Element type inference doesn't work for multi-output DoFns

import apache_beam as beam

class TripleDoFn(beam.DoFn):
  def process(self, elem):
    yield_elem
    if elem % 2 == 0:
      yield beam.pvalue.TaggedOutput('ten_times', elem * 10)
    if elem % 3 == 0:
      yield beam.pvalue.TaggedOutput('hundred_times', elem * 100)
      
@beam.typehints.with_input_types(int)
@beam.typehints.with_output_types(int)
class MultiplyBy(beam.DoFn):
  def __init__(self, multiplier):
    self._multiplier = multiplier

  def process(self, elem):
    return elem * self._multiplier
  
def main():
  with beam.Pipeline() as p:
    x, a, b = (
      p
      | 'Create' >> beam.Create([1, 2, 3])
      | 'TripleDo' >> beam.ParDo(TripleDoFn()).with_outputs(
        'ten_times', 'hundred_times', main='main_output'))

    _ = a | 'MultiplyBy2' >> beam.ParDo(MultiplyBy(2))

if __name__ == '__main__':
  main()