Class: Google::Cloud::AIPlatform::V1::IntegratedGradientsAttribution

Inherits:

Object

• Object
• Google::Cloud::AIPlatform::V1::IntegratedGradientsAttribution

Extended by:

Protobuf::MessageExts::ClassMethods

Includes:

Protobuf::MessageExts

Defined in:

proto_docs/google/cloud/aiplatform/v1/explanation.rb

Overview

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

Instance Attribute Summary

• #blur_baseline_config ⇒ ::Google::Cloud::AIPlatform::V1::BlurBaselineConfig

  Config for IG with blur baseline.

• #smooth_grad_config ⇒ ::Google::Cloud::AIPlatform::V1::SmoothGradConfig

  Config for SmoothGrad approximation of gradients.

• #step_count ⇒ ::Integer

  Required.

Instance Attribute Details

#blur_baseline_config ⇒ ::Google::Cloud::AIPlatform::V1::BlurBaselineConfig

Returns 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.

Returns:

• (::Google::Cloud::AIPlatform::V1::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

# File 'proto_docs/google/cloud/aiplatform/v1/explanation.rb', line 325

class IntegratedGradientsAttribution
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods
end

#smooth_grad_config ⇒ ::Google::Cloud::AIPlatform::V1::SmoothGradConfig

Returns 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:

• (::Google::Cloud::AIPlatform::V1::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

# File 'proto_docs/google/cloud/aiplatform/v1/explanation.rb', line 325

class IntegratedGradientsAttribution
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods
end

#step_count ⇒ ::Integer

Returns 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 within the desired error range.

Valid range of its value is [1, 100], inclusively.

Returns:

• (::Integer) —

  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 within the desired error range.

  Valid range of its value is [1, 100], inclusively.

# File 'proto_docs/google/cloud/aiplatform/v1/explanation.rb', line 325

class IntegratedGradientsAttribution
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods
end