class_docstr: DatasetDefinition input.
class_docstr_tok: ["DatasetDefinition","input","."]
docstr: Initialize DatasetDefinition.
  
  Parameters:
      data_distribution_type (str, default="ShardedByS3Key"):
          Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
      input_mode (str, default="File"):
          Whether to use File or Pipe input mode. In File (default) mode, Amazon
          SageMaker copies the data from the input source onto the local Amazon Elastic Block
          Store (Amazon EBS) volumes before starting your training algorithm. This is the most
          commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the
          source directly to your algorithm without using the EBS volume.
      local_path (str, default=None):
          The local path where you want Amazon SageMaker to download the Dataset
          Definition inputs to run a processing job. LocalPath is an absolute path to the
          input data. This is a required parameter when `AppManaged` is False (default).
      redshift_dataset_definition
          (:class:`~sagemaker.dataset_definition.inputs.RedshiftDatasetDefinition`,
          default=None):
          Configuration for Redshift Dataset Definition input.
      athena_dataset_definition
          (:class:`~sagemaker.dataset_definition.inputs.AthenaDatasetDefinition`,
          default=None):
          Configuration for Athena Dataset Definition input.
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code: def __init__(
      self,
      data_distribution_type="ShardedByS3Key",
      input_mode="File",
      local_path=None,
      redshift_dataset_definition=None,
      athena_dataset_definition=None,
  ):
      """Initialize DatasetDefinition.
  
      Parameters:
          data_distribution_type (str, default="ShardedByS3Key"):
              Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
          input_mode (str, default="File"):
              Whether to use File or Pipe input mode. In File (default) mode, Amazon
              SageMaker copies the data from the input source onto the local Amazon Elastic Block
              Store (Amazon EBS) volumes before starting your training algorithm. This is the most
              commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the
              source directly to your algorithm without using the EBS volume.
          local_path (str, default=None):
              The local path where you want Amazon SageMaker to download the Dataset
              Definition inputs to run a processing job. LocalPath is an absolute path to the
              input data. This is a required parameter when `AppManaged` is False (default).
          redshift_dataset_definition
              (:class:`~sagemaker.dataset_definition.inputs.RedshiftDatasetDefinition`,
              default=None):
              Configuration for Redshift Dataset Definition input.
          athena_dataset_definition
              (:class:`~sagemaker.dataset_definition.inputs.AthenaDatasetDefinition`,
              default=None):
              Configuration for Athena Dataset Definition input.
      """
      super(DatasetDefinition, self).__init__(
          data_distribution_type=data_distribution_type,
          input_mode=input_mode,
          local_path=local_path,
          redshift_dataset_definition=redshift_dataset_definition,
          athena_dataset_definition=athena_dataset_definition,
      )
  
file_path: sagemaker-python-sdk/src/sagemaker/dataset_definition/inputs.py
imports: from __future__ import absolute_import
  from sagemaker.apiutils._base_types import ApiObject
label_desc: Use image node_id 1 to create a new DatasetDefinition object from inherited base classes: ApiObject with example: obj = DatasetDefinition(data_distribution_type, input_mode, local_path, redshift_dataset_definition, athena_dataset_definition)