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import numpy as np import tensorflow as tf import tensorflow.experimental.numpy as tnp # tf.experimental.numpy inputs = np.arange(6 * 10 * 8).reshape([6, 10, 8]).astype(np.float32) # simple_rnn = tf.keras.layers.SimpleRNN(4) # output = simple_rnn(inputs) # The output has shape `[6, 4]`. simple_rnn = tf.keras.layers.SimpleRNN(4, return_sequences=True, return_state=True) # whole_sequence_output has shape `[6, 10, 4]`. # final_state has shape `[6, 4]`. whole_sequence_output, final_state = simple_rnn(inputs) print(whole_sequence_output) print(final_state)