class_docstr: Base class of Amazon SageMaker Explainability API model monitors.
  
  This class is an ``abstract base class``, please instantiate its subclasses
  if you want to monitor bias metrics or feature attribution of an endpoint.
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docstr: Upload analysis config to s3://<output path>/<job name>/analysis_config.json
  
  Args:
      analysis_config (dict): analysis config of a Clarify model monitor.
      output_s3_uri (str): S3 destination of the constraint_violations and analysis result.
          Default: "s3://<default_session_bucket>/<job_name>/output"
      job_definition_name (str): Job definition name.
          If not specified then a default one will be generated.
      kms_key( str): The ARN of the KMS key that is used to encrypt the
      user code file (default: None).
  
  Returns:
      str: The S3 uri of the uploaded file(s).
code: def _upload_analysis_config(
      self, analysis_config, output_s3_uri, job_definition_name, kms_key
  ):
      """Upload analysis config to s3://<output path>/<job name>/analysis_config.json
  
      Args:
          analysis_config (dict): analysis config of a Clarify model monitor.
          output_s3_uri (str): S3 destination of the constraint_violations and analysis result.
              Default: "s3://<default_session_bucket>/<job_name>/output"
          job_definition_name (str): Job definition name.
              If not specified then a default one will be generated.
          kms_key( str): The ARN of the KMS key that is used to encrypt the
          user code file (default: None).
  
      Returns:
          str: The S3 uri of the uploaded file(s).
      """
      s3_uri = s3.s3_path_join(
          output_s3_uri,
          job_definition_name,
          str(uuid.uuid4()),
          "analysis_config.json",
      )
      logger.info("Uploading analysis config to {s3_uri}.")
      return s3.S3Uploader.upload_string_as_file_body(
          json.dumps(analysis_config),
          desired_s3_uri=s3_uri,
          sagemaker_session=self.sagemaker_session,
          kms_key=kms_key,
      )
  
imports: from __future__ import print_function, absolute_import
  import copy
  import json
  import logging
  import uuid
  from sagemaker.model_monitor import model_monitoring
  from sagemaker import image_uris, s3
  from sagemaker.session import Session
  from sagemaker.utils import name_from_base, format_tags
  from sagemaker.clarify import SageMakerClarifyProcessor, ModelPredictedLabelConfig
  from sagemaker.lineage._utils import get_resource_name_from_arn
label_desc: Use image node_id 7 for calling the ClarifyModelMonitor obj's underlying member method code with example usage: obj._upload_analysis_config(analysis_config, output_s3_uri, job_definition_name, kms_key) and returns: s3