Google Cloud Ai Platform V1 Client - Class XraiAttribution (1.35.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class XraiAttribution.

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.

Generated from protobuf message google.cloud.aiplatform.v1.XraiAttribution

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name Description
data array

Optional. Data for populating the Message object.
↳ step_count int

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.
↳ smooth_grad_config 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
↳ blur_baseline_config BlurBaselineConfig

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

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.

Returns
Type Description
int

setStepCount

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.

Parameter
Name Description
var int
Returns
Type Description
$this

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

Returns
Type Description
SmoothGradConfig|null

hasSmoothGradConfig

clearSmoothGradConfig

setSmoothGradConfig

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

Parameter
Name Description
var SmoothGradConfig
Returns
Type Description
$this

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

Returns
Type Description
BlurBaselineConfig|null

hasBlurBaselineConfig

clearBlurBaselineConfig

setBlurBaselineConfig

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

Parameter
Name Description
var BlurBaselineConfig
Returns
Type Description
$this