99754e7c704346c025a21ee61efeda2f7c02a3b3,ludwig/models/modules/sequence_decoders.py,SequenceGeneratorDecoder,decoder_training,#SequenceGeneratorDecoder#Any#Any#Any#Any#Any#,134

Before Change

            sequence_length=None):

        // Prepare correct Decoder input & output sequence data
        decoder_input = target[:, :-1]  // ignore <end>
        a_tx, c_tx = encoder_end_state

        // Decoder Embeddings

After Change

            sequence_length=None):

        // ================ Setup ================
        GO_SYMBOL = self.vocab_size
        END_SYMBOL = 0

        // Prepare correct Decoder input for decoding
        start_tokens = tf.tile([GO_SYMBOL], [batch_size])
        end_tokens = tf.tile([END_SYMBOL], [batch_size])
        if self.is_timeseries:
            start_tokens = tf.cast(start_tokens, tf.float32)
            end_tokens = tf.cast(end_tokens, tf.float32)
        targets_with_go_and_eos = tf.concat([
            tf.expand_dims(start_tokens, 1),
            target,  // todo tf2: right now cast to tf.int32, fails if tf.int64
            tf.expand_dims(end_tokens, 1)], 1)
        sequence_length_with_eos = sequence_length + 1

        // Decoder Embeddings
        decoder_emb_inp = self.decoder_embedding(targets_with_go_and_eos)

Instances