Class: Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageObjectDetectionInputs

Inherits:
Object
  • Object
show all
Extended by:
Protobuf::MessageExts::ClassMethods
Includes:
Protobuf::MessageExts
Defined in:
proto_docs/google/cloud/aiplatform/v1/schema/trainingjob/definition/automl_image_object_detection.rb

Defined Under Namespace

Modules: ModelType

Instance Attribute Summary collapse

Instance Attribute Details

#budget_milli_node_hours ⇒ ::Integer

Returns 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 20,000 and 900,000 milli node hours, inclusive. The default value is 216,000 which represents one day in wall time, considering 9 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.

Returns:

  • (::Integer) —

    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 20,000 and 900,000 milli node hours, inclusive. The default value is 216,000 which represents one day in wall time, considering 9 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.



64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
 
# File 'proto_docs/google/cloud/aiplatform/v1/schema/trainingjob/definition/automl_image_object_detection.rb', line 64

class AutoMlImageObjectDetectionInputs
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  module ModelType
    # Should not be set.
    MODEL_TYPE_UNSPECIFIED = 0

    # A model best tailored to be used within Google Cloud, and which cannot
    # be exported. Expected to have a higher latency, but should also have a
    # higher prediction quality than other cloud models.
    CLOUD_HIGH_ACCURACY_1 = 1

    # A model best tailored to be used within Google Cloud, and which cannot
    # be exported. Expected to have a low latency, but may have lower
    # prediction quality than other cloud models.
    CLOUD_LOW_LATENCY_1 = 2

    # A model that, in addition to being available within Google
    # Cloud can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    # Expected to have low latency, but may have lower prediction
    # quality than other mobile models.
    MOBILE_TF_LOW_LATENCY_1 = 3

    # A model that, in addition to being available within Google
    # Cloud can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    MOBILE_TF_VERSATILE_1 = 4

    # A model that, in addition to being available within Google
    # Cloud, can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    # Expected to have a higher latency, but should also have a higher
    # prediction quality than other mobile models.
    MOBILE_TF_HIGH_ACCURACY_1 = 5
  end
end

#disable_early_stopping ⇒ ::Boolean

Returns Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Object Detection might stop training before the entire training budget has been used.

Returns:

  • (::Boolean) —

    Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Object Detection might stop training before the entire training budget has been used.



64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
 
# File 'proto_docs/google/cloud/aiplatform/v1/schema/trainingjob/definition/automl_image_object_detection.rb', line 64

class AutoMlImageObjectDetectionInputs
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  module ModelType
    # Should not be set.
    MODEL_TYPE_UNSPECIFIED = 0

    # A model best tailored to be used within Google Cloud, and which cannot
    # be exported. Expected to have a higher latency, but should also have a
    # higher prediction quality than other cloud models.
    CLOUD_HIGH_ACCURACY_1 = 1

    # A model best tailored to be used within Google Cloud, and which cannot
    # be exported. Expected to have a low latency, but may have lower
    # prediction quality than other cloud models.
    CLOUD_LOW_LATENCY_1 = 2

    # A model that, in addition to being available within Google
    # Cloud can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    # Expected to have low latency, but may have lower prediction
    # quality than other mobile models.
    MOBILE_TF_LOW_LATENCY_1 = 3

    # A model that, in addition to being available within Google
    # Cloud can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    MOBILE_TF_VERSATILE_1 = 4

    # A model that, in addition to being available within Google
    # Cloud, can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    # Expected to have a higher latency, but should also have a higher
    # prediction quality than other mobile models.
    MOBILE_TF_HIGH_ACCURACY_1 = 5
  end
end

#model_type ⇒ ::Google::Cloud::AIPlatform::V1::Schema::TrainingJob::Definition::AutoMlImageObjectDetectionInputs::ModelType

Returns:



64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
 
# File 'proto_docs/google/cloud/aiplatform/v1/schema/trainingjob/definition/automl_image_object_detection.rb', line 64

class AutoMlImageObjectDetectionInputs
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods

  module ModelType
    # Should not be set.
    MODEL_TYPE_UNSPECIFIED = 0

    # A model best tailored to be used within Google Cloud, and which cannot
    # be exported. Expected to have a higher latency, but should also have a
    # higher prediction quality than other cloud models.
    CLOUD_HIGH_ACCURACY_1 = 1

    # A model best tailored to be used within Google Cloud, and which cannot
    # be exported. Expected to have a low latency, but may have lower
    # prediction quality than other cloud models.
    CLOUD_LOW_LATENCY_1 = 2

    # A model that, in addition to being available within Google
    # Cloud can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    # Expected to have low latency, but may have lower prediction
    # quality than other mobile models.
    MOBILE_TF_LOW_LATENCY_1 = 3

    # A model that, in addition to being available within Google
    # Cloud can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    MOBILE_TF_VERSATILE_1 = 4

    # A model that, in addition to being available within Google
    # Cloud, can also be exported (see ModelService.ExportModel) and
    # used on a mobile or edge device with TensorFlow afterwards.
    # Expected to have a higher latency, but should also have a higher
    # prediction quality than other mobile models.
    MOBILE_TF_HIGH_ACCURACY_1 = 5
  end
end