lstm_model_cpu_error_example.py

from keras.models import Model
from keras.layers import Input, LSTM
import numpy as np


def model1():

    input_state = Input(shape=(1,))
    input_data = Input(shape=(1, 1))

    output, _, _ = LSTM(1, return_state=True)(input_data, initial_state=[input_state, input_state])

    return Model(inputs=[input_state, input_data], outputs=[output])


def model2():
    input_state = Input(shape=(1,))
    input_data = Input(shape=(1, 1))

    # Using model1 as a layer raises an error:
    output = model1()([input_state, input_data])
    # Using the following line instead gives no error:
    # output, _, _ = LSTM(1, return_state=True)(input_data, initial_state=[input_state, input_state])

    return Model(inputs=[input_state, input_data], outputs=[output])

  
model = model2()

p = model.predict([np.zeros((1,1)), np.zeros((1,1,1))])

print(p)