| [2025-02-23 06:34:51,720][00191] Saving configuration to /content/train_dir/default_experiment/config.json... | |
| [2025-02-23 06:34:51,722][00191] Rollout worker 0 uses device cpu | |
| [2025-02-23 06:34:51,723][00191] Rollout worker 1 uses device cpu | |
| [2025-02-23 06:34:51,724][00191] Rollout worker 2 uses device cpu | |
| [2025-02-23 06:34:51,725][00191] Rollout worker 3 uses device cpu | |
| [2025-02-23 06:34:51,726][00191] Rollout worker 4 uses device cpu | |
| [2025-02-23 06:34:51,727][00191] Rollout worker 5 uses device cpu | |
| [2025-02-23 06:34:51,729][00191] Rollout worker 6 uses device cpu | |
| [2025-02-23 06:34:51,729][00191] Rollout worker 7 uses device cpu | |
| [2025-02-23 06:34:51,870][00191] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-23 06:34:51,871][00191] InferenceWorker_p0-w0: min num requests: 2 | |
| [2025-02-23 06:34:51,902][00191] Starting all processes... | |
| [2025-02-23 06:34:51,903][00191] Starting process learner_proc0 | |
| [2025-02-23 06:34:51,960][00191] Starting all processes... | |
| [2025-02-23 06:34:51,968][00191] Starting process inference_proc0-0 | |
| [2025-02-23 06:34:51,968][00191] Starting process rollout_proc0 | |
| [2025-02-23 06:34:51,968][00191] Starting process rollout_proc1 | |
| [2025-02-23 06:34:51,968][00191] Starting process rollout_proc2 | |
| [2025-02-23 06:34:51,968][00191] Starting process rollout_proc3 | |
| [2025-02-23 06:34:51,968][00191] Starting process rollout_proc4 | |
| [2025-02-23 06:34:51,968][00191] Starting process rollout_proc5 | |
| [2025-02-23 06:34:51,968][00191] Starting process rollout_proc6 | |
| [2025-02-23 06:34:51,969][00191] Starting process rollout_proc7 | |
| [2025-02-23 06:35:07,577][03163] Worker 2 uses CPU cores [0] | |
| [2025-02-23 06:35:07,628][03160] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-23 06:35:07,632][03160] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 | |
| [2025-02-23 06:35:07,727][03160] Num visible devices: 1 | |
| [2025-02-23 06:35:07,758][03166] Worker 6 uses CPU cores [0] | |
| [2025-02-23 06:35:07,888][03167] Worker 5 uses CPU cores [1] | |
| [2025-02-23 06:35:07,933][03147] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-23 06:35:07,934][03147] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 | |
| [2025-02-23 06:35:07,955][03147] Num visible devices: 1 | |
| [2025-02-23 06:35:07,982][03164] Worker 3 uses CPU cores [1] | |
| [2025-02-23 06:35:07,985][03147] Starting seed is not provided | |
| [2025-02-23 06:35:07,985][03147] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-23 06:35:07,985][03147] Initializing actor-critic model on device cuda:0 | |
| [2025-02-23 06:35:07,986][03147] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-23 06:35:07,989][03147] RunningMeanStd input shape: (1,) | |
| [2025-02-23 06:35:07,995][03162] Worker 1 uses CPU cores [1] | |
| [2025-02-23 06:35:08,020][03147] ConvEncoder: input_channels=3 | |
| [2025-02-23 06:35:08,064][03168] Worker 7 uses CPU cores [1] | |
| [2025-02-23 06:35:08,069][03161] Worker 0 uses CPU cores [0] | |
| [2025-02-23 06:35:08,142][03165] Worker 4 uses CPU cores [0] | |
| [2025-02-23 06:35:08,311][03147] Conv encoder output size: 512 | |
| [2025-02-23 06:35:08,311][03147] Policy head output size: 512 | |
| [2025-02-23 06:35:08,372][03147] Created Actor Critic model with architecture: | |
| [2025-02-23 06:35:08,372][03147] ActorCriticSharedWeights( | |
| (obs_normalizer): ObservationNormalizer( | |
| (running_mean_std): RunningMeanStdDictInPlace( | |
| (running_mean_std): ModuleDict( | |
| (obs): RunningMeanStdInPlace() | |
| ) | |
| ) | |
| ) | |
| (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) | |
| (encoder): VizdoomEncoder( | |
| (basic_encoder): ConvEncoder( | |
| (enc): RecursiveScriptModule( | |
| original_name=ConvEncoderImpl | |
| (conv_head): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Conv2d) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| (2): RecursiveScriptModule(original_name=Conv2d) | |
| (3): RecursiveScriptModule(original_name=ELU) | |
| (4): RecursiveScriptModule(original_name=Conv2d) | |
| (5): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| (mlp_layers): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Linear) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (core): ModelCoreRNN( | |
| (core): GRU(512, 512) | |
| ) | |
| (decoder): MlpDecoder( | |
| (mlp): Identity() | |
| ) | |
| (critic_linear): Linear(in_features=512, out_features=1, bias=True) | |
| (action_parameterization): ActionParameterizationDefault( | |
| (distribution_linear): Linear(in_features=512, out_features=5, bias=True) | |
| ) | |
| ) | |
| [2025-02-23 06:35:08,621][03147] Using optimizer <class 'torch.optim.adam.Adam'> | |
| [2025-02-23 06:35:11,865][00191] Heartbeat connected on Batcher_0 | |
| [2025-02-23 06:35:11,871][00191] Heartbeat connected on InferenceWorker_p0-w0 | |
| [2025-02-23 06:35:11,879][00191] Heartbeat connected on RolloutWorker_w0 | |
| [2025-02-23 06:35:11,882][00191] Heartbeat connected on RolloutWorker_w1 | |
| [2025-02-23 06:35:11,885][00191] Heartbeat connected on RolloutWorker_w2 | |
| [2025-02-23 06:35:11,889][00191] Heartbeat connected on RolloutWorker_w3 | |
| [2025-02-23 06:35:11,894][00191] Heartbeat connected on RolloutWorker_w4 | |
| [2025-02-23 06:35:11,898][00191] Heartbeat connected on RolloutWorker_w5 | |
| [2025-02-23 06:35:11,900][00191] Heartbeat connected on RolloutWorker_w6 | |
| [2025-02-23 06:35:11,905][00191] Heartbeat connected on RolloutWorker_w7 | |
| [2025-02-23 06:35:13,159][03147] No checkpoints found | |
| [2025-02-23 06:35:13,160][03147] Did not load from checkpoint, starting from scratch! | |
| [2025-02-23 06:35:13,160][03147] Initialized policy 0 weights for model version 0 | |
| [2025-02-23 06:35:13,166][03147] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-23 06:35:13,177][03147] LearnerWorker_p0 finished initialization! | |
| [2025-02-23 06:35:13,178][00191] Heartbeat connected on LearnerWorker_p0 | |
| [2025-02-23 06:35:13,389][03160] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-23 06:35:13,391][03160] RunningMeanStd input shape: (1,) | |
| [2025-02-23 06:35:13,411][03160] ConvEncoder: input_channels=3 | |
| [2025-02-23 06:35:13,569][03160] Conv encoder output size: 512 | |
| [2025-02-23 06:35:13,570][03160] Policy head output size: 512 | |
| [2025-02-23 06:35:13,616][00191] Inference worker 0-0 is ready! | |
| [2025-02-23 06:35:13,617][00191] All inference workers are ready! Signal rollout workers to start! | |
| [2025-02-23 06:35:14,033][03163] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:14,107][03162] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:14,105][03167] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:14,132][03166] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:14,201][03161] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:14,212][03164] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:14,218][03168] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:14,242][03165] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:35:16,133][03167] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:16,132][03164] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:16,133][03162] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:16,135][03166] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:16,137][03163] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:16,132][03165] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:16,315][00191] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-23 06:35:16,944][03165] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:16,954][03166] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:17,466][03164] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:17,470][03162] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:17,475][03167] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:18,147][03163] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:18,489][03168] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:18,592][03166] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:18,868][03165] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:19,091][03162] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:19,100][03164] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:19,481][03161] Decorrelating experience for 0 frames... | |
| [2025-02-23 06:35:19,721][03163] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:19,851][03168] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:19,886][03165] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:20,454][03163] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:20,695][03167] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:20,875][03164] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:21,315][00191] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-23 06:35:21,762][03162] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:22,233][03166] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:22,324][03168] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:22,917][03167] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:23,008][03161] Decorrelating experience for 32 frames... | |
| [2025-02-23 06:35:25,583][03147] Signal inference workers to stop experience collection... | |
| [2025-02-23 06:35:25,603][03160] InferenceWorker_p0-w0: stopping experience collection | |
| [2025-02-23 06:35:25,949][03168] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:26,315][00191] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 238.8. Samples: 2388. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-23 06:35:26,322][00191] Avg episode reward: [(0, '2.526')] | |
| [2025-02-23 06:35:26,577][03161] Decorrelating experience for 64 frames... | |
| [2025-02-23 06:35:27,399][03161] Decorrelating experience for 96 frames... | |
| [2025-02-23 06:35:27,503][03147] Signal inference workers to resume experience collection... | |
| [2025-02-23 06:35:27,506][03160] InferenceWorker_p0-w0: resuming experience collection | |
| [2025-02-23 06:35:31,315][00191] Fps is (10 sec: 2047.8, 60 sec: 1365.2, 300 sec: 1365.2). Total num frames: 20480. Throughput: 0: 196.0. Samples: 2940. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:35:31,317][00191] Avg episode reward: [(0, '3.281')] | |
| [2025-02-23 06:35:35,646][03160] Updated weights for policy 0, policy_version 10 (0.0172) | |
| [2025-02-23 06:35:36,315][00191] Fps is (10 sec: 4096.0, 60 sec: 2048.0, 300 sec: 2048.0). Total num frames: 40960. Throughput: 0: 491.8. Samples: 9836. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:35:36,316][00191] Avg episode reward: [(0, '3.974')] | |
| [2025-02-23 06:35:41,317][00191] Fps is (10 sec: 3276.3, 60 sec: 2129.7, 300 sec: 2129.7). Total num frames: 53248. Throughput: 0: 561.4. Samples: 14036. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:35:41,325][00191] Avg episode reward: [(0, '4.290')] | |
| [2025-02-23 06:35:46,317][00191] Fps is (10 sec: 2866.4, 60 sec: 2320.8, 300 sec: 2320.8). Total num frames: 69632. Throughput: 0: 519.2. Samples: 15578. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:35:46,319][00191] Avg episode reward: [(0, '4.462')] | |
| [2025-02-23 06:35:49,184][03160] Updated weights for policy 0, policy_version 20 (0.0019) | |
| [2025-02-23 06:35:51,315][00191] Fps is (10 sec: 3687.2, 60 sec: 2574.6, 300 sec: 2574.6). Total num frames: 90112. Throughput: 0: 621.9. Samples: 21766. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:35:51,318][00191] Avg episode reward: [(0, '4.289')] | |
| [2025-02-23 06:35:56,315][00191] Fps is (10 sec: 3687.4, 60 sec: 2662.4, 300 sec: 2662.4). Total num frames: 106496. Throughput: 0: 689.3. Samples: 27574. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-02-23 06:35:56,317][00191] Avg episode reward: [(0, '4.196')] | |
| [2025-02-23 06:35:56,324][03147] Saving new best policy, reward=4.196! | |
| [2025-02-23 06:35:59,974][03160] Updated weights for policy 0, policy_version 30 (0.0027) | |
| [2025-02-23 06:36:01,315][00191] Fps is (10 sec: 3686.4, 60 sec: 2821.7, 300 sec: 2821.7). Total num frames: 126976. Throughput: 0: 663.6. Samples: 29864. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:36:01,316][00191] Avg episode reward: [(0, '4.302')] | |
| [2025-02-23 06:36:01,321][03147] Saving new best policy, reward=4.302! | |
| [2025-02-23 06:36:06,315][00191] Fps is (10 sec: 4505.6, 60 sec: 3031.0, 300 sec: 3031.0). Total num frames: 151552. Throughput: 0: 815.2. Samples: 36684. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:36:06,316][00191] Avg episode reward: [(0, '4.349')] | |
| [2025-02-23 06:36:06,325][03147] Saving new best policy, reward=4.349! | |
| [2025-02-23 06:36:09,256][03160] Updated weights for policy 0, policy_version 40 (0.0022) | |
| [2025-02-23 06:36:11,316][00191] Fps is (10 sec: 4095.2, 60 sec: 3053.3, 300 sec: 3053.3). Total num frames: 167936. Throughput: 0: 890.3. Samples: 42452. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:36:11,321][00191] Avg episode reward: [(0, '4.407')] | |
| [2025-02-23 06:36:11,322][03147] Saving new best policy, reward=4.407! | |
| [2025-02-23 06:36:16,315][00191] Fps is (10 sec: 3276.8, 60 sec: 3072.0, 300 sec: 3072.0). Total num frames: 184320. Throughput: 0: 927.4. Samples: 44674. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:36:16,320][00191] Avg episode reward: [(0, '4.463')] | |
| [2025-02-23 06:36:16,369][03147] Saving new best policy, reward=4.463! | |
| [2025-02-23 06:36:19,839][03160] Updated weights for policy 0, policy_version 50 (0.0024) | |
| [2025-02-23 06:36:21,315][00191] Fps is (10 sec: 4096.8, 60 sec: 3481.6, 300 sec: 3213.8). Total num frames: 208896. Throughput: 0: 923.8. Samples: 51408. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:36:21,318][00191] Avg episode reward: [(0, '4.571')] | |
| [2025-02-23 06:36:21,322][03147] Saving new best policy, reward=4.571! | |
| [2025-02-23 06:36:26,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3218.3). Total num frames: 225280. Throughput: 0: 957.2. Samples: 57110. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:36:26,321][00191] Avg episode reward: [(0, '4.483')] | |
| [2025-02-23 06:36:31,104][03160] Updated weights for policy 0, policy_version 60 (0.0015) | |
| [2025-02-23 06:36:31,315][00191] Fps is (10 sec: 3686.3, 60 sec: 3754.7, 300 sec: 3276.8). Total num frames: 245760. Throughput: 0: 973.5. Samples: 59382. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:36:31,318][00191] Avg episode reward: [(0, '4.479')] | |
| [2025-02-23 06:36:36,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3328.0). Total num frames: 266240. Throughput: 0: 984.4. Samples: 66064. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:36:36,318][00191] Avg episode reward: [(0, '4.578')] | |
| [2025-02-23 06:36:36,323][03147] Saving new best policy, reward=4.578! | |
| [2025-02-23 06:36:41,317][00191] Fps is (10 sec: 3685.4, 60 sec: 3822.9, 300 sec: 3324.9). Total num frames: 282624. Throughput: 0: 971.4. Samples: 71290. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:36:41,319][00191] Avg episode reward: [(0, '4.478')] | |
| [2025-02-23 06:36:42,077][03160] Updated weights for policy 0, policy_version 70 (0.0023) | |
| [2025-02-23 06:36:46,317][00191] Fps is (10 sec: 3685.7, 60 sec: 3891.3, 300 sec: 3367.7). Total num frames: 303104. Throughput: 0: 974.8. Samples: 73732. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:36:46,322][00191] Avg episode reward: [(0, '4.504')] | |
| [2025-02-23 06:36:46,328][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000074_303104.pth... | |
| [2025-02-23 06:36:51,315][00191] Fps is (10 sec: 4097.2, 60 sec: 3891.2, 300 sec: 3406.1). Total num frames: 323584. Throughput: 0: 966.4. Samples: 80170. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:36:51,318][00191] Avg episode reward: [(0, '4.550')] | |
| [2025-02-23 06:36:52,009][03160] Updated weights for policy 0, policy_version 80 (0.0043) | |
| [2025-02-23 06:36:56,315][00191] Fps is (10 sec: 3687.0, 60 sec: 3891.2, 300 sec: 3399.7). Total num frames: 339968. Throughput: 0: 958.8. Samples: 85598. Policy #0 lag: (min: 0.0, avg: 0.8, max: 2.0) | |
| [2025-02-23 06:36:56,321][00191] Avg episode reward: [(0, '4.462')] | |
| [2025-02-23 06:37:01,315][00191] Fps is (10 sec: 3686.3, 60 sec: 3891.2, 300 sec: 3432.8). Total num frames: 360448. Throughput: 0: 970.2. Samples: 88332. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:37:01,316][00191] Avg episode reward: [(0, '4.413')] | |
| [2025-02-23 06:37:02,414][03160] Updated weights for policy 0, policy_version 90 (0.0024) | |
| [2025-02-23 06:37:06,315][00191] Fps is (10 sec: 4505.8, 60 sec: 3891.2, 300 sec: 3500.2). Total num frames: 385024. Throughput: 0: 975.9. Samples: 95322. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:37:06,316][00191] Avg episode reward: [(0, '4.433')] | |
| [2025-02-23 06:37:11,317][00191] Fps is (10 sec: 4094.9, 60 sec: 3891.1, 300 sec: 3490.4). Total num frames: 401408. Throughput: 0: 971.9. Samples: 100850. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:37:11,319][00191] Avg episode reward: [(0, '4.438')] | |
| [2025-02-23 06:37:13,565][03160] Updated weights for policy 0, policy_version 100 (0.0017) | |
| [2025-02-23 06:37:16,315][00191] Fps is (10 sec: 3686.3, 60 sec: 3959.4, 300 sec: 3515.7). Total num frames: 421888. Throughput: 0: 974.0. Samples: 103212. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-02-23 06:37:16,318][00191] Avg episode reward: [(0, '4.568')] | |
| [2025-02-23 06:37:21,315][00191] Fps is (10 sec: 4097.2, 60 sec: 3891.2, 300 sec: 3538.9). Total num frames: 442368. Throughput: 0: 980.3. Samples: 110176. Policy #0 lag: (min: 0.0, avg: 0.8, max: 2.0) | |
| [2025-02-23 06:37:21,319][00191] Avg episode reward: [(0, '4.567')] | |
| [2025-02-23 06:37:22,355][03160] Updated weights for policy 0, policy_version 110 (0.0023) | |
| [2025-02-23 06:37:26,316][00191] Fps is (10 sec: 3685.8, 60 sec: 3891.1, 300 sec: 3528.8). Total num frames: 458752. Throughput: 0: 981.0. Samples: 115434. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:37:26,318][00191] Avg episode reward: [(0, '4.417')] | |
| [2025-02-23 06:37:31,314][00191] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3580.2). Total num frames: 483328. Throughput: 0: 993.7. Samples: 118446. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:37:31,319][00191] Avg episode reward: [(0, '4.305')] | |
| [2025-02-23 06:37:33,172][03160] Updated weights for policy 0, policy_version 120 (0.0027) | |
| [2025-02-23 06:37:36,315][00191] Fps is (10 sec: 4506.5, 60 sec: 3959.5, 300 sec: 3598.6). Total num frames: 503808. Throughput: 0: 1002.8. Samples: 125298. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-02-23 06:37:36,319][00191] Avg episode reward: [(0, '4.596')] | |
| [2025-02-23 06:37:36,325][03147] Saving new best policy, reward=4.596! | |
| [2025-02-23 06:37:41,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.7, 300 sec: 3587.5). Total num frames: 520192. Throughput: 0: 992.8. Samples: 130272. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:37:41,316][00191] Avg episode reward: [(0, '4.751')] | |
| [2025-02-23 06:37:41,319][03147] Saving new best policy, reward=4.751! | |
| [2025-02-23 06:37:44,065][03160] Updated weights for policy 0, policy_version 130 (0.0014) | |
| [2025-02-23 06:37:46,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.6, 300 sec: 3604.5). Total num frames: 540672. Throughput: 0: 997.4. Samples: 133216. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:37:46,320][00191] Avg episode reward: [(0, '4.781')] | |
| [2025-02-23 06:37:46,330][03147] Saving new best policy, reward=4.781! | |
| [2025-02-23 06:37:51,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3620.3). Total num frames: 561152. Throughput: 0: 990.0. Samples: 139872. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-02-23 06:37:51,316][00191] Avg episode reward: [(0, '4.596')] | |
| [2025-02-23 06:37:54,288][03160] Updated weights for policy 0, policy_version 140 (0.0015) | |
| [2025-02-23 06:37:56,315][00191] Fps is (10 sec: 3686.3, 60 sec: 3959.5, 300 sec: 3609.6). Total num frames: 577536. Throughput: 0: 978.7. Samples: 144888. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:37:56,320][00191] Avg episode reward: [(0, '4.501')] | |
| [2025-02-23 06:38:01,314][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3649.2). Total num frames: 602112. Throughput: 0: 997.4. Samples: 148094. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:38:01,319][00191] Avg episode reward: [(0, '4.364')] | |
| [2025-02-23 06:38:04,052][03160] Updated weights for policy 0, policy_version 150 (0.0016) | |
| [2025-02-23 06:38:06,315][00191] Fps is (10 sec: 4505.7, 60 sec: 3959.5, 300 sec: 3662.3). Total num frames: 622592. Throughput: 0: 993.7. Samples: 154892. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:38:06,319][00191] Avg episode reward: [(0, '4.475')] | |
| [2025-02-23 06:38:11,314][00191] Fps is (10 sec: 3276.8, 60 sec: 3891.4, 300 sec: 3627.9). Total num frames: 634880. Throughput: 0: 980.8. Samples: 159566. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:38:11,316][00191] Avg episode reward: [(0, '4.604')] | |
| [2025-02-23 06:38:15,164][03160] Updated weights for policy 0, policy_version 160 (0.0028) | |
| [2025-02-23 06:38:16,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3663.6). Total num frames: 659456. Throughput: 0: 986.0. Samples: 162816. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:38:16,316][00191] Avg episode reward: [(0, '4.490')] | |
| [2025-02-23 06:38:21,315][00191] Fps is (10 sec: 4505.2, 60 sec: 3959.4, 300 sec: 3675.3). Total num frames: 679936. Throughput: 0: 982.6. Samples: 169514. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:38:21,320][00191] Avg episode reward: [(0, '4.361')] | |
| [2025-02-23 06:38:26,136][03160] Updated weights for policy 0, policy_version 170 (0.0015) | |
| [2025-02-23 06:38:26,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.6, 300 sec: 3664.8). Total num frames: 696320. Throughput: 0: 976.8. Samples: 174228. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:38:26,318][00191] Avg episode reward: [(0, '4.365')] | |
| [2025-02-23 06:38:31,315][00191] Fps is (10 sec: 3686.7, 60 sec: 3891.2, 300 sec: 3675.9). Total num frames: 716800. Throughput: 0: 986.6. Samples: 177614. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:38:31,317][00191] Avg episode reward: [(0, '4.438')] | |
| [2025-02-23 06:38:34,861][03160] Updated weights for policy 0, policy_version 180 (0.0025) | |
| [2025-02-23 06:38:36,316][00191] Fps is (10 sec: 4504.7, 60 sec: 3959.3, 300 sec: 3706.8). Total num frames: 741376. Throughput: 0: 994.0. Samples: 184602. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:38:36,318][00191] Avg episode reward: [(0, '4.459')] | |
| [2025-02-23 06:38:41,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3696.4). Total num frames: 757760. Throughput: 0: 988.5. Samples: 189370. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:38:41,316][00191] Avg episode reward: [(0, '4.582')] | |
| [2025-02-23 06:38:45,456][03160] Updated weights for policy 0, policy_version 190 (0.0022) | |
| [2025-02-23 06:38:46,315][00191] Fps is (10 sec: 3687.1, 60 sec: 3959.5, 300 sec: 3705.9). Total num frames: 778240. Throughput: 0: 995.0. Samples: 192870. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:38:46,316][00191] Avg episode reward: [(0, '4.566')] | |
| [2025-02-23 06:38:46,324][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000190_778240.pth... | |
| [2025-02-23 06:38:51,320][00191] Fps is (10 sec: 4093.6, 60 sec: 3959.1, 300 sec: 3714.9). Total num frames: 798720. Throughput: 0: 993.8. Samples: 199618. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:38:51,322][00191] Avg episode reward: [(0, '4.633')] | |
| [2025-02-23 06:38:56,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3705.0). Total num frames: 815104. Throughput: 0: 995.0. Samples: 204342. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-23 06:38:56,319][00191] Avg episode reward: [(0, '4.671')] | |
| [2025-02-23 06:38:56,425][03160] Updated weights for policy 0, policy_version 200 (0.0024) | |
| [2025-02-23 06:39:01,315][00191] Fps is (10 sec: 4098.4, 60 sec: 3959.5, 300 sec: 3731.9). Total num frames: 839680. Throughput: 0: 1002.0. Samples: 207904. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:39:01,319][00191] Avg episode reward: [(0, '4.392')] | |
| [2025-02-23 06:39:05,339][03160] Updated weights for policy 0, policy_version 210 (0.0020) | |
| [2025-02-23 06:39:06,316][00191] Fps is (10 sec: 4504.8, 60 sec: 3959.3, 300 sec: 3739.8). Total num frames: 860160. Throughput: 0: 1007.9. Samples: 214872. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:39:06,319][00191] Avg episode reward: [(0, '4.488')] | |
| [2025-02-23 06:39:11,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3730.0). Total num frames: 876544. Throughput: 0: 1012.7. Samples: 219800. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:39:11,319][00191] Avg episode reward: [(0, '4.523')] | |
| [2025-02-23 06:39:15,836][03160] Updated weights for policy 0, policy_version 220 (0.0044) | |
| [2025-02-23 06:39:16,315][00191] Fps is (10 sec: 4096.8, 60 sec: 4027.7, 300 sec: 3754.7). Total num frames: 901120. Throughput: 0: 1013.7. Samples: 223230. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:39:16,319][00191] Avg episode reward: [(0, '4.474')] | |
| [2025-02-23 06:39:21,315][00191] Fps is (10 sec: 4505.5, 60 sec: 4027.8, 300 sec: 3761.6). Total num frames: 921600. Throughput: 0: 1011.7. Samples: 230126. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:39:21,318][00191] Avg episode reward: [(0, '4.478')] | |
| [2025-02-23 06:39:26,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3751.9). Total num frames: 937984. Throughput: 0: 1012.5. Samples: 234932. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:39:26,316][00191] Avg episode reward: [(0, '4.587')] | |
| [2025-02-23 06:39:26,715][03160] Updated weights for policy 0, policy_version 230 (0.0017) | |
| [2025-02-23 06:39:31,315][00191] Fps is (10 sec: 4096.1, 60 sec: 4096.0, 300 sec: 3774.7). Total num frames: 962560. Throughput: 0: 1010.7. Samples: 238352. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-02-23 06:39:31,316][00191] Avg episode reward: [(0, '4.564')] | |
| [2025-02-23 06:39:36,067][03160] Updated weights for policy 0, policy_version 240 (0.0013) | |
| [2025-02-23 06:39:36,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.9, 300 sec: 3780.9). Total num frames: 983040. Throughput: 0: 1015.4. Samples: 245304. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:39:36,325][00191] Avg episode reward: [(0, '4.538')] | |
| [2025-02-23 06:39:41,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3771.4). Total num frames: 999424. Throughput: 0: 1013.9. Samples: 249968. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:39:41,316][00191] Avg episode reward: [(0, '4.742')] | |
| [2025-02-23 06:39:46,315][00191] Fps is (10 sec: 3686.3, 60 sec: 4027.7, 300 sec: 3777.4). Total num frames: 1019904. Throughput: 0: 1011.1. Samples: 253404. Policy #0 lag: (min: 0.0, avg: 0.8, max: 2.0) | |
| [2025-02-23 06:39:46,316][00191] Avg episode reward: [(0, '4.921')] | |
| [2025-02-23 06:39:46,326][03147] Saving new best policy, reward=4.921! | |
| [2025-02-23 06:39:46,620][03160] Updated weights for policy 0, policy_version 250 (0.0032) | |
| [2025-02-23 06:39:51,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4028.1, 300 sec: 3783.2). Total num frames: 1040384. Throughput: 0: 998.4. Samples: 259796. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:39:51,316][00191] Avg episode reward: [(0, '4.782')] | |
| [2025-02-23 06:39:56,315][00191] Fps is (10 sec: 3686.5, 60 sec: 4027.7, 300 sec: 3774.2). Total num frames: 1056768. Throughput: 0: 991.6. Samples: 264420. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:39:56,320][00191] Avg episode reward: [(0, '4.772')] | |
| [2025-02-23 06:39:57,828][03160] Updated weights for policy 0, policy_version 260 (0.0016) | |
| [2025-02-23 06:40:01,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3779.8). Total num frames: 1077248. Throughput: 0: 991.2. Samples: 267834. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:40:01,316][00191] Avg episode reward: [(0, '4.738')] | |
| [2025-02-23 06:40:06,315][00191] Fps is (10 sec: 4095.9, 60 sec: 3959.6, 300 sec: 3785.3). Total num frames: 1097728. Throughput: 0: 983.1. Samples: 274364. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:40:06,316][00191] Avg episode reward: [(0, '4.711')] | |
| [2025-02-23 06:40:08,777][03160] Updated weights for policy 0, policy_version 270 (0.0024) | |
| [2025-02-23 06:40:11,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3776.7). Total num frames: 1114112. Throughput: 0: 982.6. Samples: 279148. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:40:11,316][00191] Avg episode reward: [(0, '4.831')] | |
| [2025-02-23 06:40:16,315][00191] Fps is (10 sec: 4096.2, 60 sec: 3959.5, 300 sec: 3860.0). Total num frames: 1138688. Throughput: 0: 980.7. Samples: 282482. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:40:16,316][00191] Avg episode reward: [(0, '5.150')] | |
| [2025-02-23 06:40:16,321][03147] Saving new best policy, reward=5.150! | |
| [2025-02-23 06:40:18,069][03160] Updated weights for policy 0, policy_version 280 (0.0026) | |
| [2025-02-23 06:40:21,320][00191] Fps is (10 sec: 4093.6, 60 sec: 3890.8, 300 sec: 3915.4). Total num frames: 1155072. Throughput: 0: 968.3. Samples: 288882. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-02-23 06:40:21,322][00191] Avg episode reward: [(0, '5.215')] | |
| [2025-02-23 06:40:21,323][03147] Saving new best policy, reward=5.215! | |
| [2025-02-23 06:40:26,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3915.5). Total num frames: 1175552. Throughput: 0: 974.4. Samples: 293814. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:40:26,318][00191] Avg episode reward: [(0, '5.429')] | |
| [2025-02-23 06:40:26,326][03147] Saving new best policy, reward=5.429! | |
| [2025-02-23 06:40:28,837][03160] Updated weights for policy 0, policy_version 290 (0.0026) | |
| [2025-02-23 06:40:31,315][00191] Fps is (10 sec: 4098.4, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 1196032. Throughput: 0: 973.7. Samples: 297220. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:40:31,316][00191] Avg episode reward: [(0, '5.670')] | |
| [2025-02-23 06:40:31,317][03147] Saving new best policy, reward=5.670! | |
| [2025-02-23 06:40:36,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3943.3). Total num frames: 1216512. Throughput: 0: 978.5. Samples: 303830. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:40:36,316][00191] Avg episode reward: [(0, '5.622')] | |
| [2025-02-23 06:40:39,574][03160] Updated weights for policy 0, policy_version 300 (0.0018) | |
| [2025-02-23 06:40:41,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 1236992. Throughput: 0: 990.8. Samples: 309006. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:40:41,318][00191] Avg episode reward: [(0, '5.368')] | |
| [2025-02-23 06:40:46,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 1257472. Throughput: 0: 992.8. Samples: 312512. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:40:46,319][00191] Avg episode reward: [(0, '5.445')] | |
| [2025-02-23 06:40:46,327][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000307_1257472.pth... | |
| [2025-02-23 06:40:46,454][03147] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000074_303104.pth | |
| [2025-02-23 06:40:48,443][03160] Updated weights for policy 0, policy_version 310 (0.0014) | |
| [2025-02-23 06:40:51,318][00191] Fps is (10 sec: 4094.7, 60 sec: 3959.3, 300 sec: 3971.0). Total num frames: 1277952. Throughput: 0: 991.5. Samples: 318984. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:40:51,319][00191] Avg episode reward: [(0, '5.718')] | |
| [2025-02-23 06:40:51,321][03147] Saving new best policy, reward=5.718! | |
| [2025-02-23 06:40:56,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3957.2). Total num frames: 1294336. Throughput: 0: 999.1. Samples: 324108. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:40:56,320][00191] Avg episode reward: [(0, '5.598')] | |
| [2025-02-23 06:40:59,085][03160] Updated weights for policy 0, policy_version 320 (0.0018) | |
| [2025-02-23 06:41:01,315][00191] Fps is (10 sec: 4097.3, 60 sec: 4027.7, 300 sec: 3957.2). Total num frames: 1318912. Throughput: 0: 1002.1. Samples: 327576. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:41:01,319][00191] Avg episode reward: [(0, '5.834')] | |
| [2025-02-23 06:41:01,324][03147] Saving new best policy, reward=5.834! | |
| [2025-02-23 06:41:06,317][00191] Fps is (10 sec: 4095.2, 60 sec: 3959.4, 300 sec: 3957.2). Total num frames: 1335296. Throughput: 0: 1003.8. Samples: 334048. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:41:06,322][00191] Avg episode reward: [(0, '6.335')] | |
| [2025-02-23 06:41:06,335][03147] Saving new best policy, reward=6.335! | |
| [2025-02-23 06:41:09,974][03160] Updated weights for policy 0, policy_version 330 (0.0019) | |
| [2025-02-23 06:41:11,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3971.0). Total num frames: 1355776. Throughput: 0: 1010.4. Samples: 339280. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:41:11,318][00191] Avg episode reward: [(0, '6.218')] | |
| [2025-02-23 06:41:16,315][00191] Fps is (10 sec: 4506.5, 60 sec: 4027.7, 300 sec: 3971.0). Total num frames: 1380352. Throughput: 0: 1011.1. Samples: 342718. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:41:16,316][00191] Avg episode reward: [(0, '6.196')] | |
| [2025-02-23 06:41:19,112][03160] Updated weights for policy 0, policy_version 340 (0.0023) | |
| [2025-02-23 06:41:21,315][00191] Fps is (10 sec: 4095.6, 60 sec: 4028.1, 300 sec: 3971.0). Total num frames: 1396736. Throughput: 0: 1007.0. Samples: 349148. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:41:21,317][00191] Avg episode reward: [(0, '6.346')] | |
| [2025-02-23 06:41:21,318][03147] Saving new best policy, reward=6.346! | |
| [2025-02-23 06:41:26,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3971.0). Total num frames: 1417216. Throughput: 0: 1009.4. Samples: 354430. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-23 06:41:26,316][00191] Avg episode reward: [(0, '6.384')] | |
| [2025-02-23 06:41:26,321][03147] Saving new best policy, reward=6.384! | |
| [2025-02-23 06:41:29,647][03160] Updated weights for policy 0, policy_version 350 (0.0021) | |
| [2025-02-23 06:41:31,315][00191] Fps is (10 sec: 4096.4, 60 sec: 4027.7, 300 sec: 3971.0). Total num frames: 1437696. Throughput: 0: 1006.5. Samples: 357806. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:41:31,318][00191] Avg episode reward: [(0, '5.939')] | |
| [2025-02-23 06:41:36,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3985.0). Total num frames: 1458176. Throughput: 0: 1001.0. Samples: 364026. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:41:36,316][00191] Avg episode reward: [(0, '6.087')] | |
| [2025-02-23 06:41:40,262][03160] Updated weights for policy 0, policy_version 360 (0.0021) | |
| [2025-02-23 06:41:41,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3984.9). Total num frames: 1478656. Throughput: 0: 1013.2. Samples: 369704. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:41:41,322][00191] Avg episode reward: [(0, '6.098')] | |
| [2025-02-23 06:41:46,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3984.9). Total num frames: 1499136. Throughput: 0: 1014.0. Samples: 373206. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:41:46,317][00191] Avg episode reward: [(0, '6.622')] | |
| [2025-02-23 06:41:46,400][03147] Saving new best policy, reward=6.622! | |
| [2025-02-23 06:41:49,857][03160] Updated weights for policy 0, policy_version 370 (0.0019) | |
| [2025-02-23 06:41:51,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.7, 300 sec: 3984.9). Total num frames: 1515520. Throughput: 0: 1005.3. Samples: 379286. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:41:51,316][00191] Avg episode reward: [(0, '6.836')] | |
| [2025-02-23 06:41:51,321][03147] Saving new best policy, reward=6.836! | |
| [2025-02-23 06:41:56,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3998.8). Total num frames: 1540096. Throughput: 0: 1011.1. Samples: 384778. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:41:56,316][00191] Avg episode reward: [(0, '6.437')] | |
| [2025-02-23 06:41:59,778][03160] Updated weights for policy 0, policy_version 380 (0.0018) | |
| [2025-02-23 06:42:01,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 3984.9). Total num frames: 1560576. Throughput: 0: 1013.5. Samples: 388324. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:42:01,316][00191] Avg episode reward: [(0, '7.261')] | |
| [2025-02-23 06:42:01,318][03147] Saving new best policy, reward=7.261! | |
| [2025-02-23 06:42:06,315][00191] Fps is (10 sec: 3686.3, 60 sec: 4027.8, 300 sec: 3985.0). Total num frames: 1576960. Throughput: 0: 1004.9. Samples: 394368. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:42:06,317][00191] Avg episode reward: [(0, '7.591')] | |
| [2025-02-23 06:42:06,322][03147] Saving new best policy, reward=7.591! | |
| [2025-02-23 06:42:10,544][03160] Updated weights for policy 0, policy_version 390 (0.0047) | |
| [2025-02-23 06:42:11,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3984.9). Total num frames: 1597440. Throughput: 0: 1014.3. Samples: 400074. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:42:11,316][00191] Avg episode reward: [(0, '7.889')] | |
| [2025-02-23 06:42:11,320][03147] Saving new best policy, reward=7.889! | |
| [2025-02-23 06:42:16,314][00191] Fps is (10 sec: 4505.8, 60 sec: 4027.7, 300 sec: 3998.8). Total num frames: 1622016. Throughput: 0: 1014.2. Samples: 403446. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:42:16,316][00191] Avg episode reward: [(0, '8.392')] | |
| [2025-02-23 06:42:16,324][03147] Saving new best policy, reward=8.392! | |
| [2025-02-23 06:42:20,877][03160] Updated weights for policy 0, policy_version 400 (0.0018) | |
| [2025-02-23 06:42:21,315][00191] Fps is (10 sec: 4095.9, 60 sec: 4027.8, 300 sec: 3998.8). Total num frames: 1638400. Throughput: 0: 1007.1. Samples: 409346. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:42:21,316][00191] Avg episode reward: [(0, '8.575')] | |
| [2025-02-23 06:42:21,317][03147] Saving new best policy, reward=8.575! | |
| [2025-02-23 06:42:26,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3984.9). Total num frames: 1658880. Throughput: 0: 1005.9. Samples: 414968. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:42:26,316][00191] Avg episode reward: [(0, '8.783')] | |
| [2025-02-23 06:42:26,320][03147] Saving new best policy, reward=8.783! | |
| [2025-02-23 06:42:30,426][03160] Updated weights for policy 0, policy_version 410 (0.0030) | |
| [2025-02-23 06:42:31,314][00191] Fps is (10 sec: 4505.7, 60 sec: 4096.0, 300 sec: 3998.8). Total num frames: 1683456. Throughput: 0: 1003.4. Samples: 418358. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:42:31,316][00191] Avg episode reward: [(0, '8.818')] | |
| [2025-02-23 06:42:31,317][03147] Saving new best policy, reward=8.818! | |
| [2025-02-23 06:42:36,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3984.9). Total num frames: 1695744. Throughput: 0: 997.7. Samples: 424182. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:42:36,318][00191] Avg episode reward: [(0, '9.314')] | |
| [2025-02-23 06:42:36,330][03147] Saving new best policy, reward=9.314! | |
| [2025-02-23 06:42:41,046][03160] Updated weights for policy 0, policy_version 420 (0.0028) | |
| [2025-02-23 06:42:41,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3998.8). Total num frames: 1720320. Throughput: 0: 1008.7. Samples: 430170. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:42:41,316][00191] Avg episode reward: [(0, '9.793')] | |
| [2025-02-23 06:42:41,320][03147] Saving new best policy, reward=9.793! | |
| [2025-02-23 06:42:46,315][00191] Fps is (10 sec: 4505.5, 60 sec: 4027.7, 300 sec: 3998.8). Total num frames: 1740800. Throughput: 0: 1006.9. Samples: 433634. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:42:46,316][00191] Avg episode reward: [(0, '10.344')] | |
| [2025-02-23 06:42:46,385][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000426_1744896.pth... | |
| [2025-02-23 06:42:46,510][03147] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000190_778240.pth | |
| [2025-02-23 06:42:46,527][03147] Saving new best policy, reward=10.344! | |
| [2025-02-23 06:42:51,315][00191] Fps is (10 sec: 3686.3, 60 sec: 4027.7, 300 sec: 3998.8). Total num frames: 1757184. Throughput: 0: 994.0. Samples: 439096. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:42:51,316][00191] Avg episode reward: [(0, '10.357')] | |
| [2025-02-23 06:42:51,318][03147] Saving new best policy, reward=10.357! | |
| [2025-02-23 06:42:52,038][03160] Updated weights for policy 0, policy_version 430 (0.0026) | |
| [2025-02-23 06:42:56,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.4, 300 sec: 3984.9). Total num frames: 1777664. Throughput: 0: 999.3. Samples: 445044. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:42:56,316][00191] Avg episode reward: [(0, '11.298')] | |
| [2025-02-23 06:42:56,321][03147] Saving new best policy, reward=11.298! | |
| [2025-02-23 06:43:00,892][03160] Updated weights for policy 0, policy_version 440 (0.0022) | |
| [2025-02-23 06:43:01,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 3998.8). Total num frames: 1802240. Throughput: 0: 999.3. Samples: 448416. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:43:01,316][00191] Avg episode reward: [(0, '11.108')] | |
| [2025-02-23 06:43:06,315][00191] Fps is (10 sec: 4096.1, 60 sec: 4027.7, 300 sec: 4012.7). Total num frames: 1818624. Throughput: 0: 996.3. Samples: 454178. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:43:06,316][00191] Avg episode reward: [(0, '11.496')] | |
| [2025-02-23 06:43:06,325][03147] Saving new best policy, reward=11.496! | |
| [2025-02-23 06:43:11,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3998.8). Total num frames: 1839104. Throughput: 0: 1008.6. Samples: 460356. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:43:11,320][00191] Avg episode reward: [(0, '12.285')] | |
| [2025-02-23 06:43:11,326][03147] Saving new best policy, reward=12.285! | |
| [2025-02-23 06:43:11,698][03160] Updated weights for policy 0, policy_version 450 (0.0019) | |
| [2025-02-23 06:43:16,316][00191] Fps is (10 sec: 4504.8, 60 sec: 4027.6, 300 sec: 4012.7). Total num frames: 1863680. Throughput: 0: 1008.6. Samples: 463746. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:43:16,320][00191] Avg episode reward: [(0, '12.162')] | |
| [2025-02-23 06:43:21,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4012.7). Total num frames: 1880064. Throughput: 0: 1002.9. Samples: 469312. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:43:21,316][00191] Avg episode reward: [(0, '12.567')] | |
| [2025-02-23 06:43:21,321][03147] Saving new best policy, reward=12.567! | |
| [2025-02-23 06:43:22,350][03160] Updated weights for policy 0, policy_version 460 (0.0012) | |
| [2025-02-23 06:43:26,315][00191] Fps is (10 sec: 3687.0, 60 sec: 4027.7, 300 sec: 4012.7). Total num frames: 1900544. Throughput: 0: 1004.1. Samples: 475356. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:43:26,316][00191] Avg episode reward: [(0, '12.782')] | |
| [2025-02-23 06:43:26,322][03147] Saving new best policy, reward=12.782! | |
| [2025-02-23 06:43:31,315][00191] Fps is (10 sec: 4096.1, 60 sec: 3959.5, 300 sec: 3998.8). Total num frames: 1921024. Throughput: 0: 1003.2. Samples: 478776. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:43:31,316][00191] Avg episode reward: [(0, '12.776')] | |
| [2025-02-23 06:43:31,479][03160] Updated weights for policy 0, policy_version 470 (0.0017) | |
| [2025-02-23 06:43:36,315][00191] Fps is (10 sec: 3686.5, 60 sec: 4027.7, 300 sec: 3998.8). Total num frames: 1937408. Throughput: 0: 999.1. Samples: 484056. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:43:36,316][00191] Avg episode reward: [(0, '12.186')] | |
| [2025-02-23 06:43:41,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4012.7). Total num frames: 1961984. Throughput: 0: 1013.7. Samples: 490662. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:43:41,320][00191] Avg episode reward: [(0, '11.854')] | |
| [2025-02-23 06:43:41,819][03160] Updated weights for policy 0, policy_version 480 (0.0026) | |
| [2025-02-23 06:43:46,319][00191] Fps is (10 sec: 4503.7, 60 sec: 4027.5, 300 sec: 4012.7). Total num frames: 1982464. Throughput: 0: 1015.5. Samples: 494118. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:43:46,320][00191] Avg episode reward: [(0, '11.083')] | |
| [2025-02-23 06:43:51,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.8, 300 sec: 4012.7). Total num frames: 1998848. Throughput: 0: 1003.7. Samples: 499346. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:43:51,321][00191] Avg episode reward: [(0, '11.428')] | |
| [2025-02-23 06:43:52,742][03160] Updated weights for policy 0, policy_version 490 (0.0016) | |
| [2025-02-23 06:43:56,315][00191] Fps is (10 sec: 4097.8, 60 sec: 4096.0, 300 sec: 4012.7). Total num frames: 2023424. Throughput: 0: 1011.6. Samples: 505876. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:43:56,318][00191] Avg episode reward: [(0, '11.755')] | |
| [2025-02-23 06:44:01,315][00191] Fps is (10 sec: 4505.5, 60 sec: 4027.7, 300 sec: 4012.7). Total num frames: 2043904. Throughput: 0: 1014.4. Samples: 509392. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:44:01,319][00191] Avg episode reward: [(0, '12.472')] | |
| [2025-02-23 06:44:02,018][03160] Updated weights for policy 0, policy_version 500 (0.0026) | |
| [2025-02-23 06:44:06,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4012.7). Total num frames: 2060288. Throughput: 0: 1006.0. Samples: 514584. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:44:06,316][00191] Avg episode reward: [(0, '12.811')] | |
| [2025-02-23 06:44:06,322][03147] Saving new best policy, reward=12.811! | |
| [2025-02-23 06:44:11,315][00191] Fps is (10 sec: 4096.1, 60 sec: 4096.0, 300 sec: 4012.7). Total num frames: 2084864. Throughput: 0: 1021.7. Samples: 521332. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:44:11,316][00191] Avg episode reward: [(0, '12.989')] | |
| [2025-02-23 06:44:11,317][03147] Saving new best policy, reward=12.989! | |
| [2025-02-23 06:44:11,958][03160] Updated weights for policy 0, policy_version 510 (0.0026) | |
| [2025-02-23 06:44:16,315][00191] Fps is (10 sec: 4505.5, 60 sec: 4027.8, 300 sec: 4012.7). Total num frames: 2105344. Throughput: 0: 1021.5. Samples: 524744. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:44:16,318][00191] Avg episode reward: [(0, '12.972')] | |
| [2025-02-23 06:44:21,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4012.7). Total num frames: 2121728. Throughput: 0: 1016.1. Samples: 529782. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:44:21,316][00191] Avg episode reward: [(0, '13.177')] | |
| [2025-02-23 06:44:21,317][03147] Saving new best policy, reward=13.177! | |
| [2025-02-23 06:44:22,715][03160] Updated weights for policy 0, policy_version 520 (0.0020) | |
| [2025-02-23 06:44:26,315][00191] Fps is (10 sec: 4096.1, 60 sec: 4096.0, 300 sec: 4012.7). Total num frames: 2146304. Throughput: 0: 1019.6. Samples: 536542. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:44:26,316][00191] Avg episode reward: [(0, '13.417')] | |
| [2025-02-23 06:44:26,324][03147] Saving new best policy, reward=13.417! | |
| [2025-02-23 06:44:31,315][00191] Fps is (10 sec: 4505.5, 60 sec: 4096.0, 300 sec: 4012.7). Total num frames: 2166784. Throughput: 0: 1018.8. Samples: 539960. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:44:31,319][00191] Avg episode reward: [(0, '13.152')] | |
| [2025-02-23 06:44:32,356][03160] Updated weights for policy 0, policy_version 530 (0.0027) | |
| [2025-02-23 06:44:36,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4012.7). Total num frames: 2183168. Throughput: 0: 1011.2. Samples: 544852. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-23 06:44:36,319][00191] Avg episode reward: [(0, '13.986')] | |
| [2025-02-23 06:44:36,324][03147] Saving new best policy, reward=13.986! | |
| [2025-02-23 06:44:41,315][00191] Fps is (10 sec: 4096.1, 60 sec: 4096.0, 300 sec: 4026.6). Total num frames: 2207744. Throughput: 0: 1020.3. Samples: 551790. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:44:41,319][00191] Avg episode reward: [(0, '15.185')] | |
| [2025-02-23 06:44:41,323][03147] Saving new best policy, reward=15.185! | |
| [2025-02-23 06:44:42,172][03160] Updated weights for policy 0, policy_version 540 (0.0020) | |
| [2025-02-23 06:44:46,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4028.0, 300 sec: 4012.7). Total num frames: 2224128. Throughput: 0: 1020.5. Samples: 555312. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:44:46,317][00191] Avg episode reward: [(0, '15.547')] | |
| [2025-02-23 06:44:46,330][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000543_2224128.pth... | |
| [2025-02-23 06:44:46,523][03147] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000307_1257472.pth | |
| [2025-02-23 06:44:46,539][03147] Saving new best policy, reward=15.547! | |
| [2025-02-23 06:44:51,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4026.6). Total num frames: 2244608. Throughput: 0: 1009.6. Samples: 560018. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:44:51,316][00191] Avg episode reward: [(0, '16.600')] | |
| [2025-02-23 06:44:51,320][03147] Saving new best policy, reward=16.600! | |
| [2025-02-23 06:44:53,100][03160] Updated weights for policy 0, policy_version 550 (0.0019) | |
| [2025-02-23 06:44:56,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 2265088. Throughput: 0: 1012.3. Samples: 566884. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:44:56,316][00191] Avg episode reward: [(0, '15.419')] | |
| [2025-02-23 06:45:01,316][00191] Fps is (10 sec: 4095.4, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 2285568. Throughput: 0: 1013.4. Samples: 570350. Policy #0 lag: (min: 0.0, avg: 0.8, max: 2.0) | |
| [2025-02-23 06:45:01,322][00191] Avg episode reward: [(0, '14.297')] | |
| [2025-02-23 06:45:03,448][03160] Updated weights for policy 0, policy_version 560 (0.0041) | |
| [2025-02-23 06:45:06,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 2306048. Throughput: 0: 1011.0. Samples: 575278. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-23 06:45:06,318][00191] Avg episode reward: [(0, '14.158')] | |
| [2025-02-23 06:45:11,315][00191] Fps is (10 sec: 4096.4, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 2326528. Throughput: 0: 1018.5. Samples: 582374. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:45:11,316][00191] Avg episode reward: [(0, '13.334')] | |
| [2025-02-23 06:45:12,136][03160] Updated weights for policy 0, policy_version 570 (0.0026) | |
| [2025-02-23 06:45:16,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.8, 300 sec: 4040.5). Total num frames: 2347008. Throughput: 0: 1021.2. Samples: 585916. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:45:16,316][00191] Avg episode reward: [(0, '12.843')] | |
| [2025-02-23 06:45:21,315][00191] Fps is (10 sec: 4096.1, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 2367488. Throughput: 0: 1021.2. Samples: 590808. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-23 06:45:21,316][00191] Avg episode reward: [(0, '14.172')] | |
| [2025-02-23 06:45:22,918][03160] Updated weights for policy 0, policy_version 580 (0.0019) | |
| [2025-02-23 06:45:26,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 2387968. Throughput: 0: 1018.6. Samples: 597628. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:45:26,319][00191] Avg episode reward: [(0, '14.893')] | |
| [2025-02-23 06:45:31,316][00191] Fps is (10 sec: 4095.4, 60 sec: 4027.6, 300 sec: 4040.4). Total num frames: 2408448. Throughput: 0: 1017.8. Samples: 601114. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:45:31,318][00191] Avg episode reward: [(0, '16.239')] | |
| [2025-02-23 06:45:33,518][03160] Updated weights for policy 0, policy_version 590 (0.0015) | |
| [2025-02-23 06:45:36,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 2428928. Throughput: 0: 1021.7. Samples: 605996. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:45:36,316][00191] Avg episode reward: [(0, '16.384')] | |
| [2025-02-23 06:45:41,315][00191] Fps is (10 sec: 4096.6, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 2449408. Throughput: 0: 1026.1. Samples: 613058. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:45:41,316][00191] Avg episode reward: [(0, '17.176')] | |
| [2025-02-23 06:45:41,363][03147] Saving new best policy, reward=17.176! | |
| [2025-02-23 06:45:42,270][03160] Updated weights for policy 0, policy_version 600 (0.0028) | |
| [2025-02-23 06:45:46,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 2469888. Throughput: 0: 1022.5. Samples: 616360. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:45:46,316][00191] Avg episode reward: [(0, '17.556')] | |
| [2025-02-23 06:45:46,322][03147] Saving new best policy, reward=17.556! | |
| [2025-02-23 06:45:51,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2490368. Throughput: 0: 1021.1. Samples: 621228. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:45:51,319][00191] Avg episode reward: [(0, '16.791')] | |
| [2025-02-23 06:45:53,176][03160] Updated weights for policy 0, policy_version 610 (0.0039) | |
| [2025-02-23 06:45:56,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 2510848. Throughput: 0: 1018.4. Samples: 628200. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:45:56,319][00191] Avg episode reward: [(0, '16.592')] | |
| [2025-02-23 06:46:01,315][00191] Fps is (10 sec: 4095.7, 60 sec: 4096.0, 300 sec: 4054.4). Total num frames: 2531328. Throughput: 0: 1009.4. Samples: 631340. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-23 06:46:01,322][00191] Avg episode reward: [(0, '15.695')] | |
| [2025-02-23 06:46:03,616][03160] Updated weights for policy 0, policy_version 620 (0.0017) | |
| [2025-02-23 06:46:06,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2551808. Throughput: 0: 1017.6. Samples: 636600. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:46:06,316][00191] Avg episode reward: [(0, '14.766')] | |
| [2025-02-23 06:46:11,315][00191] Fps is (10 sec: 4096.3, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 2572288. Throughput: 0: 1023.5. Samples: 643686. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:46:11,316][00191] Avg episode reward: [(0, '16.164')] | |
| [2025-02-23 06:46:12,341][03160] Updated weights for policy 0, policy_version 630 (0.0018) | |
| [2025-02-23 06:46:16,316][00191] Fps is (10 sec: 3685.8, 60 sec: 4027.6, 300 sec: 4040.5). Total num frames: 2588672. Throughput: 0: 1014.0. Samples: 646742. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:46:16,318][00191] Avg episode reward: [(0, '17.540')] | |
| [2025-02-23 06:46:21,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2613248. Throughput: 0: 1027.3. Samples: 652224. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:46:21,316][00191] Avg episode reward: [(0, '17.946')] | |
| [2025-02-23 06:46:21,317][03147] Saving new best policy, reward=17.946! | |
| [2025-02-23 06:46:22,982][03160] Updated weights for policy 0, policy_version 640 (0.0014) | |
| [2025-02-23 06:46:26,315][00191] Fps is (10 sec: 4506.3, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2633728. Throughput: 0: 1022.1. Samples: 659052. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:46:26,318][00191] Avg episode reward: [(0, '18.350')] | |
| [2025-02-23 06:46:26,325][03147] Saving new best policy, reward=18.350! | |
| [2025-02-23 06:46:31,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.8, 300 sec: 4040.5). Total num frames: 2650112. Throughput: 0: 1014.7. Samples: 662020. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:46:31,321][00191] Avg episode reward: [(0, '17.735')] | |
| [2025-02-23 06:46:33,658][03160] Updated weights for policy 0, policy_version 650 (0.0022) | |
| [2025-02-23 06:46:36,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2674688. Throughput: 0: 1025.1. Samples: 667356. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:46:36,316][00191] Avg episode reward: [(0, '16.921')] | |
| [2025-02-23 06:46:41,315][00191] Fps is (10 sec: 4915.2, 60 sec: 4164.3, 300 sec: 4068.2). Total num frames: 2699264. Throughput: 0: 1029.6. Samples: 674530. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:46:41,316][00191] Avg episode reward: [(0, '18.091')] | |
| [2025-02-23 06:46:42,098][03160] Updated weights for policy 0, policy_version 660 (0.0018) | |
| [2025-02-23 06:46:46,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 2711552. Throughput: 0: 1021.3. Samples: 677300. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-23 06:46:46,317][00191] Avg episode reward: [(0, '17.437')] | |
| [2025-02-23 06:46:46,325][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000662_2711552.pth... | |
| [2025-02-23 06:46:46,473][03147] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000426_1744896.pth | |
| [2025-02-23 06:46:51,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2736128. Throughput: 0: 1028.8. Samples: 682894. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:46:51,318][00191] Avg episode reward: [(0, '17.938')] | |
| [2025-02-23 06:46:52,833][03160] Updated weights for policy 0, policy_version 670 (0.0025) | |
| [2025-02-23 06:46:56,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2756608. Throughput: 0: 1025.0. Samples: 689810. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:46:56,316][00191] Avg episode reward: [(0, '17.260')] | |
| [2025-02-23 06:47:01,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.8, 300 sec: 4054.4). Total num frames: 2772992. Throughput: 0: 1014.7. Samples: 692404. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:47:01,316][00191] Avg episode reward: [(0, '17.464')] | |
| [2025-02-23 06:47:03,627][03160] Updated weights for policy 0, policy_version 680 (0.0021) | |
| [2025-02-23 06:47:06,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 2793472. Throughput: 0: 1017.6. Samples: 698018. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:47:06,316][00191] Avg episode reward: [(0, '17.953')] | |
| [2025-02-23 06:47:11,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 2818048. Throughput: 0: 1015.3. Samples: 704742. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:47:11,316][00191] Avg episode reward: [(0, '19.399')] | |
| [2025-02-23 06:47:11,317][03147] Saving new best policy, reward=19.399! | |
| [2025-02-23 06:47:13,747][03160] Updated weights for policy 0, policy_version 690 (0.0029) | |
| [2025-02-23 06:47:16,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.8, 300 sec: 4040.5). Total num frames: 2830336. Throughput: 0: 1000.6. Samples: 707046. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:47:16,320][00191] Avg episode reward: [(0, '19.747')] | |
| [2025-02-23 06:47:16,327][03147] Saving new best policy, reward=19.747! | |
| [2025-02-23 06:47:21,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 2854912. Throughput: 0: 1007.3. Samples: 712686. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:47:21,317][00191] Avg episode reward: [(0, '20.915')] | |
| [2025-02-23 06:47:21,320][03147] Saving new best policy, reward=20.915! | |
| [2025-02-23 06:47:23,727][03160] Updated weights for policy 0, policy_version 700 (0.0016) | |
| [2025-02-23 06:47:26,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 2875392. Throughput: 0: 998.1. Samples: 719446. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:47:26,317][00191] Avg episode reward: [(0, '20.308')] | |
| [2025-02-23 06:47:31,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 2891776. Throughput: 0: 989.4. Samples: 721824. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:47:31,318][00191] Avg episode reward: [(0, '19.873')] | |
| [2025-02-23 06:47:34,606][03160] Updated weights for policy 0, policy_version 710 (0.0031) | |
| [2025-02-23 06:47:36,315][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 4040.5). Total num frames: 2912256. Throughput: 0: 996.3. Samples: 727728. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:47:36,318][00191] Avg episode reward: [(0, '19.351')] | |
| [2025-02-23 06:47:41,316][00191] Fps is (10 sec: 4504.9, 60 sec: 3959.4, 300 sec: 4054.3). Total num frames: 2936832. Throughput: 0: 992.5. Samples: 734476. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:47:41,322][00191] Avg episode reward: [(0, '19.162')] | |
| [2025-02-23 06:47:45,601][03160] Updated weights for policy 0, policy_version 720 (0.0020) | |
| [2025-02-23 06:47:46,315][00191] Fps is (10 sec: 3686.3, 60 sec: 3959.4, 300 sec: 4040.5). Total num frames: 2949120. Throughput: 0: 981.9. Samples: 736592. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:47:46,319][00191] Avg episode reward: [(0, '18.425')] | |
| [2025-02-23 06:47:51,315][00191] Fps is (10 sec: 3687.0, 60 sec: 3959.5, 300 sec: 4054.4). Total num frames: 2973696. Throughput: 0: 993.4. Samples: 742722. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) | |
| [2025-02-23 06:47:51,316][00191] Avg episode reward: [(0, '18.677')] | |
| [2025-02-23 06:47:54,328][03160] Updated weights for policy 0, policy_version 730 (0.0020) | |
| [2025-02-23 06:47:56,315][00191] Fps is (10 sec: 4505.8, 60 sec: 3959.5, 300 sec: 4040.5). Total num frames: 2994176. Throughput: 0: 993.2. Samples: 749438. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:47:56,319][00191] Avg episode reward: [(0, '19.641')] | |
| [2025-02-23 06:48:01,314][00191] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 4040.5). Total num frames: 3010560. Throughput: 0: 989.0. Samples: 751552. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:48:01,316][00191] Avg episode reward: [(0, '19.824')] | |
| [2025-02-23 06:48:04,933][03160] Updated weights for policy 0, policy_version 740 (0.0018) | |
| [2025-02-23 06:48:06,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 3035136. Throughput: 0: 1007.8. Samples: 758038. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:48:06,316][00191] Avg episode reward: [(0, '19.156')] | |
| [2025-02-23 06:48:11,315][00191] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 4040.5). Total num frames: 3055616. Throughput: 0: 1006.7. Samples: 764748. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:48:11,316][00191] Avg episode reward: [(0, '19.059')] | |
| [2025-02-23 06:48:15,554][03160] Updated weights for policy 0, policy_version 750 (0.0025) | |
| [2025-02-23 06:48:16,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3072000. Throughput: 0: 999.6. Samples: 766808. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:48:16,316][00191] Avg episode reward: [(0, '18.034')] | |
| [2025-02-23 06:48:21,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 3096576. Throughput: 0: 1016.1. Samples: 773454. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:48:21,319][00191] Avg episode reward: [(0, '18.293')] | |
| [2025-02-23 06:48:24,537][03160] Updated weights for policy 0, policy_version 760 (0.0027) | |
| [2025-02-23 06:48:26,318][00191] Fps is (10 sec: 4503.9, 60 sec: 4027.5, 300 sec: 4054.3). Total num frames: 3117056. Throughput: 0: 1011.8. Samples: 780008. Policy #0 lag: (min: 0.0, avg: 0.8, max: 2.0) | |
| [2025-02-23 06:48:26,320][00191] Avg episode reward: [(0, '18.264')] | |
| [2025-02-23 06:48:31,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 3133440. Throughput: 0: 1011.5. Samples: 782110. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:48:31,318][00191] Avg episode reward: [(0, '18.836')] | |
| [2025-02-23 06:48:34,965][03160] Updated weights for policy 0, policy_version 770 (0.0024) | |
| [2025-02-23 06:48:36,315][00191] Fps is (10 sec: 4097.6, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3158016. Throughput: 0: 1021.8. Samples: 788704. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:48:36,320][00191] Avg episode reward: [(0, '19.546')] | |
| [2025-02-23 06:48:41,316][00191] Fps is (10 sec: 4505.1, 60 sec: 4027.8, 300 sec: 4054.4). Total num frames: 3178496. Throughput: 0: 1019.1. Samples: 795298. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:48:41,325][00191] Avg episode reward: [(0, '18.989')] | |
| [2025-02-23 06:48:45,591][03160] Updated weights for policy 0, policy_version 780 (0.0017) | |
| [2025-02-23 06:48:46,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3194880. Throughput: 0: 1018.5. Samples: 797384. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:48:46,316][00191] Avg episode reward: [(0, '19.163')] | |
| [2025-02-23 06:48:46,380][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000781_3198976.pth... | |
| [2025-02-23 06:48:46,501][03147] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000543_2224128.pth | |
| [2025-02-23 06:48:51,315][00191] Fps is (10 sec: 4096.4, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3219456. Throughput: 0: 1025.0. Samples: 804164. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:48:51,317][00191] Avg episode reward: [(0, '19.280')] | |
| [2025-02-23 06:48:54,209][03160] Updated weights for policy 0, policy_version 790 (0.0013) | |
| [2025-02-23 06:48:56,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3239936. Throughput: 0: 1014.5. Samples: 810402. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:48:56,318][00191] Avg episode reward: [(0, '19.294')] | |
| [2025-02-23 06:49:01,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3256320. Throughput: 0: 1014.4. Samples: 812458. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:01,316][00191] Avg episode reward: [(0, '20.244')] | |
| [2025-02-23 06:49:05,230][03160] Updated weights for policy 0, policy_version 800 (0.0027) | |
| [2025-02-23 06:49:06,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3280896. Throughput: 0: 1013.7. Samples: 819072. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:06,316][00191] Avg episode reward: [(0, '21.012')] | |
| [2025-02-23 06:49:06,320][03147] Saving new best policy, reward=21.012! | |
| [2025-02-23 06:49:11,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3297280. Throughput: 0: 997.6. Samples: 824898. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-23 06:49:11,317][00191] Avg episode reward: [(0, '21.335')] | |
| [2025-02-23 06:49:11,321][03147] Saving new best policy, reward=21.335! | |
| [2025-02-23 06:49:16,311][03160] Updated weights for policy 0, policy_version 810 (0.0036) | |
| [2025-02-23 06:49:16,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3317760. Throughput: 0: 994.2. Samples: 826848. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:49:16,317][00191] Avg episode reward: [(0, '20.397')] | |
| [2025-02-23 06:49:21,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3338240. Throughput: 0: 1004.1. Samples: 833888. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:21,323][00191] Avg episode reward: [(0, '19.890')] | |
| [2025-02-23 06:49:26,013][03160] Updated weights for policy 0, policy_version 820 (0.0023) | |
| [2025-02-23 06:49:26,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4028.0, 300 sec: 4040.5). Total num frames: 3358720. Throughput: 0: 992.8. Samples: 839974. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:49:26,319][00191] Avg episode reward: [(0, '19.993')] | |
| [2025-02-23 06:49:31,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3375104. Throughput: 0: 994.2. Samples: 842124. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:31,323][00191] Avg episode reward: [(0, '20.276')] | |
| [2025-02-23 06:49:35,814][03160] Updated weights for policy 0, policy_version 830 (0.0024) | |
| [2025-02-23 06:49:36,315][00191] Fps is (10 sec: 4095.8, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3399680. Throughput: 0: 998.8. Samples: 849112. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:36,316][00191] Avg episode reward: [(0, '21.554')] | |
| [2025-02-23 06:49:36,323][03147] Saving new best policy, reward=21.554! | |
| [2025-02-23 06:49:41,314][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.8, 300 sec: 4054.3). Total num frames: 3420160. Throughput: 0: 993.6. Samples: 855112. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:41,316][00191] Avg episode reward: [(0, '21.263')] | |
| [2025-02-23 06:49:46,315][00191] Fps is (10 sec: 3686.5, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3436544. Throughput: 0: 996.6. Samples: 857304. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:46,316][00191] Avg episode reward: [(0, '20.929')] | |
| [2025-02-23 06:49:46,568][03160] Updated weights for policy 0, policy_version 840 (0.0033) | |
| [2025-02-23 06:49:51,314][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 3461120. Throughput: 0: 1006.9. Samples: 864384. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:51,316][00191] Avg episode reward: [(0, '20.112')] | |
| [2025-02-23 06:49:56,315][00191] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 4040.5). Total num frames: 3477504. Throughput: 0: 1009.6. Samples: 870332. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:49:56,316][00191] Avg episode reward: [(0, '20.099')] | |
| [2025-02-23 06:49:56,532][03160] Updated weights for policy 0, policy_version 850 (0.0028) | |
| [2025-02-23 06:50:01,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3497984. Throughput: 0: 1015.6. Samples: 872550. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:50:01,316][00191] Avg episode reward: [(0, '19.376')] | |
| [2025-02-23 06:50:06,060][03160] Updated weights for policy 0, policy_version 860 (0.0028) | |
| [2025-02-23 06:50:06,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 4054.3). Total num frames: 3522560. Throughput: 0: 1012.8. Samples: 879466. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:50:06,316][00191] Avg episode reward: [(0, '20.433')] | |
| [2025-02-23 06:50:11,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3538944. Throughput: 0: 1011.2. Samples: 885478. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:50:11,316][00191] Avg episode reward: [(0, '20.754')] | |
| [2025-02-23 06:50:16,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3559424. Throughput: 0: 1015.7. Samples: 887830. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:50:16,323][00191] Avg episode reward: [(0, '19.367')] | |
| [2025-02-23 06:50:16,819][03160] Updated weights for policy 0, policy_version 870 (0.0013) | |
| [2025-02-23 06:50:21,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3584000. Throughput: 0: 1018.6. Samples: 894948. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:50:21,319][00191] Avg episode reward: [(0, '20.432')] | |
| [2025-02-23 06:50:26,315][00191] Fps is (10 sec: 4095.6, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3600384. Throughput: 0: 1014.2. Samples: 900750. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:50:26,317][00191] Avg episode reward: [(0, '20.480')] | |
| [2025-02-23 06:50:27,231][03160] Updated weights for policy 0, policy_version 880 (0.0015) | |
| [2025-02-23 06:50:31,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 3620864. Throughput: 0: 1017.2. Samples: 903080. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:50:31,316][00191] Avg episode reward: [(0, '20.220')] | |
| [2025-02-23 06:50:36,261][03160] Updated weights for policy 0, policy_version 890 (0.0025) | |
| [2025-02-23 06:50:36,315][00191] Fps is (10 sec: 4506.0, 60 sec: 4096.0, 300 sec: 4054.3). Total num frames: 3645440. Throughput: 0: 1015.3. Samples: 910072. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:50:36,316][00191] Avg episode reward: [(0, '21.042')] | |
| [2025-02-23 06:50:41,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3661824. Throughput: 0: 1010.2. Samples: 915790. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:50:41,316][00191] Avg episode reward: [(0, '21.637')] | |
| [2025-02-23 06:50:41,322][03147] Saving new best policy, reward=21.637! | |
| [2025-02-23 06:50:46,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 3682304. Throughput: 0: 1014.6. Samples: 918208. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:50:46,319][00191] Avg episode reward: [(0, '21.107')] | |
| [2025-02-23 06:50:46,328][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000899_3682304.pth... | |
| [2025-02-23 06:50:46,470][03147] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000662_2711552.pth | |
| [2025-02-23 06:50:47,074][03160] Updated weights for policy 0, policy_version 900 (0.0026) | |
| [2025-02-23 06:50:51,315][00191] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3702784. Throughput: 0: 1015.1. Samples: 925144. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:50:51,316][00191] Avg episode reward: [(0, '21.476')] | |
| [2025-02-23 06:50:56,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 3719168. Throughput: 0: 1007.2. Samples: 930802. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:50:56,318][00191] Avg episode reward: [(0, '21.044')] | |
| [2025-02-23 06:50:57,893][03160] Updated weights for policy 0, policy_version 910 (0.0031) | |
| [2025-02-23 06:51:01,315][00191] Fps is (10 sec: 3686.3, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 3739648. Throughput: 0: 1010.1. Samples: 933286. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:51:01,316][00191] Avg episode reward: [(0, '21.823')] | |
| [2025-02-23 06:51:01,317][03147] Saving new best policy, reward=21.823! | |
| [2025-02-23 06:51:06,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3764224. Throughput: 0: 1005.3. Samples: 940186. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-23 06:51:06,317][00191] Avg episode reward: [(0, '20.884')] | |
| [2025-02-23 06:51:06,724][03160] Updated weights for policy 0, policy_version 920 (0.0016) | |
| [2025-02-23 06:51:11,315][00191] Fps is (10 sec: 4096.1, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3780608. Throughput: 0: 1000.8. Samples: 945784. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:51:11,320][00191] Avg episode reward: [(0, '19.972')] | |
| [2025-02-23 06:51:16,315][00191] Fps is (10 sec: 3686.3, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 3801088. Throughput: 0: 1009.5. Samples: 948508. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-23 06:51:16,320][00191] Avg episode reward: [(0, '19.267')] | |
| [2025-02-23 06:51:17,395][03160] Updated weights for policy 0, policy_version 930 (0.0025) | |
| [2025-02-23 06:51:21,315][00191] Fps is (10 sec: 4505.6, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3825664. Throughput: 0: 1010.9. Samples: 955562. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:51:21,318][00191] Avg episode reward: [(0, '18.876')] | |
| [2025-02-23 06:51:26,315][00191] Fps is (10 sec: 4095.8, 60 sec: 4027.7, 300 sec: 4040.4). Total num frames: 3842048. Throughput: 0: 1003.9. Samples: 960968. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:51:26,317][00191] Avg episode reward: [(0, '20.349')] | |
| [2025-02-23 06:51:28,158][03160] Updated weights for policy 0, policy_version 940 (0.0019) | |
| [2025-02-23 06:51:31,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 3862528. Throughput: 0: 1010.4. Samples: 963678. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:51:31,319][00191] Avg episode reward: [(0, '20.429')] | |
| [2025-02-23 06:51:36,315][00191] Fps is (10 sec: 4506.0, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 3887104. Throughput: 0: 1012.3. Samples: 970698. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:51:36,320][00191] Avg episode reward: [(0, '21.928')] | |
| [2025-02-23 06:51:36,325][03147] Saving new best policy, reward=21.928! | |
| [2025-02-23 06:51:36,857][03160] Updated weights for policy 0, policy_version 950 (0.0023) | |
| [2025-02-23 06:51:41,315][00191] Fps is (10 sec: 4095.8, 60 sec: 4027.7, 300 sec: 4040.5). Total num frames: 3903488. Throughput: 0: 1005.2. Samples: 976038. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-23 06:51:41,316][00191] Avg episode reward: [(0, '21.856')] | |
| [2025-02-23 06:51:46,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 3923968. Throughput: 0: 1015.3. Samples: 978974. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-23 06:51:46,322][00191] Avg episode reward: [(0, '21.262')] | |
| [2025-02-23 06:51:47,655][03160] Updated weights for policy 0, policy_version 960 (0.0017) | |
| [2025-02-23 06:51:51,315][00191] Fps is (10 sec: 4505.9, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 3948544. Throughput: 0: 1017.7. Samples: 985982. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:51:51,319][00191] Avg episode reward: [(0, '19.584')] | |
| [2025-02-23 06:51:56,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 4026.6). Total num frames: 3960832. Throughput: 0: 1010.0. Samples: 991234. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-23 06:51:56,316][00191] Avg episode reward: [(0, '19.682')] | |
| [2025-02-23 06:51:58,380][03160] Updated weights for policy 0, policy_version 970 (0.0020) | |
| [2025-02-23 06:52:01,315][00191] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 4040.5). Total num frames: 3985408. Throughput: 0: 1015.2. Samples: 994192. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-23 06:52:01,321][00191] Avg episode reward: [(0, '19.865')] | |
| [2025-02-23 06:52:05,458][03147] Stopping Batcher_0... | |
| [2025-02-23 06:52:05,459][03147] Loop batcher_evt_loop terminating... | |
| [2025-02-23 06:52:05,458][00191] Component Batcher_0 stopped! | |
| [2025-02-23 06:52:05,461][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-23 06:52:05,523][03160] Weights refcount: 2 0 | |
| [2025-02-23 06:52:05,526][00191] Component InferenceWorker_p0-w0 stopped! | |
| [2025-02-23 06:52:05,536][03160] Stopping InferenceWorker_p0-w0... | |
| [2025-02-23 06:52:05,537][03160] Loop inference_proc0-0_evt_loop terminating... | |
| [2025-02-23 06:52:05,583][03147] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000781_3198976.pth | |
| [2025-02-23 06:52:05,610][03147] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-23 06:52:05,784][03147] Stopping LearnerWorker_p0... | |
| [2025-02-23 06:52:05,787][03147] Loop learner_proc0_evt_loop terminating... | |
| [2025-02-23 06:52:05,784][00191] Component LearnerWorker_p0 stopped! | |
| [2025-02-23 06:52:05,816][00191] Component RolloutWorker_w4 stopped! | |
| [2025-02-23 06:52:05,820][03165] Stopping RolloutWorker_w4... | |
| [2025-02-23 06:52:05,825][03165] Loop rollout_proc4_evt_loop terminating... | |
| [2025-02-23 06:52:05,830][00191] Component RolloutWorker_w6 stopped! | |
| [2025-02-23 06:52:05,834][03166] Stopping RolloutWorker_w6... | |
| [2025-02-23 06:52:05,835][03166] Loop rollout_proc6_evt_loop terminating... | |
| [2025-02-23 06:52:05,845][00191] Component RolloutWorker_w0 stopped! | |
| [2025-02-23 06:52:05,848][03161] Stopping RolloutWorker_w0... | |
| [2025-02-23 06:52:05,849][03161] Loop rollout_proc0_evt_loop terminating... | |
| [2025-02-23 06:52:05,857][00191] Component RolloutWorker_w2 stopped! | |
| [2025-02-23 06:52:05,861][03163] Stopping RolloutWorker_w2... | |
| [2025-02-23 06:52:05,861][03163] Loop rollout_proc2_evt_loop terminating... | |
| [2025-02-23 06:52:05,902][03164] Stopping RolloutWorker_w3... | |
| [2025-02-23 06:52:05,902][00191] Component RolloutWorker_w3 stopped! | |
| [2025-02-23 06:52:05,903][03164] Loop rollout_proc3_evt_loop terminating... | |
| [2025-02-23 06:52:05,953][03162] Stopping RolloutWorker_w1... | |
| [2025-02-23 06:52:05,952][00191] Component RolloutWorker_w1 stopped! | |
| [2025-02-23 06:52:05,953][03162] Loop rollout_proc1_evt_loop terminating... | |
| [2025-02-23 06:52:05,961][00191] Component RolloutWorker_w7 stopped! | |
| [2025-02-23 06:52:05,962][03168] Stopping RolloutWorker_w7... | |
| [2025-02-23 06:52:05,972][03168] Loop rollout_proc7_evt_loop terminating... | |
| [2025-02-23 06:52:05,990][00191] Component RolloutWorker_w5 stopped! | |
| [2025-02-23 06:52:05,991][00191] Waiting for process learner_proc0 to stop... | |
| [2025-02-23 06:52:05,994][03167] Stopping RolloutWorker_w5... | |
| [2025-02-23 06:52:06,002][03167] Loop rollout_proc5_evt_loop terminating... | |
| [2025-02-23 06:52:07,953][00191] Waiting for process inference_proc0-0 to join... | |
| [2025-02-23 06:52:07,957][00191] Waiting for process rollout_proc0 to join... | |
| [2025-02-23 06:52:10,877][00191] Waiting for process rollout_proc1 to join... | |
| [2025-02-23 06:52:10,977][00191] Waiting for process rollout_proc2 to join... | |
| [2025-02-23 06:52:10,978][00191] Waiting for process rollout_proc3 to join... | |
| [2025-02-23 06:52:10,979][00191] Waiting for process rollout_proc4 to join... | |
| [2025-02-23 06:52:10,980][00191] Waiting for process rollout_proc5 to join... | |
| [2025-02-23 06:52:10,981][00191] Waiting for process rollout_proc6 to join... | |
| [2025-02-23 06:52:10,982][00191] Waiting for process rollout_proc7 to join... | |
| [2025-02-23 06:52:10,983][00191] Batcher 0 profile tree view: | |
| batching: 26.4001, releasing_batches: 0.0274 | |
| [2025-02-23 06:52:10,984][00191] InferenceWorker_p0-w0 profile tree view: | |
| wait_policy: 0.0000 | |
| wait_policy_total: 384.6336 | |
| update_model: 8.5430 | |
| weight_update: 0.0019 | |
| one_step: 0.0025 | |
| handle_policy_step: 580.1463 | |
| deserialize: 13.6501, stack: 3.1407, obs_to_device_normalize: 122.5225, forward: 297.3303, send_messages: 28.7869 | |
| prepare_outputs: 89.9430 | |
| to_cpu: 55.7478 | |
| [2025-02-23 06:52:10,985][00191] Learner 0 profile tree view: | |
| misc: 0.0054, prepare_batch: 12.8570 | |
| train: 72.2988 | |
| epoch_init: 0.0083, minibatch_init: 0.0055, losses_postprocess: 0.6818, kl_divergence: 0.6911, after_optimizer: 33.5983 | |
| calculate_losses: 25.3999 | |
| losses_init: 0.0035, forward_head: 1.3832, bptt_initial: 16.6761, tail: 1.0576, advantages_returns: 0.2730, losses: 3.6250 | |
| bptt: 2.1013 | |
| bptt_forward_core: 2.0063 | |
| update: 11.3431 | |
| clip: 0.8777 | |
| [2025-02-23 06:52:10,987][00191] RolloutWorker_w0 profile tree view: | |
| wait_for_trajectories: 0.2915, enqueue_policy_requests: 93.2445, env_step: 798.6544, overhead: 11.9721, complete_rollouts: 7.2306 | |
| save_policy_outputs: 17.1616 | |
| split_output_tensors: 6.2938 | |
| [2025-02-23 06:52:10,988][00191] RolloutWorker_w7 profile tree view: | |
| wait_for_trajectories: 0.3496, enqueue_policy_requests: 94.9230, env_step: 797.4497, overhead: 11.7406, complete_rollouts: 6.7046 | |
| save_policy_outputs: 18.4859 | |
| split_output_tensors: 7.5162 | |
| [2025-02-23 06:52:10,989][00191] Loop Runner_EvtLoop terminating... | |
| [2025-02-23 06:52:10,990][00191] Runner profile tree view: | |
| main_loop: 1039.0881 | |
| [2025-02-23 06:52:10,991][00191] Collected {0: 4005888}, FPS: 3855.2 | |
| [2025-02-23 06:52:11,544][00191] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-23 06:52:11,545][00191] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-23 06:52:11,546][00191] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-23 06:52:11,547][00191] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-23 06:52:11,548][00191] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-23 06:52:11,549][00191] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-23 06:52:11,550][00191] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-23 06:52:11,551][00191] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-23 06:52:11,552][00191] Adding new argument 'push_to_hub'=False that is not in the saved config file! | |
| [2025-02-23 06:52:11,552][00191] Adding new argument 'hf_repository'=None that is not in the saved config file! | |
| [2025-02-23 06:52:11,553][00191] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-23 06:52:11,554][00191] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-23 06:52:11,555][00191] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-23 06:52:11,556][00191] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-23 06:52:11,556][00191] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-23 06:52:11,589][00191] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-23 06:52:11,592][00191] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-23 06:52:11,593][00191] RunningMeanStd input shape: (1,) | |
| [2025-02-23 06:52:11,607][00191] ConvEncoder: input_channels=3 | |
| [2025-02-23 06:52:11,715][00191] Conv encoder output size: 512 | |
| [2025-02-23 06:52:11,715][00191] Policy head output size: 512 | |
| [2025-02-23 06:52:11,891][00191] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-23 06:52:12,628][00191] Num frames 100... | |
| [2025-02-23 06:52:12,763][00191] Num frames 200... | |
| [2025-02-23 06:52:12,889][00191] Num frames 300... | |
| [2025-02-23 06:52:13,014][00191] Num frames 400... | |
| [2025-02-23 06:52:13,146][00191] Num frames 500... | |
| [2025-02-23 06:52:13,273][00191] Num frames 600... | |
| [2025-02-23 06:52:13,400][00191] Num frames 700... | |
| [2025-02-23 06:52:13,526][00191] Num frames 800... | |
| [2025-02-23 06:52:13,652][00191] Num frames 900... | |
| [2025-02-23 06:52:13,790][00191] Avg episode rewards: #0: 19.600, true rewards: #0: 9.600 | |
| [2025-02-23 06:52:13,791][00191] Avg episode reward: 19.600, avg true_objective: 9.600 | |
| [2025-02-23 06:52:13,843][00191] Num frames 1000... | |
| [2025-02-23 06:52:13,968][00191] Num frames 1100... | |
| [2025-02-23 06:52:14,097][00191] Num frames 1200... | |
| [2025-02-23 06:52:14,225][00191] Num frames 1300... | |
| [2025-02-23 06:52:14,353][00191] Num frames 1400... | |
| [2025-02-23 06:52:14,486][00191] Num frames 1500... | |
| [2025-02-23 06:52:14,614][00191] Avg episode rewards: #0: 16.780, true rewards: #0: 7.780 | |
| [2025-02-23 06:52:14,614][00191] Avg episode reward: 16.780, avg true_objective: 7.780 | |
| [2025-02-23 06:52:14,671][00191] Num frames 1600... | |
| [2025-02-23 06:52:14,803][00191] Num frames 1700... | |
| [2025-02-23 06:52:14,930][00191] Num frames 1800... | |
| [2025-02-23 06:52:15,055][00191] Num frames 1900... | |
| [2025-02-23 06:52:15,185][00191] Num frames 2000... | |
| [2025-02-23 06:52:15,310][00191] Num frames 2100... | |
| [2025-02-23 06:52:15,436][00191] Num frames 2200... | |
| [2025-02-23 06:52:15,562][00191] Num frames 2300... | |
| [2025-02-23 06:52:15,691][00191] Num frames 2400... | |
| [2025-02-23 06:52:15,841][00191] Num frames 2500... | |
| [2025-02-23 06:52:15,970][00191] Num frames 2600... | |
| [2025-02-23 06:52:16,122][00191] Avg episode rewards: #0: 18.587, true rewards: #0: 8.920 | |
| [2025-02-23 06:52:16,123][00191] Avg episode reward: 18.587, avg true_objective: 8.920 | |
| [2025-02-23 06:52:16,158][00191] Num frames 2700... | |
| [2025-02-23 06:52:16,285][00191] Num frames 2800... | |
| [2025-02-23 06:52:16,414][00191] Num frames 2900... | |
| [2025-02-23 06:52:16,540][00191] Num frames 3000... | |
| [2025-02-23 06:52:16,667][00191] Num frames 3100... | |
| [2025-02-23 06:52:16,799][00191] Num frames 3200... | |
| [2025-02-23 06:52:16,928][00191] Num frames 3300... | |
| [2025-02-23 06:52:17,056][00191] Num frames 3400... | |
| [2025-02-23 06:52:17,186][00191] Num frames 3500... | |
| [2025-02-23 06:52:17,314][00191] Num frames 3600... | |
| [2025-02-23 06:52:17,445][00191] Num frames 3700... | |
| [2025-02-23 06:52:17,496][00191] Avg episode rewards: #0: 19.250, true rewards: #0: 9.250 | |
| [2025-02-23 06:52:17,497][00191] Avg episode reward: 19.250, avg true_objective: 9.250 | |
| [2025-02-23 06:52:17,627][00191] Num frames 3800... | |
| [2025-02-23 06:52:17,754][00191] Num frames 3900... | |
| [2025-02-23 06:52:17,887][00191] Num frames 4000... | |
| [2025-02-23 06:52:18,016][00191] Num frames 4100... | |
| [2025-02-23 06:52:18,143][00191] Num frames 4200... | |
| [2025-02-23 06:52:18,271][00191] Num frames 4300... | |
| [2025-02-23 06:52:18,397][00191] Num frames 4400... | |
| [2025-02-23 06:52:18,528][00191] Num frames 4500... | |
| [2025-02-23 06:52:18,655][00191] Num frames 4600... | |
| [2025-02-23 06:52:18,779][00191] Num frames 4700... | |
| [2025-02-23 06:52:18,911][00191] Num frames 4800... | |
| [2025-02-23 06:52:19,039][00191] Num frames 4900... | |
| [2025-02-23 06:52:19,171][00191] Num frames 5000... | |
| [2025-02-23 06:52:19,301][00191] Num frames 5100... | |
| [2025-02-23 06:52:19,430][00191] Num frames 5200... | |
| [2025-02-23 06:52:19,557][00191] Num frames 5300... | |
| [2025-02-23 06:52:19,694][00191] Num frames 5400... | |
| [2025-02-23 06:52:19,882][00191] Num frames 5500... | |
| [2025-02-23 06:52:20,057][00191] Num frames 5600... | |
| [2025-02-23 06:52:20,234][00191] Num frames 5700... | |
| [2025-02-23 06:52:20,405][00191] Num frames 5800... | |
| [2025-02-23 06:52:20,458][00191] Avg episode rewards: #0: 26.800, true rewards: #0: 11.600 | |
| [2025-02-23 06:52:20,459][00191] Avg episode reward: 26.800, avg true_objective: 11.600 | |
| [2025-02-23 06:52:20,627][00191] Num frames 5900... | |
| [2025-02-23 06:52:20,792][00191] Num frames 6000... | |
| [2025-02-23 06:52:20,971][00191] Num frames 6100... | |
| [2025-02-23 06:52:21,145][00191] Num frames 6200... | |
| [2025-02-23 06:52:21,323][00191] Num frames 6300... | |
| [2025-02-23 06:52:21,520][00191] Avg episode rewards: #0: 23.960, true rewards: #0: 10.627 | |
| [2025-02-23 06:52:21,522][00191] Avg episode reward: 23.960, avg true_objective: 10.627 | |
| [2025-02-23 06:52:21,568][00191] Num frames 6400... | |
| [2025-02-23 06:52:21,745][00191] Num frames 6500... | |
| [2025-02-23 06:52:21,876][00191] Num frames 6600... | |
| [2025-02-23 06:52:22,012][00191] Num frames 6700... | |
| [2025-02-23 06:52:22,144][00191] Num frames 6800... | |
| [2025-02-23 06:52:22,273][00191] Num frames 6900... | |
| [2025-02-23 06:52:22,405][00191] Num frames 7000... | |
| [2025-02-23 06:52:22,536][00191] Num frames 7100... | |
| [2025-02-23 06:52:22,664][00191] Num frames 7200... | |
| [2025-02-23 06:52:22,791][00191] Num frames 7300... | |
| [2025-02-23 06:52:22,923][00191] Num frames 7400... | |
| [2025-02-23 06:52:22,975][00191] Avg episode rewards: #0: 23.429, true rewards: #0: 10.571 | |
| [2025-02-23 06:52:22,976][00191] Avg episode reward: 23.429, avg true_objective: 10.571 | |
| [2025-02-23 06:52:23,107][00191] Num frames 7500... | |
| [2025-02-23 06:52:23,237][00191] Num frames 7600... | |
| [2025-02-23 06:52:23,366][00191] Num frames 7700... | |
| [2025-02-23 06:52:23,494][00191] Num frames 7800... | |
| [2025-02-23 06:52:23,626][00191] Num frames 7900... | |
| [2025-02-23 06:52:23,754][00191] Num frames 8000... | |
| [2025-02-23 06:52:23,883][00191] Num frames 8100... | |
| [2025-02-23 06:52:24,020][00191] Num frames 8200... | |
| [2025-02-23 06:52:24,156][00191] Avg episode rewards: #0: 22.830, true rewards: #0: 10.330 | |
| [2025-02-23 06:52:24,158][00191] Avg episode reward: 22.830, avg true_objective: 10.330 | |
| [2025-02-23 06:52:24,205][00191] Num frames 8300... | |
| [2025-02-23 06:52:24,331][00191] Num frames 8400... | |
| [2025-02-23 06:52:24,459][00191] Num frames 8500... | |
| [2025-02-23 06:52:24,588][00191] Num frames 8600... | |
| [2025-02-23 06:52:24,726][00191] Num frames 8700... | |
| [2025-02-23 06:52:24,855][00191] Num frames 8800... | |
| [2025-02-23 06:52:24,988][00191] Num frames 8900... | |
| [2025-02-23 06:52:25,118][00191] Num frames 9000... | |
| [2025-02-23 06:52:25,249][00191] Num frames 9100... | |
| [2025-02-23 06:52:25,383][00191] Num frames 9200... | |
| [2025-02-23 06:52:25,510][00191] Num frames 9300... | |
| [2025-02-23 06:52:25,638][00191] Num frames 9400... | |
| [2025-02-23 06:52:25,766][00191] Num frames 9500... | |
| [2025-02-23 06:52:25,895][00191] Num frames 9600... | |
| [2025-02-23 06:52:26,081][00191] Avg episode rewards: #0: 24.110, true rewards: #0: 10.777 | |
| [2025-02-23 06:52:26,082][00191] Avg episode reward: 24.110, avg true_objective: 10.777 | |
| [2025-02-23 06:52:26,085][00191] Num frames 9700... | |
| [2025-02-23 06:52:26,214][00191] Num frames 9800... | |
| [2025-02-23 06:52:26,341][00191] Num frames 9900... | |
| [2025-02-23 06:52:26,470][00191] Num frames 10000... | |
| [2025-02-23 06:52:26,603][00191] Num frames 10100... | |
| [2025-02-23 06:52:26,732][00191] Num frames 10200... | |
| [2025-02-23 06:52:26,885][00191] Num frames 10300... | |
| [2025-02-23 06:52:26,995][00191] Avg episode rewards: #0: 22.839, true rewards: #0: 10.339 | |
| [2025-02-23 06:52:26,996][00191] Avg episode reward: 22.839, avg true_objective: 10.339 | |
| [2025-02-23 06:53:31,109][00191] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |
| [2025-02-23 06:53:31,661][00191] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-23 06:53:31,662][00191] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-23 06:53:31,663][00191] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-23 06:53:31,664][00191] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-23 06:53:31,665][00191] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-23 06:53:31,666][00191] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-23 06:53:31,667][00191] Adding new argument 'max_num_frames'=100000 that is not in the saved config file! | |
| [2025-02-23 06:53:31,668][00191] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-23 06:53:31,669][00191] Adding new argument 'push_to_hub'=True that is not in the saved config file! | |
| [2025-02-23 06:53:31,670][00191] Adding new argument 'hf_repository'='AIventurer/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file! | |
| [2025-02-23 06:53:31,671][00191] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-23 06:53:31,672][00191] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-23 06:53:31,673][00191] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-23 06:53:31,674][00191] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-23 06:53:31,675][00191] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-23 06:53:31,709][00191] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-23 06:53:31,710][00191] RunningMeanStd input shape: (1,) | |
| [2025-02-23 06:53:31,729][00191] ConvEncoder: input_channels=3 | |
| [2025-02-23 06:53:31,778][00191] Conv encoder output size: 512 | |
| [2025-02-23 06:53:31,779][00191] Policy head output size: 512 | |
| [2025-02-23 06:53:31,803][00191] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-23 06:53:32,466][00191] Num frames 100... | |
| [2025-02-23 06:53:32,629][00191] Num frames 200... | |
| [2025-02-23 06:53:32,793][00191] Num frames 300... | |
| [2025-02-23 06:53:32,953][00191] Num frames 400... | |
| [2025-02-23 06:53:33,114][00191] Num frames 500... | |
| [2025-02-23 06:53:33,275][00191] Num frames 600... | |
| [2025-02-23 06:53:33,452][00191] Num frames 700... | |
| [2025-02-23 06:53:33,657][00191] Avg episode rewards: #0: 17.940, true rewards: #0: 7.940 | |
| [2025-02-23 06:53:33,658][00191] Avg episode reward: 17.940, avg true_objective: 7.940 | |
| [2025-02-23 06:53:33,668][00191] Num frames 800... | |
| [2025-02-23 06:53:33,833][00191] Num frames 900... | |
| [2025-02-23 06:53:33,991][00191] Num frames 1000... | |
| [2025-02-23 06:53:34,155][00191] Num frames 1100... | |
| [2025-02-23 06:53:34,321][00191] Num frames 1200... | |
| [2025-02-23 06:53:34,506][00191] Num frames 1300... | |
| [2025-02-23 06:53:34,691][00191] Num frames 1400... | |
| [2025-02-23 06:53:34,752][00191] Avg episode rewards: #0: 14.010, true rewards: #0: 7.010 | |
| [2025-02-23 06:53:34,752][00191] Avg episode reward: 14.010, avg true_objective: 7.010 | |
| [2025-02-23 06:53:34,945][00191] Num frames 1500... | |
| [2025-02-23 06:53:35,076][00191] Num frames 1600... | |
| [2025-02-23 06:53:35,219][00191] Num frames 1700... | |
| [2025-02-23 06:53:35,349][00191] Num frames 1800... | |
| [2025-02-23 06:53:35,488][00191] Num frames 1900... | |
| [2025-02-23 06:53:35,646][00191] Num frames 2000... | |
| [2025-02-23 06:53:35,822][00191] Num frames 2100... | |
| [2025-02-23 06:53:35,995][00191] Num frames 2200... | |
| [2025-02-23 06:53:36,144][00191] Avg episode rewards: #0: 15.507, true rewards: #0: 7.507 | |
| [2025-02-23 06:53:36,147][00191] Avg episode reward: 15.507, avg true_objective: 7.507 | |
| [2025-02-23 06:53:36,228][00191] Num frames 2300... | |
| [2025-02-23 06:53:36,399][00191] Num frames 2400... | |
| [2025-02-23 06:53:36,589][00191] Num frames 2500... | |
| [2025-02-23 06:53:36,778][00191] Num frames 2600... | |
| [2025-02-23 06:53:36,963][00191] Num frames 2700... | |
| [2025-02-23 06:53:37,143][00191] Num frames 2800... | |
| [2025-02-23 06:53:37,316][00191] Num frames 2900... | |
| [2025-02-23 06:53:37,498][00191] Num frames 3000... | |
| [2025-02-23 06:53:37,689][00191] Num frames 3100... | |
| [2025-02-23 06:53:37,823][00191] Num frames 3200... | |
| [2025-02-23 06:53:37,953][00191] Num frames 3300... | |
| [2025-02-23 06:53:38,081][00191] Num frames 3400... | |
| [2025-02-23 06:53:38,211][00191] Num frames 3500... | |
| [2025-02-23 06:53:38,340][00191] Num frames 3600... | |
| [2025-02-23 06:53:38,469][00191] Num frames 3700... | |
| [2025-02-23 06:53:38,609][00191] Num frames 3800... | |
| [2025-02-23 06:53:38,679][00191] Avg episode rewards: #0: 22.277, true rewards: #0: 9.527 | |
| [2025-02-23 06:53:38,679][00191] Avg episode reward: 22.277, avg true_objective: 9.527 | |
| [2025-02-23 06:53:38,794][00191] Num frames 3900... | |
| [2025-02-23 06:53:38,923][00191] Num frames 4000... | |
| [2025-02-23 06:53:39,051][00191] Num frames 4100... | |
| [2025-02-23 06:53:39,183][00191] Num frames 4200... | |
| [2025-02-23 06:53:39,314][00191] Avg episode rewards: #0: 18.918, true rewards: #0: 8.518 | |
| [2025-02-23 06:53:39,314][00191] Avg episode reward: 18.918, avg true_objective: 8.518 | |
| [2025-02-23 06:53:39,368][00191] Num frames 4300... | |
| [2025-02-23 06:53:39,497][00191] Num frames 4400... | |
| [2025-02-23 06:53:39,635][00191] Num frames 4500... | |
| [2025-02-23 06:53:39,767][00191] Num frames 4600... | |
| [2025-02-23 06:53:39,905][00191] Num frames 4700... | |
| [2025-02-23 06:53:40,048][00191] Num frames 4800... | |
| [2025-02-23 06:53:40,184][00191] Num frames 4900... | |
| [2025-02-23 06:53:40,329][00191] Num frames 5000... | |
| [2025-02-23 06:53:40,462][00191] Num frames 5100... | |
| [2025-02-23 06:53:40,590][00191] Num frames 5200... | |
| [2025-02-23 06:53:40,726][00191] Num frames 5300... | |
| [2025-02-23 06:53:40,856][00191] Num frames 5400... | |
| [2025-02-23 06:53:40,985][00191] Num frames 5500... | |
| [2025-02-23 06:53:41,063][00191] Avg episode rewards: #0: 20.362, true rewards: #0: 9.195 | |
| [2025-02-23 06:53:41,064][00191] Avg episode reward: 20.362, avg true_objective: 9.195 | |
| [2025-02-23 06:53:41,170][00191] Num frames 5600... | |
| [2025-02-23 06:53:41,295][00191] Num frames 5700... | |
| [2025-02-23 06:53:41,419][00191] Num frames 5800... | |
| [2025-02-23 06:53:41,550][00191] Num frames 5900... | |
| [2025-02-23 06:53:41,681][00191] Num frames 6000... | |
| [2025-02-23 06:53:41,805][00191] Num frames 6100... | |
| [2025-02-23 06:53:41,932][00191] Num frames 6200... | |
| [2025-02-23 06:53:42,058][00191] Num frames 6300... | |
| [2025-02-23 06:53:42,187][00191] Num frames 6400... | |
| [2025-02-23 06:53:42,341][00191] Avg episode rewards: #0: 20.110, true rewards: #0: 9.253 | |
| [2025-02-23 06:53:42,342][00191] Avg episode reward: 20.110, avg true_objective: 9.253 | |
| [2025-02-23 06:53:42,373][00191] Num frames 6500... | |
| [2025-02-23 06:53:42,499][00191] Num frames 6600... | |
| [2025-02-23 06:53:42,629][00191] Num frames 6700... | |
| [2025-02-23 06:53:42,762][00191] Num frames 6800... | |
| [2025-02-23 06:53:42,891][00191] Num frames 6900... | |
| [2025-02-23 06:53:43,017][00191] Num frames 7000... | |
| [2025-02-23 06:53:43,144][00191] Num frames 7100... | |
| [2025-02-23 06:53:43,280][00191] Num frames 7200... | |
| [2025-02-23 06:53:43,409][00191] Num frames 7300... | |
| [2025-02-23 06:53:43,537][00191] Num frames 7400... | |
| [2025-02-23 06:53:43,667][00191] Num frames 7500... | |
| [2025-02-23 06:53:43,801][00191] Num frames 7600... | |
| [2025-02-23 06:53:43,932][00191] Num frames 7700... | |
| [2025-02-23 06:53:44,060][00191] Num frames 7800... | |
| [2025-02-23 06:53:44,194][00191] Num frames 7900... | |
| [2025-02-23 06:53:44,326][00191] Num frames 8000... | |
| [2025-02-23 06:53:44,454][00191] Num frames 8100... | |
| [2025-02-23 06:53:44,583][00191] Avg episode rewards: #0: 23.319, true rewards: #0: 10.194 | |
| [2025-02-23 06:53:44,584][00191] Avg episode reward: 23.319, avg true_objective: 10.194 | |
| [2025-02-23 06:53:44,648][00191] Num frames 8200... | |
| [2025-02-23 06:53:44,787][00191] Num frames 8300... | |
| [2025-02-23 06:53:44,918][00191] Num frames 8400... | |
| [2025-02-23 06:53:45,046][00191] Num frames 8500... | |
| [2025-02-23 06:53:45,176][00191] Num frames 8600... | |
| [2025-02-23 06:53:45,304][00191] Num frames 8700... | |
| [2025-02-23 06:53:45,436][00191] Num frames 8800... | |
| [2025-02-23 06:53:45,611][00191] Avg episode rewards: #0: 22.657, true rewards: #0: 9.879 | |
| [2025-02-23 06:53:45,612][00191] Avg episode reward: 22.657, avg true_objective: 9.879 | |
| [2025-02-23 06:53:45,627][00191] Num frames 8900... | |
| [2025-02-23 06:53:45,760][00191] Num frames 9000... | |
| [2025-02-23 06:53:45,892][00191] Num frames 9100... | |
| [2025-02-23 06:53:46,018][00191] Num frames 9200... | |
| [2025-02-23 06:53:46,146][00191] Num frames 9300... | |
| [2025-02-23 06:53:46,277][00191] Num frames 9400... | |
| [2025-02-23 06:53:46,406][00191] Num frames 9500... | |
| [2025-02-23 06:53:46,532][00191] Num frames 9600... | |
| [2025-02-23 06:53:46,665][00191] Num frames 9700... | |
| [2025-02-23 06:53:46,800][00191] Num frames 9800... | |
| [2025-02-23 06:53:46,930][00191] Num frames 9900... | |
| [2025-02-23 06:53:47,058][00191] Num frames 10000... | |
| [2025-02-23 06:53:47,185][00191] Num frames 10100... | |
| [2025-02-23 06:53:47,289][00191] Avg episode rewards: #0: 22.939, true rewards: #0: 10.139 | |
| [2025-02-23 06:53:47,290][00191] Avg episode reward: 22.939, avg true_objective: 10.139 | |
| [2025-02-23 06:54:49,473][00191] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |
| [2025-02-23 07:01:07,511][00191] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-23 07:01:07,511][00191] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-23 07:01:07,513][00191] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-23 07:01:07,514][00191] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-23 07:01:07,515][00191] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-23 07:01:07,515][00191] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-23 07:01:07,516][00191] Adding new argument 'max_num_frames'=100000 that is not in the saved config file! | |
| [2025-02-23 07:01:07,517][00191] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-23 07:01:07,518][00191] Adding new argument 'push_to_hub'=True that is not in the saved config file! | |
| [2025-02-23 07:01:07,519][00191] Adding new argument 'hf_repository'='AIventurer/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file! | |
| [2025-02-23 07:01:07,520][00191] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-23 07:01:07,521][00191] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-23 07:01:07,522][00191] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-23 07:01:07,522][00191] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-23 07:01:07,524][00191] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-23 07:01:07,557][00191] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-23 07:01:07,559][00191] RunningMeanStd input shape: (1,) | |
| [2025-02-23 07:01:07,570][00191] ConvEncoder: input_channels=3 | |
| [2025-02-23 07:01:07,604][00191] Conv encoder output size: 512 | |
| [2025-02-23 07:01:07,605][00191] Policy head output size: 512 | |
| [2025-02-23 07:01:07,623][00191] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-23 07:01:08,056][00191] Num frames 100... | |
| [2025-02-23 07:01:08,189][00191] Num frames 200... | |
| [2025-02-23 07:01:08,323][00191] Num frames 300... | |
| [2025-02-23 07:01:08,455][00191] Num frames 400... | |
| [2025-02-23 07:01:08,572][00191] Avg episode rewards: #0: 9.480, true rewards: #0: 4.480 | |
| [2025-02-23 07:01:08,573][00191] Avg episode reward: 9.480, avg true_objective: 4.480 | |
| [2025-02-23 07:01:08,640][00191] Num frames 500... | |
| [2025-02-23 07:01:08,769][00191] Num frames 600... | |
| [2025-02-23 07:01:08,897][00191] Num frames 700... | |
| [2025-02-23 07:01:09,025][00191] Num frames 800... | |
| [2025-02-23 07:01:09,156][00191] Num frames 900... | |
| [2025-02-23 07:01:09,291][00191] Num frames 1000... | |
| [2025-02-23 07:01:09,417][00191] Num frames 1100... | |
| [2025-02-23 07:01:09,544][00191] Num frames 1200... | |
| [2025-02-23 07:01:09,672][00191] Num frames 1300... | |
| [2025-02-23 07:01:09,799][00191] Num frames 1400... | |
| [2025-02-23 07:01:09,926][00191] Num frames 1500... | |
| [2025-02-23 07:01:10,040][00191] Avg episode rewards: #0: 16.725, true rewards: #0: 7.725 | |
| [2025-02-23 07:01:10,041][00191] Avg episode reward: 16.725, avg true_objective: 7.725 | |
| [2025-02-23 07:01:10,112][00191] Num frames 1600... | |
| [2025-02-23 07:01:10,243][00191] Num frames 1700... | |
| [2025-02-23 07:01:10,382][00191] Num frames 1800... | |
| [2025-02-23 07:01:10,509][00191] Num frames 1900... | |
| [2025-02-23 07:01:10,638][00191] Num frames 2000... | |
| [2025-02-23 07:01:10,766][00191] Num frames 2100... | |
| [2025-02-23 07:01:10,896][00191] Num frames 2200... | |
| [2025-02-23 07:01:11,025][00191] Num frames 2300... | |
| [2025-02-23 07:01:11,158][00191] Num frames 2400... | |
| [2025-02-23 07:01:11,286][00191] Num frames 2500... | |
| [2025-02-23 07:01:11,421][00191] Num frames 2600... | |
| [2025-02-23 07:01:11,554][00191] Num frames 2700... | |
| [2025-02-23 07:01:11,681][00191] Num frames 2800... | |
| [2025-02-23 07:01:11,812][00191] Num frames 2900... | |
| [2025-02-23 07:01:11,954][00191] Avg episode rewards: #0: 22.220, true rewards: #0: 9.887 | |
| [2025-02-23 07:01:11,955][00191] Avg episode reward: 22.220, avg true_objective: 9.887 | |
| [2025-02-23 07:01:11,999][00191] Num frames 3000... | |
| [2025-02-23 07:01:12,125][00191] Num frames 3100... | |
| [2025-02-23 07:01:12,256][00191] Num frames 3200... | |
| [2025-02-23 07:01:12,391][00191] Num frames 3300... | |
| [2025-02-23 07:01:12,520][00191] Num frames 3400... | |
| [2025-02-23 07:01:12,650][00191] Num frames 3500... | |
| [2025-02-23 07:01:12,780][00191] Num frames 3600... | |
| [2025-02-23 07:01:12,907][00191] Num frames 3700... | |
| [2025-02-23 07:01:13,037][00191] Num frames 3800... | |
| [2025-02-23 07:01:13,169][00191] Num frames 3900... | |
| [2025-02-23 07:01:13,299][00191] Num frames 4000... | |
| [2025-02-23 07:01:13,476][00191] Avg episode rewards: #0: 23.725, true rewards: #0: 10.225 | |
| [2025-02-23 07:01:13,477][00191] Avg episode reward: 23.725, avg true_objective: 10.225 | |
| [2025-02-23 07:01:13,492][00191] Num frames 4100... | |
| [2025-02-23 07:01:13,621][00191] Num frames 4200... | |
| [2025-02-23 07:01:13,747][00191] Num frames 4300... | |
| [2025-02-23 07:01:13,873][00191] Num frames 4400... | |
| [2025-02-23 07:01:13,996][00191] Num frames 4500... | |
| [2025-02-23 07:01:14,125][00191] Num frames 4600... | |
| [2025-02-23 07:01:14,263][00191] Num frames 4700... | |
| [2025-02-23 07:01:14,396][00191] Num frames 4800... | |
| [2025-02-23 07:01:14,528][00191] Num frames 4900... | |
| [2025-02-23 07:01:14,655][00191] Num frames 5000... | |
| [2025-02-23 07:01:14,733][00191] Avg episode rewards: #0: 23.836, true rewards: #0: 10.036 | |
| [2025-02-23 07:01:14,734][00191] Avg episode reward: 23.836, avg true_objective: 10.036 | |
| [2025-02-23 07:01:14,839][00191] Num frames 5100... | |
| [2025-02-23 07:01:14,967][00191] Num frames 5200... | |
| [2025-02-23 07:01:15,095][00191] Num frames 5300... | |
| [2025-02-23 07:01:15,227][00191] Num frames 5400... | |
| [2025-02-23 07:01:15,354][00191] Num frames 5500... | |
| [2025-02-23 07:01:15,525][00191] Num frames 5600... | |
| [2025-02-23 07:01:15,702][00191] Num frames 5700... | |
| [2025-02-23 07:01:15,874][00191] Num frames 5800... | |
| [2025-02-23 07:01:16,042][00191] Num frames 5900... | |
| [2025-02-23 07:01:16,215][00191] Num frames 6000... | |
| [2025-02-23 07:01:16,384][00191] Num frames 6100... | |
| [2025-02-23 07:01:16,454][00191] Avg episode rewards: #0: 24.343, true rewards: #0: 10.177 | |
| [2025-02-23 07:01:16,455][00191] Avg episode reward: 24.343, avg true_objective: 10.177 | |
| [2025-02-23 07:01:16,614][00191] Num frames 6200... | |
| [2025-02-23 07:01:16,788][00191] Num frames 6300... | |
| [2025-02-23 07:01:16,968][00191] Num frames 6400... | |
| [2025-02-23 07:01:17,142][00191] Num frames 6500... | |
| [2025-02-23 07:01:17,314][00191] Num frames 6600... | |
| [2025-02-23 07:01:17,508][00191] Num frames 6700... | |
| [2025-02-23 07:01:17,634][00191] Num frames 6800... | |
| [2025-02-23 07:01:17,762][00191] Num frames 6900... | |
| [2025-02-23 07:01:17,892][00191] Num frames 7000... | |
| [2025-02-23 07:01:18,022][00191] Num frames 7100... | |
| [2025-02-23 07:01:18,152][00191] Num frames 7200... | |
| [2025-02-23 07:01:18,279][00191] Num frames 7300... | |
| [2025-02-23 07:01:18,406][00191] Num frames 7400... | |
| [2025-02-23 07:01:18,539][00191] Num frames 7500... | |
| [2025-02-23 07:01:18,668][00191] Num frames 7600... | |
| [2025-02-23 07:01:18,794][00191] Num frames 7700... | |
| [2025-02-23 07:01:18,921][00191] Num frames 7800... | |
| [2025-02-23 07:01:19,049][00191] Num frames 7900... | |
| [2025-02-23 07:01:19,181][00191] Num frames 8000... | |
| [2025-02-23 07:01:19,312][00191] Num frames 8100... | |
| [2025-02-23 07:01:19,440][00191] Num frames 8200... | |
| [2025-02-23 07:01:19,504][00191] Avg episode rewards: #0: 28.723, true rewards: #0: 11.723 | |
| [2025-02-23 07:01:19,505][00191] Avg episode reward: 28.723, avg true_objective: 11.723 | |
| [2025-02-23 07:01:19,633][00191] Num frames 8300... | |
| [2025-02-23 07:01:19,762][00191] Num frames 8400... | |
| [2025-02-23 07:01:19,899][00191] Num frames 8500... | |
| [2025-02-23 07:01:20,033][00191] Avg episode rewards: #0: 26.076, true rewards: #0: 10.701 | |
| [2025-02-23 07:01:20,034][00191] Avg episode reward: 26.076, avg true_objective: 10.701 | |
| [2025-02-23 07:01:20,084][00191] Num frames 8600... | |
| [2025-02-23 07:01:20,215][00191] Num frames 8700... | |
| [2025-02-23 07:01:20,343][00191] Num frames 8800... | |
| [2025-02-23 07:01:20,474][00191] Num frames 8900... | |
| [2025-02-23 07:01:20,610][00191] Num frames 9000... | |
| [2025-02-23 07:01:20,739][00191] Num frames 9100... | |
| [2025-02-23 07:01:20,866][00191] Num frames 9200... | |
| [2025-02-23 07:01:20,994][00191] Num frames 9300... | |
| [2025-02-23 07:01:21,123][00191] Num frames 9400... | |
| [2025-02-23 07:01:21,255][00191] Num frames 9500... | |
| [2025-02-23 07:01:21,388][00191] Num frames 9600... | |
| [2025-02-23 07:01:21,520][00191] Num frames 9700... | |
| [2025-02-23 07:01:21,593][00191] Avg episode rewards: #0: 26.126, true rewards: #0: 10.792 | |
| [2025-02-23 07:01:21,594][00191] Avg episode reward: 26.126, avg true_objective: 10.792 | |
| [2025-02-23 07:01:21,705][00191] Num frames 9800... | |
| [2025-02-23 07:01:21,832][00191] Num frames 9900... | |
| [2025-02-23 07:01:21,957][00191] Num frames 10000... | |
| [2025-02-23 07:01:22,087][00191] Num frames 10100... | |
| [2025-02-23 07:01:22,226][00191] Avg episode rewards: #0: 24.361, true rewards: #0: 10.161 | |
| [2025-02-23 07:01:22,227][00191] Avg episode reward: 24.361, avg true_objective: 10.161 | |
| [2025-02-23 07:02:24,850][00191] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |