class_docstr: Handle creating, starting and waiting for Amazon SageMaker jobs to finish.
  
  This class shouldn't be directly instantiated.
  
  Subclasses must define a way to create, start and wait for an Amazon
  SageMaker job.
class_docstr_tok: ["Handle","creating",",","starting","and","waiting","for","Amazon","SageMaker","jobs","to","finish",".","This","class","should","n't","be","directly","instantiated",".","Subclasses","must","define","a","way","to","create",",","start","and","wait","for","an","Amazon","SageMaker","job","."]
docstr: Placeholder docstring
docstr_tok: ["Placeholder","docstring"]
code: def _format_inputs_to_input_config(inputs, validate_uri=True):
      """Placeholder docstring"""
      if inputs is None:
          return None
  
      # Deferred import due to circular dependency
      from sagemaker.amazon.amazon_estimator import RecordSet
      from sagemaker.amazon.amazon_estimator import FileSystemRecordSet
  
      if isinstance(inputs, (RecordSet, FileSystemRecordSet)):
          inputs = inputs.data_channel()
  
      input_dict = {}
      if isinstance(inputs, string_types):
          input_dict["training"] = _Job._format_string_uri_input(
              inputs, validate_uri
          )
      elif isinstance(inputs, TrainingInput):
          input_dict["training"] = inputs
      elif isinstance(inputs, file_input):
          input_dict["training"] = inputs
      elif isinstance(inputs, dict):
          for k, v in inputs.items():
              input_dict[k] = _Job._format_string_uri_input(
                  v, validate_uri
              )
      elif isinstance(inputs, list):
          input_dict = _Job._format_record_set_list_input(inputs)
      elif isinstance(inputs, FileSystemInput):
          input_dict["training"] = inputs
      else:
          msg = (
              "Cannot format input {}. Expecting one of str, dict, TrainingInput or "
              "FileSystemInput"
          )
          raise ValueError(msg.format(inputs))
  
      channels = [
          _Job._convert_input_to_channel(name, input)
          for name, input in input_dict.items()
      ]
  
      return channels
  
imports: from __future__ import absolute_import
  from abc import abstractmethod
  from six import string_types
  from sagemaker.inputs import FileSystemInput, TrainingInput
  from sagemaker.local import file_input
  from sagemaker.workflow import is_pipeline_variable
label_desc: Use image node_id 7 for calling the _Job obj's underlying member method code with example usage: obj._format_inputs_to_input_config(inputs, validate_uri) and returns: channels, None