Package com.google.cloud.aiplatform.v1

Class XraiAttribution.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<XraiAttribution.Builder>
com.google.cloud.aiplatform.v1.XraiAttribution.Builder
All Implemented Interfaces:
XraiAttributionOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
XraiAttribution
public static final class XraiAttribution.Builder extends com.google.protobuf.GeneratedMessage.Builder<XraiAttribution.Builder> implements XraiAttributionOrBuilder
 An explanation method that redistributes Integrated Gradients
 attributions to segmented regions, taking advantage of the model's fully
 differentiable structure. Refer to this paper for more details:
 https://arxiv.org/abs/1906.02825

 Supported only by image Models.
Protobuf type google.cloud.aiplatform.v1.XraiAttribution

  • Method Details

    • getDescriptor

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

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<XraiAttribution.Builder>

    • clear

      public XraiAttribution.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<XraiAttribution.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.GeneratedMessage.Builder<XraiAttribution.Builder>

    • getDefaultInstanceForType

      public XraiAttribution getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public XraiAttribution build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

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

    • mergeFrom

      public XraiAttribution.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<XraiAttribution.Builder>

    • mergeFrom

      public XraiAttribution.Builder mergeFrom(XraiAttribution other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<XraiAttribution.Builder>

    • mergeFrom

      public XraiAttribution.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<XraiAttribution.Builder>
      Throws:
      IOException

    • getStepCount

      public int getStepCount()
       Required. The number of steps for approximating the path integral.
 A good value to start is 50 and gradually increase until the
 sum to diff property is met within the desired error range.

 Valid range of its value is [1, 100], inclusively.
      int32 step_count = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getStepCount in interface XraiAttributionOrBuilder
      Returns:
      The stepCount.

    • setStepCount

      public XraiAttribution.Builder setStepCount(int value)
       Required. The number of steps for approximating the path integral.
 A good value to start is 50 and gradually increase until the
 sum to diff property is met within the desired error range.

 Valid range of its value is [1, 100], inclusively.
      int32 step_count = 1 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The stepCount to set.
      Returns:
      This builder for chaining.

    • clearStepCount

      public XraiAttribution.Builder clearStepCount()
       Required. The number of steps for approximating the path integral.
 A good value to start is 50 and gradually increase until the
 sum to diff property is met within the desired error range.

 Valid range of its value is [1, 100], inclusively.
      int32 step_count = 1 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      This builder for chaining.

    • hasSmoothGradConfig

      public boolean hasSmoothGradConfig()
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;
      Specified by:
      hasSmoothGradConfig in interface XraiAttributionOrBuilder
      Returns:
      Whether the smoothGradConfig field is set.

    • getSmoothGradConfig

      public SmoothGradConfig getSmoothGradConfig()
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;
      Specified by:
      getSmoothGradConfig in interface XraiAttributionOrBuilder
      Returns:
      The smoothGradConfig.

    • setSmoothGradConfig

      public XraiAttribution.Builder setSmoothGradConfig(SmoothGradConfig value)
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;

    • setSmoothGradConfig

      public XraiAttribution.Builder setSmoothGradConfig(SmoothGradConfig.Builder builderForValue)
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;

    • mergeSmoothGradConfig

      public XraiAttribution.Builder mergeSmoothGradConfig(SmoothGradConfig value)
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;

    • clearSmoothGradConfig

      public XraiAttribution.Builder clearSmoothGradConfig()
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;

    • getSmoothGradConfigBuilder

      public SmoothGradConfig.Builder getSmoothGradConfigBuilder()
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;

    • getSmoothGradConfigOrBuilder

      public SmoothGradConfigOrBuilder getSmoothGradConfigOrBuilder()
       Config for SmoothGrad approximation of gradients.

 When enabled, the gradients are approximated by averaging the gradients
 from noisy samples in the vicinity of the inputs. Adding
 noise can help improve the computed gradients. Refer to this paper for more
 details: https://arxiv.org/pdf/1706.03825.pdf
      .google.cloud.aiplatform.v1.SmoothGradConfig smooth_grad_config = 2;
      Specified by:
      getSmoothGradConfigOrBuilder in interface XraiAttributionOrBuilder

    • hasBlurBaselineConfig

      public boolean hasBlurBaselineConfig()
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;
      Specified by:
      hasBlurBaselineConfig in interface XraiAttributionOrBuilder
      Returns:
      Whether the blurBaselineConfig field is set.

    • getBlurBaselineConfig

      public BlurBaselineConfig getBlurBaselineConfig()
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;
      Specified by:
      getBlurBaselineConfig in interface XraiAttributionOrBuilder
      Returns:
      The blurBaselineConfig.

    • setBlurBaselineConfig

      public XraiAttribution.Builder setBlurBaselineConfig(BlurBaselineConfig value)
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;

    • setBlurBaselineConfig

      public XraiAttribution.Builder setBlurBaselineConfig(BlurBaselineConfig.Builder builderForValue)
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;

    • mergeBlurBaselineConfig

      public XraiAttribution.Builder mergeBlurBaselineConfig(BlurBaselineConfig value)
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;

    • clearBlurBaselineConfig

      public XraiAttribution.Builder clearBlurBaselineConfig()
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;

    • getBlurBaselineConfigBuilder

      public BlurBaselineConfig.Builder getBlurBaselineConfigBuilder()
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;

    • getBlurBaselineConfigOrBuilder

      public BlurBaselineConfigOrBuilder getBlurBaselineConfigOrBuilder()
       Config for XRAI with blur baseline.

 When enabled, a linear path from the maximally blurred image to the input
 image is created. Using a blurred baseline instead of zero (black image) is
 motivated by the BlurIG approach explained here:
 https://arxiv.org/abs/2004.03383
      .google.cloud.aiplatform.v1.BlurBaselineConfig blur_baseline_config = 3;
      Specified by:
      getBlurBaselineConfigOrBuilder in interface XraiAttributionOrBuilder