Class: Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs
- Inherits:
-
Object
- Object
- Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs
- 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
Instance Attribute Summary collapse
-
#base_model_id ⇒ String
The ID of the
base
model. -
#budget_milli_node_hours ⇒ Fixnum
The training budget of creating this model, expressed in milli node hours i.e.
-
#disable_early_stopping ⇒ Boolean
(also: #disable_early_stopping?)
Use the entire training budget.
-
#model_type ⇒ String
Corresponds to the JSON property
modelType
. -
#multi_label ⇒ Boolean
(also: #multi_label?)
If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable).
-
#tunable_parameter ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter
A wrapper class which contains the tunable parameters in an AutoML Image training job.
-
#uptrain_base_model_id ⇒ String
The ID of
base
model for upTraining.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs
constructor
A new instance of GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs
Returns a new instance of GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs.
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28558 def initialize(**args) update!(**args) end |
Instance Attribute Details
#base_model_id ⇒ String
The ID of the base
model. If it is specified, the new model will be trained
based on the base
model. Otherwise, the new model will be trained from
scratch. The base
model must be in the same Project and Location as the new
Model to train, and have the same modelType.
Corresponds to the JSON property baseModelId
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28502 def base_model_id @base_model_id end |
#budget_milli_node_hours ⇒ Fixnum
The training budget of creating this model, expressed in milli node hours i.e.
1,000 value in this field means 1 node hour. The actual metadata.
costMilliNodeHours will be equal or less than this value. If further model
training ceases to provide any improvements, it will stop without using the
full budget and the metadata.successfulStopReason will be model-converged
.
Note, node_hour = actual_hour * number_of_nodes_involved. For modelType cloud
(default), the budget must be between 8,000 and 800,000 milli node hours,
inclusive. The default value is 192,000 which represents one day in wall time,
considering 8 nodes are used. For model types mobile-tf-low-latency-1
,
mobile-tf-versatile-1
, mobile-tf-high-accuracy-1
, the training budget must
be between 1,000 and 100,000 milli node hours, inclusive. The default value is
24,000 which represents one day in wall time on a single node that is used.
Corresponds to the JSON property budgetMilliNodeHours
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28518 def budget_milli_node_hours @budget_milli_node_hours end |
#disable_early_stopping ⇒ Boolean Also known as: disable_early_stopping?
Use the entire training budget. This disables the early stopping feature. When
false the early stopping feature is enabled, which means that AutoML Image
Classification might stop training before the entire training budget has been
used.
Corresponds to the JSON property disableEarlyStopping
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28526 def disable_early_stopping @disable_early_stopping end |
#model_type ⇒ String
Corresponds to the JSON property modelType
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28532 def model_type @model_type end |
#multi_label ⇒ Boolean Also known as: multi_label?
If false, a single-label (multi-class) Model will be trained (i.e. assuming
that for each image just up to one annotation may be applicable). If true, a
multi-label Model will be trained (i.e. assuming that for each image multiple
annotations may be applicable).
Corresponds to the JSON property multiLabel
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28540 def multi_label @multi_label end |
#tunable_parameter ⇒ Google::Apis::AiplatformV1beta1::GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter
A wrapper class which contains the tunable parameters in an AutoML Image
training job.
Corresponds to the JSON property tunableParameter
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28547 def tunable_parameter @tunable_parameter end |
#uptrain_base_model_id ⇒ String
The ID of base
model for upTraining. If it is specified, the new model will
be upTrained based on the base
model for upTraining. Otherwise, the new
model will be trained from scratch. The base
model for upTraining must be in
the same Project and Location as the new Model to train, and have the same
modelType.
Corresponds to the JSON property uptrainBaseModelId
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28556 def uptrain_base_model_id @uptrain_base_model_id end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/aiplatform_v1beta1/classes.rb', line 28563 def update!(**args) @base_model_id = args[:base_model_id] if args.key?(:base_model_id) @budget_milli_node_hours = args[:budget_milli_node_hours] if args.key?(:budget_milli_node_hours) @disable_early_stopping = args[:disable_early_stopping] if args.key?(:disable_early_stopping) @model_type = args[:model_type] if args.key?(:model_type) @multi_label = args[:multi_label] if args.key?(:multi_label) @tunable_parameter = args[:tunable_parameter] if args.key?(:tunable_parameter) @uptrain_base_model_id = args[:uptrain_base_model_id] if args.key?(:uptrain_base_model_id) end |