Package com.google.cloud.aiplatform.v1

Class SmoothGradConfig.Builder

  • All Implemented Interfaces:
    SmoothGradConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
    Enclosing class:
    SmoothGradConfig
    public static final class SmoothGradConfig.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>
implements SmoothGradConfigOrBuilder
     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
    Protobuf type google.cloud.aiplatform.v1.SmoothGradConfig

    • 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<SmoothGradConfig.Builder>

      • clear

        public SmoothGradConfig.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.GeneratedMessageV3.Builder<SmoothGradConfig.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<SmoothGradConfig.Builder>

      • getDefaultInstanceForType

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

      • build

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

      • buildPartial

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

      • clone

        public SmoothGradConfig.Builder clone()
        Specified by:
        clone in interface com.google.protobuf.Message.Builder
        Specified by:
        clone in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        clone in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>

      • setField

        public SmoothGradConfig.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                         Object value)
        Specified by:
        setField in interface com.google.protobuf.Message.Builder
        Overrides:
        setField in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>

      • clearField

        public SmoothGradConfig.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>

      • clearOneof

        public SmoothGradConfig.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>

      • setRepeatedField

        public SmoothGradConfig.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                 int index,
                                                 Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>

      • addRepeatedField

        public SmoothGradConfig.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                 Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>

      • mergeFrom

        public SmoothGradConfig.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<SmoothGradConfig.Builder>

      • isInitialized

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

      • mergeFrom

        public SmoothGradConfig.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<SmoothGradConfig.Builder>
        Throws:
        IOException

      • hasNoiseSigma

        public boolean hasNoiseSigma()
         This is a single float value and will be used to add noise to all the
 features. Use this field when all features are normalized to have the
 same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where
 features are normalized to have 0-mean and 1-variance. Learn more about
 [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization).

 For best results the recommended value is about 10% - 20% of the standard
 deviation of the input feature. Refer to section 3.2 of the SmoothGrad
 paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1.

 If the distribution is different per feature, set
 [feature_noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.feature_noise_sigma]
 instead for each feature.
        float noise_sigma = 1;
        Specified by:
        hasNoiseSigma in interface SmoothGradConfigOrBuilder
        Returns:
        Whether the noiseSigma field is set.

      • getNoiseSigma

        public float getNoiseSigma()
         This is a single float value and will be used to add noise to all the
 features. Use this field when all features are normalized to have the
 same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where
 features are normalized to have 0-mean and 1-variance. Learn more about
 [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization).

 For best results the recommended value is about 10% - 20% of the standard
 deviation of the input feature. Refer to section 3.2 of the SmoothGrad
 paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1.

 If the distribution is different per feature, set
 [feature_noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.feature_noise_sigma]
 instead for each feature.
        float noise_sigma = 1;
        Specified by:
        getNoiseSigma in interface SmoothGradConfigOrBuilder
        Returns:
        The noiseSigma.

      • setNoiseSigma

        public SmoothGradConfig.Builder setNoiseSigma​(float value)
         This is a single float value and will be used to add noise to all the
 features. Use this field when all features are normalized to have the
 same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where
 features are normalized to have 0-mean and 1-variance. Learn more about
 [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization).

 For best results the recommended value is about 10% - 20% of the standard
 deviation of the input feature. Refer to section 3.2 of the SmoothGrad
 paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1.

 If the distribution is different per feature, set
 [feature_noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.feature_noise_sigma]
 instead for each feature.
        float noise_sigma = 1;
        Parameters:
        value - The noiseSigma to set.
        Returns:
        This builder for chaining.

      • clearNoiseSigma

        public SmoothGradConfig.Builder clearNoiseSigma()
         This is a single float value and will be used to add noise to all the
 features. Use this field when all features are normalized to have the
 same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where
 features are normalized to have 0-mean and 1-variance. Learn more about
 [normalization](https://developers.google.com/machine-learning/data-prep/transform/normalization).

 For best results the recommended value is about 10% - 20% of the standard
 deviation of the input feature. Refer to section 3.2 of the SmoothGrad
 paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1.

 If the distribution is different per feature, set
 [feature_noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.feature_noise_sigma]
 instead for each feature.
        float noise_sigma = 1;
        Returns:
        This builder for chaining.

      • hasFeatureNoiseSigma

        public boolean hasFeatureNoiseSigma()
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;
        Specified by:
        hasFeatureNoiseSigma in interface SmoothGradConfigOrBuilder
        Returns:
        Whether the featureNoiseSigma field is set.

      • getFeatureNoiseSigma

        public FeatureNoiseSigma getFeatureNoiseSigma()
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;
        Specified by:
        getFeatureNoiseSigma in interface SmoothGradConfigOrBuilder
        Returns:
        The featureNoiseSigma.

      • setFeatureNoiseSigma

        public SmoothGradConfig.Builder setFeatureNoiseSigma​(FeatureNoiseSigma value)
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;

      • setFeatureNoiseSigma

        public SmoothGradConfig.Builder setFeatureNoiseSigma​(FeatureNoiseSigma.Builder builderForValue)
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;

      • mergeFeatureNoiseSigma

        public SmoothGradConfig.Builder mergeFeatureNoiseSigma​(FeatureNoiseSigma value)
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;

      • clearFeatureNoiseSigma

        public SmoothGradConfig.Builder clearFeatureNoiseSigma()
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;

      • getFeatureNoiseSigmaBuilder

        public FeatureNoiseSigma.Builder getFeatureNoiseSigmaBuilder()
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;

      • getFeatureNoiseSigmaOrBuilder

        public FeatureNoiseSigmaOrBuilder getFeatureNoiseSigmaOrBuilder()
         This is similar to
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma],
 but provides additional flexibility. A separate noise sigma can be
 provided for each feature, which is useful if their distributions are
 different. No noise is added to features that are not set. If this field
 is unset,
 [noise_sigma][google.cloud.aiplatform.v1.SmoothGradConfig.noise_sigma]
 will be used for all features.
        .google.cloud.aiplatform.v1.FeatureNoiseSigma feature_noise_sigma = 2;
        Specified by:
        getFeatureNoiseSigmaOrBuilder in interface SmoothGradConfigOrBuilder

      • getNoisySampleCount

        public int getNoisySampleCount()
         The number of gradient samples to use for
 approximation. The higher this number, the more accurate the gradient
 is, but the runtime complexity increases by this factor as well.
 Valid range of its value is [1, 50]. Defaults to 3.
        int32 noisy_sample_count = 3;
        Specified by:
        getNoisySampleCount in interface SmoothGradConfigOrBuilder
        Returns:
        The noisySampleCount.

      • setNoisySampleCount

        public SmoothGradConfig.Builder setNoisySampleCount​(int value)
         The number of gradient samples to use for
 approximation. The higher this number, the more accurate the gradient
 is, but the runtime complexity increases by this factor as well.
 Valid range of its value is [1, 50]. Defaults to 3.
        int32 noisy_sample_count = 3;
        Parameters:
        value - The noisySampleCount to set.
        Returns:
        This builder for chaining.

      • clearNoisySampleCount

        public SmoothGradConfig.Builder clearNoisySampleCount()
         The number of gradient samples to use for
 approximation. The higher this number, the more accurate the gradient
 is, but the runtime complexity increases by this factor as well.
 Valid range of its value is [1, 50]. Defaults to 3.
        int32 noisy_sample_count = 3;
        Returns:
        This builder for chaining.

      • setUnknownFields

        public final SmoothGradConfig.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>

      • mergeUnknownFields

        public final SmoothGradConfig.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<SmoothGradConfig.Builder>