I would like to train a RNN with LSTM cells in Tensorflow to predict the next word of a sequence. Words are N-length vectors of 0s and 1s. By looking at different tutorials, I saw that the input tensor has a shape like this
seq_input = tf.placeholder(tf.float32, [n_steps, batch_size, seq_width])
However, it is not clear to me what these shapes represent. How do I reshape my input words to match this shape?