def decoded(self) -> tf.Tensor:
if self.beam_width == 1:
decoded, _ = tf.nn.ctc_greedy_decoder(
inputs=self.logits, sequence_length=self.input_lengths,
merge_repeated=self.merge_repeated_outputs)
else:
decoded, _ = tf.nn.ctc_beam_search_decoder(
inputs=self.logits, sequence_length=self.input_lengths,
beam_width=self.beam_width,
merge_repeated=self.merge_repeated_outputs)
return tf.sparse_tensor_to_dense(
tf.sparse_transpose(decoded[0]),
default_value=self.vocabulary.get_word_index(END_TOKEN))
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