runtool/runtool/runtool.py [54:93]:
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        self,
        experiment: Union[Experiments, Experiment],
        experiment_name: str = "default experiment name",
        runs: int = 1,
        job_name_expression: str = None,
        tags: dict = {},
    ) -> Dict[str, str]:
        """
        Execute an Experiment or a Experiments object on SageMaker.

        Parameters
        ----------
        experiment
            A `runtool.datatypes.Experiment` object
        experiment_name
            The name of the experiment
        runs
            Number of times each job should be repeated
        job_name_expression
            A python expression which will be used to set
            the `TrainingJobName` field in the generated JSON.
        tags
            Any tags that should be set in the training job JSON

        Returns
        -------
        Dict
            Dictionary with the training job name as a key and the AWS ARN of the
            training job as a value.
        """
        json_stream = generate_sagemaker_json(
            experiment,
            runs=runs,
            experiment_name=experiment_name,
            job_name_expression=job_name_expression,
            tags=tags,
            creation_time=datetime.utcnow().strftime("%Y-%m-%d-%H-%M-%S"),
            bucket=self.bucket,
            role=self.role,
        )
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runtool/runtool/runtool.py [97:135]:
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        self,
        experiment: Union[Experiments, Experiment],
        experiment_name: str = "default experiment name",
        runs: int = 1,
        job_name_expression: str = None,
        tags: dict = {},
    ) -> Dict[str, str]:
        """
        Summarize jobs which would be created when calling `Client.run`.

        Parameters
        ----------
        experiment
            A `runtool.datatypes.Experiment` object
        experiment_name
            The name of the experiment
        runs
            Number of times each job should be repeated
        job_name_expression
            A python expression which will be used to set
            the `TrainingJobName` field in the generated JSON.
        tags
            Any tags that should be set in the training job JSON

        Returns
        -------
        Pandas.Dataframe
            The dry run table
        """
        json_stream = generate_sagemaker_json(
            experiment,
            runs=runs,
            experiment_name=experiment_name,
            job_name_expression=job_name_expression,
            tags=tags,
            creation_time=datetime.utcnow().strftime("%Y-%m-%d-%H-%M-%S"),
            bucket=self.bucket,
            role=self.role,
        )
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