Class: Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1EvaluationJobConfig

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
lib/google/apis/datalabeling_v1beta1/classes.rb,
lib/google/apis/datalabeling_v1beta1/representations.rb,
lib/google/apis/datalabeling_v1beta1/representations.rb

Overview

Configures specific details of how a continuous evaluation job works. Provide this configuration when you create an EvaluationJob.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudDatalabelingV1beta1EvaluationJobConfig

Returns a new instance of GoogleCloudDatalabelingV1beta1EvaluationJobConfig.



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1976

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

Instance Attribute Details

#bigquery_import_keys ⇒ Hash<String,String>

Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON. You can provide the following entries in this field: * data_json_key: the data key for prediction input. You must provide either this key or reference_json_key. * reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key. * label_json_key: the label key for prediction output. Required. * label_score_json_key: the score key for prediction output. Required. * bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection. Learn how to configure prediction keys. Corresponds to the JSON property bigqueryImportKeys

Returns:

  • (Hash<String,String>) 


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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1921

def bigquery_import_keys
  @bigquery_import_keys
end

#bounding_poly_config ⇒ Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1BoundingPolyConfig

Config for image bounding poly (and bounding box) human labeling task. Corresponds to the JSON property boundingPolyConfig

Returns:



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1926

def bounding_poly_config
  @bounding_poly_config
end

#evaluation_config ⇒ Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1EvaluationConfig

Configuration details used for calculating evaluation metrics and creating an Evaluation. Corresponds to the JSON property evaluationConfig

Returns:



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1932

def evaluation_config
  @evaluation_config
end

#evaluation_job_alert_config ⇒ Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1EvaluationJobAlertConfig

Provides details for how an evaluation job sends email alerts based on the results of a run. Corresponds to the JSON property evaluationJobAlertConfig

Returns:



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1938

def evaluation_job_alert_config
  @evaluation_job_alert_config
end

#example_count ⇒ Fixnum

Required. The maximum number of predictions to sample and save to BigQuery during each evaluation interval. This limit overrides example_sample_percentage: even if the service has not sampled enough predictions to fulfill example_sample_perecentage during an interval, it stops sampling predictions when it meets this limit. Corresponds to the JSON property exampleCount

Returns:

  • (Fixnum) 


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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1947

def example_count
  @example_count
end

#example_sample_percentage ⇒ Float

Required. Fraction of predictions to sample and save to BigQuery during each evaluation interval. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery. Corresponds to the JSON property exampleSamplePercentage

Returns:

  • (Float) 


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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1954

def example_sample_percentage
  @example_sample_percentage
end

#human_annotation_config ⇒ Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1HumanAnnotationConfig

Configuration for how human labeling task should be done. Corresponds to the JSON property humanAnnotationConfig

Returns:



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1959

def human_annotation_config
  @human_annotation_config
end

#image_classification_config ⇒ Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1ImageClassificationConfig

Config for image classification human labeling task. Corresponds to the JSON property imageClassificationConfig

Returns:



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1964

def image_classification_config
  @image_classification_config
end

#input_config ⇒ Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1InputConfig

The configuration of input data, including data type, location, etc. Corresponds to the JSON property inputConfig

Returns:



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1969

def input_config
  @input_config
end

#text_classification_config ⇒ Google::Apis::DatalabelingV1beta1::GoogleCloudDatalabelingV1beta1TextClassificationConfig

Config for text classification human labeling task. Corresponds to the JSON property textClassificationConfig

Returns:



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1974

def text_classification_config
  @text_classification_config
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



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# File 'lib/google/apis/datalabeling_v1beta1/classes.rb', line 1981

def update!(**args)
  @bigquery_import_keys = args[:bigquery_import_keys] if args.key?(:bigquery_import_keys)
  @bounding_poly_config = args[:bounding_poly_config] if args.key?(:bounding_poly_config)
  @evaluation_config = args[:evaluation_config] if args.key?(:evaluation_config)
  @evaluation_job_alert_config = args[:evaluation_job_alert_config] if args.key?(:evaluation_job_alert_config)
  @example_count = args[:example_count] if args.key?(:example_count)
  @example_sample_percentage = args[:example_sample_percentage] if args.key?(:example_sample_percentage)
  @human_annotation_config = args[:human_annotation_config] if args.key?(:human_annotation_config)
  @image_classification_config = args[:image_classification_config] if args.key?(:image_classification_config)
  @input_config = args[:input_config] if args.key?(:input_config)
  @text_classification_config = args[:text_classification_config] if args.key?(:text_classification_config)
end