EfficientZero
EfficientZero copied to clipboard
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Is it something wrong with this warning?
CUDA_VISIBLE_DEVICES="1,2" python main.py --env BreakoutNoFrameskip-v4 --case atari --opr train --amp_type torch_amp --num_gpus 1 --num_cpus 10 --cpu
_actor 1 --gpu_actor 1 --force
2024-07-22 16:47:01,232 INFO services.py:1164 -- View the Ray dashboard at http://127.0.0.1:8265
A.L.E: Arcade Learning Environment (version 0.7.4+069f8bd)
[Powered by Stella]
[2024-07-22 16:47:02,593][train][INFO][main.py><module>] ==> Path: /mgData4/dengjianhao/EfficientZero/results/atari/none/BreakoutNoFrameskip-v4/seed=0/Mon Jul 22 16:47:02 2024
[2024-07-22 16:47:02,594][train][INFO][main.py><module>] ==> Param: {'action_space_size': 4, 'num_actors': 1, 'do_consistency': True, 'use_value_prefix': True, 'off_correction': True, 'gray_scale': False, 'auto_td_steps_ratio': 0.3, 'episode_life': True, 'change_temperature': True, 'init_zero': True, 'state_norm': False, 'clip_reward': True, 'random_start': True, 'cvt_string': True, 'image_based': True, 'max_moves': 3000, 'test_max_moves': 3000, 'history_length': 400, 'num_simulations': 50, 'discount': 0.988053892081, 'max_grad_norm': 5, 'test_interval': 10000, 'test_episodes': 32, 'value_delta_max': 0.01, 'root_dirichlet_alpha': 0.3, 'root_exploration_fraction': 0.25, 'pb_c_base': 19652, 'pb_c_init': 1.25, 'training_steps': 100000, 'last_steps': 20000, 'checkpoint_interval': 100, 'target_model_interval': 200, 'save_ckpt_interval': 10000, 'log_interval': 1000, 'vis_interval': 1000, 'start_transitions': 2000, 'total_transitions': 100000, 'transition_num': 1, 'batch_size': 256, 'num_unroll_steps': 5, 'td_steps': 5, 'frame_skip': 4, 'stacked_observations': 4, 'lstm_hidden_size': 512, 'lstm_horizon_len': 5, 'reward_loss_coeff': 1, 'value_loss_coeff': 0.25, 'policy_loss_coeff': 1, 'consistency_coeff': 2, 'device': 'cuda', 'debug': False, 'seed': 0, 'value_support': <core.config.DiscreteSupport object at 0x7fd58c7bf100>, 'reward_support': <core.config.DiscreteSupport object at 0x7fd58c7bf160>, 'weight_decay': 0.0001, 'momentum': 0.9, 'lr_warm_up': 0.01, 'lr_warm_step': 1000, 'lr_init': 0.2, 'lr_decay_rate': 0.1, 'lr_decay_steps': 100000, 'mini_infer_size': 64, 'priority_prob_alpha': 0, 'priority_prob_beta': 0.4, 'prioritized_replay_eps': 1e-06, 'image_channel': 3, 'proj_hid': 1024, 'proj_out': 1024, 'pred_hid': 512, 'pred_out': 1024, 'bn_mt': 0.1, 'blocks': 1, 'channels': 64, 'reduced_channels_reward': 16, 'reduced_channels_value': 16, 'reduced_channels_policy': 16, 'resnet_fc_reward_layers': [32], 'resnet_fc_value_layers': [32], 'resnet_fc_policy_layers': [32], 'downsample': True, 'env_name': 'BreakoutNoFrameskip-v4', 'obs_shape': (12, 96, 96), 'case': 'atari', 'amp_type': 'torch_amp', 'use_priority': False, 'use_max_priority': False, 'cpu_actor': 1, 'gpu_actor': 1, 'p_mcts_num': 4, 'use_root_value': False, 'auto_td_steps': 30000.0, 'use_augmentation': True, 'augmentation': ['shift', 'intensity'], 'revisit_policy_search_rate': 0.99, 'model_dir': '/mgData4/dengjianhao/EfficientZero/results/atari/none/BreakoutNoFrameskip-v4/seed=0/Mon Jul 22 16:47:02 2024/model'}
(pid=1482750) A.L.E: Arcade Learning Environment (version 0.7.4+069f8bd)
(pid=1482750) [Powered by Stella]
(pid=1482751) A.L.E: Arcade Learning Environment (version 0.7.4+069f8bd)
(pid=1482751) [Powered by Stella]
(pid=1482751) Start evaluation at step 0.
(pid=1482751) Training step 0, test scores:
(pid=1482751) [9. 0. 5. 2. 0. 0. 0. 9. 0. 0. 0. 0. 3. 3. 0. 5. 0. 0. 0. 0. 2. 2. 3. 9.
(pid=1482751) 0. 0. 0. 5. 2. 0. 0. 5.] of 416 eval steps.
Begin training...
/mgData4/dengjianhao/EfficientZero/core/train.py:68: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:206.)
obs_batch_ori = torch.from_numpy(obs_batch_ori).to(config.device).float() / 255.0
[2024-07-22 16:49:37,539][train][INFO][log.py>_log] ==> #0 Total Loss: 47.875 [weighted Loss:47.875 Policy Loss: 7.901 Value Loss: 37.092 Reward Sum Loss: 30.693 Consistency Loss: 0.004 ] Replay Episodes Collected: 55 Buffer Size: 55 Transition Number: 2.068 k Batch Size: 256 Lr: 0.000
[2024-07-22 16:49:37,539][train_test][INFO][log.py>_log] ==> #0 Test Mean Score of BreakoutNoFrameskip-v4: 2.0 (max: 9.0 , min:0.0 , std: 2.839454172900137)
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
[2024-07-22 17:13:06,564][train][INFO][log.py>_log] ==> #1000 Total Loss: -0.068 [weighted Loss:-0.068 Policy Loss: 7.664 Value Loss: 0.189 Reward Sum Loss: 0.087 Consistency Loss: -3.933 ] Replay Episodes Collected: 55 Buffer Size: 55 Transition Number: 2.068 k Batch Size: 256 Lr: 0.200
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).
Warning: Batch Queue is empty (Require more batch actors Or batch actor fails).