code: def test_multi_cem_input():
      input1 = Input(shape=(2, 3))
      input2 = Input(shape=(2, 4))
      x = Concatenate()([input1, input2])
      x = Flatten()(x)
      x = Dense(2)(x)
      model = Model(inputs=[input1, input2], outputs=x)
  
      memory = EpisodeParameterMemory(limit=10, window_length=2)
      processor = MultiInputProcessor(nb_inputs=2)
      agent = CEMAgent(
          model,
          memory=memory,
          nb_actions=2,
          nb_steps_warmup=5,
          batch_size=4,
          processor=processor,
          train_interval=50,
      )
      agent.compile()
      agent.fit(MultiInputTestEnv([(3,), (4,)]), nb_steps=100)
  
file_path: keras-rl/tests/rl/agents/test_cem.py
imports: from __future__ import division
  from __future__ import absolute_import
  import pytest
  import numpy
  from numpy.testing import assert_allclose
  from keras.models import Model, Sequential
  from keras.layers import Input, Dense, Flatten, Concatenate
  from rl.agents.cem import CEMAgent
  from rl.memory import EpisodeParameterMemory
  from rl.processors import MultiInputProcessor
  from ..util import MultiInputTestEnv
label_desc: Use image node_id 2 for calling a global function with example usage: test_multi_cem_input() without return types