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)