def create_beam_op(self, models, len_normalization):
self.len_normalization = len_normalization
self.models = models
beam_funs = [model.beam_fun for model in models]
initial_data = [model.initial_data for model in models]
beam_output = beam_search.rnn_beam_search(beam_funs, initial_data, self.max_output_len[0], self.beam_size,
len_normalization, temperature=self.temperature,
parallel_iterations=self.decoders[0].parallel_iterations,
swap_memory=self.decoders[0].swap_memory)
self.beam_outputs, self.beam_scores = beam_output
def create_beam_op(self, models, beam_size, len_normalization, early_stopping=True):
self.beam_size = beam_size
self.len_normalization = len_normalization
self.models = models
if beam_size > 1 or len(models) > 1:
beam_funs = [model.beam_fun for model in models]
initial_data = [model.initial_data for model in models]
beam_output = beam_search.rnn_beam_search(beam_funs, initial_data, self.max_output_len[0], beam_size,
len_normalization, early_stopping, temperature=self.temperature)
self.beam_outputs, self.beam_scores = beam_output