class_docstr: Class to store results from the matcher.
  
  This class is used to store the results from the matcher. It provides
  convenient methods to query the matching results.
docstr: Gathers elements from `input_tensor` based on match results.
  
  For columns that are matched to a row, gathered_tensor[col] is set to
  input_tensor[match_results[col]]. For columns that are unmatched,
  gathered_tensor[col] is set to unmatched_value. Finally, for columns that
  are ignored gathered_tensor[col] is set to ignored_value.
  
  Note that the input_tensor.shape[1:] must match with unmatched_value.shape
  and ignored_value.shape
  
  Args:
    input_tensor: Tensor to gather values from.
    unmatched_value: Constant tensor value for unmatched columns.
    ignored_value: Constant tensor value for ignored columns.
  
  Returns:
    gathered_tensor: A tensor containing values gathered from input_tensor.
      The shape of the gathered tensor is [match_results.shape[0]] +
      input_tensor.shape[1:].
docstr_tok: ["Gathers","elements","from","`","input_tensor","`","based","on","match","results",".","For","columns","that","are","matched","to","a","row",",","gathered_tensor","[","col","]","is","set","to","input_tensor","[","match_results","[","col","]","]",".","For","columns","that","are","unmatched",",","gathered_tensor","[","col","]","is","set","to","unmatched_value",".","Finally",",","for","columns","that","are","ignored","gathered_tensor","[","col","]","is","set","to","ignored_value",".","Note","that","the","input_tensor.shape","[","1",":","]","must","match","with","unmatched_value.shape","and","ignored_value.shape","Args",":","input_tensor",":","Tensor","to","gather","values","from",".","unmatched_value",":","Constant","tensor","value","for","unmatched","columns",".","ignored_value",":","Constant","tensor","value","for","ignored","columns",".","Returns",":","gathered_tensor",":","A","tensor","containing","values","gathered","from","input_tensor",".","The","shape","of","the","gathered","tensor","is","[","match_results.shape","[","0","]","]","+","input_tensor.shape","[","1",":","]","."]
code: def gather_based_on_match(
      self, input_tensor, unmatched_value, ignored_value
  ):
      """Gathers elements from `input_tensor` based on match results.
  
      For columns that are matched to a row, gathered_tensor[col] is set to
      input_tensor[match_results[col]]. For columns that are unmatched,
      gathered_tensor[col] is set to unmatched_value. Finally, for columns that
      are ignored gathered_tensor[col] is set to ignored_value.
  
      Note that the input_tensor.shape[1:] must match with unmatched_value.shape
      and ignored_value.shape
  
      Args:
        input_tensor: Tensor to gather values from.
        unmatched_value: Constant tensor value for unmatched columns.
        ignored_value: Constant tensor value for ignored columns.
  
      Returns:
        gathered_tensor: A tensor containing values gathered from input_tensor.
          The shape of the gathered tensor is [match_results.shape[0]] +
          input_tensor.shape[1:].
      """
      input_tensor = tf.concat(
          [tf.stack([ignored_value, unmatched_value]), input_tensor],
          axis=0,
      )
      gather_indices = tf.maximum(self.match_results + 2, 0)
      gathered_tensor = tf.gather(input_tensor, gather_indices)
      return gathered_tensor
  
imports: import abc
  import tensorflow.compat.v1
label_desc: Use image node_id 15 for calling the Match obj's underlying member method code with example usage: obj.gather_based_on_match(input_tensor, unmatched_value, ignored_value) and returns: gathered_tensor