def test_soak(self): state_shape = (50, 50, 6) rm = ReplayMemory(self.sess, buffer_size=10000, state_shape=state_shape, action_dim=2, load_factor=1.5) self.sess.run(tf.initialize_all_variables()) def s_for(i): return np.random.random(state_shape) import random i = 0 for e in xrange(10000): # add an episode to rm episode_len = random.choice([5, 7, 9, 10, 15]) initial_state = s_for(i) action_reward_state = [] for i in range(i + 1, i + episode_len + 1): a, r, s2 = (i * 10) + 7, (i * 10) + 8, s_for(i) action_reward_state.append((a, r, s2)) rm.add_episode(initial_state, action_reward_state) i += episode_len + 1 # dump print rm.current_stats() # fetch a batch, of all items, but do nothing with it. _ = rm.batch(idxs=range(10))