class_docstr: Configuration for the SHAP baseline of the Kernal SHAP algorithm.
docstr: Initialize a config object for SHAP baseline.
  
  Args:
      mime_type (str): Optional. The MIME type of the baseline data. Choose
          from ``"text/csv"`` or ``"application/jsonlines"``. (Default: ``"text/csv"``)
      shap_baseline (str): Optional. The inline SHAP baseline data in string format.
          ShapBaseline can have one or multiple records to be used as the baseline dataset.
          The format of the SHAP baseline file should be the same format as the training
          dataset. For example, if the training dataset is in CSV format and each record
          contains four features, and all features are numerical, then the format of the
          baseline data should also share these characteristics. For NLP of text columns, the
          baseline value should be the value used to replace the unit of text specified by
          the ``granularity`` of the
          :class:`~sagemaker.explainer.clarify_explainer_config.ClarifyTextConfig`
          parameter. The size limit for ``shap_baseline`` is 4 KB. Use the
          ``shap_baseline_uri`` parameter if you want to provide more than 4 KB of baseline
          data.
      shap_baseline_uri (str): Optional. The S3 URI where the SHAP baseline file is stored.
          The format of the SHAP baseline file should be the same format as the format of
          the training dataset. For example, if the training dataset is in CSV format,
          and each record in the training dataset has four features, and all features are
          numerical, then the baseline file should also have this same format. Each record
          should contain only the features. If you are using a virtual private cloud (VPC),
          the ``shap_baseline_uri`` should be accessible to the VPC.
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code: def __init__(
      self,
      mime_type: Optional[str] = "text/csv",
      shap_baseline: Optional[str] = None,
      shap_baseline_uri: Optional[str] = None,
  ):
      """Initialize a config object for SHAP baseline.
  
      Args:
          mime_type (str): Optional. The MIME type of the baseline data. Choose
              from ``"text/csv"`` or ``"application/jsonlines"``. (Default: ``"text/csv"``)
          shap_baseline (str): Optional. The inline SHAP baseline data in string format.
              ShapBaseline can have one or multiple records to be used as the baseline dataset.
              The format of the SHAP baseline file should be the same format as the training
              dataset. For example, if the training dataset is in CSV format and each record
              contains four features, and all features are numerical, then the format of the
              baseline data should also share these characteristics. For NLP of text columns, the
              baseline value should be the value used to replace the unit of text specified by
              the ``granularity`` of the
              :class:`~sagemaker.explainer.clarify_explainer_config.ClarifyTextConfig`
              parameter. The size limit for ``shap_baseline`` is 4 KB. Use the
              ``shap_baseline_uri`` parameter if you want to provide more than 4 KB of baseline
              data.
          shap_baseline_uri (str): Optional. The S3 URI where the SHAP baseline file is stored.
              The format of the SHAP baseline file should be the same format as the format of
              the training dataset. For example, if the training dataset is in CSV format,
              and each record in the training dataset has four features, and all features are
              numerical, then the baseline file should also have this same format. Each record
              should contain only the features. If you are using a virtual private cloud (VPC),
              the ``shap_baseline_uri`` should be accessible to the VPC.
      """
      self.mime_type = mime_type
      self.shap_baseline = shap_baseline
      self.shap_baseline_uri = shap_baseline_uri
  
imports: from __future__ import print_function, absolute_import
  from typing import List, Optional
label_desc: Use image node_id 1 to create a new ClarifyShapBaselineConfig object from inherited base classes: object with example: obj = ClarifyShapBaselineConfig(mime_type, shap_baseline, shap_baseline_uri)