Package com.google.cloud.aiplatform.v1

Class ExplanationMetadata.InputMetadata.Visualization.Builder

    • Method Detail

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>

      • getDefaultInstanceForType

        public ExplanationMetadata.InputMetadata.Visualization getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

      • buildPartial

        public ExplanationMetadata.InputMetadata.Visualization buildPartial()
        Specified by:
        buildPartial in interface com.google.protobuf.Message.Builder
        Specified by:
        buildPartial in interface com.google.protobuf.MessageLite.Builder

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.InputMetadata.Visualization.Builder>

      • getTypeValue

        public int getTypeValue()
         Type of the image visualization. Only applicable to
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution].
 OUTLINES shows regions of attribution, while PIXELS shows per-pixel
 attribution. Defaults to OUTLINES.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
        Specified by:
        getTypeValue in interface ExplanationMetadata.InputMetadata.VisualizationOrBuilder
        Returns:
        The enum numeric value on the wire for type.

      • setTypeValue

        public ExplanationMetadata.InputMetadata.Visualization.Builder setTypeValue​(int value)
         Type of the image visualization. Only applicable to
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution].
 OUTLINES shows regions of attribution, while PIXELS shows per-pixel
 attribution. Defaults to OUTLINES.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
        Parameters:
        value - The enum numeric value on the wire for type to set.
        Returns:
        This builder for chaining.

      • setType

        public ExplanationMetadata.InputMetadata.Visualization.Builder setType​(ExplanationMetadata.InputMetadata.Visualization.Type value)
         Type of the image visualization. Only applicable to
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution].
 OUTLINES shows regions of attribution, while PIXELS shows per-pixel
 attribution. Defaults to OUTLINES.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
        Parameters:
        value - The type to set.
        Returns:
        This builder for chaining.

      • clearType

        public ExplanationMetadata.InputMetadata.Visualization.Builder clearType()
         Type of the image visualization. Only applicable to
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution].
 OUTLINES shows regions of attribution, while PIXELS shows per-pixel
 attribution. Defaults to OUTLINES.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Type type = 1;
        Returns:
        This builder for chaining.

      • getPolarityValue

        public int getPolarityValue()
         Whether to only highlight pixels with positive contributions, negative
 or both. Defaults to POSITIVE.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
        Specified by:
        getPolarityValue in interface ExplanationMetadata.InputMetadata.VisualizationOrBuilder
        Returns:
        The enum numeric value on the wire for polarity.

      • setPolarityValue

        public ExplanationMetadata.InputMetadata.Visualization.Builder setPolarityValue​(int value)
         Whether to only highlight pixels with positive contributions, negative
 or both. Defaults to POSITIVE.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
        Parameters:
        value - The enum numeric value on the wire for polarity to set.
        Returns:
        This builder for chaining.

      • clearPolarity

        public ExplanationMetadata.InputMetadata.Visualization.Builder clearPolarity()
         Whether to only highlight pixels with positive contributions, negative
 or both. Defaults to POSITIVE.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.Polarity polarity = 2;
        Returns:
        This builder for chaining.

      • getColorMapValue

        public int getColorMapValue()
         The color scheme used for the highlighted areas.

 Defaults to PINK_GREEN for
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution],
 which shows positive attributions in green and negative in pink.

 Defaults to VIRIDIS for
 [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution],
 which highlights the most influential regions in yellow and the least
 influential in blue.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
        Specified by:
        getColorMapValue in interface ExplanationMetadata.InputMetadata.VisualizationOrBuilder
        Returns:
        The enum numeric value on the wire for colorMap.

      • setColorMapValue

        public ExplanationMetadata.InputMetadata.Visualization.Builder setColorMapValue​(int value)
         The color scheme used for the highlighted areas.

 Defaults to PINK_GREEN for
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution],
 which shows positive attributions in green and negative in pink.

 Defaults to VIRIDIS for
 [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution],
 which highlights the most influential regions in yellow and the least
 influential in blue.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
        Parameters:
        value - The enum numeric value on the wire for colorMap to set.
        Returns:
        This builder for chaining.

      • getColorMap

        public ExplanationMetadata.InputMetadata.Visualization.ColorMap getColorMap()
         The color scheme used for the highlighted areas.

 Defaults to PINK_GREEN for
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution],
 which shows positive attributions in green and negative in pink.

 Defaults to VIRIDIS for
 [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution],
 which highlights the most influential regions in yellow and the least
 influential in blue.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
        Specified by:
        getColorMap in interface ExplanationMetadata.InputMetadata.VisualizationOrBuilder
        Returns:
        The colorMap.

      • setColorMap

        public ExplanationMetadata.InputMetadata.Visualization.Builder setColorMap​(ExplanationMetadata.InputMetadata.Visualization.ColorMap value)
         The color scheme used for the highlighted areas.

 Defaults to PINK_GREEN for
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution],
 which shows positive attributions in green and negative in pink.

 Defaults to VIRIDIS for
 [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution],
 which highlights the most influential regions in yellow and the least
 influential in blue.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
        Parameters:
        value - The colorMap to set.
        Returns:
        This builder for chaining.

      • clearColorMap

        public ExplanationMetadata.InputMetadata.Visualization.Builder clearColorMap()
         The color scheme used for the highlighted areas.

 Defaults to PINK_GREEN for
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution],
 which shows positive attributions in green and negative in pink.

 Defaults to VIRIDIS for
 [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution],
 which highlights the most influential regions in yellow and the least
 influential in blue.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.ColorMap color_map = 3;
        Returns:
        This builder for chaining.

      • getClipPercentUpperbound

        public float getClipPercentUpperbound()
         Excludes attributions above the specified percentile from the
 highlighted areas. Using the clip_percent_upperbound and
 clip_percent_lowerbound together can be useful for filtering out noise
 and making it easier to see areas of strong attribution. Defaults to
 99.9.
        float clip_percent_upperbound = 4;
        Specified by:
        getClipPercentUpperbound in interface ExplanationMetadata.InputMetadata.VisualizationOrBuilder
        Returns:
        The clipPercentUpperbound.

      • setClipPercentUpperbound

        public ExplanationMetadata.InputMetadata.Visualization.Builder setClipPercentUpperbound​(float value)
         Excludes attributions above the specified percentile from the
 highlighted areas. Using the clip_percent_upperbound and
 clip_percent_lowerbound together can be useful for filtering out noise
 and making it easier to see areas of strong attribution. Defaults to
 99.9.
        float clip_percent_upperbound = 4;
        Parameters:
        value - The clipPercentUpperbound to set.
        Returns:
        This builder for chaining.

      • clearClipPercentUpperbound

        public ExplanationMetadata.InputMetadata.Visualization.Builder clearClipPercentUpperbound()
         Excludes attributions above the specified percentile from the
 highlighted areas. Using the clip_percent_upperbound and
 clip_percent_lowerbound together can be useful for filtering out noise
 and making it easier to see areas of strong attribution. Defaults to
 99.9.
        float clip_percent_upperbound = 4;
        Returns:
        This builder for chaining.

      • setClipPercentLowerbound

        public ExplanationMetadata.InputMetadata.Visualization.Builder setClipPercentLowerbound​(float value)
         Excludes attributions below the specified percentile, from the
 highlighted areas. Defaults to 62.
        float clip_percent_lowerbound = 5;
        Parameters:
        value - The clipPercentLowerbound to set.
        Returns:
        This builder for chaining.

      • clearClipPercentLowerbound

        public ExplanationMetadata.InputMetadata.Visualization.Builder clearClipPercentLowerbound()
         Excludes attributions below the specified percentile, from the
 highlighted areas. Defaults to 62.
        float clip_percent_lowerbound = 5;
        Returns:
        This builder for chaining.

      • getOverlayTypeValue

        public int getOverlayTypeValue()
         How the original image is displayed in the visualization.
 Adjusting the overlay can help increase visual clarity if the original
 image makes it difficult to view the visualization. Defaults to NONE.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;
        Specified by:
        getOverlayTypeValue in interface ExplanationMetadata.InputMetadata.VisualizationOrBuilder
        Returns:
        The enum numeric value on the wire for overlayType.

      • setOverlayTypeValue

        public ExplanationMetadata.InputMetadata.Visualization.Builder setOverlayTypeValue​(int value)
         How the original image is displayed in the visualization.
 Adjusting the overlay can help increase visual clarity if the original
 image makes it difficult to view the visualization. Defaults to NONE.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;
        Parameters:
        value - The enum numeric value on the wire for overlayType to set.
        Returns:
        This builder for chaining.

      • clearOverlayType

        public ExplanationMetadata.InputMetadata.Visualization.Builder clearOverlayType()
         How the original image is displayed in the visualization.
 Adjusting the overlay can help increase visual clarity if the original
 image makes it difficult to view the visualization. Defaults to NONE.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization.OverlayType overlay_type = 6;
        Returns:
        This builder for chaining.