Class: Google::Cloud::AIPlatform::V1::ModelEvaluationSlice

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

Overview

A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.

Defined Under Namespace

Classes: Slice

Instance Attribute Summary collapse

Instance Attribute Details

#create_time ⇒ ::Google::Protobuf::Timestamp (readonly)

Returns Output only. Timestamp when this ModelEvaluationSlice was created.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/model_evaluation_slice.rb', line 53

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

  # Definition of a slice.
  # @!attribute [r] dimension
  #   @return [::String]
  #     Output only. The dimension of the slice.
  #     Well-known dimensions are:
  #       * `annotationSpec`: This slice is on the test data that has either
  #         ground truth or prediction with
  #         {::Google::Cloud::AIPlatform::V1::AnnotationSpec#display_name AnnotationSpec.display_name}
  #         equals to
  #         {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice#value value}.
  #       * `slice`: This slice is a user customized slice defined by its
  #         SliceSpec.
  # @!attribute [r] value
  #   @return [::String]
  #     Output only. The value of the dimension in this slice.
  # @!attribute [r] slice_spec
  #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec]
  #     Output only. Specification for how the data was sliced.
  class Slice
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Specification for how the data should be sliced.
    # @!attribute [rw] configs
    #   @return [::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig}]
    #     Mapping configuration for this SliceSpec.
    #     The key is the name of the feature.
    #     By default, the key will be prefixed by "instance" as a dictionary
    #     prefix for Vertex Batch Predictions output format.
    class SliceSpec
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # Specification message containing the config for this SliceSpec.
      # When `kind` is selected as `value` and/or `range`, only a single slice
      # will be computed.
      # When `all_values` is present, a separate slice will be computed for
      # each possible label/value for the corresponding key in `config`.
      # Examples, with feature zip_code with values 12345, 23334, 88888 and
      # feature country with values "US", "Canada", "Mexico" in the dataset:
      #
      # Example 1:
      #
      #     {
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # A single slice for any data with zip_code 12345 in the dataset.
      #
      # Example 2:
      #
      #     {
      #       "zip_code": { "range": { "low": 12345, "high": 20000 } }
      #     }
      #
      # A single slice containing data where the zip_codes between 12345 and
      # 20000 For this example, data with the zip_code of 12345 will be in this
      # slice.
      #
      # Example 3:
      #
      #     {
      #       "zip_code": { "range": { "low": 10000, "high": 20000 } },
      #       "country": { "value": { "string_value": "US" } }
      #     }
      #
      # A single slice containing data where the zip_codes between 10000 and
      # 20000 has the country "US". For this example, data with the zip_code of
      # 12345 and country "US" will be in this slice.
      #
      # Example 4:
      #
      #     { "country": {"all_values": { "value": true } } }
      #
      # Three slices are computed, one for each unique country in the dataset.
      #
      # Example 5:
      #
      #     {
      #       "country": { "all_values": { "value": true } },
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # Three slices are computed, one for each unique country in the dataset
      # where the zip_code is also 12345. For this example, data with zip_code
      # 12345 and country "US" will be in one slice, zip_code 12345 and country
      # "Canada" in another slice, and zip_code 12345 and country "Mexico" in
      # another slice, totaling 3 slices.
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Value]
      #     A unique specific value for a given feature.
      #     Example: `{ "value": { "string_value": "12345" } }`
      # @!attribute [rw] range
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Range]
      #     A range of values for a numerical feature.
      #     Example: `{"range":{"low":10000.0,"high":50000.0}}`
      #     will capture 12345 and 23334 in the slice.
      # @!attribute [rw] all_values
      #   @return [::Google::Protobuf::BoolValue]
      #     If all_values is set to true, then all possible labels of the keyed
      #     feature will have another slice computed.
      #     Example: `{"all_values":{"value":true}}`
      class SliceConfig
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # A range of values for slice(s).
      # `low` is inclusive, `high` is exclusive.
      # @!attribute [rw] low
      #   @return [::Float]
      #     Inclusive low value for the range.
      # @!attribute [rw] high
      #   @return [::Float]
      #     Exclusive high value for the range.
      class Range
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # Single value that supports strings and floats.
      # @!attribute [rw] string_value
      #   @return [::String]
      #     String type.
      # @!attribute [rw] float_value
      #   @return [::Float]
      #     Float type.
      class Value
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # @!attribute [rw] key
      #   @return [::String]
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig]
      class ConfigsEntry
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end
end

#metrics ⇒ ::Google::Protobuf::Value (readonly)

Returns Output only. Sliced evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/model_evaluation_slice.rb', line 53

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

  # Definition of a slice.
  # @!attribute [r] dimension
  #   @return [::String]
  #     Output only. The dimension of the slice.
  #     Well-known dimensions are:
  #       * `annotationSpec`: This slice is on the test data that has either
  #         ground truth or prediction with
  #         {::Google::Cloud::AIPlatform::V1::AnnotationSpec#display_name AnnotationSpec.display_name}
  #         equals to
  #         {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice#value value}.
  #       * `slice`: This slice is a user customized slice defined by its
  #         SliceSpec.
  # @!attribute [r] value
  #   @return [::String]
  #     Output only. The value of the dimension in this slice.
  # @!attribute [r] slice_spec
  #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec]
  #     Output only. Specification for how the data was sliced.
  class Slice
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Specification for how the data should be sliced.
    # @!attribute [rw] configs
    #   @return [::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig}]
    #     Mapping configuration for this SliceSpec.
    #     The key is the name of the feature.
    #     By default, the key will be prefixed by "instance" as a dictionary
    #     prefix for Vertex Batch Predictions output format.
    class SliceSpec
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # Specification message containing the config for this SliceSpec.
      # When `kind` is selected as `value` and/or `range`, only a single slice
      # will be computed.
      # When `all_values` is present, a separate slice will be computed for
      # each possible label/value for the corresponding key in `config`.
      # Examples, with feature zip_code with values 12345, 23334, 88888 and
      # feature country with values "US", "Canada", "Mexico" in the dataset:
      #
      # Example 1:
      #
      #     {
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # A single slice for any data with zip_code 12345 in the dataset.
      #
      # Example 2:
      #
      #     {
      #       "zip_code": { "range": { "low": 12345, "high": 20000 } }
      #     }
      #
      # A single slice containing data where the zip_codes between 12345 and
      # 20000 For this example, data with the zip_code of 12345 will be in this
      # slice.
      #
      # Example 3:
      #
      #     {
      #       "zip_code": { "range": { "low": 10000, "high": 20000 } },
      #       "country": { "value": { "string_value": "US" } }
      #     }
      #
      # A single slice containing data where the zip_codes between 10000 and
      # 20000 has the country "US". For this example, data with the zip_code of
      # 12345 and country "US" will be in this slice.
      #
      # Example 4:
      #
      #     { "country": {"all_values": { "value": true } } }
      #
      # Three slices are computed, one for each unique country in the dataset.
      #
      # Example 5:
      #
      #     {
      #       "country": { "all_values": { "value": true } },
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # Three slices are computed, one for each unique country in the dataset
      # where the zip_code is also 12345. For this example, data with zip_code
      # 12345 and country "US" will be in one slice, zip_code 12345 and country
      # "Canada" in another slice, and zip_code 12345 and country "Mexico" in
      # another slice, totaling 3 slices.
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Value]
      #     A unique specific value for a given feature.
      #     Example: `{ "value": { "string_value": "12345" } }`
      # @!attribute [rw] range
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Range]
      #     A range of values for a numerical feature.
      #     Example: `{"range":{"low":10000.0,"high":50000.0}}`
      #     will capture 12345 and 23334 in the slice.
      # @!attribute [rw] all_values
      #   @return [::Google::Protobuf::BoolValue]
      #     If all_values is set to true, then all possible labels of the keyed
      #     feature will have another slice computed.
      #     Example: `{"all_values":{"value":true}}`
      class SliceConfig
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # A range of values for slice(s).
      # `low` is inclusive, `high` is exclusive.
      # @!attribute [rw] low
      #   @return [::Float]
      #     Inclusive low value for the range.
      # @!attribute [rw] high
      #   @return [::Float]
      #     Exclusive high value for the range.
      class Range
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # Single value that supports strings and floats.
      # @!attribute [rw] string_value
      #   @return [::String]
      #     String type.
      # @!attribute [rw] float_value
      #   @return [::Float]
      #     Float type.
      class Value
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # @!attribute [rw] key
      #   @return [::String]
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig]
      class ConfigsEntry
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end
end

#metrics_schema_uri ⇒ ::String (readonly)

Returns Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 Schema Object.

Returns:

  • (::String) —

    Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 Schema Object.



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# File 'proto_docs/google/cloud/aiplatform/v1/model_evaluation_slice.rb', line 53

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

  # Definition of a slice.
  # @!attribute [r] dimension
  #   @return [::String]
  #     Output only. The dimension of the slice.
  #     Well-known dimensions are:
  #       * `annotationSpec`: This slice is on the test data that has either
  #         ground truth or prediction with
  #         {::Google::Cloud::AIPlatform::V1::AnnotationSpec#display_name AnnotationSpec.display_name}
  #         equals to
  #         {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice#value value}.
  #       * `slice`: This slice is a user customized slice defined by its
  #         SliceSpec.
  # @!attribute [r] value
  #   @return [::String]
  #     Output only. The value of the dimension in this slice.
  # @!attribute [r] slice_spec
  #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec]
  #     Output only. Specification for how the data was sliced.
  class Slice
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Specification for how the data should be sliced.
    # @!attribute [rw] configs
    #   @return [::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig}]
    #     Mapping configuration for this SliceSpec.
    #     The key is the name of the feature.
    #     By default, the key will be prefixed by "instance" as a dictionary
    #     prefix for Vertex Batch Predictions output format.
    class SliceSpec
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # Specification message containing the config for this SliceSpec.
      # When `kind` is selected as `value` and/or `range`, only a single slice
      # will be computed.
      # When `all_values` is present, a separate slice will be computed for
      # each possible label/value for the corresponding key in `config`.
      # Examples, with feature zip_code with values 12345, 23334, 88888 and
      # feature country with values "US", "Canada", "Mexico" in the dataset:
      #
      # Example 1:
      #
      #     {
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # A single slice for any data with zip_code 12345 in the dataset.
      #
      # Example 2:
      #
      #     {
      #       "zip_code": { "range": { "low": 12345, "high": 20000 } }
      #     }
      #
      # A single slice containing data where the zip_codes between 12345 and
      # 20000 For this example, data with the zip_code of 12345 will be in this
      # slice.
      #
      # Example 3:
      #
      #     {
      #       "zip_code": { "range": { "low": 10000, "high": 20000 } },
      #       "country": { "value": { "string_value": "US" } }
      #     }
      #
      # A single slice containing data where the zip_codes between 10000 and
      # 20000 has the country "US". For this example, data with the zip_code of
      # 12345 and country "US" will be in this slice.
      #
      # Example 4:
      #
      #     { "country": {"all_values": { "value": true } } }
      #
      # Three slices are computed, one for each unique country in the dataset.
      #
      # Example 5:
      #
      #     {
      #       "country": { "all_values": { "value": true } },
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # Three slices are computed, one for each unique country in the dataset
      # where the zip_code is also 12345. For this example, data with zip_code
      # 12345 and country "US" will be in one slice, zip_code 12345 and country
      # "Canada" in another slice, and zip_code 12345 and country "Mexico" in
      # another slice, totaling 3 slices.
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Value]
      #     A unique specific value for a given feature.
      #     Example: `{ "value": { "string_value": "12345" } }`
      # @!attribute [rw] range
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Range]
      #     A range of values for a numerical feature.
      #     Example: `{"range":{"low":10000.0,"high":50000.0}}`
      #     will capture 12345 and 23334 in the slice.
      # @!attribute [rw] all_values
      #   @return [::Google::Protobuf::BoolValue]
      #     If all_values is set to true, then all possible labels of the keyed
      #     feature will have another slice computed.
      #     Example: `{"all_values":{"value":true}}`
      class SliceConfig
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # A range of values for slice(s).
      # `low` is inclusive, `high` is exclusive.
      # @!attribute [rw] low
      #   @return [::Float]
      #     Inclusive low value for the range.
      # @!attribute [rw] high
      #   @return [::Float]
      #     Exclusive high value for the range.
      class Range
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # Single value that supports strings and floats.
      # @!attribute [rw] string_value
      #   @return [::String]
      #     String type.
      # @!attribute [rw] float_value
      #   @return [::Float]
      #     Float type.
      class Value
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # @!attribute [rw] key
      #   @return [::String]
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig]
      class ConfigsEntry
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end
end

#model_explanation ⇒ ::Google::Cloud::AIPlatform::V1::ModelExplanation (readonly)

Returns Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for tabular Models.

Returns:

  • (::Google::Cloud::AIPlatform::V1::ModelExplanation) —

    Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for tabular Models.



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# File 'proto_docs/google/cloud/aiplatform/v1/model_evaluation_slice.rb', line 53

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

  # Definition of a slice.
  # @!attribute [r] dimension
  #   @return [::String]
  #     Output only. The dimension of the slice.
  #     Well-known dimensions are:
  #       * `annotationSpec`: This slice is on the test data that has either
  #         ground truth or prediction with
  #         {::Google::Cloud::AIPlatform::V1::AnnotationSpec#display_name AnnotationSpec.display_name}
  #         equals to
  #         {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice#value value}.
  #       * `slice`: This slice is a user customized slice defined by its
  #         SliceSpec.
  # @!attribute [r] value
  #   @return [::String]
  #     Output only. The value of the dimension in this slice.
  # @!attribute [r] slice_spec
  #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec]
  #     Output only. Specification for how the data was sliced.
  class Slice
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Specification for how the data should be sliced.
    # @!attribute [rw] configs
    #   @return [::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig}]
    #     Mapping configuration for this SliceSpec.
    #     The key is the name of the feature.
    #     By default, the key will be prefixed by "instance" as a dictionary
    #     prefix for Vertex Batch Predictions output format.
    class SliceSpec
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # Specification message containing the config for this SliceSpec.
      # When `kind` is selected as `value` and/or `range`, only a single slice
      # will be computed.
      # When `all_values` is present, a separate slice will be computed for
      # each possible label/value for the corresponding key in `config`.
      # Examples, with feature zip_code with values 12345, 23334, 88888 and
      # feature country with values "US", "Canada", "Mexico" in the dataset:
      #
      # Example 1:
      #
      #     {
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # A single slice for any data with zip_code 12345 in the dataset.
      #
      # Example 2:
      #
      #     {
      #       "zip_code": { "range": { "low": 12345, "high": 20000 } }
      #     }
      #
      # A single slice containing data where the zip_codes between 12345 and
      # 20000 For this example, data with the zip_code of 12345 will be in this
      # slice.
      #
      # Example 3:
      #
      #     {
      #       "zip_code": { "range": { "low": 10000, "high": 20000 } },
      #       "country": { "value": { "string_value": "US" } }
      #     }
      #
      # A single slice containing data where the zip_codes between 10000 and
      # 20000 has the country "US". For this example, data with the zip_code of
      # 12345 and country "US" will be in this slice.
      #
      # Example 4:
      #
      #     { "country": {"all_values": { "value": true } } }
      #
      # Three slices are computed, one for each unique country in the dataset.
      #
      # Example 5:
      #
      #     {
      #       "country": { "all_values": { "value": true } },
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # Three slices are computed, one for each unique country in the dataset
      # where the zip_code is also 12345. For this example, data with zip_code
      # 12345 and country "US" will be in one slice, zip_code 12345 and country
      # "Canada" in another slice, and zip_code 12345 and country "Mexico" in
      # another slice, totaling 3 slices.
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Value]
      #     A unique specific value for a given feature.
      #     Example: `{ "value": { "string_value": "12345" } }`
      # @!attribute [rw] range
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Range]
      #     A range of values for a numerical feature.
      #     Example: `{"range":{"low":10000.0,"high":50000.0}}`
      #     will capture 12345 and 23334 in the slice.
      # @!attribute [rw] all_values
      #   @return [::Google::Protobuf::BoolValue]
      #     If all_values is set to true, then all possible labels of the keyed
      #     feature will have another slice computed.
      #     Example: `{"all_values":{"value":true}}`
      class SliceConfig
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # A range of values for slice(s).
      # `low` is inclusive, `high` is exclusive.
      # @!attribute [rw] low
      #   @return [::Float]
      #     Inclusive low value for the range.
      # @!attribute [rw] high
      #   @return [::Float]
      #     Exclusive high value for the range.
      class Range
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # Single value that supports strings and floats.
      # @!attribute [rw] string_value
      #   @return [::String]
      #     String type.
      # @!attribute [rw] float_value
      #   @return [::Float]
      #     Float type.
      class Value
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # @!attribute [rw] key
      #   @return [::String]
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig]
      class ConfigsEntry
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end
end

#name ⇒ ::String (readonly)

Returns Output only. The resource name of the ModelEvaluationSlice.

Returns:

  • (::String) —

    Output only. The resource name of the ModelEvaluationSlice.



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# File 'proto_docs/google/cloud/aiplatform/v1/model_evaluation_slice.rb', line 53

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

  # Definition of a slice.
  # @!attribute [r] dimension
  #   @return [::String]
  #     Output only. The dimension of the slice.
  #     Well-known dimensions are:
  #       * `annotationSpec`: This slice is on the test data that has either
  #         ground truth or prediction with
  #         {::Google::Cloud::AIPlatform::V1::AnnotationSpec#display_name AnnotationSpec.display_name}
  #         equals to
  #         {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice#value value}.
  #       * `slice`: This slice is a user customized slice defined by its
  #         SliceSpec.
  # @!attribute [r] value
  #   @return [::String]
  #     Output only. The value of the dimension in this slice.
  # @!attribute [r] slice_spec
  #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec]
  #     Output only. Specification for how the data was sliced.
  class Slice
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Specification for how the data should be sliced.
    # @!attribute [rw] configs
    #   @return [::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig}]
    #     Mapping configuration for this SliceSpec.
    #     The key is the name of the feature.
    #     By default, the key will be prefixed by "instance" as a dictionary
    #     prefix for Vertex Batch Predictions output format.
    class SliceSpec
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # Specification message containing the config for this SliceSpec.
      # When `kind` is selected as `value` and/or `range`, only a single slice
      # will be computed.
      # When `all_values` is present, a separate slice will be computed for
      # each possible label/value for the corresponding key in `config`.
      # Examples, with feature zip_code with values 12345, 23334, 88888 and
      # feature country with values "US", "Canada", "Mexico" in the dataset:
      #
      # Example 1:
      #
      #     {
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # A single slice for any data with zip_code 12345 in the dataset.
      #
      # Example 2:
      #
      #     {
      #       "zip_code": { "range": { "low": 12345, "high": 20000 } }
      #     }
      #
      # A single slice containing data where the zip_codes between 12345 and
      # 20000 For this example, data with the zip_code of 12345 will be in this
      # slice.
      #
      # Example 3:
      #
      #     {
      #       "zip_code": { "range": { "low": 10000, "high": 20000 } },
      #       "country": { "value": { "string_value": "US" } }
      #     }
      #
      # A single slice containing data where the zip_codes between 10000 and
      # 20000 has the country "US". For this example, data with the zip_code of
      # 12345 and country "US" will be in this slice.
      #
      # Example 4:
      #
      #     { "country": {"all_values": { "value": true } } }
      #
      # Three slices are computed, one for each unique country in the dataset.
      #
      # Example 5:
      #
      #     {
      #       "country": { "all_values": { "value": true } },
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # Three slices are computed, one for each unique country in the dataset
      # where the zip_code is also 12345. For this example, data with zip_code
      # 12345 and country "US" will be in one slice, zip_code 12345 and country
      # "Canada" in another slice, and zip_code 12345 and country "Mexico" in
      # another slice, totaling 3 slices.
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Value]
      #     A unique specific value for a given feature.
      #     Example: `{ "value": { "string_value": "12345" } }`
      # @!attribute [rw] range
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Range]
      #     A range of values for a numerical feature.
      #     Example: `{"range":{"low":10000.0,"high":50000.0}}`
      #     will capture 12345 and 23334 in the slice.
      # @!attribute [rw] all_values
      #   @return [::Google::Protobuf::BoolValue]
      #     If all_values is set to true, then all possible labels of the keyed
      #     feature will have another slice computed.
      #     Example: `{"all_values":{"value":true}}`
      class SliceConfig
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # A range of values for slice(s).
      # `low` is inclusive, `high` is exclusive.
      # @!attribute [rw] low
      #   @return [::Float]
      #     Inclusive low value for the range.
      # @!attribute [rw] high
      #   @return [::Float]
      #     Exclusive high value for the range.
      class Range
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # Single value that supports strings and floats.
      # @!attribute [rw] string_value
      #   @return [::String]
      #     String type.
      # @!attribute [rw] float_value
      #   @return [::Float]
      #     Float type.
      class Value
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # @!attribute [rw] key
      #   @return [::String]
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig]
      class ConfigsEntry
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end
end

#slice ⇒ ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice (readonly)

Returns Output only. The slice of the test data that is used to evaluate the Model.

Returns:



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# File 'proto_docs/google/cloud/aiplatform/v1/model_evaluation_slice.rb', line 53

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

  # Definition of a slice.
  # @!attribute [r] dimension
  #   @return [::String]
  #     Output only. The dimension of the slice.
  #     Well-known dimensions are:
  #       * `annotationSpec`: This slice is on the test data that has either
  #         ground truth or prediction with
  #         {::Google::Cloud::AIPlatform::V1::AnnotationSpec#display_name AnnotationSpec.display_name}
  #         equals to
  #         {::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice#value value}.
  #       * `slice`: This slice is a user customized slice defined by its
  #         SliceSpec.
  # @!attribute [r] value
  #   @return [::String]
  #     Output only. The value of the dimension in this slice.
  # @!attribute [r] slice_spec
  #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec]
  #     Output only. Specification for how the data was sliced.
  class Slice
    include ::Google::Protobuf::MessageExts
    extend ::Google::Protobuf::MessageExts::ClassMethods

    # Specification for how the data should be sliced.
    # @!attribute [rw] configs
    #   @return [::Google::Protobuf::Map{::String => ::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig}]
    #     Mapping configuration for this SliceSpec.
    #     The key is the name of the feature.
    #     By default, the key will be prefixed by "instance" as a dictionary
    #     prefix for Vertex Batch Predictions output format.
    class SliceSpec
      include ::Google::Protobuf::MessageExts
      extend ::Google::Protobuf::MessageExts::ClassMethods

      # Specification message containing the config for this SliceSpec.
      # When `kind` is selected as `value` and/or `range`, only a single slice
      # will be computed.
      # When `all_values` is present, a separate slice will be computed for
      # each possible label/value for the corresponding key in `config`.
      # Examples, with feature zip_code with values 12345, 23334, 88888 and
      # feature country with values "US", "Canada", "Mexico" in the dataset:
      #
      # Example 1:
      #
      #     {
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # A single slice for any data with zip_code 12345 in the dataset.
      #
      # Example 2:
      #
      #     {
      #       "zip_code": { "range": { "low": 12345, "high": 20000 } }
      #     }
      #
      # A single slice containing data where the zip_codes between 12345 and
      # 20000 For this example, data with the zip_code of 12345 will be in this
      # slice.
      #
      # Example 3:
      #
      #     {
      #       "zip_code": { "range": { "low": 10000, "high": 20000 } },
      #       "country": { "value": { "string_value": "US" } }
      #     }
      #
      # A single slice containing data where the zip_codes between 10000 and
      # 20000 has the country "US". For this example, data with the zip_code of
      # 12345 and country "US" will be in this slice.
      #
      # Example 4:
      #
      #     { "country": {"all_values": { "value": true } } }
      #
      # Three slices are computed, one for each unique country in the dataset.
      #
      # Example 5:
      #
      #     {
      #       "country": { "all_values": { "value": true } },
      #       "zip_code": { "value": { "float_value": 12345.0 } }
      #     }
      #
      # Three slices are computed, one for each unique country in the dataset
      # where the zip_code is also 12345. For this example, data with zip_code
      # 12345 and country "US" will be in one slice, zip_code 12345 and country
      # "Canada" in another slice, and zip_code 12345 and country "Mexico" in
      # another slice, totaling 3 slices.
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Value]
      #     A unique specific value for a given feature.
      #     Example: `{ "value": { "string_value": "12345" } }`
      # @!attribute [rw] range
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::Range]
      #     A range of values for a numerical feature.
      #     Example: `{"range":{"low":10000.0,"high":50000.0}}`
      #     will capture 12345 and 23334 in the slice.
      # @!attribute [rw] all_values
      #   @return [::Google::Protobuf::BoolValue]
      #     If all_values is set to true, then all possible labels of the keyed
      #     feature will have another slice computed.
      #     Example: `{"all_values":{"value":true}}`
      class SliceConfig
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # A range of values for slice(s).
      # `low` is inclusive, `high` is exclusive.
      # @!attribute [rw] low
      #   @return [::Float]
      #     Inclusive low value for the range.
      # @!attribute [rw] high
      #   @return [::Float]
      #     Exclusive high value for the range.
      class Range
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # Single value that supports strings and floats.
      # @!attribute [rw] string_value
      #   @return [::String]
      #     String type.
      # @!attribute [rw] float_value
      #   @return [::Float]
      #     Float type.
      class Value
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end

      # @!attribute [rw] key
      #   @return [::String]
      # @!attribute [rw] value
      #   @return [::Google::Cloud::AIPlatform::V1::ModelEvaluationSlice::Slice::SliceSpec::SliceConfig]
      class ConfigsEntry
        include ::Google::Protobuf::MessageExts
        extend ::Google::Protobuf::MessageExts::ClassMethods
      end
    end
  end
end