| [2025-04-28 08:24:57,495][04703] Saving configuration to /content/train_dir/default_experiment/config.json... | |
| [2025-04-28 08:24:57,497][04703] Rollout worker 0 uses device cpu | |
| [2025-04-28 08:24:57,498][04703] Rollout worker 1 uses device cpu | |
| [2025-04-28 08:24:57,499][04703] Rollout worker 2 uses device cpu | |
| [2025-04-28 08:24:57,499][04703] Rollout worker 3 uses device cpu | |
| [2025-04-28 08:24:57,500][04703] Rollout worker 4 uses device cpu | |
| [2025-04-28 08:24:57,505][04703] Rollout worker 5 uses device cpu | |
| [2025-04-28 08:24:57,506][04703] Rollout worker 6 uses device cpu | |
| [2025-04-28 08:24:57,507][04703] Rollout worker 7 uses device cpu | |
| [2025-04-28 08:24:57,599][04703] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-04-28 08:24:57,601][04703] InferenceWorker_p0-w0: min num requests: 2 | |
| [2025-04-28 08:24:57,630][04703] Starting all processes... | |
| [2025-04-28 08:24:57,631][04703] Starting process learner_proc0 | |
| [2025-04-28 08:24:59,882][04703] Starting all processes... | |
| [2025-04-28 08:24:59,892][04703] Starting process inference_proc0-0 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc0 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc1 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc2 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc3 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc4 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc5 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc6 | |
| [2025-04-28 08:24:59,892][04703] Starting process rollout_proc7 | |
| [2025-04-28 08:25:16,461][05267] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-04-28 08:25:16,464][05267] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 | |
| [2025-04-28 08:25:16,568][05267] Num visible devices: 1 | |
| [2025-04-28 08:25:16,604][05267] Starting seed is not provided | |
| [2025-04-28 08:25:16,606][05267] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-04-28 08:25:16,606][05267] Initializing actor-critic model on device cuda:0 | |
| [2025-04-28 08:25:16,607][05267] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-04-28 08:25:16,609][05267] RunningMeanStd input shape: (1,) | |
| [2025-04-28 08:25:16,740][05267] ConvEncoder: input_channels=3 | |
| [2025-04-28 08:25:17,593][04703] Heartbeat connected on Batcher_0 | |
| [2025-04-28 08:25:17,736][05285] Worker 5 uses CPU cores [1] | |
| [2025-04-28 08:25:17,823][05282] Worker 4 uses CPU cores [0] | |
| [2025-04-28 08:25:17,920][05283] Worker 2 uses CPU cores [0] | |
| [2025-04-28 08:25:17,954][05288] Worker 7 uses CPU cores [1] | |
| [2025-04-28 08:25:17,967][05284] Worker 3 uses CPU cores [1] | |
| [2025-04-28 08:25:17,998][04703] Heartbeat connected on RolloutWorker_w5 | |
| [2025-04-28 08:25:18,017][04703] Heartbeat connected on RolloutWorker_w2 | |
| [2025-04-28 08:25:18,032][04703] Heartbeat connected on RolloutWorker_w4 | |
| [2025-04-28 08:25:18,095][05287] Worker 6 uses CPU cores [0] | |
| [2025-04-28 08:25:18,125][04703] Heartbeat connected on RolloutWorker_w6 | |
| [2025-04-28 08:25:18,136][05267] Conv encoder output size: 512 | |
| [2025-04-28 08:25:18,143][05267] Policy head output size: 512 | |
| [2025-04-28 08:25:18,164][04703] Heartbeat connected on RolloutWorker_w7 | |
| [2025-04-28 08:25:18,193][04703] Heartbeat connected on RolloutWorker_w3 | |
| [2025-04-28 08:25:18,216][05280] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-04-28 08:25:18,217][05280] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 | |
| [2025-04-28 08:25:18,251][05267] Created Actor Critic model with architecture: | |
| [2025-04-28 08:25:18,263][05267] 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) | |
| ) | |
| ) | |
| [2025-04-28 08:25:18,309][05280] Num visible devices: 1 | |
| [2025-04-28 08:25:18,330][04703] Heartbeat connected on InferenceWorker_p0-w0 | |
| [2025-04-28 08:25:18,357][05281] Worker 0 uses CPU cores [0] | |
| [2025-04-28 08:25:18,562][04703] Heartbeat connected on RolloutWorker_w0 | |
| [2025-04-28 08:25:18,703][05286] Worker 1 uses CPU cores [1] | |
| [2025-04-28 08:25:18,769][04703] Heartbeat connected on RolloutWorker_w1 | |
| [2025-04-28 08:25:19,020][05267] Using optimizer <class 'torch.optim.adam.Adam'> | |
| [2025-04-28 08:25:20,370][05267] No checkpoints found | |
| [2025-04-28 08:25:20,370][05267] Did not load from checkpoint, starting from scratch! | |
| [2025-04-28 08:25:20,371][05267] Initialized policy 0 weights for model version 0 | |
| [2025-04-28 08:25:20,375][05267] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-04-28 08:25:20,383][05267] LearnerWorker_p0 finished initialization! | |
| [2025-04-28 08:25:20,384][04703] Heartbeat connected on LearnerWorker_p0 | |
| [2025-04-28 08:25:20,618][05280] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-04-28 08:25:20,619][05280] RunningMeanStd input shape: (1,) | |
| [2025-04-28 08:25:20,630][05280] ConvEncoder: input_channels=3 | |
| [2025-04-28 08:25:20,754][05280] Conv encoder output size: 512 | |
| [2025-04-28 08:25:20,754][05280] Policy head output size: 512 | |
| [2025-04-28 08:25:20,789][04703] Inference worker 0-0 is ready! | |
| [2025-04-28 08:25:20,790][04703] All inference workers are ready! Signal rollout workers to start! | |
| [2025-04-28 08:25:21,029][05288] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:21,040][05285] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:21,058][05284] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:21,062][05287] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:21,075][05282] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:21,090][05283] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:21,111][05286] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:21,119][05281] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:25:22,017][04703] 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) | |
| [2025-04-28 08:25:22,358][05281] Decorrelating experience for 0 frames... | |
| [2025-04-28 08:25:22,358][05286] Decorrelating experience for 0 frames... | |
| [2025-04-28 08:25:22,360][05283] Decorrelating experience for 0 frames... | |
| [2025-04-28 08:25:22,732][05281] Decorrelating experience for 32 frames... | |
| [2025-04-28 08:25:22,735][05286] Decorrelating experience for 32 frames... | |
| [2025-04-28 08:25:23,242][05286] Decorrelating experience for 64 frames... | |
| [2025-04-28 08:25:23,496][05283] Decorrelating experience for 32 frames... | |
| [2025-04-28 08:25:23,659][05286] Decorrelating experience for 96 frames... | |
| [2025-04-28 08:25:23,664][05281] Decorrelating experience for 64 frames... | |
| [2025-04-28 08:25:24,300][05283] Decorrelating experience for 64 frames... | |
| [2025-04-28 08:25:24,308][05281] Decorrelating experience for 96 frames... | |
| [2025-04-28 08:25:24,690][05283] Decorrelating experience for 96 frames... | |
| [2025-04-28 08:25:27,021][04703] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 318.1. Samples: 1592. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-04-28 08:25:27,026][04703] Avg episode reward: [(0, '3.427')] | |
| [2025-04-28 08:25:27,739][05267] Signal inference workers to stop experience collection... | |
| [2025-04-28 08:25:27,764][05280] InferenceWorker_p0-w0: stopping experience collection | |
| [2025-04-28 08:25:29,624][05267] Signal inference workers to resume experience collection... | |
| [2025-04-28 08:25:29,627][05280] InferenceWorker_p0-w0: resuming experience collection | |
| [2025-04-28 08:25:32,017][04703] Fps is (10 sec: 819.2, 60 sec: 819.2, 300 sec: 819.2). Total num frames: 8192. Throughput: 0: 223.4. Samples: 2234. Policy #0 lag: (min: 0.0, avg: 0.0, max: 0.0) | |
| [2025-04-28 08:25:32,019][04703] Avg episode reward: [(0, '3.804')] | |
| [2025-04-28 08:25:37,017][04703] Fps is (10 sec: 2868.3, 60 sec: 1911.5, 300 sec: 1911.5). Total num frames: 28672. Throughput: 0: 441.3. Samples: 6620. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:25:37,019][04703] Avg episode reward: [(0, '4.109')] | |
| [2025-04-28 08:25:39,417][05280] Updated weights for policy 0, policy_version 10 (0.0021) | |
| [2025-04-28 08:25:42,017][04703] Fps is (10 sec: 4096.0, 60 sec: 2457.6, 300 sec: 2457.6). Total num frames: 49152. Throughput: 0: 629.0. Samples: 12580. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:25:42,019][04703] Avg episode reward: [(0, '4.368')] | |
| [2025-04-28 08:25:47,017][04703] Fps is (10 sec: 3276.8, 60 sec: 2457.6, 300 sec: 2457.6). Total num frames: 61440. Throughput: 0: 605.8. Samples: 15144. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:25:47,019][04703] Avg episode reward: [(0, '4.391')] | |
| [2025-04-28 08:25:51,057][05280] Updated weights for policy 0, policy_version 20 (0.0014) | |
| [2025-04-28 08:25:52,017][04703] Fps is (10 sec: 3276.8, 60 sec: 2730.7, 300 sec: 2730.7). Total num frames: 81920. Throughput: 0: 682.2. Samples: 20466. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:25:52,021][04703] Avg episode reward: [(0, '4.428')] | |
| [2025-04-28 08:25:57,018][04703] Fps is (10 sec: 4505.2, 60 sec: 3042.7, 300 sec: 3042.7). Total num frames: 106496. Throughput: 0: 760.5. Samples: 26618. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:25:57,023][04703] Avg episode reward: [(0, '4.368')] | |
| [2025-04-28 08:25:57,024][05267] Saving new best policy, reward=4.368! | |
| [2025-04-28 08:26:02,017][04703] Fps is (10 sec: 3686.4, 60 sec: 2969.6, 300 sec: 2969.6). Total num frames: 118784. Throughput: 0: 713.5. Samples: 28542. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:26:02,020][04703] Avg episode reward: [(0, '4.502')] | |
| [2025-04-28 08:26:02,030][05267] Saving new best policy, reward=4.502! | |
| [2025-04-28 08:26:02,419][05280] Updated weights for policy 0, policy_version 30 (0.0013) | |
| [2025-04-28 08:26:07,017][04703] Fps is (10 sec: 3277.1, 60 sec: 3094.7, 300 sec: 3094.7). Total num frames: 139264. Throughput: 0: 764.4. Samples: 34400. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:26:07,019][04703] Avg episode reward: [(0, '4.679')] | |
| [2025-04-28 08:26:07,020][05267] Saving new best policy, reward=4.679! | |
| [2025-04-28 08:26:12,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3113.0, 300 sec: 3113.0). Total num frames: 155648. Throughput: 0: 854.7. Samples: 40048. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:26:12,019][04703] Avg episode reward: [(0, '4.600')] | |
| [2025-04-28 08:26:13,496][05280] Updated weights for policy 0, policy_version 40 (0.0012) | |
| [2025-04-28 08:26:17,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3202.3, 300 sec: 3202.3). Total num frames: 176128. Throughput: 0: 886.1. Samples: 42108. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:26:17,020][04703] Avg episode reward: [(0, '4.566')] | |
| [2025-04-28 08:26:22,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3276.8, 300 sec: 3276.8). Total num frames: 196608. Throughput: 0: 926.6. Samples: 48318. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:26:22,019][04703] Avg episode reward: [(0, '4.590')] | |
| [2025-04-28 08:26:23,886][05280] Updated weights for policy 0, policy_version 50 (0.0014) | |
| [2025-04-28 08:26:27,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3550.1, 300 sec: 3276.8). Total num frames: 212992. Throughput: 0: 908.1. Samples: 53444. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:26:27,021][04703] Avg episode reward: [(0, '4.450')] | |
| [2025-04-28 08:26:32,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3276.8). Total num frames: 229376. Throughput: 0: 912.3. Samples: 56198. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:26:32,019][04703] Avg episode reward: [(0, '4.523')] | |
| [2025-04-28 08:26:35,159][05280] Updated weights for policy 0, policy_version 60 (0.0014) | |
| [2025-04-28 08:26:37,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3331.4). Total num frames: 249856. Throughput: 0: 932.4. Samples: 62426. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:26:37,021][04703] Avg episode reward: [(0, '4.788')] | |
| [2025-04-28 08:26:37,024][05267] Saving new best policy, reward=4.788! | |
| [2025-04-28 08:26:42,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3328.0). Total num frames: 266240. Throughput: 0: 897.6. Samples: 67008. Policy #0 lag: (min: 0.0, avg: 0.0, max: 1.0) | |
| [2025-04-28 08:26:42,019][04703] Avg episode reward: [(0, '4.666')] | |
| [2025-04-28 08:26:46,509][05280] Updated weights for policy 0, policy_version 70 (0.0014) | |
| [2025-04-28 08:26:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3373.2). Total num frames: 286720. Throughput: 0: 922.0. Samples: 70030. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:26:47,021][04703] Avg episode reward: [(0, '4.690')] | |
| [2025-04-28 08:26:52,020][04703] Fps is (10 sec: 4095.0, 60 sec: 3754.5, 300 sec: 3413.2). Total num frames: 307200. Throughput: 0: 928.8. Samples: 76200. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:26:52,025][04703] Avg episode reward: [(0, '4.570')] | |
| [2025-04-28 08:26:52,041][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000075_307200.pth... | |
| [2025-04-28 08:26:57,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3363.0). Total num frames: 319488. Throughput: 0: 906.1. Samples: 80822. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:26:57,019][04703] Avg episode reward: [(0, '4.429')] | |
| [2025-04-28 08:26:58,457][05280] Updated weights for policy 0, policy_version 80 (0.0019) | |
| [2025-04-28 08:27:02,017][04703] Fps is (10 sec: 3277.6, 60 sec: 3686.4, 300 sec: 3399.7). Total num frames: 339968. Throughput: 0: 921.5. Samples: 83574. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:27:02,022][04703] Avg episode reward: [(0, '4.662')] | |
| [2025-04-28 08:27:07,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3393.8). Total num frames: 356352. Throughput: 0: 910.0. Samples: 89266. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:27:07,018][04703] Avg episode reward: [(0, '4.757')] | |
| [2025-04-28 08:27:09,682][05280] Updated weights for policy 0, policy_version 90 (0.0013) | |
| [2025-04-28 08:27:12,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3425.7). Total num frames: 376832. Throughput: 0: 910.8. Samples: 94430. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:27:12,018][04703] Avg episode reward: [(0, '4.798')] | |
| [2025-04-28 08:27:12,024][05267] Saving new best policy, reward=4.798! | |
| [2025-04-28 08:27:17,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3454.9). Total num frames: 397312. Throughput: 0: 917.2. Samples: 97474. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:27:17,019][04703] Avg episode reward: [(0, '4.850')] | |
| [2025-04-28 08:27:17,022][05267] Saving new best policy, reward=4.850! | |
| [2025-04-28 08:27:21,165][05280] Updated weights for policy 0, policy_version 100 (0.0017) | |
| [2025-04-28 08:27:22,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3413.3). Total num frames: 409600. Throughput: 0: 888.0. Samples: 102388. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:27:22,023][04703] Avg episode reward: [(0, '4.923')] | |
| [2025-04-28 08:27:22,028][05267] Saving new best policy, reward=4.923! | |
| [2025-04-28 08:27:27,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3440.6). Total num frames: 430080. Throughput: 0: 915.0. Samples: 108182. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:27:27,023][04703] Avg episode reward: [(0, '4.804')] | |
| [2025-04-28 08:27:31,402][05280] Updated weights for policy 0, policy_version 110 (0.0012) | |
| [2025-04-28 08:27:32,022][04703] Fps is (10 sec: 4094.2, 60 sec: 3686.1, 300 sec: 3465.7). Total num frames: 450560. Throughput: 0: 916.2. Samples: 111262. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:27:32,024][04703] Avg episode reward: [(0, '5.091')] | |
| [2025-04-28 08:27:32,036][05267] Saving new best policy, reward=5.091! | |
| [2025-04-28 08:27:37,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3458.8). Total num frames: 466944. Throughput: 0: 883.7. Samples: 115964. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:27:37,023][04703] Avg episode reward: [(0, '4.901')] | |
| [2025-04-28 08:27:42,017][04703] Fps is (10 sec: 3688.0, 60 sec: 3686.4, 300 sec: 3481.6). Total num frames: 487424. Throughput: 0: 916.8. Samples: 122080. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:27:42,022][04703] Avg episode reward: [(0, '4.928')] | |
| [2025-04-28 08:27:42,692][05280] Updated weights for policy 0, policy_version 120 (0.0013) | |
| [2025-04-28 08:27:47,020][04703] Fps is (10 sec: 3685.5, 60 sec: 3618.0, 300 sec: 3474.5). Total num frames: 503808. Throughput: 0: 923.0. Samples: 125110. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:27:47,021][04703] Avg episode reward: [(0, '4.893')] | |
| [2025-04-28 08:27:52,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3467.9). Total num frames: 520192. Throughput: 0: 905.9. Samples: 130032. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:27:52,018][04703] Avg episode reward: [(0, '4.528')] | |
| [2025-04-28 08:27:54,020][05280] Updated weights for policy 0, policy_version 130 (0.0012) | |
| [2025-04-28 08:27:57,017][04703] Fps is (10 sec: 4097.0, 60 sec: 3754.7, 300 sec: 3514.6). Total num frames: 544768. Throughput: 0: 927.8. Samples: 136182. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:27:57,022][04703] Avg episode reward: [(0, '4.542')] | |
| [2025-04-28 08:28:02,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3481.6). Total num frames: 557056. Throughput: 0: 913.9. Samples: 138600. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:28:02,023][04703] Avg episode reward: [(0, '4.594')] | |
| [2025-04-28 08:28:05,344][05280] Updated weights for policy 0, policy_version 140 (0.0014) | |
| [2025-04-28 08:28:07,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3500.2). Total num frames: 577536. Throughput: 0: 926.0. Samples: 144056. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:07,022][04703] Avg episode reward: [(0, '4.763')] | |
| [2025-04-28 08:28:12,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3517.7). Total num frames: 598016. Throughput: 0: 931.4. Samples: 150094. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:12,019][04703] Avg episode reward: [(0, '4.946')] | |
| [2025-04-28 08:28:16,609][05280] Updated weights for policy 0, policy_version 150 (0.0012) | |
| [2025-04-28 08:28:17,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3510.9). Total num frames: 614400. Throughput: 0: 905.0. Samples: 151984. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:28:17,022][04703] Avg episode reward: [(0, '4.890')] | |
| [2025-04-28 08:28:22,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3527.1). Total num frames: 634880. Throughput: 0: 935.6. Samples: 158066. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:22,023][04703] Avg episode reward: [(0, '4.739')] | |
| [2025-04-28 08:28:27,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3686.4, 300 sec: 3520.3). Total num frames: 651264. Throughput: 0: 922.8. Samples: 163604. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:27,021][04703] Avg episode reward: [(0, '4.681')] | |
| [2025-04-28 08:28:27,477][05280] Updated weights for policy 0, policy_version 160 (0.0014) | |
| [2025-04-28 08:28:32,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.7, 300 sec: 3535.5). Total num frames: 671744. Throughput: 0: 909.4. Samples: 166032. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:28:32,018][04703] Avg episode reward: [(0, '4.820')] | |
| [2025-04-28 08:28:37,017][04703] Fps is (10 sec: 4096.1, 60 sec: 3754.7, 300 sec: 3549.9). Total num frames: 692224. Throughput: 0: 937.2. Samples: 172204. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:37,023][04703] Avg episode reward: [(0, '4.941')] | |
| [2025-04-28 08:28:37,847][05280] Updated weights for policy 0, policy_version 170 (0.0011) | |
| [2025-04-28 08:28:42,017][04703] Fps is (10 sec: 3276.7, 60 sec: 3618.1, 300 sec: 3522.6). Total num frames: 704512. Throughput: 0: 909.5. Samples: 177112. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:42,019][04703] Avg episode reward: [(0, '4.837')] | |
| [2025-04-28 08:28:47,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.6, 300 sec: 3536.5). Total num frames: 724992. Throughput: 0: 922.4. Samples: 180106. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:47,023][04703] Avg episode reward: [(0, '4.809')] | |
| [2025-04-28 08:28:49,123][05280] Updated weights for policy 0, policy_version 180 (0.0013) | |
| [2025-04-28 08:28:52,018][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.6, 300 sec: 3549.9). Total num frames: 745472. Throughput: 0: 938.2. Samples: 186274. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:28:52,021][04703] Avg episode reward: [(0, '5.031')] | |
| [2025-04-28 08:28:52,035][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000182_745472.pth... | |
| [2025-04-28 08:28:57,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3543.5). Total num frames: 761856. Throughput: 0: 909.3. Samples: 191012. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:28:57,023][04703] Avg episode reward: [(0, '5.029')] | |
| [2025-04-28 08:29:00,456][05280] Updated weights for policy 0, policy_version 190 (0.0014) | |
| [2025-04-28 08:29:02,021][04703] Fps is (10 sec: 3685.3, 60 sec: 3754.4, 300 sec: 3556.0). Total num frames: 782336. Throughput: 0: 935.8. Samples: 194100. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:02,022][04703] Avg episode reward: [(0, '4.927')] | |
| [2025-04-28 08:29:07,018][04703] Fps is (10 sec: 4095.5, 60 sec: 3754.6, 300 sec: 3568.1). Total num frames: 802816. Throughput: 0: 934.3. Samples: 200112. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:07,023][04703] Avg episode reward: [(0, '5.374')] | |
| [2025-04-28 08:29:07,025][05267] Saving new best policy, reward=5.374! | |
| [2025-04-28 08:29:11,604][05280] Updated weights for policy 0, policy_version 200 (0.0012) | |
| [2025-04-28 08:29:12,017][04703] Fps is (10 sec: 3687.6, 60 sec: 3686.4, 300 sec: 3561.7). Total num frames: 819200. Throughput: 0: 923.8. Samples: 205176. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:12,023][04703] Avg episode reward: [(0, '5.575')] | |
| [2025-04-28 08:29:12,033][05267] Saving new best policy, reward=5.575! | |
| [2025-04-28 08:29:17,017][04703] Fps is (10 sec: 3686.8, 60 sec: 3754.7, 300 sec: 3573.1). Total num frames: 839680. Throughput: 0: 935.9. Samples: 208146. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:17,019][04703] Avg episode reward: [(0, '5.946')] | |
| [2025-04-28 08:29:17,020][05267] Saving new best policy, reward=5.946! | |
| [2025-04-28 08:29:22,017][04703] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3566.9). Total num frames: 856064. Throughput: 0: 920.0. Samples: 213606. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:22,023][04703] Avg episode reward: [(0, '5.711')] | |
| [2025-04-28 08:29:22,924][05280] Updated weights for policy 0, policy_version 210 (0.0016) | |
| [2025-04-28 08:29:27,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3577.7). Total num frames: 876544. Throughput: 0: 935.4. Samples: 219206. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:27,021][04703] Avg episode reward: [(0, '5.950')] | |
| [2025-04-28 08:29:27,029][05267] Saving new best policy, reward=5.950! | |
| [2025-04-28 08:29:32,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3588.1). Total num frames: 897024. Throughput: 0: 935.8. Samples: 222218. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:29:32,021][04703] Avg episode reward: [(0, '5.563')] | |
| [2025-04-28 08:29:33,422][05280] Updated weights for policy 0, policy_version 220 (0.0012) | |
| [2025-04-28 08:29:37,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3565.9). Total num frames: 909312. Throughput: 0: 904.9. Samples: 226992. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:37,018][04703] Avg episode reward: [(0, '5.470')] | |
| [2025-04-28 08:29:42,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3576.1). Total num frames: 929792. Throughput: 0: 936.0. Samples: 233132. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:42,018][04703] Avg episode reward: [(0, '5.544')] | |
| [2025-04-28 08:29:44,365][05280] Updated weights for policy 0, policy_version 230 (0.0012) | |
| [2025-04-28 08:29:47,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3585.9). Total num frames: 950272. Throughput: 0: 933.5. Samples: 236102. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:47,018][04703] Avg episode reward: [(0, '5.815')] | |
| [2025-04-28 08:29:52,019][04703] Fps is (10 sec: 3685.8, 60 sec: 3686.3, 300 sec: 3580.2). Total num frames: 966656. Throughput: 0: 906.6. Samples: 240910. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:52,024][04703] Avg episode reward: [(0, '6.036')] | |
| [2025-04-28 08:29:52,032][05267] Saving new best policy, reward=6.036! | |
| [2025-04-28 08:29:55,803][05280] Updated weights for policy 0, policy_version 240 (0.0012) | |
| [2025-04-28 08:29:57,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3589.6). Total num frames: 987136. Throughput: 0: 930.0. Samples: 247026. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:29:57,023][04703] Avg episode reward: [(0, '6.446')] | |
| [2025-04-28 08:29:57,027][05267] Saving new best policy, reward=6.446! | |
| [2025-04-28 08:30:02,018][04703] Fps is (10 sec: 3686.8, 60 sec: 3686.6, 300 sec: 3584.0). Total num frames: 1003520. Throughput: 0: 927.2. Samples: 249872. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:30:02,019][04703] Avg episode reward: [(0, '6.101')] | |
| [2025-04-28 08:30:07,011][05280] Updated weights for policy 0, policy_version 250 (0.0014) | |
| [2025-04-28 08:30:07,018][04703] Fps is (10 sec: 3685.9, 60 sec: 3686.4, 300 sec: 3593.0). Total num frames: 1024000. Throughput: 0: 920.0. Samples: 255008. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:30:07,020][04703] Avg episode reward: [(0, '5.731')] | |
| [2025-04-28 08:30:12,017][04703] Fps is (10 sec: 4096.1, 60 sec: 3754.7, 300 sec: 3601.7). Total num frames: 1044480. Throughput: 0: 933.6. Samples: 261220. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:30:12,019][04703] Avg episode reward: [(0, '6.048')] | |
| [2025-04-28 08:30:17,017][04703] Fps is (10 sec: 3277.3, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 1056768. Throughput: 0: 915.2. Samples: 263400. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:30:17,018][04703] Avg episode reward: [(0, '6.307')] | |
| [2025-04-28 08:30:18,310][05280] Updated weights for policy 0, policy_version 260 (0.0013) | |
| [2025-04-28 08:30:22,017][04703] Fps is (10 sec: 3276.9, 60 sec: 3686.4, 300 sec: 3651.7). Total num frames: 1077248. Throughput: 0: 936.6. Samples: 269140. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:30:22,018][04703] Avg episode reward: [(0, '6.215')] | |
| [2025-04-28 08:30:27,019][04703] Fps is (10 sec: 4095.3, 60 sec: 3686.3, 300 sec: 3693.3). Total num frames: 1097728. Throughput: 0: 933.3. Samples: 275130. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:30:27,022][04703] Avg episode reward: [(0, '6.073')] | |
| [2025-04-28 08:30:29,165][05280] Updated weights for policy 0, policy_version 270 (0.0016) | |
| [2025-04-28 08:30:32,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 1114112. Throughput: 0: 910.8. Samples: 277088. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:30:32,018][04703] Avg episode reward: [(0, '6.212')] | |
| [2025-04-28 08:30:37,017][04703] Fps is (10 sec: 3687.0, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 1134592. Throughput: 0: 941.8. Samples: 283290. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:30:37,018][04703] Avg episode reward: [(0, '6.766')] | |
| [2025-04-28 08:30:37,020][05267] Saving new best policy, reward=6.766! | |
| [2025-04-28 08:30:39,413][05280] Updated weights for policy 0, policy_version 280 (0.0012) | |
| [2025-04-28 08:30:42,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1150976. Throughput: 0: 921.2. Samples: 288480. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:30:42,018][04703] Avg episode reward: [(0, '7.325')] | |
| [2025-04-28 08:30:42,026][05267] Saving new best policy, reward=7.325! | |
| [2025-04-28 08:30:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1171456. Throughput: 0: 914.6. Samples: 291030. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:30:47,020][04703] Avg episode reward: [(0, '7.350')] | |
| [2025-04-28 08:30:47,025][05267] Saving new best policy, reward=7.350! | |
| [2025-04-28 08:30:50,744][05280] Updated weights for policy 0, policy_version 290 (0.0022) | |
| [2025-04-28 08:30:52,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.8, 300 sec: 3679.5). Total num frames: 1191936. Throughput: 0: 936.9. Samples: 297166. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:30:52,021][04703] Avg episode reward: [(0, '7.264')] | |
| [2025-04-28 08:30:52,030][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000291_1191936.pth... | |
| [2025-04-28 08:30:52,112][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000075_307200.pth | |
| [2025-04-28 08:30:57,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 1204224. Throughput: 0: 907.2. Samples: 302044. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:30:57,023][04703] Avg episode reward: [(0, '7.246')] | |
| [2025-04-28 08:31:02,011][05280] Updated weights for policy 0, policy_version 300 (0.0019) | |
| [2025-04-28 08:31:02,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 1228800. Throughput: 0: 927.3. Samples: 305128. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:02,018][04703] Avg episode reward: [(0, '7.542')] | |
| [2025-04-28 08:31:02,029][05267] Saving new best policy, reward=7.542! | |
| [2025-04-28 08:31:07,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3686.5, 300 sec: 3693.3). Total num frames: 1245184. Throughput: 0: 936.9. Samples: 311302. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:07,019][04703] Avg episode reward: [(0, '8.085')] | |
| [2025-04-28 08:31:07,025][05267] Saving new best policy, reward=8.085! | |
| [2025-04-28 08:31:12,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 1261568. Throughput: 0: 909.1. Samples: 316036. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:12,018][04703] Avg episode reward: [(0, '8.117')] | |
| [2025-04-28 08:31:12,029][05267] Saving new best policy, reward=8.117! | |
| [2025-04-28 08:31:13,479][05280] Updated weights for policy 0, policy_version 310 (0.0012) | |
| [2025-04-28 08:31:17,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 1282048. Throughput: 0: 932.4. Samples: 319046. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:17,023][04703] Avg episode reward: [(0, '8.208')] | |
| [2025-04-28 08:31:17,026][05267] Saving new best policy, reward=8.208! | |
| [2025-04-28 08:31:22,020][04703] Fps is (10 sec: 3685.5, 60 sec: 3686.3, 300 sec: 3679.4). Total num frames: 1298432. Throughput: 0: 923.3. Samples: 324840. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:31:22,023][04703] Avg episode reward: [(0, '8.253')] | |
| [2025-04-28 08:31:22,032][05267] Saving new best policy, reward=8.253! | |
| [2025-04-28 08:31:24,734][05280] Updated weights for policy 0, policy_version 320 (0.0017) | |
| [2025-04-28 08:31:27,018][04703] Fps is (10 sec: 3686.0, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1318912. Throughput: 0: 923.1. Samples: 330022. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:27,022][04703] Avg episode reward: [(0, '8.571')] | |
| [2025-04-28 08:31:27,025][05267] Saving new best policy, reward=8.571! | |
| [2025-04-28 08:31:32,017][04703] Fps is (10 sec: 4097.0, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 1339392. Throughput: 0: 934.4. Samples: 333080. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:32,022][04703] Avg episode reward: [(0, '10.103')] | |
| [2025-04-28 08:31:32,028][05267] Saving new best policy, reward=10.103! | |
| [2025-04-28 08:31:35,453][05280] Updated weights for policy 0, policy_version 330 (0.0013) | |
| [2025-04-28 08:31:37,017][04703] Fps is (10 sec: 3277.2, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 1351680. Throughput: 0: 913.7. Samples: 338284. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:31:37,022][04703] Avg episode reward: [(0, '10.401')] | |
| [2025-04-28 08:31:37,026][05267] Saving new best policy, reward=10.401! | |
| [2025-04-28 08:31:42,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 1376256. Throughput: 0: 934.2. Samples: 344084. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:42,022][04703] Avg episode reward: [(0, '11.206')] | |
| [2025-04-28 08:31:42,032][05267] Saving new best policy, reward=11.206! | |
| [2025-04-28 08:31:46,053][05280] Updated weights for policy 0, policy_version 340 (0.0013) | |
| [2025-04-28 08:31:47,018][04703] Fps is (10 sec: 4095.8, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 1392640. Throughput: 0: 931.7. Samples: 347056. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:47,019][04703] Avg episode reward: [(0, '10.600')] | |
| [2025-04-28 08:31:52,019][04703] Fps is (10 sec: 3276.0, 60 sec: 3618.0, 300 sec: 3693.3). Total num frames: 1409024. Throughput: 0: 901.6. Samples: 351876. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:31:52,021][04703] Avg episode reward: [(0, '10.592')] | |
| [2025-04-28 08:31:57,017][04703] Fps is (10 sec: 3686.6, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 1429504. Throughput: 0: 932.0. Samples: 357974. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:31:57,021][04703] Avg episode reward: [(0, '11.092')] | |
| [2025-04-28 08:31:57,377][05280] Updated weights for policy 0, policy_version 350 (0.0018) | |
| [2025-04-28 08:32:02,017][04703] Fps is (10 sec: 3687.3, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 1445888. Throughput: 0: 932.1. Samples: 360990. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:32:02,020][04703] Avg episode reward: [(0, '12.033')] | |
| [2025-04-28 08:32:02,030][05267] Saving new best policy, reward=12.033! | |
| [2025-04-28 08:32:07,020][04703] Fps is (10 sec: 3685.4, 60 sec: 3686.2, 300 sec: 3693.3). Total num frames: 1466368. Throughput: 0: 907.8. Samples: 365690. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:32:07,028][04703] Avg episode reward: [(0, '12.178')] | |
| [2025-04-28 08:32:07,034][05267] Saving new best policy, reward=12.178! | |
| [2025-04-28 08:32:09,013][05280] Updated weights for policy 0, policy_version 360 (0.0014) | |
| [2025-04-28 08:32:12,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 1486848. Throughput: 0: 927.0. Samples: 371736. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:32:12,022][04703] Avg episode reward: [(0, '12.776')] | |
| [2025-04-28 08:32:12,029][05267] Saving new best policy, reward=12.776! | |
| [2025-04-28 08:32:17,017][04703] Fps is (10 sec: 3277.7, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 1499136. Throughput: 0: 914.8. Samples: 374248. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:32:17,020][04703] Avg episode reward: [(0, '12.461')] | |
| [2025-04-28 08:32:20,379][05280] Updated weights for policy 0, policy_version 370 (0.0017) | |
| [2025-04-28 08:32:22,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.5, 300 sec: 3693.3). Total num frames: 1519616. Throughput: 0: 915.9. Samples: 379498. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:32:22,019][04703] Avg episode reward: [(0, '12.138')] | |
| [2025-04-28 08:32:27,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3686.5, 300 sec: 3693.4). Total num frames: 1540096. Throughput: 0: 926.5. Samples: 385776. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:32:27,018][04703] Avg episode reward: [(0, '12.676')] | |
| [2025-04-28 08:32:31,536][05280] Updated weights for policy 0, policy_version 380 (0.0013) | |
| [2025-04-28 08:32:32,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 1556480. Throughput: 0: 906.0. Samples: 387826. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:32:32,020][04703] Avg episode reward: [(0, '13.611')] | |
| [2025-04-28 08:32:32,025][05267] Saving new best policy, reward=13.611! | |
| [2025-04-28 08:32:37,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 1576960. Throughput: 0: 928.4. Samples: 393654. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:32:37,026][04703] Avg episode reward: [(0, '14.046')] | |
| [2025-04-28 08:32:37,033][05267] Saving new best policy, reward=14.046! | |
| [2025-04-28 08:32:42,021][04703] Fps is (10 sec: 3685.1, 60 sec: 3617.9, 300 sec: 3693.3). Total num frames: 1593344. Throughput: 0: 918.9. Samples: 399326. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:32:42,022][04703] Avg episode reward: [(0, '14.894')] | |
| [2025-04-28 08:32:42,031][05267] Saving new best policy, reward=14.894! | |
| [2025-04-28 08:32:42,383][05280] Updated weights for policy 0, policy_version 390 (0.0018) | |
| [2025-04-28 08:32:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 1613824. Throughput: 0: 899.1. Samples: 401448. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:32:47,018][04703] Avg episode reward: [(0, '15.185')] | |
| [2025-04-28 08:32:47,020][05267] Saving new best policy, reward=15.185! | |
| [2025-04-28 08:32:52,017][04703] Fps is (10 sec: 4097.4, 60 sec: 3754.8, 300 sec: 3693.3). Total num frames: 1634304. Throughput: 0: 930.5. Samples: 407562. Policy #0 lag: (min: 0.0, avg: 0.0, max: 1.0) | |
| [2025-04-28 08:32:52,023][04703] Avg episode reward: [(0, '14.940')] | |
| [2025-04-28 08:32:52,031][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000399_1634304.pth... | |
| [2025-04-28 08:32:52,114][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000182_745472.pth | |
| [2025-04-28 08:32:52,951][05280] Updated weights for policy 0, policy_version 400 (0.0014) | |
| [2025-04-28 08:32:57,018][04703] Fps is (10 sec: 3276.6, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 1646592. Throughput: 0: 907.5. Samples: 412572. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:32:57,022][04703] Avg episode reward: [(0, '15.244')] | |
| [2025-04-28 08:32:57,027][05267] Saving new best policy, reward=15.244! | |
| [2025-04-28 08:33:02,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1667072. Throughput: 0: 913.4. Samples: 415350. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:33:02,021][04703] Avg episode reward: [(0, '14.484')] | |
| [2025-04-28 08:33:04,458][05280] Updated weights for policy 0, policy_version 410 (0.0011) | |
| [2025-04-28 08:33:07,017][04703] Fps is (10 sec: 4096.2, 60 sec: 3686.6, 300 sec: 3693.3). Total num frames: 1687552. Throughput: 0: 933.8. Samples: 421518. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:33:07,022][04703] Avg episode reward: [(0, '15.509')] | |
| [2025-04-28 08:33:07,024][05267] Saving new best policy, reward=15.509! | |
| [2025-04-28 08:33:12,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 1703936. Throughput: 0: 900.6. Samples: 426304. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:33:12,022][04703] Avg episode reward: [(0, '15.758')] | |
| [2025-04-28 08:33:12,033][05267] Saving new best policy, reward=15.758! | |
| [2025-04-28 08:33:15,753][05280] Updated weights for policy 0, policy_version 420 (0.0015) | |
| [2025-04-28 08:33:17,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 1724416. Throughput: 0: 920.4. Samples: 429244. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:33:17,018][04703] Avg episode reward: [(0, '15.496')] | |
| [2025-04-28 08:33:22,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1740800. Throughput: 0: 928.8. Samples: 435450. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:33:22,019][04703] Avg episode reward: [(0, '16.452')] | |
| [2025-04-28 08:33:22,028][05267] Saving new best policy, reward=16.452! | |
| [2025-04-28 08:33:27,020][04703] Fps is (10 sec: 3275.8, 60 sec: 3618.0, 300 sec: 3679.4). Total num frames: 1757184. Throughput: 0: 908.5. Samples: 440210. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:33:27,027][04703] Avg episode reward: [(0, '15.632')] | |
| [2025-04-28 08:33:27,094][05280] Updated weights for policy 0, policy_version 430 (0.0013) | |
| [2025-04-28 08:33:32,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 1777664. Throughput: 0: 930.6. Samples: 443324. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:33:32,018][04703] Avg episode reward: [(0, '14.845')] | |
| [2025-04-28 08:33:37,017][04703] Fps is (10 sec: 4097.2, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 1798144. Throughput: 0: 919.2. Samples: 448924. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:33:37,018][04703] Avg episode reward: [(0, '14.311')] | |
| [2025-04-28 08:33:38,349][05280] Updated weights for policy 0, policy_version 440 (0.0020) | |
| [2025-04-28 08:33:42,017][04703] Fps is (10 sec: 3686.5, 60 sec: 3686.6, 300 sec: 3693.3). Total num frames: 1814528. Throughput: 0: 927.7. Samples: 454316. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:33:42,023][04703] Avg episode reward: [(0, '13.565')] | |
| [2025-04-28 08:33:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1835008. Throughput: 0: 933.3. Samples: 457348. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:33:47,023][04703] Avg episode reward: [(0, '14.333')] | |
| [2025-04-28 08:33:48,549][05280] Updated weights for policy 0, policy_version 450 (0.0014) | |
| [2025-04-28 08:33:52,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 1851392. Throughput: 0: 908.2. Samples: 462388. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:33:52,018][04703] Avg episode reward: [(0, '14.671')] | |
| [2025-04-28 08:33:57,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3754.7, 300 sec: 3693.4). Total num frames: 1871872. Throughput: 0: 935.2. Samples: 468390. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:33:57,019][04703] Avg episode reward: [(0, '15.650')] | |
| [2025-04-28 08:33:59,546][05280] Updated weights for policy 0, policy_version 460 (0.0014) | |
| [2025-04-28 08:34:02,017][04703] Fps is (10 sec: 4095.9, 60 sec: 3754.6, 300 sec: 3693.4). Total num frames: 1892352. Throughput: 0: 937.6. Samples: 471438. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:34:02,022][04703] Avg episode reward: [(0, '16.498')] | |
| [2025-04-28 08:34:02,029][05267] Saving new best policy, reward=16.498! | |
| [2025-04-28 08:34:07,017][04703] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 1904640. Throughput: 0: 905.6. Samples: 476200. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:34:07,018][04703] Avg episode reward: [(0, '16.318')] | |
| [2025-04-28 08:34:11,001][05280] Updated weights for policy 0, policy_version 470 (0.0012) | |
| [2025-04-28 08:34:12,020][04703] Fps is (10 sec: 3685.6, 60 sec: 3754.5, 300 sec: 3693.3). Total num frames: 1929216. Throughput: 0: 937.4. Samples: 482394. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:34:12,024][04703] Avg episode reward: [(0, '16.660')] | |
| [2025-04-28 08:34:12,032][05267] Saving new best policy, reward=16.660! | |
| [2025-04-28 08:34:17,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1945600. Throughput: 0: 932.7. Samples: 485296. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:34:17,022][04703] Avg episode reward: [(0, '16.975')] | |
| [2025-04-28 08:34:17,023][05267] Saving new best policy, reward=16.975! | |
| [2025-04-28 08:34:22,017][04703] Fps is (10 sec: 3277.6, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 1961984. Throughput: 0: 914.0. Samples: 490056. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:34:22,023][04703] Avg episode reward: [(0, '17.657')] | |
| [2025-04-28 08:34:22,031][05267] Saving new best policy, reward=17.657! | |
| [2025-04-28 08:34:22,390][05280] Updated weights for policy 0, policy_version 480 (0.0013) | |
| [2025-04-28 08:34:27,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.9, 300 sec: 3679.5). Total num frames: 1982464. Throughput: 0: 929.0. Samples: 496120. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:34:27,023][04703] Avg episode reward: [(0, '17.510')] | |
| [2025-04-28 08:34:32,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 1998848. Throughput: 0: 916.1. Samples: 498572. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:34:32,024][04703] Avg episode reward: [(0, '18.416')] | |
| [2025-04-28 08:34:32,032][05267] Saving new best policy, reward=18.416! | |
| [2025-04-28 08:34:33,996][05280] Updated weights for policy 0, policy_version 490 (0.0018) | |
| [2025-04-28 08:34:37,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 2019328. Throughput: 0: 922.8. Samples: 503914. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:34:37,023][04703] Avg episode reward: [(0, '18.717')] | |
| [2025-04-28 08:34:37,033][05267] Saving new best policy, reward=18.717! | |
| [2025-04-28 08:34:42,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 2035712. Throughput: 0: 924.7. Samples: 510000. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:34:42,020][04703] Avg episode reward: [(0, '19.128')] | |
| [2025-04-28 08:34:42,091][05267] Saving new best policy, reward=19.128! | |
| [2025-04-28 08:34:45,403][05280] Updated weights for policy 0, policy_version 500 (0.0016) | |
| [2025-04-28 08:34:47,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 2052096. Throughput: 0: 899.0. Samples: 511894. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:34:47,018][04703] Avg episode reward: [(0, '19.617')] | |
| [2025-04-28 08:34:47,022][05267] Saving new best policy, reward=19.617! | |
| [2025-04-28 08:34:52,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 2072576. Throughput: 0: 924.0. Samples: 517782. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:34:52,018][04703] Avg episode reward: [(0, '19.779')] | |
| [2025-04-28 08:34:52,025][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000506_2072576.pth... | |
| [2025-04-28 08:34:52,115][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000291_1191936.pth | |
| [2025-04-28 08:34:52,123][05267] Saving new best policy, reward=19.779! | |
| [2025-04-28 08:34:55,479][05280] Updated weights for policy 0, policy_version 510 (0.0014) | |
| [2025-04-28 08:34:57,020][04703] Fps is (10 sec: 4095.0, 60 sec: 3686.3, 300 sec: 3693.3). Total num frames: 2093056. Throughput: 0: 909.7. Samples: 523330. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:34:57,021][04703] Avg episode reward: [(0, '19.955')] | |
| [2025-04-28 08:34:57,022][05267] Saving new best policy, reward=19.955! | |
| [2025-04-28 08:35:02,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 2109440. Throughput: 0: 893.7. Samples: 525514. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:35:02,023][04703] Avg episode reward: [(0, '20.957')] | |
| [2025-04-28 08:35:02,029][05267] Saving new best policy, reward=20.957! | |
| [2025-04-28 08:35:06,742][05280] Updated weights for policy 0, policy_version 520 (0.0014) | |
| [2025-04-28 08:35:07,018][04703] Fps is (10 sec: 3687.2, 60 sec: 3754.6, 300 sec: 3679.5). Total num frames: 2129920. Throughput: 0: 924.0. Samples: 531638. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:35:07,023][04703] Avg episode reward: [(0, '20.866')] | |
| [2025-04-28 08:35:12,022][04703] Fps is (10 sec: 3275.3, 60 sec: 3549.7, 300 sec: 3679.4). Total num frames: 2142208. Throughput: 0: 900.6. Samples: 536650. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:35:12,023][04703] Avg episode reward: [(0, '20.032')] | |
| [2025-04-28 08:35:17,017][04703] Fps is (10 sec: 3277.0, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 2162688. Throughput: 0: 910.9. Samples: 539564. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:35:17,018][04703] Avg episode reward: [(0, '18.920')] | |
| [2025-04-28 08:35:18,120][05280] Updated weights for policy 0, policy_version 530 (0.0019) | |
| [2025-04-28 08:35:22,017][04703] Fps is (10 sec: 4098.0, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 2183168. Throughput: 0: 931.2. Samples: 545816. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:35:22,023][04703] Avg episode reward: [(0, '16.885')] | |
| [2025-04-28 08:35:27,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3679.5). Total num frames: 2199552. Throughput: 0: 904.5. Samples: 550702. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:35:27,022][04703] Avg episode reward: [(0, '15.167')] | |
| [2025-04-28 08:35:29,164][05280] Updated weights for policy 0, policy_version 540 (0.0021) | |
| [2025-04-28 08:35:32,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 2220032. Throughput: 0: 931.5. Samples: 553810. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:35:32,027][04703] Avg episode reward: [(0, '15.942')] | |
| [2025-04-28 08:35:37,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 2240512. Throughput: 0: 937.0. Samples: 559948. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:35:37,020][04703] Avg episode reward: [(0, '16.872')] | |
| [2025-04-28 08:35:40,256][05280] Updated weights for policy 0, policy_version 550 (0.0013) | |
| [2025-04-28 08:35:42,020][04703] Fps is (10 sec: 3685.5, 60 sec: 3686.3, 300 sec: 3679.4). Total num frames: 2256896. Throughput: 0: 926.0. Samples: 565000. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:35:42,022][04703] Avg episode reward: [(0, '17.910')] | |
| [2025-04-28 08:35:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 2277376. Throughput: 0: 947.4. Samples: 568148. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:35:47,019][04703] Avg episode reward: [(0, '19.530')] | |
| [2025-04-28 08:35:50,916][05280] Updated weights for policy 0, policy_version 560 (0.0019) | |
| [2025-04-28 08:35:52,018][04703] Fps is (10 sec: 3686.8, 60 sec: 3686.3, 300 sec: 3693.3). Total num frames: 2293760. Throughput: 0: 932.2. Samples: 573586. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:35:52,021][04703] Avg episode reward: [(0, '21.438')] | |
| [2025-04-28 08:35:52,033][05267] Saving new best policy, reward=21.438! | |
| [2025-04-28 08:35:57,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.6, 300 sec: 3679.5). Total num frames: 2314240. Throughput: 0: 943.4. Samples: 579100. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:35:57,028][04703] Avg episode reward: [(0, '21.872')] | |
| [2025-04-28 08:35:57,036][05267] Saving new best policy, reward=21.872! | |
| [2025-04-28 08:36:01,483][05280] Updated weights for policy 0, policy_version 570 (0.0012) | |
| [2025-04-28 08:36:02,017][04703] Fps is (10 sec: 4096.5, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 2334720. Throughput: 0: 946.9. Samples: 582174. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:36:02,019][04703] Avg episode reward: [(0, '19.596')] | |
| [2025-04-28 08:36:07,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 2351104. Throughput: 0: 915.6. Samples: 587016. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:36:07,022][04703] Avg episode reward: [(0, '19.880')] | |
| [2025-04-28 08:36:12,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3823.3, 300 sec: 3693.3). Total num frames: 2371584. Throughput: 0: 944.0. Samples: 593184. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:36:12,022][04703] Avg episode reward: [(0, '18.818')] | |
| [2025-04-28 08:36:12,633][05280] Updated weights for policy 0, policy_version 580 (0.0019) | |
| [2025-04-28 08:36:17,018][04703] Fps is (10 sec: 3686.1, 60 sec: 3754.6, 300 sec: 3693.4). Total num frames: 2387968. Throughput: 0: 943.7. Samples: 596276. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:36:17,021][04703] Avg episode reward: [(0, '18.605')] | |
| [2025-04-28 08:36:22,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3693.4). Total num frames: 2408448. Throughput: 0: 915.6. Samples: 601150. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:36:22,025][04703] Avg episode reward: [(0, '17.765')] | |
| [2025-04-28 08:36:23,864][05280] Updated weights for policy 0, policy_version 590 (0.0017) | |
| [2025-04-28 08:36:27,017][04703] Fps is (10 sec: 4096.4, 60 sec: 3822.9, 300 sec: 3693.3). Total num frames: 2428928. Throughput: 0: 942.6. Samples: 607416. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:36:27,023][04703] Avg episode reward: [(0, '19.314')] | |
| [2025-04-28 08:36:32,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3693.3). Total num frames: 2441216. Throughput: 0: 933.2. Samples: 610144. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:36:32,020][04703] Avg episode reward: [(0, '19.557')] | |
| [2025-04-28 08:36:35,125][05280] Updated weights for policy 0, policy_version 600 (0.0020) | |
| [2025-04-28 08:36:37,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3679.5). Total num frames: 2461696. Throughput: 0: 929.5. Samples: 615412. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:36:37,027][04703] Avg episode reward: [(0, '20.215')] | |
| [2025-04-28 08:36:42,017][04703] Fps is (10 sec: 4505.6, 60 sec: 3823.1, 300 sec: 3707.2). Total num frames: 2486272. Throughput: 0: 943.2. Samples: 621546. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:36:42,018][04703] Avg episode reward: [(0, '20.406')] | |
| [2025-04-28 08:36:46,355][05280] Updated weights for policy 0, policy_version 610 (0.0013) | |
| [2025-04-28 08:36:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3693.4). Total num frames: 2498560. Throughput: 0: 920.8. Samples: 623612. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:36:47,023][04703] Avg episode reward: [(0, '20.192')] | |
| [2025-04-28 08:36:52,020][04703] Fps is (10 sec: 3276.0, 60 sec: 3754.6, 300 sec: 3693.3). Total num frames: 2519040. Throughput: 0: 938.9. Samples: 629268. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:36:52,026][04703] Avg episode reward: [(0, '21.096')] | |
| [2025-04-28 08:36:52,034][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000615_2519040.pth... | |
| [2025-04-28 08:36:52,119][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000399_1634304.pth | |
| [2025-04-28 08:36:56,863][05280] Updated weights for policy 0, policy_version 620 (0.0017) | |
| [2025-04-28 08:36:57,018][04703] Fps is (10 sec: 4095.8, 60 sec: 3754.6, 300 sec: 3707.2). Total num frames: 2539520. Throughput: 0: 930.3. Samples: 635046. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:36:57,019][04703] Avg episode reward: [(0, '20.055')] | |
| [2025-04-28 08:37:02,017][04703] Fps is (10 sec: 3687.2, 60 sec: 3686.4, 300 sec: 3693.4). Total num frames: 2555904. Throughput: 0: 908.6. Samples: 637162. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:37:02,023][04703] Avg episode reward: [(0, '18.819')] | |
| [2025-04-28 08:37:07,017][04703] Fps is (10 sec: 3686.6, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 2576384. Throughput: 0: 938.0. Samples: 643358. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:37:07,023][04703] Avg episode reward: [(0, '18.606')] | |
| [2025-04-28 08:37:07,676][05280] Updated weights for policy 0, policy_version 630 (0.0012) | |
| [2025-04-28 08:37:12,017][04703] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 2592768. Throughput: 0: 914.0. Samples: 648544. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:37:12,022][04703] Avg episode reward: [(0, '18.470')] | |
| [2025-04-28 08:37:17,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3707.2). Total num frames: 2613248. Throughput: 0: 915.6. Samples: 651344. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:37:17,023][04703] Avg episode reward: [(0, '17.685')] | |
| [2025-04-28 08:37:18,938][05280] Updated weights for policy 0, policy_version 640 (0.0014) | |
| [2025-04-28 08:37:22,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3707.2). Total num frames: 2633728. Throughput: 0: 935.2. Samples: 657494. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:37:22,018][04703] Avg episode reward: [(0, '18.893')] | |
| [2025-04-28 08:37:27,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2646016. Throughput: 0: 906.8. Samples: 662352. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:37:27,018][04703] Avg episode reward: [(0, '19.514')] | |
| [2025-04-28 08:37:30,097][05280] Updated weights for policy 0, policy_version 650 (0.0012) | |
| [2025-04-28 08:37:32,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 2666496. Throughput: 0: 930.1. Samples: 665466. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:37:32,020][04703] Avg episode reward: [(0, '20.703')] | |
| [2025-04-28 08:37:37,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3707.3). Total num frames: 2686976. Throughput: 0: 942.1. Samples: 671658. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:37:37,018][04703] Avg episode reward: [(0, '21.511')] | |
| [2025-04-28 08:37:41,313][05280] Updated weights for policy 0, policy_version 660 (0.0015) | |
| [2025-04-28 08:37:42,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2703360. Throughput: 0: 921.8. Samples: 676526. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:37:42,023][04703] Avg episode reward: [(0, '22.519')] | |
| [2025-04-28 08:37:42,033][05267] Saving new best policy, reward=22.519! | |
| [2025-04-28 08:37:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3693.3). Total num frames: 2723840. Throughput: 0: 942.4. Samples: 679570. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:37:47,023][04703] Avg episode reward: [(0, '23.478')] | |
| [2025-04-28 08:37:47,026][05267] Saving new best policy, reward=23.478! | |
| [2025-04-28 08:37:52,020][04703] Fps is (10 sec: 3685.5, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 2740224. Throughput: 0: 929.2. Samples: 685174. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:37:52,021][04703] Avg episode reward: [(0, '21.678')] | |
| [2025-04-28 08:37:52,530][05280] Updated weights for policy 0, policy_version 670 (0.0016) | |
| [2025-04-28 08:37:57,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 2760704. Throughput: 0: 934.1. Samples: 690578. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:37:57,023][04703] Avg episode reward: [(0, '21.914')] | |
| [2025-04-28 08:38:02,017][04703] Fps is (10 sec: 4097.0, 60 sec: 3754.7, 300 sec: 3707.2). Total num frames: 2781184. Throughput: 0: 940.0. Samples: 693644. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:38:02,023][04703] Avg episode reward: [(0, '20.311')] | |
| [2025-04-28 08:38:02,521][05280] Updated weights for policy 0, policy_version 680 (0.0012) | |
| [2025-04-28 08:38:07,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 2797568. Throughput: 0: 915.1. Samples: 698674. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:38:07,023][04703] Avg episode reward: [(0, '19.833')] | |
| [2025-04-28 08:38:12,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3707.2). Total num frames: 2818048. Throughput: 0: 943.2. Samples: 704796. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:38:12,019][04703] Avg episode reward: [(0, '17.382')] | |
| [2025-04-28 08:38:13,730][05280] Updated weights for policy 0, policy_version 690 (0.0015) | |
| [2025-04-28 08:38:17,018][04703] Fps is (10 sec: 4095.5, 60 sec: 3754.6, 300 sec: 3721.1). Total num frames: 2838528. Throughput: 0: 943.4. Samples: 707922. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:38:17,023][04703] Avg episode reward: [(0, '17.142')] | |
| [2025-04-28 08:38:22,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 2854912. Throughput: 0: 913.9. Samples: 712784. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:38:22,021][04703] Avg episode reward: [(0, '16.727')] | |
| [2025-04-28 08:38:24,951][05280] Updated weights for policy 0, policy_version 700 (0.0020) | |
| [2025-04-28 08:38:27,017][04703] Fps is (10 sec: 3686.9, 60 sec: 3822.9, 300 sec: 3721.1). Total num frames: 2875392. Throughput: 0: 944.4. Samples: 719022. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:38:27,024][04703] Avg episode reward: [(0, '15.863')] | |
| [2025-04-28 08:38:32,018][04703] Fps is (10 sec: 3686.2, 60 sec: 3754.6, 300 sec: 3707.2). Total num frames: 2891776. Throughput: 0: 944.0. Samples: 722052. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:38:32,022][04703] Avg episode reward: [(0, '17.317')] | |
| [2025-04-28 08:38:35,991][05280] Updated weights for policy 0, policy_version 710 (0.0021) | |
| [2025-04-28 08:38:37,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 2912256. Throughput: 0: 931.6. Samples: 727094. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:38:37,018][04703] Avg episode reward: [(0, '18.106')] | |
| [2025-04-28 08:38:42,017][04703] Fps is (10 sec: 4096.2, 60 sec: 3822.9, 300 sec: 3721.1). Total num frames: 2932736. Throughput: 0: 949.9. Samples: 733322. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:38:42,019][04703] Avg episode reward: [(0, '19.225')] | |
| [2025-04-28 08:38:47,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 2945024. Throughput: 0: 934.0. Samples: 735676. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:38:47,019][04703] Avg episode reward: [(0, '18.583')] | |
| [2025-04-28 08:38:47,082][05280] Updated weights for policy 0, policy_version 720 (0.0015) | |
| [2025-04-28 08:38:52,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3754.8, 300 sec: 3707.2). Total num frames: 2965504. Throughput: 0: 946.5. Samples: 741266. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:38:52,019][04703] Avg episode reward: [(0, '20.317')] | |
| [2025-04-28 08:38:52,050][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000725_2969600.pth... | |
| [2025-04-28 08:38:52,125][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000506_2072576.pth | |
| [2025-04-28 08:38:57,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3707.2). Total num frames: 2985984. Throughput: 0: 942.4. Samples: 747206. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:38:57,020][04703] Avg episode reward: [(0, '19.764')] | |
| [2025-04-28 08:38:57,647][05280] Updated weights for policy 0, policy_version 730 (0.0012) | |
| [2025-04-28 08:39:02,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3002368. Throughput: 0: 915.1. Samples: 749100. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:02,019][04703] Avg episode reward: [(0, '20.925')] | |
| [2025-04-28 08:39:07,020][04703] Fps is (10 sec: 3685.5, 60 sec: 3754.5, 300 sec: 3707.2). Total num frames: 3022848. Throughput: 0: 943.4. Samples: 755240. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:07,023][04703] Avg episode reward: [(0, '20.606')] | |
| [2025-04-28 08:39:08,469][05280] Updated weights for policy 0, policy_version 740 (0.0014) | |
| [2025-04-28 08:39:12,017][04703] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 3039232. Throughput: 0: 923.8. Samples: 760592. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:12,020][04703] Avg episode reward: [(0, '21.935')] | |
| [2025-04-28 08:39:17,017][04703] Fps is (10 sec: 3687.2, 60 sec: 3686.5, 300 sec: 3721.1). Total num frames: 3059712. Throughput: 0: 912.0. Samples: 763092. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:17,023][04703] Avg episode reward: [(0, '22.827')] | |
| [2025-04-28 08:39:19,692][05280] Updated weights for policy 0, policy_version 750 (0.0018) | |
| [2025-04-28 08:39:22,020][04703] Fps is (10 sec: 4094.9, 60 sec: 3754.5, 300 sec: 3721.1). Total num frames: 3080192. Throughput: 0: 937.0. Samples: 769260. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:22,025][04703] Avg episode reward: [(0, '22.462')] | |
| [2025-04-28 08:39:27,017][04703] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3096576. Throughput: 0: 907.8. Samples: 774172. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:39:27,019][04703] Avg episode reward: [(0, '22.266')] | |
| [2025-04-28 08:39:30,855][05280] Updated weights for policy 0, policy_version 760 (0.0016) | |
| [2025-04-28 08:39:32,017][04703] Fps is (10 sec: 3687.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3117056. Throughput: 0: 924.2. Samples: 777266. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:32,019][04703] Avg episode reward: [(0, '22.359')] | |
| [2025-04-28 08:39:37,019][04703] Fps is (10 sec: 4095.3, 60 sec: 3754.6, 300 sec: 3735.0). Total num frames: 3137536. Throughput: 0: 938.2. Samples: 783488. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:37,024][04703] Avg episode reward: [(0, '21.084')] | |
| [2025-04-28 08:39:42,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3721.1). Total num frames: 3149824. Throughput: 0: 914.9. Samples: 788378. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:39:42,022][04703] Avg episode reward: [(0, '20.730')] | |
| [2025-04-28 08:39:42,116][05280] Updated weights for policy 0, policy_version 770 (0.0013) | |
| [2025-04-28 08:39:47,017][04703] Fps is (10 sec: 3277.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3170304. Throughput: 0: 941.9. Samples: 791486. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:39:47,021][04703] Avg episode reward: [(0, '20.687')] | |
| [2025-04-28 08:39:52,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3190784. Throughput: 0: 935.3. Samples: 797324. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:52,018][04703] Avg episode reward: [(0, '21.417')] | |
| [2025-04-28 08:39:53,264][05280] Updated weights for policy 0, policy_version 780 (0.0016) | |
| [2025-04-28 08:39:57,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3207168. Throughput: 0: 929.9. Samples: 802436. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:39:57,018][04703] Avg episode reward: [(0, '21.339')] | |
| [2025-04-28 08:40:02,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3227648. Throughput: 0: 943.0. Samples: 805526. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:02,018][04703] Avg episode reward: [(0, '21.022')] | |
| [2025-04-28 08:40:03,393][05280] Updated weights for policy 0, policy_version 790 (0.0012) | |
| [2025-04-28 08:40:07,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3686.5, 300 sec: 3735.1). Total num frames: 3244032. Throughput: 0: 922.7. Samples: 810778. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:07,019][04703] Avg episode reward: [(0, '21.353')] | |
| [2025-04-28 08:40:12,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3735.0). Total num frames: 3264512. Throughput: 0: 943.1. Samples: 816612. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:40:12,018][04703] Avg episode reward: [(0, '21.664')] | |
| [2025-04-28 08:40:14,475][05280] Updated weights for policy 0, policy_version 800 (0.0012) | |
| [2025-04-28 08:40:17,017][04703] Fps is (10 sec: 4096.1, 60 sec: 3754.7, 300 sec: 3735.0). Total num frames: 3284992. Throughput: 0: 944.0. Samples: 819744. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:40:17,018][04703] Avg episode reward: [(0, '22.011')] | |
| [2025-04-28 08:40:22,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.6, 300 sec: 3735.0). Total num frames: 3301376. Throughput: 0: 910.9. Samples: 824476. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:22,019][04703] Avg episode reward: [(0, '22.221')] | |
| [2025-04-28 08:40:25,670][05280] Updated weights for policy 0, policy_version 810 (0.0011) | |
| [2025-04-28 08:40:27,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3754.7, 300 sec: 3735.0). Total num frames: 3321856. Throughput: 0: 940.4. Samples: 830696. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:27,021][04703] Avg episode reward: [(0, '24.663')] | |
| [2025-04-28 08:40:27,024][05267] Saving new best policy, reward=24.663! | |
| [2025-04-28 08:40:32,022][04703] Fps is (10 sec: 3684.6, 60 sec: 3686.1, 300 sec: 3721.1). Total num frames: 3338240. Throughput: 0: 938.7. Samples: 833734. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:32,026][04703] Avg episode reward: [(0, '24.872')] | |
| [2025-04-28 08:40:32,035][05267] Saving new best policy, reward=24.872! | |
| [2025-04-28 08:40:37,017][04703] Fps is (10 sec: 3276.9, 60 sec: 3618.2, 300 sec: 3721.1). Total num frames: 3354624. Throughput: 0: 917.5. Samples: 838612. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:40:37,018][04703] Avg episode reward: [(0, '25.763')] | |
| [2025-04-28 08:40:37,034][05267] Saving new best policy, reward=25.763! | |
| [2025-04-28 08:40:37,047][05280] Updated weights for policy 0, policy_version 820 (0.0013) | |
| [2025-04-28 08:40:42,019][04703] Fps is (10 sec: 4097.4, 60 sec: 3822.8, 300 sec: 3735.0). Total num frames: 3379200. Throughput: 0: 940.5. Samples: 844760. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:42,024][04703] Avg episode reward: [(0, '25.702')] | |
| [2025-04-28 08:40:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3391488. Throughput: 0: 928.9. Samples: 847326. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:47,024][04703] Avg episode reward: [(0, '25.901')] | |
| [2025-04-28 08:40:47,032][05267] Saving new best policy, reward=25.901! | |
| [2025-04-28 08:40:48,320][05280] Updated weights for policy 0, policy_version 830 (0.0012) | |
| [2025-04-28 08:40:52,019][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.3, 300 sec: 3721.1). Total num frames: 3411968. Throughput: 0: 928.6. Samples: 852566. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:52,025][04703] Avg episode reward: [(0, '26.114')] | |
| [2025-04-28 08:40:52,034][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000833_3411968.pth... | |
| [2025-04-28 08:40:52,123][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000615_2519040.pth | |
| [2025-04-28 08:40:52,139][05267] Saving new best policy, reward=26.114! | |
| [2025-04-28 08:40:57,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3432448. Throughput: 0: 934.3. Samples: 858654. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:40:57,019][04703] Avg episode reward: [(0, '25.005')] | |
| [2025-04-28 08:40:59,333][05280] Updated weights for policy 0, policy_version 840 (0.0012) | |
| [2025-04-28 08:41:02,017][04703] Fps is (10 sec: 3687.0, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3448832. Throughput: 0: 909.6. Samples: 860678. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:41:02,023][04703] Avg episode reward: [(0, '25.738')] | |
| [2025-04-28 08:41:07,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3469312. Throughput: 0: 936.7. Samples: 866626. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:41:07,021][04703] Avg episode reward: [(0, '25.474')] | |
| [2025-04-28 08:41:09,712][05280] Updated weights for policy 0, policy_version 850 (0.0012) | |
| [2025-04-28 08:41:12,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3485696. Throughput: 0: 925.6. Samples: 872348. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:41:12,021][04703] Avg episode reward: [(0, '26.063')] | |
| [2025-04-28 08:41:17,017][04703] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3506176. Throughput: 0: 908.6. Samples: 874618. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:41:17,023][04703] Avg episode reward: [(0, '25.218')] | |
| [2025-04-28 08:41:20,831][05280] Updated weights for policy 0, policy_version 860 (0.0017) | |
| [2025-04-28 08:41:22,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3526656. Throughput: 0: 936.0. Samples: 880734. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:41:22,019][04703] Avg episode reward: [(0, '25.023')] | |
| [2025-04-28 08:41:27,018][04703] Fps is (10 sec: 3276.4, 60 sec: 3618.1, 300 sec: 3721.1). Total num frames: 3538944. Throughput: 0: 910.6. Samples: 885736. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:41:27,022][04703] Avg episode reward: [(0, '24.614')] | |
| [2025-04-28 08:41:32,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3686.7, 300 sec: 3721.1). Total num frames: 3559424. Throughput: 0: 918.1. Samples: 888642. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:41:32,022][04703] Avg episode reward: [(0, '24.583')] | |
| [2025-04-28 08:41:32,188][05280] Updated weights for policy 0, policy_version 870 (0.0014) | |
| [2025-04-28 08:41:37,017][04703] Fps is (10 sec: 4096.5, 60 sec: 3754.7, 300 sec: 3707.2). Total num frames: 3579904. Throughput: 0: 938.7. Samples: 894804. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:41:37,022][04703] Avg episode reward: [(0, '24.959')] | |
| [2025-04-28 08:41:42,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3618.2, 300 sec: 3721.1). Total num frames: 3596288. Throughput: 0: 911.0. Samples: 899648. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:41:42,023][04703] Avg episode reward: [(0, '26.678')] | |
| [2025-04-28 08:41:42,033][05267] Saving new best policy, reward=26.678! | |
| [2025-04-28 08:41:43,530][05280] Updated weights for policy 0, policy_version 880 (0.0012) | |
| [2025-04-28 08:41:47,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3616768. Throughput: 0: 934.2. Samples: 902718. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-04-28 08:41:47,022][04703] Avg episode reward: [(0, '26.719')] | |
| [2025-04-28 08:41:47,032][05267] Saving new best policy, reward=26.719! | |
| [2025-04-28 08:41:52,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.8, 300 sec: 3721.1). Total num frames: 3637248. Throughput: 0: 935.7. Samples: 908734. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:41:52,022][04703] Avg episode reward: [(0, '25.845')] | |
| [2025-04-28 08:41:54,747][05280] Updated weights for policy 0, policy_version 890 (0.0012) | |
| [2025-04-28 08:41:57,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3653632. Throughput: 0: 916.8. Samples: 913604. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:41:57,022][04703] Avg episode reward: [(0, '27.067')] | |
| [2025-04-28 08:41:57,025][05267] Saving new best policy, reward=27.067! | |
| [2025-04-28 08:42:02,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3674112. Throughput: 0: 934.2. Samples: 916656. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:42:02,019][04703] Avg episode reward: [(0, '26.459')] | |
| [2025-04-28 08:42:05,056][05280] Updated weights for policy 0, policy_version 900 (0.0013) | |
| [2025-04-28 08:42:07,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3690496. Throughput: 0: 923.6. Samples: 922296. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:07,020][04703] Avg episode reward: [(0, '26.323')] | |
| [2025-04-28 08:42:12,017][04703] Fps is (10 sec: 3686.5, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3710976. Throughput: 0: 934.4. Samples: 927784. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:12,018][04703] Avg episode reward: [(0, '25.283')] | |
| [2025-04-28 08:42:15,850][05280] Updated weights for policy 0, policy_version 910 (0.0014) | |
| [2025-04-28 08:42:17,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3731456. Throughput: 0: 938.8. Samples: 930888. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:42:17,018][04703] Avg episode reward: [(0, '26.514')] | |
| [2025-04-28 08:42:22,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3721.1). Total num frames: 3743744. Throughput: 0: 910.7. Samples: 935786. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:22,021][04703] Avg episode reward: [(0, '25.586')] | |
| [2025-04-28 08:42:27,017][04703] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3764224. Throughput: 0: 938.8. Samples: 941894. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:27,018][04703] Avg episode reward: [(0, '24.951')] | |
| [2025-04-28 08:42:27,197][05280] Updated weights for policy 0, policy_version 920 (0.0013) | |
| [2025-04-28 08:42:32,017][04703] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3784704. Throughput: 0: 939.9. Samples: 945014. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:32,019][04703] Avg episode reward: [(0, '26.066')] | |
| [2025-04-28 08:42:37,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3801088. Throughput: 0: 913.4. Samples: 949838. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:37,020][04703] Avg episode reward: [(0, '26.137')] | |
| [2025-04-28 08:42:38,457][05280] Updated weights for policy 0, policy_version 930 (0.0013) | |
| [2025-04-28 08:42:42,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3821568. Throughput: 0: 943.7. Samples: 956072. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:42,023][04703] Avg episode reward: [(0, '25.299')] | |
| [2025-04-28 08:42:47,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3837952. Throughput: 0: 940.7. Samples: 958986. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:42:47,022][04703] Avg episode reward: [(0, '25.488')] | |
| [2025-04-28 08:42:49,600][05280] Updated weights for policy 0, policy_version 940 (0.0014) | |
| [2025-04-28 08:42:52,017][04703] Fps is (10 sec: 3686.3, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 3858432. Throughput: 0: 925.3. Samples: 963936. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:42:52,024][04703] Avg episode reward: [(0, '28.178')] | |
| [2025-04-28 08:42:52,036][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000942_3858432.pth... | |
| [2025-04-28 08:42:52,124][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000725_2969600.pth | |
| [2025-04-28 08:42:52,137][05267] Saving new best policy, reward=28.178! | |
| [2025-04-28 08:42:57,017][04703] Fps is (10 sec: 4096.1, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3878912. Throughput: 0: 939.3. Samples: 970052. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:42:57,022][04703] Avg episode reward: [(0, '29.924')] | |
| [2025-04-28 08:42:57,025][05267] Saving new best policy, reward=29.924! | |
| [2025-04-28 08:43:00,792][05280] Updated weights for policy 0, policy_version 950 (0.0016) | |
| [2025-04-28 08:43:02,020][04703] Fps is (10 sec: 3685.6, 60 sec: 3686.3, 300 sec: 3721.1). Total num frames: 3895296. Throughput: 0: 922.1. Samples: 972386. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:43:02,025][04703] Avg episode reward: [(0, '30.065')] | |
| [2025-04-28 08:43:02,035][05267] Saving new best policy, reward=30.065! | |
| [2025-04-28 08:43:07,018][04703] Fps is (10 sec: 3685.9, 60 sec: 3754.6, 300 sec: 3721.1). Total num frames: 3915776. Throughput: 0: 934.8. Samples: 977854. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-04-28 08:43:07,022][04703] Avg episode reward: [(0, '28.065')] | |
| [2025-04-28 08:43:11,070][05280] Updated weights for policy 0, policy_version 960 (0.0015) | |
| [2025-04-28 08:43:12,017][04703] Fps is (10 sec: 3687.3, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 3932160. Throughput: 0: 932.9. Samples: 983876. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:43:12,018][04703] Avg episode reward: [(0, '28.928')] | |
| [2025-04-28 08:43:17,017][04703] Fps is (10 sec: 3277.2, 60 sec: 3618.1, 300 sec: 3707.2). Total num frames: 3948544. Throughput: 0: 907.4. Samples: 985846. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:43:17,019][04703] Avg episode reward: [(0, '28.216')] | |
| [2025-04-28 08:43:22,017][04703] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3707.2). Total num frames: 3969024. Throughput: 0: 934.7. Samples: 991900. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:43:22,019][04703] Avg episode reward: [(0, '28.431')] | |
| [2025-04-28 08:43:22,331][05280] Updated weights for policy 0, policy_version 970 (0.0012) | |
| [2025-04-28 08:43:27,017][04703] Fps is (10 sec: 4096.1, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 3989504. Throughput: 0: 919.6. Samples: 997452. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-04-28 08:43:27,018][04703] Avg episode reward: [(0, '28.605')] | |
| [2025-04-28 08:43:31,474][05267] Stopping Batcher_0... | |
| [2025-04-28 08:43:31,474][05267] Loop batcher_evt_loop terminating... | |
| [2025-04-28 08:43:31,475][04703] Component Batcher_0 stopped! | |
| [2025-04-28 08:43:31,476][04703] Component RolloutWorker_w3 process died already! Don't wait for it. | |
| [2025-04-28 08:43:31,486][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-04-28 08:43:31,485][04703] Component RolloutWorker_w4 process died already! Don't wait for it. | |
| [2025-04-28 08:43:31,486][04703] Component RolloutWorker_w5 process died already! Don't wait for it. | |
| [2025-04-28 08:43:31,489][04703] Component RolloutWorker_w6 process died already! Don't wait for it. | |
| [2025-04-28 08:43:31,491][04703] Component RolloutWorker_w7 process died already! Don't wait for it. | |
| [2025-04-28 08:43:31,536][05280] Weights refcount: 2 0 | |
| [2025-04-28 08:43:31,538][05280] Stopping InferenceWorker_p0-w0... | |
| [2025-04-28 08:43:31,539][05280] Loop inference_proc0-0_evt_loop terminating... | |
| [2025-04-28 08:43:31,538][04703] Component InferenceWorker_p0-w0 stopped! | |
| [2025-04-28 08:43:31,572][05267] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000833_3411968.pth | |
| [2025-04-28 08:43:31,581][05267] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-04-28 08:43:31,708][04703] Component LearnerWorker_p0 stopped! | |
| [2025-04-28 08:43:31,712][05267] Stopping LearnerWorker_p0... | |
| [2025-04-28 08:43:31,712][05267] Loop learner_proc0_evt_loop terminating... | |
| [2025-04-28 08:43:31,793][04703] Component RolloutWorker_w1 stopped! | |
| [2025-04-28 08:43:31,796][05286] Stopping RolloutWorker_w1... | |
| [2025-04-28 08:43:31,808][05286] Loop rollout_proc1_evt_loop terminating... | |
| [2025-04-28 08:43:31,829][05283] Stopping RolloutWorker_w2... | |
| [2025-04-28 08:43:31,829][04703] Component RolloutWorker_w2 stopped! | |
| [2025-04-28 08:43:31,833][05283] Loop rollout_proc2_evt_loop terminating... | |
| [2025-04-28 08:43:31,853][04703] Component RolloutWorker_w0 stopped! | |
| [2025-04-28 08:43:31,862][04703] Waiting for process learner_proc0 to stop... | |
| [2025-04-28 08:43:31,853][05281] Stopping RolloutWorker_w0... | |
| [2025-04-28 08:43:31,872][05281] Loop rollout_proc0_evt_loop terminating... | |
| [2025-04-28 08:43:32,971][04703] Waiting for process inference_proc0-0 to join... | |
| [2025-04-28 08:43:32,976][04703] Waiting for process rollout_proc0 to join... | |
| [2025-04-28 08:43:33,675][04703] Waiting for process rollout_proc1 to join... | |
| [2025-04-28 08:43:33,676][04703] Waiting for process rollout_proc2 to join... | |
| [2025-04-28 08:43:33,677][04703] Waiting for process rollout_proc3 to join... | |
| [2025-04-28 08:43:33,678][04703] Waiting for process rollout_proc4 to join... | |
| [2025-04-28 08:43:33,679][04703] Waiting for process rollout_proc5 to join... | |
| [2025-04-28 08:43:33,680][04703] Waiting for process rollout_proc6 to join... | |
| [2025-04-28 08:43:33,680][04703] Waiting for process rollout_proc7 to join... | |
| [2025-04-28 08:43:33,681][04703] Batcher 0 profile tree view: | |
| batching: 21.0519, releasing_batches: 0.0292 | |
| [2025-04-28 08:43:33,682][04703] InferenceWorker_p0-w0 profile tree view: | |
| wait_policy: 0.0019 | |
| wait_policy_total: 401.7263 | |
| update_model: 9.8199 | |
| weight_update: 0.0015 | |
| one_step: 0.0044 | |
| handle_policy_step: 640.1655 | |
| deserialize: 15.2396, stack: 3.8366, obs_to_device_normalize: 140.6284, forward: 350.9021, send_messages: 20.7002 | |
| prepare_outputs: 81.8668 | |
| to_cpu: 49.9315 | |
| [2025-04-28 08:43:33,683][04703] Learner 0 profile tree view: | |
| misc: 0.0042, prepare_batch: 13.0207 | |
| train: 64.9924 | |
| epoch_init: 0.0166, minibatch_init: 0.0054, losses_postprocess: 0.5542, kl_divergence: 0.5681, after_optimizer: 32.1773 | |
| calculate_losses: 21.4595 | |
| losses_init: 0.0030, forward_head: 1.2915, bptt_initial: 14.6942, tail: 0.8170, advantages_returns: 0.2104, losses: 2.7741 | |
| bptt: 1.4654 | |
| bptt_forward_core: 1.4151 | |
| update: 9.7496 | |
| clip: 0.7911 | |
| [2025-04-28 08:43:33,685][04703] RolloutWorker_w0 profile tree view: | |
| wait_for_trajectories: 0.5000, enqueue_policy_requests: 129.6878, env_step: 769.0892, overhead: 22.7449, complete_rollouts: 8.4847 | |
| save_policy_outputs: 31.0829 | |
| split_output_tensors: 11.7481 | |
| [2025-04-28 08:43:33,686][04703] Loop Runner_EvtLoop terminating... | |
| [2025-04-28 08:43:33,687][04703] Runner profile tree view: | |
| main_loop: 1116.0576 | |
| [2025-04-28 08:43:33,688][04703] Collected {0: 4005888}, FPS: 3589.3 | |
| [2025-04-28 08:43:46,619][04703] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-04-28 08:43:46,620][04703] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-04-28 08:43:46,621][04703] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-04-28 08:43:46,622][04703] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-04-28 08:43:46,623][04703] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-04-28 08:43:46,624][04703] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-04-28 08:43:46,625][04703] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-04-28 08:43:46,627][04703] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-04-28 08:43:46,628][04703] Adding new argument 'push_to_hub'=False that is not in the saved config file! | |
| [2025-04-28 08:43:46,629][04703] Adding new argument 'hf_repository'=None that is not in the saved config file! | |
| [2025-04-28 08:43:46,630][04703] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-04-28 08:43:46,631][04703] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-04-28 08:43:46,632][04703] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-04-28 08:43:46,633][04703] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-04-28 08:43:46,634][04703] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-04-28 08:43:46,662][04703] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-04-28 08:43:46,665][04703] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-04-28 08:43:46,667][04703] RunningMeanStd input shape: (1,) | |
| [2025-04-28 08:43:46,682][04703] ConvEncoder: input_channels=3 | |
| [2025-04-28 08:43:46,781][04703] Conv encoder output size: 512 | |
| [2025-04-28 08:43:46,782][04703] Policy head output size: 512 | |
| [2025-04-28 08:43:47,042][04703] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-04-28 08:43:47,786][04703] Num frames 100... | |
| [2025-04-28 08:43:47,916][04703] Num frames 200... | |
| [2025-04-28 08:43:48,066][04703] Num frames 300... | |
| [2025-04-28 08:43:48,242][04703] Num frames 400... | |
| [2025-04-28 08:43:48,419][04703] Num frames 500... | |
| [2025-04-28 08:43:48,609][04703] Num frames 600... | |
| [2025-04-28 08:43:48,768][04703] Num frames 700... | |
| [2025-04-28 08:43:48,893][04703] Num frames 800... | |
| [2025-04-28 08:43:49,021][04703] Num frames 900... | |
| [2025-04-28 08:43:49,152][04703] Num frames 1000... | |
| [2025-04-28 08:43:49,278][04703] Avg episode rewards: #0: 21.560, true rewards: #0: 10.560 | |
| [2025-04-28 08:43:49,279][04703] Avg episode reward: 21.560, avg true_objective: 10.560 | |
| [2025-04-28 08:43:49,338][04703] Num frames 1100... | |
| [2025-04-28 08:43:49,472][04703] Num frames 1200... | |
| [2025-04-28 08:43:49,612][04703] Num frames 1300... | |
| [2025-04-28 08:43:49,746][04703] Num frames 1400... | |
| [2025-04-28 08:43:49,878][04703] Num frames 1500... | |
| [2025-04-28 08:43:50,010][04703] Num frames 1600... | |
| [2025-04-28 08:43:50,140][04703] Num frames 1700... | |
| [2025-04-28 08:43:50,275][04703] Num frames 1800... | |
| [2025-04-28 08:43:50,405][04703] Num frames 1900... | |
| [2025-04-28 08:43:50,536][04703] Num frames 2000... | |
| [2025-04-28 08:43:50,682][04703] Num frames 2100... | |
| [2025-04-28 08:43:50,857][04703] Num frames 2200... | |
| [2025-04-28 08:43:51,038][04703] Num frames 2300... | |
| [2025-04-28 08:43:51,208][04703] Num frames 2400... | |
| [2025-04-28 08:43:51,380][04703] Num frames 2500... | |
| [2025-04-28 08:43:51,549][04703] Num frames 2600... | |
| [2025-04-28 08:43:51,729][04703] Num frames 2700... | |
| [2025-04-28 08:43:51,901][04703] Num frames 2800... | |
| [2025-04-28 08:43:52,074][04703] Num frames 2900... | |
| [2025-04-28 08:43:52,256][04703] Num frames 3000... | |
| [2025-04-28 08:43:52,468][04703] Avg episode rewards: #0: 37.860, true rewards: #0: 15.360 | |
| [2025-04-28 08:43:52,469][04703] Avg episode reward: 37.860, avg true_objective: 15.360 | |
| [2025-04-28 08:43:52,518][04703] Num frames 3100... | |
| [2025-04-28 08:43:52,702][04703] Num frames 3200... | |
| [2025-04-28 08:43:52,887][04703] Num frames 3300... | |
| [2025-04-28 08:43:53,045][04703] Num frames 3400... | |
| [2025-04-28 08:43:53,174][04703] Num frames 3500... | |
| [2025-04-28 08:43:53,301][04703] Num frames 3600... | |
| [2025-04-28 08:43:53,461][04703] Avg episode rewards: #0: 28.933, true rewards: #0: 12.267 | |
| [2025-04-28 08:43:53,462][04703] Avg episode reward: 28.933, avg true_objective: 12.267 | |
| [2025-04-28 08:43:53,490][04703] Num frames 3700... | |
| [2025-04-28 08:43:53,617][04703] Num frames 3800... | |
| [2025-04-28 08:43:53,749][04703] Num frames 3900... | |
| [2025-04-28 08:43:53,886][04703] Num frames 4000... | |
| [2025-04-28 08:43:54,024][04703] Num frames 4100... | |
| [2025-04-28 08:43:54,152][04703] Num frames 4200... | |
| [2025-04-28 08:43:54,283][04703] Num frames 4300... | |
| [2025-04-28 08:43:54,415][04703] Num frames 4400... | |
| [2025-04-28 08:43:54,547][04703] Num frames 4500... | |
| [2025-04-28 08:43:54,678][04703] Num frames 4600... | |
| [2025-04-28 08:43:54,817][04703] Num frames 4700... | |
| [2025-04-28 08:43:54,945][04703] Num frames 4800... | |
| [2025-04-28 08:43:55,124][04703] Avg episode rewards: #0: 29.740, true rewards: #0: 12.240 | |
| [2025-04-28 08:43:55,125][04703] Avg episode reward: 29.740, avg true_objective: 12.240 | |
| [2025-04-28 08:43:55,134][04703] Num frames 4900... | |
| [2025-04-28 08:43:55,266][04703] Num frames 5000... | |
| [2025-04-28 08:43:55,397][04703] Num frames 5100... | |
| [2025-04-28 08:43:55,525][04703] Num frames 5200... | |
| [2025-04-28 08:43:55,651][04703] Num frames 5300... | |
| [2025-04-28 08:43:55,781][04703] Num frames 5400... | |
| [2025-04-28 08:43:55,918][04703] Num frames 5500... | |
| [2025-04-28 08:43:55,978][04703] Avg episode rewards: #0: 26.408, true rewards: #0: 11.008 | |
| [2025-04-28 08:43:55,979][04703] Avg episode reward: 26.408, avg true_objective: 11.008 | |
| [2025-04-28 08:43:56,106][04703] Num frames 5600... | |
| [2025-04-28 08:43:56,236][04703] Num frames 5700... | |
| [2025-04-28 08:43:56,363][04703] Num frames 5800... | |
| [2025-04-28 08:43:56,494][04703] Num frames 5900... | |
| [2025-04-28 08:43:56,625][04703] Num frames 6000... | |
| [2025-04-28 08:43:56,756][04703] Num frames 6100... | |
| [2025-04-28 08:43:56,895][04703] Num frames 6200... | |
| [2025-04-28 08:43:57,027][04703] Num frames 6300... | |
| [2025-04-28 08:43:57,158][04703] Num frames 6400... | |
| [2025-04-28 08:43:57,289][04703] Num frames 6500... | |
| [2025-04-28 08:43:57,418][04703] Num frames 6600... | |
| [2025-04-28 08:43:57,546][04703] Num frames 6700... | |
| [2025-04-28 08:43:57,675][04703] Num frames 6800... | |
| [2025-04-28 08:43:57,802][04703] Num frames 6900... | |
| [2025-04-28 08:43:57,940][04703] Num frames 7000... | |
| [2025-04-28 08:43:58,068][04703] Num frames 7100... | |
| [2025-04-28 08:43:58,200][04703] Num frames 7200... | |
| [2025-04-28 08:43:58,337][04703] Num frames 7300... | |
| [2025-04-28 08:43:58,468][04703] Num frames 7400... | |
| [2025-04-28 08:43:58,597][04703] Num frames 7500... | |
| [2025-04-28 08:43:58,729][04703] Num frames 7600... | |
| [2025-04-28 08:43:58,790][04703] Avg episode rewards: #0: 31.506, true rewards: #0: 12.673 | |
| [2025-04-28 08:43:58,791][04703] Avg episode reward: 31.506, avg true_objective: 12.673 | |
| [2025-04-28 08:43:58,923][04703] Num frames 7700... | |
| [2025-04-28 08:43:59,060][04703] Num frames 7800... | |
| [2025-04-28 08:43:59,189][04703] Num frames 7900... | |
| [2025-04-28 08:43:59,317][04703] Num frames 8000... | |
| [2025-04-28 08:43:59,447][04703] Num frames 8100... | |
| [2025-04-28 08:43:59,584][04703] Num frames 8200... | |
| [2025-04-28 08:43:59,788][04703] Num frames 8300... | |
| [2025-04-28 08:44:00,070][04703] Avg episode rewards: #0: 29.124, true rewards: #0: 11.981 | |
| [2025-04-28 08:44:00,074][04703] Avg episode reward: 29.124, avg true_objective: 11.981 | |
| [2025-04-28 08:44:00,118][04703] Num frames 8400... | |
| [2025-04-28 08:44:00,299][04703] Num frames 8500... | |
| [2025-04-28 08:44:00,520][04703] Num frames 8600... | |
| [2025-04-28 08:44:00,704][04703] Num frames 8700... | |
| [2025-04-28 08:44:00,831][04703] Num frames 8800... | |
| [2025-04-28 08:44:00,957][04703] Num frames 8900... | |
| [2025-04-28 08:44:01,101][04703] Avg episode rewards: #0: 26.829, true rewards: #0: 11.204 | |
| [2025-04-28 08:44:01,102][04703] Avg episode reward: 26.829, avg true_objective: 11.204 | |
| [2025-04-28 08:44:01,157][04703] Num frames 9000... | |
| [2025-04-28 08:44:01,286][04703] Num frames 9100... | |
| [2025-04-28 08:44:01,416][04703] Num frames 9200... | |
| [2025-04-28 08:44:01,543][04703] Num frames 9300... | |
| [2025-04-28 08:44:01,668][04703] Num frames 9400... | |
| [2025-04-28 08:44:01,798][04703] Num frames 9500... | |
| [2025-04-28 08:44:01,925][04703] Num frames 9600... | |
| [2025-04-28 08:44:02,062][04703] Num frames 9700... | |
| [2025-04-28 08:44:02,190][04703] Num frames 9800... | |
| [2025-04-28 08:44:02,324][04703] Num frames 9900... | |
| [2025-04-28 08:44:02,453][04703] Num frames 10000... | |
| [2025-04-28 08:44:02,587][04703] Num frames 10100... | |
| [2025-04-28 08:44:02,718][04703] Num frames 10200... | |
| [2025-04-28 08:44:02,859][04703] Num frames 10300... | |
| [2025-04-28 08:44:02,924][04703] Avg episode rewards: #0: 27.341, true rewards: #0: 11.452 | |
| [2025-04-28 08:44:02,925][04703] Avg episode reward: 27.341, avg true_objective: 11.452 | |
| [2025-04-28 08:44:03,081][04703] Num frames 10400... | |
| [2025-04-28 08:44:03,260][04703] Num frames 10500... | |
| [2025-04-28 08:44:03,434][04703] Num frames 10600... | |
| [2025-04-28 08:44:03,609][04703] Num frames 10700... | |
| [2025-04-28 08:44:03,776][04703] Num frames 10800... | |
| [2025-04-28 08:44:03,945][04703] Num frames 10900... | |
| [2025-04-28 08:44:04,110][04703] Num frames 11000... | |
| [2025-04-28 08:44:04,299][04703] Num frames 11100... | |
| [2025-04-28 08:44:04,478][04703] Num frames 11200... | |
| [2025-04-28 08:44:04,651][04703] Num frames 11300... | |
| [2025-04-28 08:44:04,824][04703] Num frames 11400... | |
| [2025-04-28 08:44:05,006][04703] Num frames 11500... | |
| [2025-04-28 08:44:05,187][04703] Num frames 11600... | |
| [2025-04-28 08:44:05,337][04703] Num frames 11700... | |
| [2025-04-28 08:44:05,466][04703] Num frames 11800... | |
| [2025-04-28 08:44:05,593][04703] Num frames 11900... | |
| [2025-04-28 08:44:05,724][04703] Num frames 12000... | |
| [2025-04-28 08:44:05,866][04703] Avg episode rewards: #0: 29.067, true rewards: #0: 12.067 | |
| [2025-04-28 08:44:05,867][04703] Avg episode reward: 29.067, avg true_objective: 12.067 | |
| [2025-04-28 08:45:14,431][04703] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |
| [2025-04-28 08:45:24,092][04703] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-04-28 08:45:24,093][04703] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-04-28 08:45:24,095][04703] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-04-28 08:45:24,096][04703] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-04-28 08:45:24,096][04703] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-04-28 08:45:24,097][04703] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-04-28 08:45:24,098][04703] Adding new argument 'max_num_frames'=100000 that is not in the saved config file! | |
| [2025-04-28 08:45:24,099][04703] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-04-28 08:45:24,100][04703] Adding new argument 'push_to_hub'=True that is not in the saved config file! | |
| [2025-04-28 08:45:24,101][04703] Adding new argument 'hf_repository'='ranranrunforit/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file! | |
| [2025-04-28 08:45:24,102][04703] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-04-28 08:45:24,102][04703] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-04-28 08:45:24,104][04703] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-04-28 08:45:24,106][04703] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-04-28 08:45:24,108][04703] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-04-28 08:45:24,131][04703] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-04-28 08:45:24,133][04703] RunningMeanStd input shape: (1,) | |
| [2025-04-28 08:45:24,143][04703] ConvEncoder: input_channels=3 | |
| [2025-04-28 08:45:24,174][04703] Conv encoder output size: 512 | |
| [2025-04-28 08:45:24,175][04703] Policy head output size: 512 | |
| [2025-04-28 08:45:24,192][04703] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-04-28 08:45:24,627][04703] Num frames 100... | |
| [2025-04-28 08:45:24,755][04703] Num frames 200... | |
| [2025-04-28 08:45:24,882][04703] Num frames 300... | |
| [2025-04-28 08:45:25,009][04703] Num frames 400... | |
| [2025-04-28 08:45:25,133][04703] Num frames 500... | |
| [2025-04-28 08:45:25,263][04703] Num frames 600... | |
| [2025-04-28 08:45:25,393][04703] Num frames 700... | |
| [2025-04-28 08:45:25,536][04703] Num frames 800... | |
| [2025-04-28 08:45:25,588][04703] Avg episode rewards: #0: 19.000, true rewards: #0: 8.000 | |
| [2025-04-28 08:45:25,589][04703] Avg episode reward: 19.000, avg true_objective: 8.000 | |
| [2025-04-28 08:45:25,718][04703] Num frames 900... | |
| [2025-04-28 08:45:25,844][04703] Num frames 1000... | |
| [2025-04-28 08:45:25,968][04703] Num frames 1100... | |
| [2025-04-28 08:45:26,093][04703] Num frames 1200... | |
| [2025-04-28 08:45:26,229][04703] Num frames 1300... | |
| [2025-04-28 08:45:26,357][04703] Num frames 1400... | |
| [2025-04-28 08:45:26,488][04703] Num frames 1500... | |
| [2025-04-28 08:45:26,624][04703] Num frames 1600... | |
| [2025-04-28 08:45:26,754][04703] Num frames 1700... | |
| [2025-04-28 08:45:26,886][04703] Num frames 1800... | |
| [2025-04-28 08:45:27,017][04703] Num frames 1900... | |
| [2025-04-28 08:45:27,143][04703] Num frames 2000... | |
| [2025-04-28 08:45:27,275][04703] Num frames 2100... | |
| [2025-04-28 08:45:27,404][04703] Num frames 2200... | |
| [2025-04-28 08:45:27,537][04703] Num frames 2300... | |
| [2025-04-28 08:45:27,671][04703] Num frames 2400... | |
| [2025-04-28 08:45:27,801][04703] Num frames 2500... | |
| [2025-04-28 08:45:27,929][04703] Num frames 2600... | |
| [2025-04-28 08:45:28,058][04703] Num frames 2700... | |
| [2025-04-28 08:45:28,183][04703] Num frames 2800... | |
| [2025-04-28 08:45:28,319][04703] Num frames 2900... | |
| [2025-04-28 08:45:28,371][04703] Avg episode rewards: #0: 36.999, true rewards: #0: 14.500 | |
| [2025-04-28 08:45:28,372][04703] Avg episode reward: 36.999, avg true_objective: 14.500 | |
| [2025-04-28 08:45:28,503][04703] Num frames 3000... | |
| [2025-04-28 08:45:28,646][04703] Num frames 3100... | |
| [2025-04-28 08:45:28,775][04703] Num frames 3200... | |
| [2025-04-28 08:45:28,907][04703] Num frames 3300... | |
| [2025-04-28 08:45:29,023][04703] Avg episode rewards: #0: 27.493, true rewards: #0: 11.160 | |
| [2025-04-28 08:45:29,024][04703] Avg episode reward: 27.493, avg true_objective: 11.160 | |
| [2025-04-28 08:45:29,093][04703] Num frames 3400... | |
| [2025-04-28 08:45:29,224][04703] Num frames 3500... | |
| [2025-04-28 08:45:29,348][04703] Num frames 3600... | |
| [2025-04-28 08:45:29,475][04703] Num frames 3700... | |
| [2025-04-28 08:45:29,616][04703] Num frames 3800... | |
| [2025-04-28 08:45:29,747][04703] Num frames 3900... | |
| [2025-04-28 08:45:29,875][04703] Num frames 4000... | |
| [2025-04-28 08:45:30,009][04703] Num frames 4100... | |
| [2025-04-28 08:45:30,061][04703] Avg episode rewards: #0: 25.000, true rewards: #0: 10.250 | |
| [2025-04-28 08:45:30,062][04703] Avg episode reward: 25.000, avg true_objective: 10.250 | |
| [2025-04-28 08:45:30,192][04703] Num frames 4200... | |
| [2025-04-28 08:45:30,323][04703] Num frames 4300... | |
| [2025-04-28 08:45:30,449][04703] Num frames 4400... | |
| [2025-04-28 08:45:30,576][04703] Num frames 4500... | |
| [2025-04-28 08:45:30,712][04703] Num frames 4600... | |
| [2025-04-28 08:45:30,870][04703] Num frames 4700... | |
| [2025-04-28 08:45:31,046][04703] Num frames 4800... | |
| [2025-04-28 08:45:31,218][04703] Num frames 4900... | |
| [2025-04-28 08:45:31,385][04703] Num frames 5000... | |
| [2025-04-28 08:45:31,551][04703] Num frames 5100... | |
| [2025-04-28 08:45:31,736][04703] Num frames 5200... | |
| [2025-04-28 08:45:31,901][04703] Num frames 5300... | |
| [2025-04-28 08:45:32,067][04703] Num frames 5400... | |
| [2025-04-28 08:45:32,237][04703] Num frames 5500... | |
| [2025-04-28 08:45:32,416][04703] Num frames 5600... | |
| [2025-04-28 08:45:32,587][04703] Num frames 5700... | |
| [2025-04-28 08:45:32,774][04703] Num frames 5800... | |
| [2025-04-28 08:45:32,962][04703] Num frames 5900... | |
| [2025-04-28 08:45:33,113][04703] Num frames 6000... | |
| [2025-04-28 08:45:33,246][04703] Num frames 6100... | |
| [2025-04-28 08:45:33,321][04703] Avg episode rewards: #0: 30.626, true rewards: #0: 12.226 | |
| [2025-04-28 08:45:33,322][04703] Avg episode reward: 30.626, avg true_objective: 12.226 | |
| [2025-04-28 08:45:33,432][04703] Num frames 6200... | |
| [2025-04-28 08:45:33,559][04703] Num frames 6300... | |
| [2025-04-28 08:45:33,686][04703] Num frames 6400... | |
| [2025-04-28 08:45:33,823][04703] Num frames 6500... | |
| [2025-04-28 08:45:33,948][04703] Num frames 6600... | |
| [2025-04-28 08:45:34,072][04703] Num frames 6700... | |
| [2025-04-28 08:45:34,196][04703] Num frames 6800... | |
| [2025-04-28 08:45:34,323][04703] Num frames 6900... | |
| [2025-04-28 08:45:34,452][04703] Num frames 7000... | |
| [2025-04-28 08:45:34,578][04703] Num frames 7100... | |
| [2025-04-28 08:45:34,708][04703] Num frames 7200... | |
| [2025-04-28 08:45:34,838][04703] Num frames 7300... | |
| [2025-04-28 08:45:34,971][04703] Num frames 7400... | |
| [2025-04-28 08:45:35,154][04703] Avg episode rewards: #0: 31.330, true rewards: #0: 12.497 | |
| [2025-04-28 08:45:35,155][04703] Avg episode reward: 31.330, avg true_objective: 12.497 | |
| [2025-04-28 08:45:35,161][04703] Num frames 7500... | |
| [2025-04-28 08:45:35,294][04703] Num frames 7600... | |
| [2025-04-28 08:45:35,422][04703] Num frames 7700... | |
| [2025-04-28 08:45:35,548][04703] Num frames 7800... | |
| [2025-04-28 08:45:35,675][04703] Num frames 7900... | |
| [2025-04-28 08:45:35,801][04703] Num frames 8000... | |
| [2025-04-28 08:45:35,941][04703] Num frames 8100... | |
| [2025-04-28 08:45:36,069][04703] Num frames 8200... | |
| [2025-04-28 08:45:36,197][04703] Num frames 8300... | |
| [2025-04-28 08:45:36,324][04703] Num frames 8400... | |
| [2025-04-28 08:45:36,454][04703] Num frames 8500... | |
| [2025-04-28 08:45:36,592][04703] Num frames 8600... | |
| [2025-04-28 08:45:36,721][04703] Num frames 8700... | |
| [2025-04-28 08:45:36,796][04703] Avg episode rewards: #0: 31.448, true rewards: #0: 12.449 | |
| [2025-04-28 08:45:36,796][04703] Avg episode reward: 31.448, avg true_objective: 12.449 | |
| [2025-04-28 08:45:36,914][04703] Num frames 8800... | |
| [2025-04-28 08:45:37,044][04703] Num frames 8900... | |
| [2025-04-28 08:45:37,167][04703] Num frames 9000... | |
| [2025-04-28 08:45:37,296][04703] Num frames 9100... | |
| [2025-04-28 08:45:37,426][04703] Num frames 9200... | |
| [2025-04-28 08:45:37,557][04703] Num frames 9300... | |
| [2025-04-28 08:45:37,690][04703] Num frames 9400... | |
| [2025-04-28 08:45:37,816][04703] Num frames 9500... | |
| [2025-04-28 08:45:37,956][04703] Num frames 9600... | |
| [2025-04-28 08:45:38,085][04703] Num frames 9700... | |
| [2025-04-28 08:45:38,214][04703] Num frames 9800... | |
| [2025-04-28 08:45:38,343][04703] Num frames 9900... | |
| [2025-04-28 08:45:38,433][04703] Avg episode rewards: #0: 31.157, true rewards: #0: 12.407 | |
| [2025-04-28 08:45:38,434][04703] Avg episode reward: 31.157, avg true_objective: 12.407 | |
| [2025-04-28 08:45:38,527][04703] Num frames 10000... | |
| [2025-04-28 08:45:38,656][04703] Num frames 10100... | |
| [2025-04-28 08:45:38,785][04703] Num frames 10200... | |
| [2025-04-28 08:45:38,912][04703] Num frames 10300... | |
| [2025-04-28 08:45:39,053][04703] Num frames 10400... | |
| [2025-04-28 08:45:39,180][04703] Num frames 10500... | |
| [2025-04-28 08:45:39,310][04703] Num frames 10600... | |
| [2025-04-28 08:45:39,439][04703] Num frames 10700... | |
| [2025-04-28 08:45:39,570][04703] Num frames 10800... | |
| [2025-04-28 08:45:39,629][04703] Avg episode rewards: #0: 30.001, true rewards: #0: 12.001 | |
| [2025-04-28 08:45:39,630][04703] Avg episode reward: 30.001, avg true_objective: 12.001 | |
| [2025-04-28 08:45:39,758][04703] Num frames 10900... | |
| [2025-04-28 08:45:39,885][04703] Num frames 11000... | |
| [2025-04-28 08:45:40,019][04703] Num frames 11100... | |
| [2025-04-28 08:45:40,152][04703] Num frames 11200... | |
| [2025-04-28 08:45:40,279][04703] Num frames 11300... | |
| [2025-04-28 08:45:40,431][04703] Avg episode rewards: #0: 28.177, true rewards: #0: 11.377 | |
| [2025-04-28 08:45:40,433][04703] Avg episode reward: 28.177, avg true_objective: 11.377 | |
| [2025-04-28 08:46:45,969][04703] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |