GoogleCloudAiplatformV1IntegratedGradientsAttributionResponse class

An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

Constructors

GoogleCloudAiplatformV1IntegratedGradientsAttributionResponse({required Input<GoogleCloudAiplatformV1BlurBaselineConfigResponse> blurBaselineConfig, required Input<GoogleCloudAiplatformV1SmoothGradConfigResponse> smoothGradConfig, required Input<int> stepCount})
Creates a new GoogleCloudAiplatformV1IntegratedGradientsAttributionResponse. blurBaselineConfig Config for IG 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 smoothGradConfig 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 stepCount 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 within the desired error range. Valid range of its value is 1, 100, inclusively.
const
GoogleCloudAiplatformV1IntegratedGradientsAttributionResponse.fromMap(Map<String, dynamic> map)
factory

Properties

blurBaselineConfig → Input<GoogleCloudAiplatformV1BlurBaselineConfigResponse>
Config for IG 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
final
hashCode → int
The hash code for this object.
no setterinherited
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited
smoothGradConfig → Input<GoogleCloudAiplatformV1SmoothGradConfigResponse>
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
final
stepCount → Input<int>
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 within the desired error range. Valid range of its value is 1, 100, inclusively.
final

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toMap() → Map<String, dynamic>
toString() → String
A string representation of this object.
inherited

Operators

operator ==(Object other) → bool
The equality operator.
inherited