I am attempting to write my own basic seq2seq classifier. Im doing this by using tf.nn.dynamic_rnn and the code is shown below. However, there seems to be a problem with the shape of the tensor I'm sending to tf.nn.dynamic_rnn . The reason I'm doing this is because tensorflow's documentation when it comes to seq2seq is very much all over the place.

Running

import numpy as np source_batch = np.random.randint(x_letters, size=[batch_size, x_seq_length]) target_batch = np.random.randint(y_letters, size=[batch_size, y_seq_length+1]) sess.run(tf.global_variables_initializer()) loss = sess.run([loss], feed_dict = {inputs: source_batch, outputs: target_batch[:, :-1], targets: target_batch[:, 1:]})

gives me the error: ValueError: Cannot feed value of shape (128, 10) for Tensor 'decoding/rnn/transpose:0', which has shape '(128, 10, 32)' .

The graph is shown below: