnknown(m)
|
|
}
|
|
|
|
var xxx_messageInfo_CancelJobRequest proto.InternalMessageInfo
|
|
|
|
func (m *CancelJobRequest) GetName() string {
|
|
if m != nil {
|
|
return m.Name
|
|
}
|
|
return ""
|
|
}
|
|
|
|
func init() {
|
|
proto.RegisterType((*TrainingInput)(nil), "google.cloud.ml.v1.TrainingInput")
|
|
proto.RegisterType((*HyperparameterSpec)(nil), "google.cloud.ml.v1.HyperparameterSpec")
|
|
proto.RegisterType((*ParameterSpec)(nil), "google.cloud.ml.v1.ParameterSpec")
|
|
proto.RegisterType((*HyperparameterOutput)(nil), "google.cloud.ml.v1.HyperparameterOutput")
|
|
proto.RegisterMapType((map[string]string)(nil), "google.cloud.ml.v1.HyperparameterOutput.HyperparametersEntry")
|
|
proto.RegisterType((*HyperparameterOutput_HyperparameterMetric)(nil), "google.cloud.ml.v1.HyperparameterOutput.HyperparameterMetric")
|
|
proto.RegisterType((*TrainingOutput)(nil), "google.cloud.ml.v1.TrainingOutput")
|
|
proto.RegisterType((*PredictionInput)(nil), "google.cloud.ml.v1.PredictionInput")
|
|
proto.RegisterType((*PredictionOutput)(nil), "google.cloud.ml.v1.PredictionOutput")
|
|
proto.RegisterType((*Job)(nil), "google.cloud.ml.v1.Job")
|
|
proto.RegisterType((*CreateJobRequest)(nil), "google.cloud.ml.v1.CreateJobRequest")
|
|
proto.RegisterType((*ListJobsRequest)(nil), "google.cloud.ml.v1.ListJobsRequest")
|
|
proto.RegisterType((*ListJobsResponse)(nil), "google.cloud.ml.v1.ListJobsResponse")
|
|
proto.RegisterType((*GetJobRequest)(nil), "google.cloud.ml.v1.GetJobRequest")
|
|
proto.RegisterType((*CancelJobRequest)(nil), "google.cloud.ml.v1.CancelJobRequest")
|
|
proto.RegisterEnum("google.cloud.ml.v1.TrainingInput_ScaleTier", TrainingInput_ScaleTier_name, TrainingInput_ScaleTier_value)
|
|
proto.RegisterEnum("google.cloud.ml.v1.HyperparameterSpec_GoalType", HyperparameterSpec_GoalType_name, HyperparameterSpec_GoalType_value)
|
|
proto.RegisterEnum("google.cloud.ml.v1.ParameterSpec_ParameterType", ParameterSpec_ParameterType_name, ParameterSpec_ParameterType_value)
|
|
proto.RegisterEnum("google.cloud.ml.v1.ParameterSpec_ScaleType", ParameterSpec_ScaleType_name, ParameterSpec_ScaleType_value)
|
|
proto.RegisterEnum("google.cloud.ml.v1.PredictionInput_DataFormat", PredictionInput_DataFormat_name, PredictionInput_DataFormat_value)
|
|
proto.RegisterEnum("google.cloud.ml.v1.Job_State", Job_State_name, Job_State_value)
|
|
}
|
|
|
|
// Reference imports to suppress errors if they are not otherwise used.
|
|
var _ context.Context
|
|
var _ grpc.ClientConn
|
|
|
|
// This is a compile-time assertion to ensure that this generated file
|
|
// is compatible with the grpc package it is being compiled against.
|
|
const _ = grpc.SupportPackageIsVersion4
|
|
|
|
// JobServiceClient is the client API for JobService service.
|
|
//
|
|
// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
|
|
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) (*empty.Empty, error)
|
|
}
|
|
|
|
type jobServiceClient struct {
|
|
cc *grpc.ClientConn
|
|
}
|
|
|
|
func NewJobServiceClient(cc *grpc.ClientConn) JobServiceClient {
|
|
return &jobServiceClient{cc}
|
|
}
|
|
|
|
func (c *jobServiceClient) CreateJob(ctx context.Context, in *CreateJobRequest, opts ...grpc.CallOption) (*Job, error) {
|
|
out := new(Job)
|
|
err := c.cc.Invoke(ctx, "/google.cloud.ml.v1.JobService/CreateJob", in, out, opts...)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return out, nil
|
|
}
|
|
|
|
func (c *jobServiceClient) ListJobs(ctx context.Context, in *ListJobsRequest, opts ...grpc.CallOption) (*ListJobsResponse, error) {
|
|
out := new(ListJobsResponse)
|
|
err := c.cc.Invoke(ctx, "/google.cloud.ml.v1.JobService/ListJobs", in, out, opts...)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return out, nil
|
|
}
|
|
|
|
func (c *jobServiceClient) GetJob(ctx context.Context, in *GetJobRequest, opts ...grpc.CallOption) (*Job, error) {
|
|
out := new(Job)
|
|
err := c.cc.Invoke(ctx, "/google.cloud.ml.v1.JobService/GetJob", in, out, opts...)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return out, nil
|
|
}
|
|
|
|
func (c *jobServiceClient) CancelJob(ctx context.Context, in *CancelJobRequest, opts ...grpc.CallOption) (*empty.Empty, error) {
|
|
out := new(empty.Empty)
|
|
err := c.cc.Invoke(ctx, "/google.cloud.ml.v1.JobService/CancelJob", in, out, opts...)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return out, nil
|
|
}
|
|
|
|
// JobServiceServer is the server API for JobService service.
|
|
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) (*empty.Empty, error)
|
|
}
|
|
|
|
func RegisterJobServiceServer(s *grpc.Server, srv JobServiceServer) {
|
|
s.RegisterService(&_JobService_serviceDesc, srv)
|
|
}
|
|
|
|
func _JobService_CreateJob_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
|
|
in := new(CreateJobRequest)
|
|
if err := dec(in); err != nil {
|
|
return nil, err
|
|
}
|
|
if interceptor == nil {
|
|
return srv.(JobServiceServer).CreateJob(ctx, in)
|
|
}
|
|
info := &grpc.UnaryServerInfo{
|
|
Server: srv,
|
|
FullMethod: "/google.cloud.ml.v1.JobService/CreateJob",
|
|
}
|
|
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
|
|
return srv.(JobServiceServer).CreateJob(ctx, req.(*CreateJobRequest))
|
|
}
|
|
return interceptor(ctx, in, info, handler)
|
|
}
|
|
|
|
func _JobService_ListJobs_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
|
|
in := new(ListJobsRequest)
|
|
if err := dec(in); err != nil {
|
|
return nil, err
|
|
}
|
|
if interceptor == nil {
|
|
return srv.(JobServiceServer).ListJobs(ctx, in)
|
|
}
|
|
info := &grpc.UnaryServerInfo{
|
|
Server: srv,
|
|
FullMethod: "/google.cloud.ml.v1.JobService/ListJobs",
|
|
}
|
|
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
|
|
return srv.(JobServiceServer).ListJobs(ctx, req.(*ListJobsRequest))
|
|
}
|
|
return interceptor(ctx, in, info, handler)
|
|
}
|
|
|
|
func _JobService_GetJob_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
|
|
in := new(GetJobRequest)
|
|
if err := dec(in); err != nil {
|
|
return nil, err
|
|
}
|
|
if interceptor == nil {
|
|
return srv.(JobServiceServer).GetJob(ctx, in)
|
|
}
|
|
info := &grpc.UnaryServerInfo{
|
|
Server: srv,
|
|
FullMethod: "/google.cloud.ml.v1.JobService/GetJob",
|
|
}
|
|
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
|
|
return srv.(JobServiceServer).GetJob(ctx, req.(*GetJobRequest))
|
|
}
|
|
return interceptor(ctx, in, info, handler)
|
|
}
|
|
|
|
func _JobService_CancelJob_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
|
|
in := new(CancelJobRequest)
|
|
if err := dec(in); err != nil {
|
|
return nil, err
|
|
}
|
|
if interceptor == nil {
|
|
return srv.(JobServiceServer).CancelJob(ctx, in)
|
|
}
|
|
info := &grpc.UnaryServerInfo{
|
|
Server: srv,
|
|
FullMethod: "/google.cloud.ml.v1.JobService/CancelJob",
|
|
}
|
|
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
|
|
return srv.(JobServiceServer).CancelJob(ctx, req.(*CancelJobRequest))
|
|
}
|
|
return interceptor(ctx, in, info, handler)
|
|
}
|
|
|
|
var _JobService_serviceDesc = grpc.ServiceDesc{
|
|
ServiceName: "google.cloud.ml.v1.JobService",
|
|
HandlerType: (*JobServiceServer)(nil),
|
|
Methods: []grpc.MethodDesc{
|
|
{
|
|
MethodName: "CreateJob",
|
|
Handler: _JobService_CreateJob_Handler,
|
|
},
|
|
{
|
|
MethodName: "ListJobs",
|
|
Handler: _JobService_ListJobs_Handler,
|
|
},
|
|
{
|
|
MethodName: "GetJob",
|
|
Handler: _JobService_GetJob_Handler,
|
|
},
|
|
{
|
|
MethodName: "CancelJob",
|
|
Handler: _JobService_CancelJob_Handler,
|
|
},
|
|
},
|
|
Streams: []grpc.StreamDesc{},
|
|
Metadata: "google/cloud/ml/v1/job_service.proto",
|
|
}
|
|
|
|
func init() {
|
|
proto.RegisterFile("google/cloud/ml/v1/job_service.proto", fileDescriptor_job_service_fd7c04231fa00b5c)
|
|
}
|
|
|
|
var fileDescriptor_job_service_fd7c04231fa00b5c = []byte{
|
|
// 2070 bytes of a gzipped FileDescriptorProto
|
|
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0x97, 0x72, 0xaf, 0xff, 0x25, 0x01, 0xda, 0x2c, 0x80, 0xaa, 0x98, 0x97, 0x22, 0x91, 0xb8, 0x12,
|
|
0x89, 0xe7, 0xa0, 0x05, 0xb1, 0x92, 0x8a, 0x44, 0x52, 0x44, 0xa2, 0x34, 0xc3, 0x65, 0x28, 0x1e,
|
|
0x43, 0x81, 0x86, 0xa1, 0x3f, 0x8d, 0x57, 0x4a, 0xb0, 0x40, 0x40, 0x92, 0xf0, 0x08, 0xc0, 0xf3,
|
|
0x47, 0xd4, 0x7a, 0xe7, 0x4f, 0x42, 0x39, 0x1e, 0x24, 0x70, 0x9e, 0x23, 0x47, 0x1c, 0xd0, 0xff,
|
|
0x93, 0x81, 0xd4, 0xb1, 0x3f, 0x40, 0x5b, 0xc0, 0x27, 0xb1, 0x59, 0x87, 0xcd, 0x9c, 0xf9, 0x83,
|
|
0xd6, 0x08, 0x1d, 0x43, 0x31, 0x6e, 0x0e, 0x22, 0x97, 0x62, 0x1f, 0xd7, 0xcc, 0x31, 0x0b, 0x43,
|
|
0xf9, 0xd1, 0x1a, 0x8e, 0xfb, 0x8a, 0x2c, 0xe6, 0xee, 0xc2, 0xa9, 0xa4, 0x35, 0xd9, 0x46, 0x77,
|
|
0x3e, 0xa1, 0xee, 0x8e, 0xd6, 0xe6, 0x0f, 0x2f, 0x2d, 0x7e, 0x0d, 0x85, 0x61, 0x48, 0x09, 0xe3,
|
|
0xdf, 0x0b, 0xae, 0x1c, 0x11, 0x0a, 0xfb, 0x95, 0xa9, 0xb1, 0xe9, 0x77, 0x47, 0xd5, 0x9c, 0x7e,
|
|
0x77, 0x60, 0x90, 0x74, 0x0e, 0xa0, 0xaf, 0x00, 0x22, 0x46, 0x42, 0x26, 0x75, 0x33, 0x1f, 0xd5,
|
|
0xcd, 0x0b, 0xb6, 0x50, 0xfd, 0x31, 0xe4, 0xa8, 0x37, 0x92, 0x8a, 0xd9, 0x8f, 0x2a, 0xae, 0x53,
|
|
0x6f, 0x24, 0xd4, 0xbe, 0x80, 0x4c, 0xc4, 0x08, 0x9b, 0x3e, 0xf7, 0x8f, 0x56, 0x9d, 0xfa, 0xd8,
|
|
0x1f, 0x54, 0x7b, 0x9c, 0x84, 0x25, 0x97, 0xb7, 0x67, 0x99, 0x60, 0x97, 0x46, 0x11, 0x19, 0xc7,
|
|
0x43, 0xbd, 0x00, 0xdb, 0x12, 0x43, 0x6d, 0x28, 0xc5, 0x69, 0x92, 0x75, 0x24, 0x6e, 0x7b, 0x61,
|
|
0x5f, 0xbf, 0x29, 0x4f, 0xb2, 0x1c, 0x8f, 0x12, 0x38, 0xce, 0xb1, 0x2a, 0xd0, 0x1e, 0xdc, 0x9a,
|
|
0xcb, 0x94, 0x32, 0x08, 0xc2, 0xe0, 0xd3, 0x9b, 0x53, 0x15, 0x9b, 0x9c, 0x4b, 0xb5, 0xc4, 0xf4,
|
|
0xdf, 0x27, 0x20, 0x23, 0x4e, 0xc6, 0xe7, 0x85, 0x9e, 0x59, 0x37, 0x57, 0x4c, 0x25, 0x3f, 0xef,
|
|
0x1b, 0x7d, 0xa3, 0x19, 0x4f, 0xef, 0xdd, 0x3a, 0x6e, 0x75, 0x0e, 0xb5, 0x24, 0x1f, 0x52, 0x70,
|
|
0xbf, 0xd3, 0xe1, 0x0b, 0x31, 0xca, 0xf7, 0xfa, 0x8d, 0x86, 0x61, 0x34, 0x8d, 0xa6, 0x96, 0xe6,
|
|
0x6a, 0xaf, 0xea, 0xad, 0x13, 0xa3, 0xa9, 0x65, 0xf8, 0x47, 0x40, 0xa3, 0xde, 0x69, 0x18, 0x27,
|
|
0x27, 0x9c, 0x9a, 0xe5, 0x54, 0xb5, 0x36, 0x9a, 0xda, 0xfa, 0xc1, 0x3a, 0x64, 0x44, 0xd9, 0x1d,
|
|
0xe4, 0x20, 0x2b, 0x4f, 0xa5, 0xf7, 0x41, 0x6b, 0x88, 0x9a, 0x38, 0xf6, 0x07, 0x98, 0xfe, 0x76,
|
|
0x42, 0x23, 0xd1, 0x5e, 0x02, 0x12, 0x52, 0xf5, 0xba, 0xe4, 0xb1, 0x5a, 0xa1, 0xe7, 0x90, 0xe2,
|
|
0x9d, 0x5c, 0xde, 0x80, 0x7b, 0xd7, 0x64, 0x0f, 0x73, 0x8e, 0xfe, 0x01, 0x4a, 0x27, 0x76, 0xc4,
|
|
0x8e, 0xfd, 0x41, 0xf4, 0x31, 0xab, 0x77, 0x21, 0xfb, 0xd6, 0x76, 0x18, 0x0d, 0xd5, 0x43, 0xa8,
|
|
0x56, 0xfc, 0xe2, 0x06, 0xfc, 0x6b, 0x8f, 0xf9, 0xef, 0xa9, 0xa7, 0x3e, 0x39, 0xf3, 0x1c, 0x31,
|
|
0x39, 0xc0, 0xa7, 0x56, 0x21, 0x8e, 0xec, 0xef, 0x64, 0xf5, 0x66, 0x70, 0x8e, 0x03, 0x3d, 0xfb,
|
|
0x3b, 0x3e, 0x11, 0x6a, 0x33, 0xf7, 0x51, 0xe0, 0x7b, 0x11, 0x45, 0x9f, 0x43, 0xfa, 0xcc, 0x1f,
|
|
0x44, 0xe5, 0x84, 0x78, 0x0c, 0xaf, 0xdd, 0xbe, 0x20, 0xa1, 0x67, 0x50, 0xf2, 0xe8, 0x05, 0x6f,
|
|
0x50, 0xf1, 0x0e, 0xe4, 0xee, 0x36, 0x39, 0xdc, 0x9d, 0xee, 0x42, 0xdf, 0x81, 0xcd, 0x43, 0xca,
|
|
0xe6, 0x62, 0x87, 0x20, 0x3d, 0x37, 0xcb, 0x8b, 0xdf, 0xfa, 0x33, 0xd0, 0x1a, 0xc4, 0x1b, 0x52,
|
|
0xe7, 0x66, 0xde, 0xfe, 0xbf, 0x52, 0x00, 0xc7, 0xfe, 0xa0, 0x27, 0xff, 0xab, 0x40, 0x13, 0xc8,
|
|
0xc7, 0xa9, 0x41, 0x2b, 0xeb, 0x6e, 0x39, 0x73, 0x95, 0xeb, 0x4e, 0xa5, 0x3f, 0xff, 0xc3, 0xdf,
|
|
0xff, 0xf9, 0xe7, 0xe4, 0x8e, 0xfe, 0xb0, 0x76, 0xbe, 0x57, 0xfb, 0x5e, 0x46, 0xfe, 0x9b, 0x20,
|
|
0xf4, 0xf9, 0xec, 0x12, 0xd5, 0x5e, 0x7c, 0xa8, 0xf1, 0x53, 0xbf, 0xe4, 0xa9, 0x43, 0xdf, 0x43,
|
|
0x6e, 0x1a, 0x3b, 0xb4, 0xb2, 0x31, 0x2d, 0x25, 0xb6, 0xf2, 0xf4, 0x66, 0x92, 0x0c, 0xbf, 0xfe,
|
|
0x54, 0xec, 0xe0, 0x33, 0x74, 0xe3, 0x0e, 0xd0, 0x19, 0x64, 0x65, 0x3c, 0xd1, 0xca, 0x0e, 0xbb,
|
|
0x10, 0xeb, 0xeb, 0x4f, 0xbb, 0xe8, 0x8b, 0xc7, 0x76, 0xce, 0x93, 0x70, 0x54, 0x7b, 0xf1, 0x01,
|
|
0x5d, 0x42, 0x3e, 0x4e, 0xcb, 0x35, 0xf1, 0x5d, 0xca, 0x5a, 0xe5, 0xee, 0x95, 0x36, 0x67, 0xb8,
|
|
0x01, 0xbb, 0xd4, 0xab, 0xc2, 0xe1, 0xae, 0xbe, 0x73, 0x93, 0xc3, 0x97, 0x43, 0x61, 0xee, 0x65,
|
|
0xe2, 0xc5, 0x01, 0x85, 0xca, 0xd0, 0x77, 0xaf, 0xb8, 0x24, 0x81, 0x5d, 0x3d, 0xdf, 0x3b, 0x28,
|
|
0xcd, 0x8a, 0xa0, 0xcb, 0xfd, 0x74, 0x13, 0x6f, 0xbe, 0x54, 0xd4, 0xb1, 0xef, 0x10, 0x6f, 0x5c,
|
|
0xf5, 0xc3, 0x71, 0x6d, 0x4c, 0x3d, 0xb1, 0x8b, 0x9a, 0x14, 0x91, 0xc0, 0x8e, 0xe6, 0xff, 0xf6,
|
|
0xfa, 0xda, 0x75, 0x06, 0x59, 0x41, 0xf8, 0xe2, 0xbf, 0x01, 0x00, 0x00, 0xff, 0xff, 0x4c, 0x7b,
|
|
0x72, 0xd5, 0x16, 0x13, 0x00, 0x00,
|
|
}
|