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How to use tensorflow seq2seq without embeddings?

I have been working on LSTM for timeseries forecasting by using tensorflow. Now, i want to try sequence to sequence (seq2seq). In the official site there is a tutorial which shows NMT with embeddings . So, how can I use this new seq2seq module without embeddings? (directly using time series "sequences").

# 1. Encoder
encoder_cell = tf.contrib.rnn.BasicLSTMCell(LSTM_SIZE)
encoder_outputs, encoder_state = tf.nn.static_rnn(
  encoder_cell,
  x,
  dtype=tf.float32)

# Decoder
decoder_cell = tf.nn.rnn_cell.BasicLSTMCell(LSTM_SIZE)


helper = tf.contrib.seq2seq.TrainingHelper(
    decoder_emb_inp, decoder_lengths, time_major=True)


decoder = tf.contrib.seq2seq.BasicDecoder(
  decoder_cell, helper, …
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time-series forecasting tensorflow

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forecasting ×1

tensorflow ×1

time-series ×1