import tensorflow as tf
import tensorflow.keras.layers as l

import generic as g

m = tf.keras.models.Sequential([
    l.Input(shape = (2, 1)),
    l.SimpleRNN(100, activation = "relu", return_sequences = True),
    l.SimpleRNN(100, activation = "relu", return_sequences = True),
    l.SimpleRNN(100, activation = "relu"),
    l.Dense(1)
])
#i = l.Input(shape = (2,))
#h1 = l.SimpleRNN(10, activation = "relu", input_shape = (2, 1))(i)
#o = l.Dense(1)(h1)


#m = tf.keras.models.Model(inputs = i, outputs = o)

m.summary()

#g.train_generic(m, "r3")
g.verify_generic(m, "r3")