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src/sagemaker/workflow/clarify_check_step.py

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@@ -132,8 +132,10 @@ class ModelExplainabilityCheckConfig(ClarifyCheckConfig):
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Attributes:
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model_config (ModelConfig): Config of the model and its endpoint to be created.
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explainability_config (SHAPConfig): Config of the specific explainability method.
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Currently, only SHAP is supported.
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explainability_config (SHAPConfig or PDPConfig): Config of the explainability method.
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Supports SHAP or PDP.
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For `PDPConfig`, `features` must be specified.
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`top_k_features` based on SHAP is currently not supported.
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model_scores (str or int or ModelPredictedLabelConfig): Index or JMESPath expression
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to locate the predicted scores in the model output (default: None).
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This is not required if the model output is a single score. Alternatively,
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):
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"""Constructs a ClarifyCheckStep.
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To understand the `skip_check`, `fail_on_violation`, `register_new_baseline`
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and `supplied_baseline_constraints` parameters, check the following documentation:
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https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html
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Args:
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name (str): The name of the ClarifyCheckStep step.
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clarify_check_config (ClarifyCheckConfig): A ClarifyCheckConfig instance.

src/sagemaker/workflow/quality_check_step.py

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@@ -135,6 +135,11 @@ def __init__(
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):
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"""Constructs a QualityCheckStep.
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To understand the `skip_check`, `fail_on_violation`, `register_new_baseline`,
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`supplied_baseline_constraints` and `supplied_baseline_constraints` parameters,
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check the following documentation:
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https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html
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Args:
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name (str): The name of the QualityCheckStep step.
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quality_check_config (QualityCheckConfig): A QualityCheckConfig instance.

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