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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::HyperparameterTuningJob.
Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#create_time
def create_time() -> ::Google::Protobuf::Timestamp
- (::Google::Protobuf::Timestamp) — Output only. Time when the HyperparameterTuningJob was created.
#display_name
def display_name() -> ::String
- (::String) — Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
#display_name=
def display_name=(value) -> ::String
- value (::String) — Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
- (::String) — Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can be consist of any UTF-8 characters.
#encryption_spec
def encryption_spec() -> ::Google::Cloud::AIPlatform::V1::EncryptionSpec
- (::Google::Cloud::AIPlatform::V1::EncryptionSpec) — Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.
#encryption_spec=
def encryption_spec=(value) -> ::Google::Cloud::AIPlatform::V1::EncryptionSpec
- value (::Google::Cloud::AIPlatform::V1::EncryptionSpec) — Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.
- (::Google::Cloud::AIPlatform::V1::EncryptionSpec) — Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key.
#end_time
def end_time() -> ::Google::Protobuf::Timestamp
-
(::Google::Protobuf::Timestamp) — Output only. Time when the HyperparameterTuningJob entered any of the following states:
JOB_STATE_SUCCEEDED
,JOB_STATE_FAILED
,JOB_STATE_CANCELLED
.
#error
def error() -> ::Google::Rpc::Status
- (::Google::Rpc::Status) — Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.
#labels
def labels() -> ::Google::Protobuf::Map{::String => ::String}
-
(::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize HyperparameterTuningJobs.
Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
#labels=
def labels=(value) -> ::Google::Protobuf::Map{::String => ::String}
-
value (::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize HyperparameterTuningJobs.
Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
-
(::Google::Protobuf::Map{::String => ::String}) — The labels with user-defined metadata to organize HyperparameterTuningJobs.
Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.
See https://goo.gl/xmQnxf for more information and examples of labels.
#max_failed_trial_count
def max_failed_trial_count() -> ::Integer
-
(::Integer) — The number of failed Trials that need to be seen before failing
the HyperparameterTuningJob.
If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
#max_failed_trial_count=
def max_failed_trial_count=(value) -> ::Integer
-
value (::Integer) — The number of failed Trials that need to be seen before failing
the HyperparameterTuningJob.
If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
-
(::Integer) — The number of failed Trials that need to be seen before failing
the HyperparameterTuningJob.
If set to 0, Vertex AI decides how many Trials must fail before the whole job fails.
#max_trial_count
def max_trial_count() -> ::Integer
- (::Integer) — Required. The desired total number of Trials.
#max_trial_count=
def max_trial_count=(value) -> ::Integer
- value (::Integer) — Required. The desired total number of Trials.
- (::Integer) — Required. The desired total number of Trials.
#name
def name() -> ::String
- (::String) — Output only. Resource name of the HyperparameterTuningJob.
#parallel_trial_count
def parallel_trial_count() -> ::Integer
- (::Integer) — Required. The desired number of Trials to run in parallel.
#parallel_trial_count=
def parallel_trial_count=(value) -> ::Integer
- value (::Integer) — Required. The desired number of Trials to run in parallel.
- (::Integer) — Required. The desired number of Trials to run in parallel.
#start_time
def start_time() -> ::Google::Protobuf::Timestamp
-
(::Google::Protobuf::Timestamp) — Output only. Time when the HyperparameterTuningJob for the first time entered the
JOB_STATE_RUNNING
state.
#state
def state() -> ::Google::Cloud::AIPlatform::V1::JobState
- (::Google::Cloud::AIPlatform::V1::JobState) — Output only. The detailed state of the job.
#study_spec
def study_spec() -> ::Google::Cloud::AIPlatform::V1::StudySpec
- (::Google::Cloud::AIPlatform::V1::StudySpec) — Required. Study configuration of the HyperparameterTuningJob.
#study_spec=
def study_spec=(value) -> ::Google::Cloud::AIPlatform::V1::StudySpec
- value (::Google::Cloud::AIPlatform::V1::StudySpec) — Required. Study configuration of the HyperparameterTuningJob.
- (::Google::Cloud::AIPlatform::V1::StudySpec) — Required. Study configuration of the HyperparameterTuningJob.
#trial_job_spec
def trial_job_spec() -> ::Google::Cloud::AIPlatform::V1::CustomJobSpec
- (::Google::Cloud::AIPlatform::V1::CustomJobSpec) — Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.
#trial_job_spec=
def trial_job_spec=(value) -> ::Google::Cloud::AIPlatform::V1::CustomJobSpec
- value (::Google::Cloud::AIPlatform::V1::CustomJobSpec) — Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.
- (::Google::Cloud::AIPlatform::V1::CustomJobSpec) — Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials.
#trials
def trials() -> ::Array<::Google::Cloud::AIPlatform::V1::Trial>
- (::Array<::Google::Cloud::AIPlatform::V1::Trial>) — Output only. Trials of the HyperparameterTuningJob.
#update_time
def update_time() -> ::Google::Protobuf::Timestamp
- (::Google::Protobuf::Timestamp) — Output only. Time when the HyperparameterTuningJob was most recently updated.