(export_output, tensors)
Clones `export_output` but with new `tensors`.

  Args:
    export_output: an `ExportOutput` object such as `ClassificationOutput`,
      `RegressionOutput`, or `PredictOutput`.
    tensors: a list of `Tensors` used to construct a new `export_output`.

  Returns:
    A dict similar to `export_output` but with `tensors`.

  Raises:
    ValueError: if `export_output` is not one of `ClassificationOutput`,
        `RegressionOutput`, or `PredictOutput`.
Clones `export_output` but with new `tensors`.
Clones export_output but with new tensors .
def _clone_export_output_with_tensors(export_output, tensors):
  """Clones `export_output` but with new `tensors`.

  Args:
    export_output: an `ExportOutput` object such as `ClassificationOutput`,
      `RegressionOutput`, or `PredictOutput`.
    tensors: a list of `Tensors` used to construct a new `export_output`.

  Returns:
    A dict similar to `export_output` but with `tensors`.

  Raises:
    ValueError: if `export_output` is not one of `ClassificationOutput`,
        `RegressionOutput`, or `PredictOutput`.
  """
  if isinstance(export_output, export_output_lib.ClassificationOutput):
    if len(tensors) != 2:
      raise ValueError('tensors must be of length 2; '
                       'got {}.'.format(len(tensors)))
    return export_output_lib.ClassificationOutput(*tensors)
  elif isinstance(export_output, export_output_lib.RegressionOutput):
    if len(tensors) != 1:
      raise ValueError('tensors must be of length 1; '
                       'got {}'.format(len(tensors)))
    return export_output_lib.RegressionOutput(*tensors)
  elif isinstance(export_output, export_output_lib.PredictOutput):
    return export_output_lib.PredictOutput(
        dict(zip(export_output.outputs.keys(), tensors)))
  else:
    raise ValueError(
        '`export_output` must be have type `ClassificationOutput`, '
        '`RegressionOutput`, or `PredictOutput`; got {}.'.format(export_output))
def _clone_export_output_with_tensors ( export_output , tensors ) : if isinstance ( export_output , export_output_lib . ClassificationOutput ) : if len ( tensors ) != 2 : raise ValueError ( 'tensors must be of length 2; ' 'got {}.' . format ( len ( tensors ) ) ) return export_output_lib . ClassificationOutput ( * tensors ) elif isinstance ( export_output , export_output_lib . RegressionOutput ) : if len ( tensors ) != 1 : raise ValueError ( 'tensors must be of length 1; ' 'got {}' . format ( len ( tensors ) ) ) return export_output_lib . RegressionOutput ( * tensors ) elif isinstance ( export_output , export_output_lib . PredictOutput ) : return export_output_lib . PredictOutput ( dict ( zip ( export_output . outputs . keys ( ) , tensors ) ) ) else : raise ValueError ( '`export_output` must be have type `ClassificationOutput`, ' '`RegressionOutput`, or `PredictOutput`; got {}.' . format ( export_output ) )