你好，之前的错误是因为numpy的版本错误，纠正版本后，仍然有报错，如下：（一定要安装cuda库吗？我的机器是云上虚拟机，没有cuda设备）

2023-02-11 05:01:10.764147: E tensorflow/compiler/xla/stream_executor/cuda/cuda_driver.cc:267] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected 2023-02-11 05:01:10.764322: I tensorflow/compiler/xla/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (qinh154): /proc/driver/nvidia/version does not exist numpy() is only available when eager execution is enabled. Traceback (most recent call last): File "/mnt/disk01/hadb-opengauss/opengauss/bin/dbmind/components/xtuner/tuner/main.py", line 262, in main return procedure_main(mode, db_info, config) File "/mnt/disk01/hadb-opengauss/opengauss/bin/dbmind/components/xtuner/tuner/xtuner.py", line 130, in procedure_main rl_model('train', env, config) File "/mnt/disk01/hadb-opengauss/opengauss/bin/dbmind/components/xtuner/tuner/xtuner.py", line 174, in rl_model rl = RLAgent(env, alg=config['rl_algorithm']) File "/mnt/disk01/hadb-opengauss/opengauss/bin/dbmind/components/xtuner/tuner/algorithms/rl_agent.py", line 33, in __init__ self.agent = self._build_ddpg(nb_actions, nb_states) File "/mnt/disk01/hadb-opengauss/opengauss/bin/dbmind/components/xtuner/tuner/algorithms/rl_agent.py", line 94, in _build_ddpg ddpg.compile(Adam(), metrics=['mae']) File "/mnt/disk01/hadb-opengauss/python3/lib/python3.8/site-packages/rl/agents/ddpg.py", line 79, in compile critic_optimizer = clone_optimizer(optimizer) File "/mnt/disk01/hadb-opengauss/python3/lib/python3.8/site-packages/rl/util.py", line 25, in clone_optimizer params = {k: v for k, v in optimizer.get_config().items()} File "/mnt/disk01/hadb-opengauss/python3/lib/python3.8/site-packages/keras/optimizers/optimizer_experimental/adam.py", line 207, in get_config "learning_rate": self._serialize_hyperparameter( File "/mnt/disk01/hadb-opengauss/python3/lib/python3.8/site-packages/keras/optimizers/optimizer_experimental/optimizer.py", line 718, in _serialize_hyperparameter return hyperparameter.numpy()

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