Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1TrainingPipeline

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/aiplatform_v1beta1/classes.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb,
lib/google/apis/aiplatform_v1beta1/representations.rb

Overview

The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1TrainingPipeline

Returns a new instance of GoogleCloudAiplatformV1beta1TrainingPipeline.



25185
25186
25187
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25185

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#create_time ⇒ String

Output only. Time when the TrainingPipeline was created. Corresponds to the JSON property createTime

Returns:

  • (String) 


25074
25075
25076
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25074

def create_time
  @create_time
end

#display_name ⇒ String

Required. The user-defined name of this TrainingPipeline. Corresponds to the JSON property displayName

Returns:

  • (String) 


25079
25080
25081
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25079

def display_name
  @display_name
end

#encryption_spec ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1EncryptionSpec

Represents a customer-managed encryption key spec that can be applied to a top- level resource. Corresponds to the JSON property encryptionSpec

Returns:



25085
25086
25087
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25085

def encryption_spec
  @encryption_spec
end

#end_time ⇒ String

Output only. Time when the TrainingPipeline entered any of the following states: PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED, PIPELINE_STATE_CANCELLED. Corresponds to the JSON property endTime

Returns:

  • (String) 


25092
25093
25094
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25092

def end_time
  @end_time
end

#error ⇒ Google::Apis::AiplatformV1beta1::GoogleRpcStatus

The Status type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by gRPC. Each Status message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the API Design Guide. Corresponds to the JSON property error

Returns:



25102
25103
25104
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25102

def error
  @error
end

#input_data_config ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1InputDataConfig

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model. Corresponds to the JSON property inputDataConfig

Returns:



25108
25109
25110
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25108

def input_data_config
  @input_data_config
end

#labels ⇒ Hash<String,String>

The labels with user-defined metadata to organize TrainingPipelines. 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. Corresponds to the JSON property labels

Returns:

  • (Hash<String,String>) 


25117
25118
25119
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25117

def labels
  @labels
end

#model_id ⇒ String

Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are [a-z0-9_-]. The first character cannot be a number or hyphen. Corresponds to the JSON property modelId

Returns:

  • (String) 


25125
25126
25127
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25125

def model_id
  @model_id
end

#model_to_upload ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1Model

A trained machine learning Model. Corresponds to the JSON property modelToUpload

Returns:



25130
25131
25132
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25130

def model_to_upload
  @model_to_upload
end

#name ⇒ String

Output only. Resource name of the TrainingPipeline. Corresponds to the JSON property name

Returns:

  • (String) 


25135
25136
25137
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25135

def name
  @name
end

#parent_model ⇒ String

Optional. When specify this field, the model_to_upload will not be uploaded as a new model, instead, it will become a new version of this parent_model. Corresponds to the JSON property parentModel

Returns:

  • (String) 


25141
25142
25143
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25141

def parent_model
  @parent_model
end

#start_time ⇒ String

Output only. Time when the TrainingPipeline for the first time entered the PIPELINE_STATE_RUNNING state. Corresponds to the JSON property startTime

Returns:

  • (String) 


25147
25148
25149
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25147

def start_time
  @start_time
end

#state ⇒ String

Output only. The detailed state of the pipeline. Corresponds to the JSON property state

Returns:

  • (String) 


25152
25153
25154
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25152

def state
  @state
end

#training_task_definition ⇒ String

Required. A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud-aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. Corresponds to the JSON property trainingTaskDefinition

Returns:

  • (String) 


25163
25164
25165
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25163

def training_task_definition
  @training_task_definition
end

#training_task_inputs ⇒ Object

Required. The training task's parameter(s), as specified in the training_task_definition's inputs. Corresponds to the JSON property trainingTaskInputs

Returns:

  • (Object) 


25169
25170
25171
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25169

def training_task_inputs
  @training_task_inputs
end

#training_task_metadata ⇒ Object

Output only. The metadata information as specified in the training_task_definition's metadata. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains metadata object. Corresponds to the JSON property trainingTaskMetadata

Returns:

  • (Object) 


25178
25179
25180
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25178

def training_task_metadata
  @training_task_metadata
end

#update_time ⇒ String

Output only. Time when the TrainingPipeline was most recently updated. Corresponds to the JSON property updateTime

Returns:

  • (String) 


25183
25184
25185
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25183

def update_time
  @update_time
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



25190
25191
25192
25193
25194
25195
25196
25197
25198
25199
25200
25201
25202
25203
25204
25205
25206
25207
25208
 
# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 25190

def update!(**args)
  @create_time = args[:create_time] if args.key?(:create_time)
  @display_name = args[:display_name] if args.key?(:display_name)
  @encryption_spec = args[:encryption_spec] if args.key?(:encryption_spec)
  @end_time = args[:end_time] if args.key?(:end_time)
  @error = args[:error] if args.key?(:error)
  @input_data_config = args[:input_data_config] if args.key?(:input_data_config)
  @labels = args[:labels] if args.key?(:labels)
  @model_id = args[:model_id] if args.key?(:model_id)
  @model_to_upload = args[:model_to_upload] if args.key?(:model_to_upload)
  @name = args[:name] if args.key?(:name)
  @parent_model = args[:parent_model] if args.key?(:parent_model)
  @start_time = args[:start_time] if args.key?(:start_time)
  @state = args[:state] if args.key?(:state)
  @training_task_definition = args[:training_task_definition] if args.key?(:training_task_definition)
  @training_task_inputs = args[:training_task_inputs] if args.key?(:training_task_inputs)
  @training_task_metadata = args[:training_task_metadata] if args.key?(:training_task_metadata)
  @update_time = args[:update_time] if args.key?(:update_time)
end