original_docstring: 
          This function output information that
           guides the formating of input features. 
  
          Input description:
            `output_type` determine where to assign the formatting 
            information. 
            When output_type == 'data_convertor', it produces a function to 
              convert the data into the input feature space. 
            When output_type == 'tf_type', it produces a dict containing 
              the tf_type information of the input features. 
            When output_type == 'tf_shape', it produces a dict containing 
              the shape information of the input features. 
          
docstring: This function output information that
  guides the formating of input features.
  
  Input description:
  `output_type` determine where to assign the formatting
  information.
  When output_type == 'data_convertor', it produces a function to
  convert the data into the input feature space.
  When output_type == 'tf_type', it produces a dict containing
  the tf_type information of the input features.
  When output_type == 'tf_shape', it produces a dict containing
  the shape information of the input features.
docstring_tokens: This function output information that guides the formating of input features . Input description : ` output_type ` determine where to assign the formatting information . When output_type == ' data_convertor ' it produces a function to convert the data into the input feature space . When output_type == ' tf_type ' it produces a dict containing the tf_type information of the input features . When output_type == ' tf_shape ' it produces a dict containing the shape information of the input features .
code: def input_formatter(output_type):
          '''
          This function output information that
           guides the formating of input features. 
  
          Input description:
            `output_type` determine where to assign the formatting 
            information. 
            When output_type == 'data_convertor', it produces a function to 
              convert the data into the input feature space. 
            When output_type == 'tf_type', it produces a dict containing 
              the tf_type information of the input features. 
            When output_type == 'tf_shape', it produces a dict containing 
              the shape information of the input features. 
          '''
          if output_type == 'data_convertor':
              return lambda x: {'token_ids': x['token_ids'],
                                'segment_ids': x['segment_ids'],
                                'mask_ids': x['mask_ids']}
          elif output_type == 'tf_type':
              return {'token_ids': tf.int32,
                      'segment_ids': tf.int32,
                      'mask_ids': tf.int32}
          elif output_type == 'tf_shape':
              return {'token_ids': tf.TensorShape([512]),
                      'segment_ids': tf.TensorShape([512]),
                      'mask_ids': tf.TensorShape([512])}
code_tokens: def input_formatter ( output_type ) : if output_type == 'data_convertor' : return lambda x : { 'token_ids' : x [ 'token_ids' ] , 'segment_ids' : x [ 'segment_ids' ] , 'mask_ids' : x [ 'mask_ids' ] } elif output_type == 'tf_type' : return { 'token_ids' : tf . int32 , 'segment_ids' : tf . int32 , 'mask_ids' : tf . int32 } elif output_type == 'tf_shape' : return { 'token_ids' : tf . TensorShape ( [ 512 ] ) , 'segment_ids' : tf . TensorShape ( [ 512 ] ) , 'mask_ids' : tf . TensorShape ( [ 512 ] ) }
short_docstring: This function output information that
  guides the formating of input features.
short_docstring_tokens: This function output information that guides the formating of input features .
comment: '''
          This function output information that
           guides the formating of input features. 
  
          Input description:
            `output_type` determine where to assign the formatting 
            information. 
            When output_type == 'data_convertor', it produces a function to 
              convert the data into the input feature space. 
            When output_type == 'tf_type', it produces a dict containing 
              the tf_type information of the input features. 
            When output_type == 'tf_shape', it produces a dict containing 
              the shape information of the input features. 
          '''