2021-08-11 22:09:32,774 ERROR trial_runner.py:482 -- Error processing event.
Traceback (most recent call last):
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/tune/trial_runner.py", line 426, in _process_trial
result = self.trial_executor.fetch_result(trial)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/tune/ray_trial_executor.py", line 378, in fetch_result
result = ray.get(trial_future[0], DEFAULT_GET_TIMEOUT)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/worker.py", line 1457, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(ValueError): ray::PPO.train() (pid=29651, ip=127.0.1.1)
File "python/ray/_raylet.pyx", line 636, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 619, in ray._raylet.execute_task.function_executor
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/agents/trainer.py", line 444, in train
raise e
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/agents/trainer.py", line 433, in train
result = Trainable.train(self)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/tune/trainable.py", line 176, in train
result = self._train()
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/agents/trainer_template.py", line 129, in _train
fetches = self.optimizer.step()
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/optimizers/multi_gpu_optimizer.py", line 140, in step
self.num_envs_per_worker, self.train_batch_size)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/optimizers/rollout.py", line 29, in collect_samples
next_sample = ray_get_and_free(fut_sample)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/utils/memory.py", line 33, in ray_get_and_free
result = ray.get(object_ids)
ray.exceptions.RayTaskError(ValueError): ray::RolloutWorker.sample() (pid=30009, ip=127.0.1.1)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/utils/tf_run_builder.py", line 94, in run_timeline
fetches = sess.run(ops, feed_dict=feed_dict)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 956, in run
run_metadata_ptr)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1156, in _run
(np_val.shape, subfeed_t.name, str(subfeed_t.get_shape())))
ValueError: Cannot feed value of shape (1, 132) for Tensor 'default_policy/observation:0', which has shape '(?, 129)'
During handling of the above exception, another exception occurred:
ray::RolloutWorker.sample() (pid=30009, ip=127.0.1.1)
File "python/ray/_raylet.pyx", line 633, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 634, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 636, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 619, in ray._raylet.execute_task.function_executor
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/evaluation/rollout_worker.py", line 471, in sample
batches = [self.input_reader.next()]
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/evaluation/sampler.py", line 56, in next
batches = [self.get_data()]
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/evaluation/sampler.py", line 99, in get_data
item = next(self.rollout_provider)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/evaluation/sampler.py", line 327, in _env_runner
active_episodes)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/evaluation/sampler.py", line 551, in _do_policy_eval
eval_results[k] = builder.get(v)
File "/home/neousys/anaconda3/envs/flow/lib/python3.7/site-packages/ray/rllib/utils/tf_run_builder.py", line 53, in get
self.fetches, self.feed_dict))
ValueError: Error fetching: [<tf.Tensor 'default_policy/add:0' shape=(?, 2) dtype=float32>, {'action_prob': <tf.Tensor 'default_policy/Exp_1:0' shape=(?,) dtype=float32>, 'action_logp': <tf.Tensor 'default_policy/sub_2:0' shape=(?,) dtype=float32>, 'vf_preds': <tf.Tensor 'default_policy/Reshape:0' shape=(?,) dtype=float32>, 'behaviour_logits': <tf.Tensor 'default_policy/model/fc_out/BiasAdd:0' shape=(?, 4) dtype=float32>}], feed_dict={<tf.Tensor 'default_policy/observation:0' shape=(?, 129) dtype=float32>: [array([3.62607287e-01, 3.62607287e-01, 3.62607287e-01, 3.62607287e-01,
3.62607287e-01, 3.62607287e-01, 3.62607287e-01, 3.62607287e-01,
3.62607340e-01, 3.62607340e-01, 3.62607340e-01, 3.62607340e-01,
3.62607287e-01, 3.62607287e-01, 3.62607287e-01, 3.62607287e-01,
3.62607287e-01, 3.62607273e-01, 3.62607287e-01, 3.62607287e-01,
3.62607340e-01, 3.33613052e-01, 3.62607340e-01, 3.62607340e-01,
3.62607287e-01, 3.62607287e-01, 3.62607287e-01, 3.62607287e-01,
3.62607287e-01, 3.62607287e-01, 3.62607287e-01, 3.62607287e-01,
3.62607287e-01, 3.62607287e-01, 3.62607287e-01, 3.62607287e-01,
3.62607287e-01, 3.62607287e-01, 3.62607287e-01, 3.62607340e-01,
3.62607340e-01, 3.62607340e-01, 3.62607340e-01, 3.33333333e-01,
9.43940256e-05, 1.20095672e-04, 9.43940256e-05, 9.43940256e-05,
9.30966234e-02, 9.31132363e-02, 9.31395871e-02, 9.31451387e-02,
1.86117317e-01, 1.86149407e-01, 1.86156975e-01, 1.86150932e-01,
2.79174202e-01, 2.79149417e-01, 2.79173169e-01, 2.79159042e-01,
3.72200282e-01, 3.72188549e-01, 3.72195222e-01, 3.72175878e-01,
4.65219661e-01, 4.65186232e-01, 4.65201644e-01, 4.65181475e-01,
5.58237048e-01, 5.58225759e-01, 5.58259103e-01, 5.58234339e-01,
6.51255705e-01, 6.51230188e-01, 6.51253134e-01, 6.51250062e-01,
7.44284794e-01, 7.44298284e-01, 7.44270765e-01, 7.44280813e-01,
8.37336632e-01, 8.37314828e-01, 8.37329671e-01, 8.37286100e-01,
9.30318294e-01, 9.30349433e-01, 9.30293162e-01, 7.50051750e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01,
0.00000000e+00, 2.50000000e-01, 5.00000000e-01, 7.50000000e-01])], <tf.Tensor 'default_policy/action:0' shape=(?, 2) dtype=float32>: [array([-0.8724061, -0.5400728], dtype=float32)], <tf.Tensor 'default_policy/prev_reward:0' shape=(?,) dtype=float32>: [1.0425041000281703], <tf.Tensor 'default_policy/PlaceholderWithDefault:0' shape=() dtype=bool>: False}
当我添加许多车辆时，会产生值错误，特别是当我使用除 RingNetwork 之外的网络时。有时，当我的车辆数量不太多，网络长度较长时，不会产生错误。我不知道错误在哪里产生。我应该修改什么代码以避免错误重现。谁能给我一些建议？