code: def test_single_ddpg_input():
      nb_actions = 2
  
      actor = Sequential()
      actor.add(Flatten(input_shape=(2, 3)))
      actor.add(Dense(nb_actions))
  
      action_input = Input(shape=(nb_actions,), name="action_input")
      observation_input = Input(shape=(2, 3), name="observation_input")
      x = Concatenate()([action_input, Flatten()(observation_input)])
      x = Dense(1)(x)
      critic = Model(
          inputs=[action_input, observation_input], outputs=x
      )
  
      memory = SequentialMemory(limit=10, window_length=2)
      agent = DDPGAgent(
          actor=actor,
          critic=critic,
          critic_action_input=action_input,
          memory=memory,
          nb_actions=2,
          nb_steps_warmup_critic=5,
          nb_steps_warmup_actor=5,
          batch_size=4,
      )
      agent.compile("sgd")
      agent.fit(MultiInputTestEnv((3,)), nb_steps=10)
  
file_path: keras-rl/tests/rl/agents/test_ddpg.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.ddpg import DDPGAgent
  from rl.memory import SequentialMemory
  from rl.processors import MultiInputProcessor
  from ..util import MultiInputTestEnv
label_desc: Use image node_id 1 for calling a global function with example usage: test_single_ddpg_input() without return types