| [2025-02-25 10:53:24,611][00253] Saving configuration to /content/train_dir/default_experiment/config.json... | |
| [2025-02-25 10:53:24,612][00253] Rollout worker 0 uses device cpu | |
| [2025-02-25 10:53:24,613][00253] Rollout worker 1 uses device cpu | |
| [2025-02-25 10:53:24,614][00253] Rollout worker 2 uses device cpu | |
| [2025-02-25 10:53:24,615][00253] Rollout worker 3 uses device cpu | |
| [2025-02-25 10:53:24,616][00253] Rollout worker 4 uses device cpu | |
| [2025-02-25 10:53:24,617][00253] Rollout worker 5 uses device cpu | |
| [2025-02-25 10:53:24,618][00253] Rollout worker 6 uses device cpu | |
| [2025-02-25 10:53:24,619][00253] Rollout worker 7 uses device cpu | |
| [2025-02-25 10:53:24,766][00253] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 10:53:24,767][00253] InferenceWorker_p0-w0: min num requests: 2 | |
| [2025-02-25 10:53:24,826][00253] Starting all processes... | |
| [2025-02-25 10:53:24,827][00253] Starting process learner_proc0 | |
| [2025-02-25 10:53:24,882][00253] Starting all processes... | |
| [2025-02-25 10:53:24,890][00253] Starting process inference_proc0-0 | |
| [2025-02-25 10:53:24,891][00253] Starting process rollout_proc0 | |
| [2025-02-25 10:53:24,892][00253] Starting process rollout_proc1 | |
| [2025-02-25 10:53:24,892][00253] Starting process rollout_proc2 | |
| [2025-02-25 10:53:24,893][00253] Starting process rollout_proc3 | |
| [2025-02-25 10:53:24,893][00253] Starting process rollout_proc4 | |
| [2025-02-25 10:53:24,893][00253] Starting process rollout_proc5 | |
| [2025-02-25 10:53:24,893][00253] Starting process rollout_proc6 | |
| [2025-02-25 10:53:24,893][00253] Starting process rollout_proc7 | |
| [2025-02-25 10:53:40,362][02481] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 10:53:40,369][02481] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 | |
| [2025-02-25 10:53:40,441][02481] Num visible devices: 1 | |
| [2025-02-25 10:53:40,485][02481] Starting seed is not provided | |
| [2025-02-25 10:53:40,486][02481] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 10:53:40,486][02481] Initializing actor-critic model on device cuda:0 | |
| [2025-02-25 10:53:40,487][02481] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 10:53:40,491][02481] RunningMeanStd input shape: (1,) | |
| [2025-02-25 10:53:40,593][02481] ConvEncoder: input_channels=3 | |
| [2025-02-25 10:53:41,356][02501] Worker 6 uses CPU cores [0] | |
| [2025-02-25 10:53:41,547][02498] Worker 3 uses CPU cores [1] | |
| [2025-02-25 10:53:41,569][02481] Conv encoder output size: 512 | |
| [2025-02-25 10:53:41,570][02481] Policy head output size: 512 | |
| [2025-02-25 10:53:41,576][02500] Worker 5 uses CPU cores [1] | |
| [2025-02-25 10:53:41,704][02499] Worker 4 uses CPU cores [0] | |
| [2025-02-25 10:53:41,739][02481] Created Actor Critic model with architecture: | |
| [2025-02-25 10:53:41,740][02481] ActorCriticSharedWeights( | |
| (obs_normalizer): ObservationNormalizer( | |
| (running_mean_std): RunningMeanStdDictInPlace( | |
| (running_mean_std): ModuleDict( | |
| (obs): RunningMeanStdInPlace() | |
| ) | |
| ) | |
| ) | |
| (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) | |
| (encoder): VizdoomEncoder( | |
| (basic_encoder): ConvEncoder( | |
| (enc): RecursiveScriptModule( | |
| original_name=ConvEncoderImpl | |
| (conv_head): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Conv2d) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| (2): RecursiveScriptModule(original_name=Conv2d) | |
| (3): RecursiveScriptModule(original_name=ELU) | |
| (4): RecursiveScriptModule(original_name=Conv2d) | |
| (5): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| (mlp_layers): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Linear) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (core): ModelCoreRNN( | |
| (core): GRU(512, 512) | |
| ) | |
| (decoder): MlpDecoder( | |
| (mlp): Identity() | |
| ) | |
| (critic_linear): Linear(in_features=512, out_features=1, bias=True) | |
| (action_parameterization): ActionParameterizationDefault( | |
| (distribution_linear): Linear(in_features=512, out_features=5, bias=True) | |
| ) | |
| ) | |
| [2025-02-25 10:53:41,833][02496] Worker 1 uses CPU cores [1] | |
| [2025-02-25 10:53:41,843][02494] Worker 0 uses CPU cores [0] | |
| [2025-02-25 10:53:41,955][02497] Worker 2 uses CPU cores [0] | |
| [2025-02-25 10:53:41,958][02502] Worker 7 uses CPU cores [1] | |
| [2025-02-25 10:53:41,991][02495] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 10:53:41,992][02495] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 | |
| [2025-02-25 10:53:42,013][02495] Num visible devices: 1 | |
| [2025-02-25 10:53:42,086][02481] Using optimizer <class 'torch.optim.adam.Adam'> | |
| [2025-02-25 10:53:44,767][00253] Heartbeat connected on InferenceWorker_p0-w0 | |
| [2025-02-25 10:53:44,774][00253] Heartbeat connected on RolloutWorker_w0 | |
| [2025-02-25 10:53:44,784][00253] Heartbeat connected on RolloutWorker_w1 | |
| [2025-02-25 10:53:44,790][00253] Heartbeat connected on RolloutWorker_w2 | |
| [2025-02-25 10:53:44,800][00253] Heartbeat connected on RolloutWorker_w3 | |
| [2025-02-25 10:53:44,809][00253] Heartbeat connected on RolloutWorker_w4 | |
| [2025-02-25 10:53:44,815][00253] Heartbeat connected on RolloutWorker_w5 | |
| [2025-02-25 10:53:44,820][00253] Heartbeat connected on RolloutWorker_w6 | |
| [2025-02-25 10:53:44,825][00253] Heartbeat connected on RolloutWorker_w7 | |
| [2025-02-25 10:53:44,899][00253] Heartbeat connected on Batcher_0 | |
| [2025-02-25 10:53:46,227][02481] No checkpoints found | |
| [2025-02-25 10:53:46,227][02481] Did not load from checkpoint, starting from scratch! | |
| [2025-02-25 10:53:46,228][02481] Initialized policy 0 weights for model version 0 | |
| [2025-02-25 10:53:46,230][02481] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 10:53:46,237][02481] LearnerWorker_p0 finished initialization! | |
| [2025-02-25 10:53:46,237][00253] Heartbeat connected on LearnerWorker_p0 | |
| [2025-02-25 10:53:46,388][02495] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 10:53:46,389][02495] RunningMeanStd input shape: (1,) | |
| [2025-02-25 10:53:46,401][02495] ConvEncoder: input_channels=3 | |
| [2025-02-25 10:53:46,501][02495] Conv encoder output size: 512 | |
| [2025-02-25 10:53:46,501][02495] Policy head output size: 512 | |
| [2025-02-25 10:53:46,539][00253] Inference worker 0-0 is ready! | |
| [2025-02-25 10:53:46,540][00253] All inference workers are ready! Signal rollout workers to start! | |
| [2025-02-25 10:53:46,825][02499] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:46,835][02498] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:46,850][02494] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:46,857][02496] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:46,867][02500] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:46,912][02497] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:46,945][02501] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:46,950][02502] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 10:53:48,391][02501] Decorrelating experience for 0 frames... | |
| [2025-02-25 10:53:48,391][02496] Decorrelating experience for 0 frames... | |
| [2025-02-25 10:53:48,398][02499] Decorrelating experience for 0 frames... | |
| [2025-02-25 10:53:48,997][00253] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-25 10:53:49,312][02498] Decorrelating experience for 0 frames... | |
| [2025-02-25 10:53:49,375][02496] Decorrelating experience for 32 frames... | |
| [2025-02-25 10:53:49,751][02499] Decorrelating experience for 32 frames... | |
| [2025-02-25 10:53:49,759][02501] Decorrelating experience for 32 frames... | |
| [2025-02-25 10:53:50,591][02498] Decorrelating experience for 32 frames... | |
| [2025-02-25 10:53:50,781][02497] Decorrelating experience for 0 frames... | |
| [2025-02-25 10:53:51,010][02496] Decorrelating experience for 64 frames... | |
| [2025-02-25 10:53:51,495][02496] Decorrelating experience for 96 frames... | |
| [2025-02-25 10:53:51,505][02501] Decorrelating experience for 64 frames... | |
| [2025-02-25 10:53:51,936][02499] Decorrelating experience for 64 frames... | |
| [2025-02-25 10:53:51,938][02497] Decorrelating experience for 32 frames... | |
| [2025-02-25 10:53:52,721][02501] Decorrelating experience for 96 frames... | |
| [2025-02-25 10:53:52,851][02498] Decorrelating experience for 64 frames... | |
| [2025-02-25 10:53:53,250][02499] Decorrelating experience for 96 frames... | |
| [2025-02-25 10:53:53,550][02497] Decorrelating experience for 64 frames... | |
| [2025-02-25 10:53:53,993][00253] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 2.4. Samples: 12. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-25 10:53:53,994][00253] Avg episode reward: [(0, '2.102')] | |
| [2025-02-25 10:53:54,218][02498] Decorrelating experience for 96 frames... | |
| [2025-02-25 10:53:56,383][02497] Decorrelating experience for 96 frames... | |
| [2025-02-25 10:53:56,574][02481] Signal inference workers to stop experience collection... | |
| [2025-02-25 10:53:56,585][02495] InferenceWorker_p0-w0: stopping experience collection | |
| [2025-02-25 10:53:58,023][02481] Signal inference workers to resume experience collection... | |
| [2025-02-25 10:53:58,024][02495] InferenceWorker_p0-w0: resuming experience collection | |
| [2025-02-25 10:53:58,993][00253] Fps is (10 sec: 819.5, 60 sec: 819.5, 300 sec: 819.5). Total num frames: 8192. Throughput: 0: 265.5. Samples: 2654. Policy #0 lag: (min: 0.0, avg: 0.0, max: 0.0) | |
| [2025-02-25 10:53:58,994][00253] Avg episode reward: [(0, '3.378')] | |
| [2025-02-25 10:54:03,993][00253] Fps is (10 sec: 2457.6, 60 sec: 1638.9, 300 sec: 1638.9). Total num frames: 24576. Throughput: 0: 373.0. Samples: 5594. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:03,994][00253] Avg episode reward: [(0, '3.874')] | |
| [2025-02-25 10:54:07,933][02495] Updated weights for policy 0, policy_version 10 (0.0014) | |
| [2025-02-25 10:54:08,993][00253] Fps is (10 sec: 3686.4, 60 sec: 2253.3, 300 sec: 2253.3). Total num frames: 45056. Throughput: 0: 510.4. Samples: 10206. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:08,994][00253] Avg episode reward: [(0, '4.237')] | |
| [2025-02-25 10:54:13,993][00253] Fps is (10 sec: 3686.4, 60 sec: 2458.0, 300 sec: 2458.0). Total num frames: 61440. Throughput: 0: 629.7. Samples: 15740. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:13,994][00253] Avg episode reward: [(0, '4.325')] | |
| [2025-02-25 10:54:18,993][00253] Fps is (10 sec: 2867.0, 60 sec: 2457.9, 300 sec: 2457.9). Total num frames: 73728. Throughput: 0: 603.6. Samples: 18106. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:19,002][00253] Avg episode reward: [(0, '4.322')] | |
| [2025-02-25 10:54:20,142][02495] Updated weights for policy 0, policy_version 20 (0.0026) | |
| [2025-02-25 10:54:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 2809.0, 300 sec: 2809.0). Total num frames: 98304. Throughput: 0: 668.9. Samples: 23408. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:23,996][00253] Avg episode reward: [(0, '4.499')] | |
| [2025-02-25 10:54:28,993][00253] Fps is (10 sec: 4505.9, 60 sec: 2969.9, 300 sec: 2969.9). Total num frames: 118784. Throughput: 0: 744.3. Samples: 29768. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:28,996][00253] Avg episode reward: [(0, '4.564')] | |
| [2025-02-25 10:54:29,001][02481] Saving new best policy, reward=4.564! | |
| [2025-02-25 10:54:30,360][02495] Updated weights for policy 0, policy_version 30 (0.0014) | |
| [2025-02-25 10:54:33,993][00253] Fps is (10 sec: 3276.7, 60 sec: 2913.0, 300 sec: 2913.0). Total num frames: 131072. Throughput: 0: 709.8. Samples: 31940. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:54:33,994][00253] Avg episode reward: [(0, '4.441')] | |
| [2025-02-25 10:54:38,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3031.3, 300 sec: 3031.3). Total num frames: 151552. Throughput: 0: 834.5. Samples: 37566. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:38,994][00253] Avg episode reward: [(0, '4.321')] | |
| [2025-02-25 10:54:40,956][02495] Updated weights for policy 0, policy_version 40 (0.0018) | |
| [2025-02-25 10:54:43,995][00253] Fps is (10 sec: 4095.3, 60 sec: 3128.0, 300 sec: 3128.0). Total num frames: 172032. Throughput: 0: 916.0. Samples: 43878. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:43,996][00253] Avg episode reward: [(0, '4.275')] | |
| [2025-02-25 10:54:48,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3140.5, 300 sec: 3140.5). Total num frames: 188416. Throughput: 0: 894.4. Samples: 45842. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:54:48,994][00253] Avg episode reward: [(0, '4.557')] | |
| [2025-02-25 10:54:52,283][02495] Updated weights for policy 0, policy_version 50 (0.0017) | |
| [2025-02-25 10:54:53,993][00253] Fps is (10 sec: 3687.2, 60 sec: 3481.6, 300 sec: 3214.0). Total num frames: 208896. Throughput: 0: 925.2. Samples: 51840. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:54:53,994][00253] Avg episode reward: [(0, '4.481')] | |
| [2025-02-25 10:54:58,995][00253] Fps is (10 sec: 3685.6, 60 sec: 3618.0, 300 sec: 3218.4). Total num frames: 225280. Throughput: 0: 924.2. Samples: 57330. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:54:58,997][00253] Avg episode reward: [(0, '4.321')] | |
| [2025-02-25 10:55:03,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3222.4). Total num frames: 241664. Throughput: 0: 913.7. Samples: 59220. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:03,996][00253] Avg episode reward: [(0, '4.331')] | |
| [2025-02-25 10:55:04,090][02495] Updated weights for policy 0, policy_version 60 (0.0017) | |
| [2025-02-25 10:55:08,993][00253] Fps is (10 sec: 4097.0, 60 sec: 3686.4, 300 sec: 3328.2). Total num frames: 266240. Throughput: 0: 932.2. Samples: 65358. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:08,997][00253] Avg episode reward: [(0, '4.457')] | |
| [2025-02-25 10:55:13,994][00253] Fps is (10 sec: 4095.5, 60 sec: 3686.3, 300 sec: 3325.1). Total num frames: 282624. Throughput: 0: 916.8. Samples: 71026. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:13,996][00253] Avg episode reward: [(0, '4.518')] | |
| [2025-02-25 10:55:15,133][02495] Updated weights for policy 0, policy_version 70 (0.0022) | |
| [2025-02-25 10:55:18,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3322.5). Total num frames: 299008. Throughput: 0: 917.2. Samples: 73216. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:18,994][00253] Avg episode reward: [(0, '4.591')] | |
| [2025-02-25 10:55:19,008][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000073_299008.pth... | |
| [2025-02-25 10:55:19,127][02481] Saving new best policy, reward=4.591! | |
| [2025-02-25 10:55:23,993][00253] Fps is (10 sec: 3686.8, 60 sec: 3686.4, 300 sec: 3363.2). Total num frames: 319488. Throughput: 0: 934.3. Samples: 79608. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:23,994][00253] Avg episode reward: [(0, '4.737')] | |
| [2025-02-25 10:55:24,014][02481] Saving new best policy, reward=4.737! | |
| [2025-02-25 10:55:25,223][02495] Updated weights for policy 0, policy_version 80 (0.0017) | |
| [2025-02-25 10:55:28,997][00253] Fps is (10 sec: 3684.9, 60 sec: 3617.9, 300 sec: 3358.7). Total num frames: 335872. Throughput: 0: 905.7. Samples: 84638. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:55:28,998][00253] Avg episode reward: [(0, '4.621')] | |
| [2025-02-25 10:55:33,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3394.0). Total num frames: 356352. Throughput: 0: 917.8. Samples: 87142. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:33,996][00253] Avg episode reward: [(0, '4.233')] | |
| [2025-02-25 10:55:36,721][02495] Updated weights for policy 0, policy_version 90 (0.0014) | |
| [2025-02-25 10:55:38,993][00253] Fps is (10 sec: 4097.6, 60 sec: 3754.7, 300 sec: 3425.9). Total num frames: 376832. Throughput: 0: 921.3. Samples: 93300. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:38,998][00253] Avg episode reward: [(0, '4.392')] | |
| [2025-02-25 10:55:43,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3618.3, 300 sec: 3383.8). Total num frames: 389120. Throughput: 0: 906.8. Samples: 98134. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:43,998][00253] Avg episode reward: [(0, '4.429')] | |
| [2025-02-25 10:55:48,187][02495] Updated weights for policy 0, policy_version 100 (0.0014) | |
| [2025-02-25 10:55:48,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3413.5). Total num frames: 409600. Throughput: 0: 929.0. Samples: 101024. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:48,996][00253] Avg episode reward: [(0, '4.458')] | |
| [2025-02-25 10:55:53,993][00253] Fps is (10 sec: 4095.9, 60 sec: 3686.4, 300 sec: 3440.7). Total num frames: 430080. Throughput: 0: 931.6. Samples: 107280. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:53,997][00253] Avg episode reward: [(0, '4.435')] | |
| [2025-02-25 10:55:58,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.5, 300 sec: 3434.4). Total num frames: 446464. Throughput: 0: 910.8. Samples: 112010. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:55:58,995][00253] Avg episode reward: [(0, '4.422')] | |
| [2025-02-25 10:55:59,508][02495] Updated weights for policy 0, policy_version 110 (0.0014) | |
| [2025-02-25 10:56:03,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3754.7, 300 sec: 3459.0). Total num frames: 466944. Throughput: 0: 931.9. Samples: 115150. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:56:03,994][00253] Avg episode reward: [(0, '4.508')] | |
| [2025-02-25 10:56:08,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3481.7). Total num frames: 487424. Throughput: 0: 932.3. Samples: 121562. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:56:08,997][00253] Avg episode reward: [(0, '4.592')] | |
| [2025-02-25 10:56:09,613][02495] Updated weights for policy 0, policy_version 120 (0.0021) | |
| [2025-02-25 10:56:13,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.5, 300 sec: 3474.6). Total num frames: 503808. Throughput: 0: 929.6. Samples: 126468. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:56:13,997][00253] Avg episode reward: [(0, '4.414')] | |
| [2025-02-25 10:56:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3495.4). Total num frames: 524288. Throughput: 0: 944.4. Samples: 129640. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:56:18,997][00253] Avg episode reward: [(0, '4.294')] | |
| [2025-02-25 10:56:20,136][02495] Updated weights for policy 0, policy_version 130 (0.0017) | |
| [2025-02-25 10:56:23,995][00253] Fps is (10 sec: 4095.2, 60 sec: 3754.5, 300 sec: 3514.7). Total num frames: 544768. Throughput: 0: 945.9. Samples: 135868. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:56:23,996][00253] Avg episode reward: [(0, '4.443')] | |
| [2025-02-25 10:56:28,993][00253] Fps is (10 sec: 3686.3, 60 sec: 3754.9, 300 sec: 3507.3). Total num frames: 561152. Throughput: 0: 952.4. Samples: 140994. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:56:28,994][00253] Avg episode reward: [(0, '4.634')] | |
| [2025-02-25 10:56:31,235][02495] Updated weights for policy 0, policy_version 140 (0.0013) | |
| [2025-02-25 10:56:33,993][00253] Fps is (10 sec: 3687.0, 60 sec: 3754.7, 300 sec: 3525.1). Total num frames: 581632. Throughput: 0: 957.4. Samples: 144108. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:56:33,996][00253] Avg episode reward: [(0, '4.863')] | |
| [2025-02-25 10:56:34,039][02481] Saving new best policy, reward=4.863! | |
| [2025-02-25 10:56:38,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3517.8). Total num frames: 598016. Throughput: 0: 943.5. Samples: 149736. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:56:38,996][00253] Avg episode reward: [(0, '4.528')] | |
| [2025-02-25 10:56:42,311][02495] Updated weights for policy 0, policy_version 150 (0.0026) | |
| [2025-02-25 10:56:43,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3822.9, 300 sec: 3534.3). Total num frames: 618496. Throughput: 0: 962.4. Samples: 155316. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:56:43,994][00253] Avg episode reward: [(0, '4.392')] | |
| [2025-02-25 10:56:48,993][00253] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3572.7). Total num frames: 643072. Throughput: 0: 963.9. Samples: 158524. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:56:48,994][00253] Avg episode reward: [(0, '4.522')] | |
| [2025-02-25 10:56:53,214][02495] Updated weights for policy 0, policy_version 160 (0.0014) | |
| [2025-02-25 10:56:53,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3542.6). Total num frames: 655360. Throughput: 0: 936.2. Samples: 163692. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:56:53,994][00253] Avg episode reward: [(0, '4.587')] | |
| [2025-02-25 10:56:58,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3557.1). Total num frames: 675840. Throughput: 0: 960.6. Samples: 169694. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:56:58,994][00253] Avg episode reward: [(0, '4.500')] | |
| [2025-02-25 10:57:03,061][02495] Updated weights for policy 0, policy_version 170 (0.0013) | |
| [2025-02-25 10:57:03,993][00253] Fps is (10 sec: 4095.9, 60 sec: 3822.9, 300 sec: 3570.9). Total num frames: 696320. Throughput: 0: 957.9. Samples: 172744. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:03,996][00253] Avg episode reward: [(0, '4.494')] | |
| [2025-02-25 10:57:08,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3563.6). Total num frames: 712704. Throughput: 0: 927.1. Samples: 177584. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:08,997][00253] Avg episode reward: [(0, '4.535')] | |
| [2025-02-25 10:57:13,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3822.9, 300 sec: 3576.6). Total num frames: 733184. Throughput: 0: 955.5. Samples: 183992. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:13,997][00253] Avg episode reward: [(0, '4.515')] | |
| [2025-02-25 10:57:14,186][02495] Updated weights for policy 0, policy_version 180 (0.0012) | |
| [2025-02-25 10:57:18,996][00253] Fps is (10 sec: 4094.7, 60 sec: 3822.7, 300 sec: 3588.9). Total num frames: 753664. Throughput: 0: 958.1. Samples: 187226. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:18,997][00253] Avg episode reward: [(0, '4.410')] | |
| [2025-02-25 10:57:19,011][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000184_753664.pth... | |
| [2025-02-25 10:57:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.8, 300 sec: 3581.7). Total num frames: 770048. Throughput: 0: 939.2. Samples: 192000. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:23,994][00253] Avg episode reward: [(0, '4.494')] | |
| [2025-02-25 10:57:25,156][02495] Updated weights for policy 0, policy_version 190 (0.0022) | |
| [2025-02-25 10:57:28,993][00253] Fps is (10 sec: 4097.2, 60 sec: 3891.2, 300 sec: 3612.0). Total num frames: 794624. Throughput: 0: 960.6. Samples: 198542. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:28,997][00253] Avg episode reward: [(0, '4.582')] | |
| [2025-02-25 10:57:33,993][00253] Fps is (10 sec: 4095.9, 60 sec: 3822.9, 300 sec: 3604.5). Total num frames: 811008. Throughput: 0: 960.6. Samples: 201750. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:33,997][00253] Avg episode reward: [(0, '4.858')] | |
| [2025-02-25 10:57:36,159][02495] Updated weights for policy 0, policy_version 200 (0.0020) | |
| [2025-02-25 10:57:38,996][00253] Fps is (10 sec: 3685.3, 60 sec: 3891.0, 300 sec: 3615.2). Total num frames: 831488. Throughput: 0: 954.7. Samples: 206658. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:57:38,997][00253] Avg episode reward: [(0, '4.778')] | |
| [2025-02-25 10:57:43,993][00253] Fps is (10 sec: 4096.1, 60 sec: 3891.2, 300 sec: 3625.5). Total num frames: 851968. Throughput: 0: 967.5. Samples: 213230. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:57:43,995][00253] Avg episode reward: [(0, '4.509')] | |
| [2025-02-25 10:57:45,542][02495] Updated weights for policy 0, policy_version 210 (0.0014) | |
| [2025-02-25 10:57:48,993][00253] Fps is (10 sec: 3687.5, 60 sec: 3754.7, 300 sec: 3618.2). Total num frames: 868352. Throughput: 0: 964.8. Samples: 216158. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:48,994][00253] Avg episode reward: [(0, '4.580')] | |
| [2025-02-25 10:57:53,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3627.9). Total num frames: 888832. Throughput: 0: 975.9. Samples: 221498. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:53,994][00253] Avg episode reward: [(0, '4.672')] | |
| [2025-02-25 10:57:56,246][02495] Updated weights for policy 0, policy_version 220 (0.0015) | |
| [2025-02-25 10:57:58,993][00253] Fps is (10 sec: 4095.9, 60 sec: 3891.2, 300 sec: 3637.3). Total num frames: 909312. Throughput: 0: 980.1. Samples: 228096. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:57:58,994][00253] Avg episode reward: [(0, '4.683')] | |
| [2025-02-25 10:58:03,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3630.2). Total num frames: 925696. Throughput: 0: 962.8. Samples: 230550. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:58:03,994][00253] Avg episode reward: [(0, '4.728')] | |
| [2025-02-25 10:58:07,301][02495] Updated weights for policy 0, policy_version 230 (0.0024) | |
| [2025-02-25 10:58:08,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3891.2, 300 sec: 3639.2). Total num frames: 946176. Throughput: 0: 982.4. Samples: 236206. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:58:08,994][00253] Avg episode reward: [(0, '4.895')] | |
| [2025-02-25 10:58:09,000][02481] Saving new best policy, reward=4.895! | |
| [2025-02-25 10:58:14,009][00253] Fps is (10 sec: 4089.5, 60 sec: 3890.2, 300 sec: 3647.6). Total num frames: 966656. Throughput: 0: 978.3. Samples: 242582. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:58:14,015][00253] Avg episode reward: [(0, '4.930')] | |
| [2025-02-25 10:58:14,042][02481] Saving new best policy, reward=4.930! | |
| [2025-02-25 10:58:18,319][02495] Updated weights for policy 0, policy_version 240 (0.0016) | |
| [2025-02-25 10:58:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3823.1, 300 sec: 3640.9). Total num frames: 983040. Throughput: 0: 950.7. Samples: 244530. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:58:18,996][00253] Avg episode reward: [(0, '4.851')] | |
| [2025-02-25 10:58:23,993][00253] Fps is (10 sec: 4102.6, 60 sec: 3959.5, 300 sec: 3664.1). Total num frames: 1007616. Throughput: 0: 978.8. Samples: 250700. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:58:23,994][00253] Avg episode reward: [(0, '5.002')] | |
| [2025-02-25 10:58:23,995][02481] Saving new best policy, reward=5.002! | |
| [2025-02-25 10:58:28,061][02495] Updated weights for policy 0, policy_version 250 (0.0011) | |
| [2025-02-25 10:58:29,000][00253] Fps is (10 sec: 4093.1, 60 sec: 3822.5, 300 sec: 3657.1). Total num frames: 1024000. Throughput: 0: 965.7. Samples: 256692. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:58:29,001][00253] Avg episode reward: [(0, '5.212')] | |
| [2025-02-25 10:58:29,012][02481] Saving new best policy, reward=5.212! | |
| [2025-02-25 10:58:33,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3823.0, 300 sec: 3650.5). Total num frames: 1040384. Throughput: 0: 943.7. Samples: 258624. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:58:33,997][00253] Avg episode reward: [(0, '5.079')] | |
| [2025-02-25 10:58:38,772][02495] Updated weights for policy 0, policy_version 260 (0.0014) | |
| [2025-02-25 10:58:38,993][00253] Fps is (10 sec: 4098.9, 60 sec: 3891.4, 300 sec: 3672.3). Total num frames: 1064960. Throughput: 0: 972.4. Samples: 265256. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:58:38,994][00253] Avg episode reward: [(0, '5.377')] | |
| [2025-02-25 10:58:39,003][02481] Saving new best policy, reward=5.377! | |
| [2025-02-25 10:58:43,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3665.6). Total num frames: 1081344. Throughput: 0: 947.2. Samples: 270722. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:58:43,994][00253] Avg episode reward: [(0, '5.258')] | |
| [2025-02-25 10:58:48,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3735.0). Total num frames: 1101824. Throughput: 0: 950.2. Samples: 273310. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:58:48,994][00253] Avg episode reward: [(0, '5.236')] | |
| [2025-02-25 10:58:49,857][02495] Updated weights for policy 0, policy_version 270 (0.0018) | |
| [2025-02-25 10:58:53,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3776.7). Total num frames: 1122304. Throughput: 0: 969.5. Samples: 279834. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:58:53,997][00253] Avg episode reward: [(0, '5.227')] | |
| [2025-02-25 10:58:58,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3822.9, 300 sec: 3776.7). Total num frames: 1138688. Throughput: 0: 943.1. Samples: 285008. Policy #0 lag: (min: 0.0, avg: 0.3, max: 2.0) | |
| [2025-02-25 10:58:58,996][00253] Avg episode reward: [(0, '5.451')] | |
| [2025-02-25 10:58:59,006][02481] Saving new best policy, reward=5.451! | |
| [2025-02-25 10:59:00,691][02495] Updated weights for policy 0, policy_version 280 (0.0020) | |
| [2025-02-25 10:59:03,994][00253] Fps is (10 sec: 3686.1, 60 sec: 3891.1, 300 sec: 3776.6). Total num frames: 1159168. Throughput: 0: 965.8. Samples: 287990. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:59:03,998][00253] Avg episode reward: [(0, '5.518')] | |
| [2025-02-25 10:59:04,000][02481] Saving new best policy, reward=5.518! | |
| [2025-02-25 10:59:08,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3790.5). Total num frames: 1179648. Throughput: 0: 969.1. Samples: 294310. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:59:08,994][00253] Avg episode reward: [(0, '5.433')] | |
| [2025-02-25 10:59:10,900][02495] Updated weights for policy 0, policy_version 290 (0.0013) | |
| [2025-02-25 10:59:13,993][00253] Fps is (10 sec: 3686.7, 60 sec: 3824.0, 300 sec: 3804.4). Total num frames: 1196032. Throughput: 0: 946.4. Samples: 299274. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:59:13,996][00253] Avg episode reward: [(0, '5.492')] | |
| [2025-02-25 10:59:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3790.5). Total num frames: 1216512. Throughput: 0: 976.4. Samples: 302560. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:59:18,997][00253] Avg episode reward: [(0, '5.374')] | |
| [2025-02-25 10:59:19,004][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000297_1216512.pth... | |
| [2025-02-25 10:59:19,103][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000073_299008.pth | |
| [2025-02-25 10:59:21,267][02495] Updated weights for policy 0, policy_version 300 (0.0015) | |
| [2025-02-25 10:59:24,001][00253] Fps is (10 sec: 4092.6, 60 sec: 3822.4, 300 sec: 3790.4). Total num frames: 1236992. Throughput: 0: 971.9. Samples: 309000. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:59:24,002][00253] Avg episode reward: [(0, '5.398')] | |
| [2025-02-25 10:59:28,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3823.4, 300 sec: 3804.4). Total num frames: 1253376. Throughput: 0: 960.0. Samples: 313920. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:59:28,994][00253] Avg episode reward: [(0, '5.489')] | |
| [2025-02-25 10:59:32,091][02495] Updated weights for policy 0, policy_version 310 (0.0014) | |
| [2025-02-25 10:59:33,993][00253] Fps is (10 sec: 4099.4, 60 sec: 3959.5, 300 sec: 3818.3). Total num frames: 1277952. Throughput: 0: 976.4. Samples: 317250. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 10:59:33,997][00253] Avg episode reward: [(0, '5.932')] | |
| [2025-02-25 10:59:34,001][02481] Saving new best policy, reward=5.932! | |
| [2025-02-25 10:59:38,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3804.4). Total num frames: 1294336. Throughput: 0: 972.5. Samples: 323598. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:59:38,996][00253] Avg episode reward: [(0, '6.225')] | |
| [2025-02-25 10:59:39,002][02481] Saving new best policy, reward=6.225! | |
| [2025-02-25 10:59:42,954][02495] Updated weights for policy 0, policy_version 320 (0.0013) | |
| [2025-02-25 10:59:43,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 1314816. Throughput: 0: 968.6. Samples: 328594. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 10:59:43,997][00253] Avg episode reward: [(0, '6.209')] | |
| [2025-02-25 10:59:48,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 1335296. Throughput: 0: 976.0. Samples: 331910. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:59:48,998][00253] Avg episode reward: [(0, '6.138')] | |
| [2025-02-25 10:59:53,049][02495] Updated weights for policy 0, policy_version 330 (0.0021) | |
| [2025-02-25 10:59:53,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3818.3). Total num frames: 1351680. Throughput: 0: 968.4. Samples: 337890. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:59:53,998][00253] Avg episode reward: [(0, '5.650')] | |
| [2025-02-25 10:59:58,993][00253] Fps is (10 sec: 3686.3, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1372160. Throughput: 0: 979.1. Samples: 343332. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 10:59:58,994][00253] Avg episode reward: [(0, '6.014')] | |
| [2025-02-25 11:00:03,473][02495] Updated weights for policy 0, policy_version 340 (0.0019) | |
| [2025-02-25 11:00:03,993][00253] Fps is (10 sec: 4095.9, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 1392640. Throughput: 0: 979.0. Samples: 346614. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:00:03,998][00253] Avg episode reward: [(0, '5.865')] | |
| [2025-02-25 11:00:08,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3822.9, 300 sec: 3818.3). Total num frames: 1409024. Throughput: 0: 955.9. Samples: 352006. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:00:08,994][00253] Avg episode reward: [(0, '5.833')] | |
| [2025-02-25 11:00:13,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1429504. Throughput: 0: 976.7. Samples: 357872. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:00:13,994][00253] Avg episode reward: [(0, '5.914')] | |
| [2025-02-25 11:00:14,233][02495] Updated weights for policy 0, policy_version 350 (0.0012) | |
| [2025-02-25 11:00:18,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1449984. Throughput: 0: 974.1. Samples: 361086. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:00:18,994][00253] Avg episode reward: [(0, '6.055')] | |
| [2025-02-25 11:00:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3823.5, 300 sec: 3832.2). Total num frames: 1466368. Throughput: 0: 946.0. Samples: 366168. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:00:23,995][00253] Avg episode reward: [(0, '6.215')] | |
| [2025-02-25 11:00:25,351][02495] Updated weights for policy 0, policy_version 360 (0.0017) | |
| [2025-02-25 11:00:28,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1486848. Throughput: 0: 975.2. Samples: 372478. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:00:28,997][00253] Avg episode reward: [(0, '6.125')] | |
| [2025-02-25 11:00:33,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 1507328. Throughput: 0: 973.1. Samples: 375698. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:00:33,996][00253] Avg episode reward: [(0, '6.520')] | |
| [2025-02-25 11:00:34,000][02481] Saving new best policy, reward=6.520! | |
| [2025-02-25 11:00:36,143][02495] Updated weights for policy 0, policy_version 370 (0.0016) | |
| [2025-02-25 11:00:38,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 1523712. Throughput: 0: 939.6. Samples: 380172. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:00:38,998][00253] Avg episode reward: [(0, '6.747')] | |
| [2025-02-25 11:00:39,006][02481] Saving new best policy, reward=6.747! | |
| [2025-02-25 11:00:43,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 1544192. Throughput: 0: 954.8. Samples: 386298. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:00:43,994][00253] Avg episode reward: [(0, '6.995')] | |
| [2025-02-25 11:00:43,997][02481] Saving new best policy, reward=6.995! | |
| [2025-02-25 11:00:46,602][02495] Updated weights for policy 0, policy_version 380 (0.0012) | |
| [2025-02-25 11:00:48,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3832.2). Total num frames: 1560576. Throughput: 0: 950.1. Samples: 389368. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:00:48,994][00253] Avg episode reward: [(0, '6.974')] | |
| [2025-02-25 11:00:53,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3832.2). Total num frames: 1576960. Throughput: 0: 932.9. Samples: 393986. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:00:53,994][00253] Avg episode reward: [(0, '6.835')] | |
| [2025-02-25 11:00:58,052][02495] Updated weights for policy 0, policy_version 390 (0.0013) | |
| [2025-02-25 11:00:58,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3832.2). Total num frames: 1597440. Throughput: 0: 939.3. Samples: 400142. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:00:58,997][00253] Avg episode reward: [(0, '7.258')] | |
| [2025-02-25 11:00:59,044][02481] Saving new best policy, reward=7.258! | |
| [2025-02-25 11:01:03,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3818.3). Total num frames: 1613824. Throughput: 0: 933.1. Samples: 403074. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:01:03,998][00253] Avg episode reward: [(0, '7.913')] | |
| [2025-02-25 11:01:04,003][02481] Saving new best policy, reward=7.913! | |
| [2025-02-25 11:01:08,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3832.2). Total num frames: 1634304. Throughput: 0: 923.6. Samples: 407728. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:01:08,997][00253] Avg episode reward: [(0, '8.538')] | |
| [2025-02-25 11:01:09,006][02481] Saving new best policy, reward=8.538! | |
| [2025-02-25 11:01:09,692][02495] Updated weights for policy 0, policy_version 400 (0.0015) | |
| [2025-02-25 11:01:13,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3832.2). Total num frames: 1654784. Throughput: 0: 920.4. Samples: 413898. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:01:13,997][00253] Avg episode reward: [(0, '8.731')] | |
| [2025-02-25 11:01:13,998][02481] Saving new best policy, reward=8.731! | |
| [2025-02-25 11:01:18,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3804.4). Total num frames: 1667072. Throughput: 0: 904.9. Samples: 416420. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:01:18,994][00253] Avg episode reward: [(0, '8.649')] | |
| [2025-02-25 11:01:19,004][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000407_1667072.pth... | |
| [2025-02-25 11:01:19,149][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000184_753664.pth | |
| [2025-02-25 11:01:21,338][02495] Updated weights for policy 0, policy_version 410 (0.0014) | |
| [2025-02-25 11:01:23,993][00253] Fps is (10 sec: 3276.7, 60 sec: 3686.4, 300 sec: 3818.3). Total num frames: 1687552. Throughput: 0: 916.0. Samples: 421392. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:01:23,997][00253] Avg episode reward: [(0, '8.756')] | |
| [2025-02-25 11:01:24,000][02481] Saving new best policy, reward=8.756! | |
| [2025-02-25 11:01:28,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3818.3). Total num frames: 1708032. Throughput: 0: 915.9. Samples: 427512. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:01:28,996][00253] Avg episode reward: [(0, '9.028')] | |
| [2025-02-25 11:01:29,003][02481] Saving new best policy, reward=9.028! | |
| [2025-02-25 11:01:32,785][02495] Updated weights for policy 0, policy_version 420 (0.0012) | |
| [2025-02-25 11:01:33,998][00253] Fps is (10 sec: 3684.7, 60 sec: 3617.8, 300 sec: 3818.2). Total num frames: 1724416. Throughput: 0: 895.9. Samples: 429688. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:01:33,999][00253] Avg episode reward: [(0, '9.518')] | |
| [2025-02-25 11:01:34,000][02481] Saving new best policy, reward=9.518! | |
| [2025-02-25 11:01:38,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3818.3). Total num frames: 1744896. Throughput: 0: 912.7. Samples: 435056. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:01:38,996][00253] Avg episode reward: [(0, '9.387')] | |
| [2025-02-25 11:01:43,117][02495] Updated weights for policy 0, policy_version 430 (0.0014) | |
| [2025-02-25 11:01:43,994][00253] Fps is (10 sec: 3687.7, 60 sec: 3618.1, 300 sec: 3790.5). Total num frames: 1761280. Throughput: 0: 909.6. Samples: 441074. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:01:43,995][00253] Avg episode reward: [(0, '9.004')] | |
| [2025-02-25 11:01:48,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3804.4). Total num frames: 1777664. Throughput: 0: 886.0. Samples: 442942. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:01:48,997][00253] Avg episode reward: [(0, '7.790')] | |
| [2025-02-25 11:01:53,993][00253] Fps is (10 sec: 3686.9, 60 sec: 3686.4, 300 sec: 3804.4). Total num frames: 1798144. Throughput: 0: 912.4. Samples: 448786. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:01:53,996][00253] Avg episode reward: [(0, '8.535')] | |
| [2025-02-25 11:01:54,722][02495] Updated weights for policy 0, policy_version 440 (0.0015) | |
| [2025-02-25 11:01:58,995][00253] Fps is (10 sec: 3685.6, 60 sec: 3618.0, 300 sec: 3790.5). Total num frames: 1814528. Throughput: 0: 902.3. Samples: 454504. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:01:58,998][00253] Avg episode reward: [(0, '8.674')] | |
| [2025-02-25 11:02:03,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3790.5). Total num frames: 1830912. Throughput: 0: 890.1. Samples: 456476. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:02:03,997][00253] Avg episode reward: [(0, '10.173')] | |
| [2025-02-25 11:02:04,001][02481] Saving new best policy, reward=10.173! | |
| [2025-02-25 11:02:06,262][02495] Updated weights for policy 0, policy_version 450 (0.0018) | |
| [2025-02-25 11:02:08,993][00253] Fps is (10 sec: 3687.2, 60 sec: 3618.1, 300 sec: 3790.5). Total num frames: 1851392. Throughput: 0: 912.1. Samples: 462436. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:02:08,994][00253] Avg episode reward: [(0, '10.099')] | |
| [2025-02-25 11:02:13,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3776.7). Total num frames: 1867776. Throughput: 0: 899.9. Samples: 468008. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:02:13,994][00253] Avg episode reward: [(0, '10.630')] | |
| [2025-02-25 11:02:14,106][02481] Saving new best policy, reward=10.630! | |
| [2025-02-25 11:02:17,523][02495] Updated weights for policy 0, policy_version 460 (0.0015) | |
| [2025-02-25 11:02:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3790.5). Total num frames: 1888256. Throughput: 0: 904.8. Samples: 470400. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:02:18,998][00253] Avg episode reward: [(0, '10.568')] | |
| [2025-02-25 11:02:23,993][00253] Fps is (10 sec: 4505.6, 60 sec: 3754.7, 300 sec: 3790.5). Total num frames: 1912832. Throughput: 0: 931.2. Samples: 476962. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:02:23,994][00253] Avg episode reward: [(0, '10.614')] | |
| [2025-02-25 11:02:27,718][02495] Updated weights for policy 0, policy_version 470 (0.0015) | |
| [2025-02-25 11:02:28,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3776.7). Total num frames: 1925120. Throughput: 0: 913.7. Samples: 482190. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:02:28,994][00253] Avg episode reward: [(0, '11.084')] | |
| [2025-02-25 11:02:29,000][02481] Saving new best policy, reward=11.084! | |
| [2025-02-25 11:02:33,994][00253] Fps is (10 sec: 3276.5, 60 sec: 3686.6, 300 sec: 3776.7). Total num frames: 1945600. Throughput: 0: 932.8. Samples: 484920. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:02:33,995][00253] Avg episode reward: [(0, '11.734')] | |
| [2025-02-25 11:02:33,996][02481] Saving new best policy, reward=11.734! | |
| [2025-02-25 11:02:38,043][02495] Updated weights for policy 0, policy_version 480 (0.0013) | |
| [2025-02-25 11:02:38,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3776.7). Total num frames: 1966080. Throughput: 0: 944.8. Samples: 491300. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-25 11:02:38,994][00253] Avg episode reward: [(0, '12.155')] | |
| [2025-02-25 11:02:39,036][02481] Saving new best policy, reward=12.155! | |
| [2025-02-25 11:02:43,993][00253] Fps is (10 sec: 3686.8, 60 sec: 3686.5, 300 sec: 3776.7). Total num frames: 1982464. Throughput: 0: 924.3. Samples: 496096. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:02:43,994][00253] Avg episode reward: [(0, '12.747')] | |
| [2025-02-25 11:02:44,001][02481] Saving new best policy, reward=12.747! | |
| [2025-02-25 11:02:48,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3776.7). Total num frames: 2002944. Throughput: 0: 951.6. Samples: 499300. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:02:48,994][00253] Avg episode reward: [(0, '12.783')] | |
| [2025-02-25 11:02:49,003][02481] Saving new best policy, reward=12.783! | |
| [2025-02-25 11:02:49,197][02495] Updated weights for policy 0, policy_version 490 (0.0013) | |
| [2025-02-25 11:02:53,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3776.7). Total num frames: 2023424. Throughput: 0: 962.8. Samples: 505762. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:02:53,999][00253] Avg episode reward: [(0, '12.459')] | |
| [2025-02-25 11:02:58,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.8, 300 sec: 3776.7). Total num frames: 2039808. Throughput: 0: 942.4. Samples: 510418. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:02:58,994][00253] Avg episode reward: [(0, '12.698')] | |
| [2025-02-25 11:03:00,327][02495] Updated weights for policy 0, policy_version 500 (0.0018) | |
| [2025-02-25 11:03:03,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3776.7). Total num frames: 2060288. Throughput: 0: 961.8. Samples: 513680. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:03,994][00253] Avg episode reward: [(0, '13.137')] | |
| [2025-02-25 11:03:03,996][02481] Saving new best policy, reward=13.137! | |
| [2025-02-25 11:03:08,993][00253] Fps is (10 sec: 4095.9, 60 sec: 3822.9, 300 sec: 3776.9). Total num frames: 2080768. Throughput: 0: 953.6. Samples: 519876. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:08,994][00253] Avg episode reward: [(0, '12.798')] | |
| [2025-02-25 11:03:11,627][02495] Updated weights for policy 0, policy_version 510 (0.0013) | |
| [2025-02-25 11:03:13,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3776.7). Total num frames: 2097152. Throughput: 0: 942.0. Samples: 524582. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:13,997][00253] Avg episode reward: [(0, '13.555')] | |
| [2025-02-25 11:03:14,003][02481] Saving new best policy, reward=13.555! | |
| [2025-02-25 11:03:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3762.8). Total num frames: 2117632. Throughput: 0: 950.0. Samples: 527670. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:03:18,998][00253] Avg episode reward: [(0, '14.138')] | |
| [2025-02-25 11:03:19,007][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000517_2117632.pth... | |
| [2025-02-25 11:03:19,124][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000297_1216512.pth | |
| [2025-02-25 11:03:19,140][02481] Saving new best policy, reward=14.138! | |
| [2025-02-25 11:03:21,727][02495] Updated weights for policy 0, policy_version 520 (0.0024) | |
| [2025-02-25 11:03:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3762.9). Total num frames: 2134016. Throughput: 0: 935.1. Samples: 533378. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:23,996][00253] Avg episode reward: [(0, '14.770')] | |
| [2025-02-25 11:03:24,000][02481] Saving new best policy, reward=14.770! | |
| [2025-02-25 11:03:28,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3762.8). Total num frames: 2150400. Throughput: 0: 936.4. Samples: 538236. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:28,994][00253] Avg episode reward: [(0, '14.646')] | |
| [2025-02-25 11:03:33,228][02495] Updated weights for policy 0, policy_version 530 (0.0016) | |
| [2025-02-25 11:03:33,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 2170880. Throughput: 0: 935.4. Samples: 541394. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:33,994][00253] Avg episode reward: [(0, '15.506')] | |
| [2025-02-25 11:03:33,999][02481] Saving new best policy, reward=15.506! | |
| [2025-02-25 11:03:38,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3748.9). Total num frames: 2187264. Throughput: 0: 912.8. Samples: 546836. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:03:38,998][00253] Avg episode reward: [(0, '15.120')] | |
| [2025-02-25 11:03:43,993][00253] Fps is (10 sec: 3686.3, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 2207744. Throughput: 0: 931.2. Samples: 552320. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:43,994][00253] Avg episode reward: [(0, '15.743')] | |
| [2025-02-25 11:03:44,001][02481] Saving new best policy, reward=15.743! | |
| [2025-02-25 11:03:44,567][02495] Updated weights for policy 0, policy_version 540 (0.0015) | |
| [2025-02-25 11:03:48,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 2228224. Throughput: 0: 928.0. Samples: 555440. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:48,994][00253] Avg episode reward: [(0, '16.596')] | |
| [2025-02-25 11:03:49,001][02481] Saving new best policy, reward=16.596! | |
| [2025-02-25 11:03:53,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3748.9). Total num frames: 2244608. Throughput: 0: 906.4. Samples: 560662. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:03:53,996][00253] Avg episode reward: [(0, '17.523')] | |
| [2025-02-25 11:03:54,000][02481] Saving new best policy, reward=17.523! | |
| [2025-02-25 11:03:55,867][02495] Updated weights for policy 0, policy_version 550 (0.0021) | |
| [2025-02-25 11:03:58,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 2265088. Throughput: 0: 929.3. Samples: 566402. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:03:58,994][00253] Avg episode reward: [(0, '16.678')] | |
| [2025-02-25 11:04:03,994][00253] Fps is (10 sec: 4095.6, 60 sec: 3754.6, 300 sec: 3748.9). Total num frames: 2285568. Throughput: 0: 933.5. Samples: 569676. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:04:04,002][00253] Avg episode reward: [(0, '16.385')] | |
| [2025-02-25 11:04:06,173][02495] Updated weights for policy 0, policy_version 560 (0.0020) | |
| [2025-02-25 11:04:08,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3748.9). Total num frames: 2301952. Throughput: 0: 914.8. Samples: 574546. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:04:08,994][00253] Avg episode reward: [(0, '16.599')] | |
| [2025-02-25 11:04:13,993][00253] Fps is (10 sec: 3686.7, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 2322432. Throughput: 0: 947.3. Samples: 580866. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:04:13,996][00253] Avg episode reward: [(0, '15.832')] | |
| [2025-02-25 11:04:16,370][02495] Updated weights for policy 0, policy_version 570 (0.0016) | |
| [2025-02-25 11:04:18,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3749.0). Total num frames: 2342912. Throughput: 0: 947.9. Samples: 584050. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:04:18,997][00253] Avg episode reward: [(0, '16.319')] | |
| [2025-02-25 11:04:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 2359296. Throughput: 0: 937.8. Samples: 589036. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:04:23,994][00253] Avg episode reward: [(0, '17.830')] | |
| [2025-02-25 11:04:24,001][02481] Saving new best policy, reward=17.830! | |
| [2025-02-25 11:04:27,409][02495] Updated weights for policy 0, policy_version 580 (0.0014) | |
| [2025-02-25 11:04:28,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3735.0). Total num frames: 2379776. Throughput: 0: 957.6. Samples: 595410. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:04:28,994][00253] Avg episode reward: [(0, '17.322')] | |
| [2025-02-25 11:04:33,996][00253] Fps is (10 sec: 4094.8, 60 sec: 3822.7, 300 sec: 3748.8). Total num frames: 2400256. Throughput: 0: 960.4. Samples: 598662. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:04:33,997][00253] Avg episode reward: [(0, '17.840')] | |
| [2025-02-25 11:04:33,998][02481] Saving new best policy, reward=17.840! | |
| [2025-02-25 11:04:38,698][02495] Updated weights for policy 0, policy_version 590 (0.0012) | |
| [2025-02-25 11:04:38,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3735.0). Total num frames: 2416640. Throughput: 0: 948.4. Samples: 603340. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:04:38,997][00253] Avg episode reward: [(0, '18.285')] | |
| [2025-02-25 11:04:39,004][02481] Saving new best policy, reward=18.285! | |
| [2025-02-25 11:04:43,993][00253] Fps is (10 sec: 3277.7, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 2433024. Throughput: 0: 948.1. Samples: 609068. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:04:43,996][00253] Avg episode reward: [(0, '17.801')] | |
| [2025-02-25 11:04:48,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3721.1). Total num frames: 2449408. Throughput: 0: 941.4. Samples: 612040. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:04:48,994][00253] Avg episode reward: [(0, '17.542')] | |
| [2025-02-25 11:04:50,344][02495] Updated weights for policy 0, policy_version 600 (0.0015) | |
| [2025-02-25 11:04:53,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 2469888. Throughput: 0: 945.1. Samples: 617074. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:04:53,997][00253] Avg episode reward: [(0, '17.508')] | |
| [2025-02-25 11:04:58,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2482176. Throughput: 0: 896.8. Samples: 621224. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:04:58,994][00253] Avg episode reward: [(0, '17.172')] | |
| [2025-02-25 11:05:03,530][02495] Updated weights for policy 0, policy_version 610 (0.0035) | |
| [2025-02-25 11:05:03,993][00253] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3693.3). Total num frames: 2498560. Throughput: 0: 882.6. Samples: 623768. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:05:03,997][00253] Avg episode reward: [(0, '17.468')] | |
| [2025-02-25 11:05:08,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2519040. Throughput: 0: 893.3. Samples: 629234. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:05:08,994][00253] Avg episode reward: [(0, '17.520')] | |
| [2025-02-25 11:05:13,226][02495] Updated weights for policy 0, policy_version 620 (0.0012) | |
| [2025-02-25 11:05:13,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2539520. Throughput: 0: 889.6. Samples: 635440. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:05:13,994][00253] Avg episode reward: [(0, '17.134')] | |
| [2025-02-25 11:05:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3693.3). Total num frames: 2555904. Throughput: 0: 862.5. Samples: 637474. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:05:18,994][00253] Avg episode reward: [(0, '16.860')] | |
| [2025-02-25 11:05:19,001][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000624_2555904.pth... | |
| [2025-02-25 11:05:19,102][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000407_1667072.pth | |
| [2025-02-25 11:05:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2576384. Throughput: 0: 891.0. Samples: 643434. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:05:23,996][00253] Avg episode reward: [(0, '17.784')] | |
| [2025-02-25 11:05:24,428][02495] Updated weights for policy 0, policy_version 630 (0.0021) | |
| [2025-02-25 11:05:28,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2596864. Throughput: 0: 899.6. Samples: 649552. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:05:28,994][00253] Avg episode reward: [(0, '18.285')] | |
| [2025-02-25 11:05:33,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3550.0, 300 sec: 3693.3). Total num frames: 2613248. Throughput: 0: 878.4. Samples: 651566. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:05:33,995][00253] Avg episode reward: [(0, '18.328')] | |
| [2025-02-25 11:05:34,000][02481] Saving new best policy, reward=18.328! | |
| [2025-02-25 11:05:35,588][02495] Updated weights for policy 0, policy_version 640 (0.0019) | |
| [2025-02-25 11:05:38,993][00253] Fps is (10 sec: 3686.3, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2633728. Throughput: 0: 905.6. Samples: 657828. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:05:38,995][00253] Avg episode reward: [(0, '19.246')] | |
| [2025-02-25 11:05:38,999][02481] Saving new best policy, reward=19.246! | |
| [2025-02-25 11:05:43,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3693.3). Total num frames: 2650112. Throughput: 0: 940.2. Samples: 663532. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:05:43,996][00253] Avg episode reward: [(0, '20.020')] | |
| [2025-02-25 11:05:43,997][02481] Saving new best policy, reward=20.020! | |
| [2025-02-25 11:05:46,610][02495] Updated weights for policy 0, policy_version 650 (0.0014) | |
| [2025-02-25 11:05:48,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 2670592. Throughput: 0: 933.7. Samples: 665786. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:05:48,996][00253] Avg episode reward: [(0, '18.548')] | |
| [2025-02-25 11:05:53,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3707.2). Total num frames: 2691072. Throughput: 0: 955.0. Samples: 672208. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0) | |
| [2025-02-25 11:05:53,994][00253] Avg episode reward: [(0, '18.409')] | |
| [2025-02-25 11:05:56,625][02495] Updated weights for policy 0, policy_version 660 (0.0014) | |
| [2025-02-25 11:05:59,000][00253] Fps is (10 sec: 3683.8, 60 sec: 3754.2, 300 sec: 3707.1). Total num frames: 2707456. Throughput: 0: 936.3. Samples: 677578. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:05:59,009][00253] Avg episode reward: [(0, '17.279')] | |
| [2025-02-25 11:06:03,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3707.2). Total num frames: 2727936. Throughput: 0: 952.2. Samples: 680322. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:06:03,997][00253] Avg episode reward: [(0, '16.117')] | |
| [2025-02-25 11:06:07,129][02495] Updated weights for policy 0, policy_version 670 (0.0016) | |
| [2025-02-25 11:06:08,993][00253] Fps is (10 sec: 4098.9, 60 sec: 3822.9, 300 sec: 3707.2). Total num frames: 2748416. Throughput: 0: 963.8. Samples: 686804. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:06:08,994][00253] Avg episode reward: [(0, '16.856')] | |
| [2025-02-25 11:06:13,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3721.1). Total num frames: 2764800. Throughput: 0: 932.7. Samples: 691524. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:06:13,994][00253] Avg episode reward: [(0, '17.063')] | |
| [2025-02-25 11:06:18,536][02495] Updated weights for policy 0, policy_version 680 (0.0017) | |
| [2025-02-25 11:06:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3721.1). Total num frames: 2785280. Throughput: 0: 955.7. Samples: 694574. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:06:18,994][00253] Avg episode reward: [(0, '18.314')] | |
| [2025-02-25 11:06:23,994][00253] Fps is (10 sec: 4095.6, 60 sec: 3822.9, 300 sec: 3721.1). Total num frames: 2805760. Throughput: 0: 959.4. Samples: 701004. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:06:23,995][00253] Avg episode reward: [(0, '18.449')] | |
| [2025-02-25 11:06:28,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3721.2). Total num frames: 2822144. Throughput: 0: 939.5. Samples: 705808. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:06:28,996][00253] Avg episode reward: [(0, '19.067')] | |
| [2025-02-25 11:06:29,634][02495] Updated weights for policy 0, policy_version 690 (0.0019) | |
| [2025-02-25 11:06:33,993][00253] Fps is (10 sec: 3686.8, 60 sec: 3822.9, 300 sec: 3721.1). Total num frames: 2842624. Throughput: 0: 959.0. Samples: 708940. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:06:33,997][00253] Avg episode reward: [(0, '19.916')] | |
| [2025-02-25 11:06:38,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3735.0). Total num frames: 2863104. Throughput: 0: 960.5. Samples: 715432. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:06:38,994][00253] Avg episode reward: [(0, '19.767')] | |
| [2025-02-25 11:06:40,186][02495] Updated weights for policy 0, policy_version 700 (0.0027) | |
| [2025-02-25 11:06:43,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3735.0). Total num frames: 2879488. Throughput: 0: 944.1. Samples: 720054. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:06:43,999][00253] Avg episode reward: [(0, '20.513')] | |
| [2025-02-25 11:06:44,007][02481] Saving new best policy, reward=20.513! | |
| [2025-02-25 11:06:48,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3735.0). Total num frames: 2899968. Throughput: 0: 952.7. Samples: 723194. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:06:48,996][00253] Avg episode reward: [(0, '19.113')] | |
| [2025-02-25 11:06:50,550][02495] Updated weights for policy 0, policy_version 710 (0.0016) | |
| [2025-02-25 11:06:53,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3735.0). Total num frames: 2916352. Throughput: 0: 944.5. Samples: 729306. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:06:54,000][00253] Avg episode reward: [(0, '19.204')] | |
| [2025-02-25 11:06:58,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3823.4, 300 sec: 3748.9). Total num frames: 2936832. Throughput: 0: 952.5. Samples: 734388. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:06:58,999][00253] Avg episode reward: [(0, '18.546')] | |
| [2025-02-25 11:07:01,578][02495] Updated weights for policy 0, policy_version 720 (0.0019) | |
| [2025-02-25 11:07:03,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3748.9). Total num frames: 2957312. Throughput: 0: 956.2. Samples: 737604. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:07:03,998][00253] Avg episode reward: [(0, '18.864')] | |
| [2025-02-25 11:07:08,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 2973696. Throughput: 0: 941.4. Samples: 743364. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:07:08,995][00253] Avg episode reward: [(0, '19.238')] | |
| [2025-02-25 11:07:12,615][02495] Updated weights for policy 0, policy_version 730 (0.0027) | |
| [2025-02-25 11:07:13,993][00253] Fps is (10 sec: 3686.3, 60 sec: 3822.9, 300 sec: 3748.9). Total num frames: 2994176. Throughput: 0: 956.1. Samples: 748834. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:07:13,994][00253] Avg episode reward: [(0, '20.645')] | |
| [2025-02-25 11:07:14,001][02481] Saving new best policy, reward=20.645! | |
| [2025-02-25 11:07:18,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3735.0). Total num frames: 3014656. Throughput: 0: 956.2. Samples: 751968. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:07:18,994][00253] Avg episode reward: [(0, '20.738')] | |
| [2025-02-25 11:07:19,004][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000736_3014656.pth... | |
| [2025-02-25 11:07:19,117][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000517_2117632.pth | |
| [2025-02-25 11:07:19,134][02481] Saving new best policy, reward=20.738! | |
| [2025-02-25 11:07:23,938][02495] Updated weights for policy 0, policy_version 740 (0.0014) | |
| [2025-02-25 11:07:23,993][00253] Fps is (10 sec: 3686.5, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 3031040. Throughput: 0: 927.5. Samples: 757168. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:07:23,997][00253] Avg episode reward: [(0, '21.240')] | |
| [2025-02-25 11:07:24,001][02481] Saving new best policy, reward=21.240! | |
| [2025-02-25 11:07:28,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3748.9). Total num frames: 3051520. Throughput: 0: 957.9. Samples: 763158. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:07:28,994][00253] Avg episode reward: [(0, '20.760')] | |
| [2025-02-25 11:07:33,288][02495] Updated weights for policy 0, policy_version 750 (0.0012) | |
| [2025-02-25 11:07:33,995][00253] Fps is (10 sec: 4094.9, 60 sec: 3822.8, 300 sec: 3748.8). Total num frames: 3072000. Throughput: 0: 959.7. Samples: 766382. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:07:33,997][00253] Avg episode reward: [(0, '20.774')] | |
| [2025-02-25 11:07:38,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3748.9). Total num frames: 3088384. Throughput: 0: 935.9. Samples: 771420. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:07:38,995][00253] Avg episode reward: [(0, '20.772')] | |
| [2025-02-25 11:07:43,993][00253] Fps is (10 sec: 3687.3, 60 sec: 3822.9, 300 sec: 3748.9). Total num frames: 3108864. Throughput: 0: 964.4. Samples: 777788. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:07:43,994][00253] Avg episode reward: [(0, '20.014')] | |
| [2025-02-25 11:07:44,291][02495] Updated weights for policy 0, policy_version 760 (0.0026) | |
| [2025-02-25 11:07:48,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3748.9). Total num frames: 3129344. Throughput: 0: 965.0. Samples: 781028. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:07:48,998][00253] Avg episode reward: [(0, '20.004')] | |
| [2025-02-25 11:07:53,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3748.9). Total num frames: 3145728. Throughput: 0: 945.6. Samples: 785914. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:07:53,995][00253] Avg episode reward: [(0, '20.544')] | |
| [2025-02-25 11:07:55,199][02495] Updated weights for policy 0, policy_version 770 (0.0014) | |
| [2025-02-25 11:07:58,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3762.8). Total num frames: 3170304. Throughput: 0: 970.8. Samples: 792518. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:07:58,994][00253] Avg episode reward: [(0, '21.763')] | |
| [2025-02-25 11:07:59,000][02481] Saving new best policy, reward=21.763! | |
| [2025-02-25 11:08:03,995][00253] Fps is (10 sec: 4095.2, 60 sec: 3822.8, 300 sec: 3748.9). Total num frames: 3186688. Throughput: 0: 973.2. Samples: 795766. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:08:03,998][00253] Avg episode reward: [(0, '22.867')] | |
| [2025-02-25 11:08:04,004][02481] Saving new best policy, reward=22.867! | |
| [2025-02-25 11:08:06,133][02495] Updated weights for policy 0, policy_version 780 (0.0015) | |
| [2025-02-25 11:08:08,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3748.9). Total num frames: 3203072. Throughput: 0: 964.6. Samples: 800576. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:08:08,994][00253] Avg episode reward: [(0, '24.230')] | |
| [2025-02-25 11:08:09,001][02481] Saving new best policy, reward=24.230! | |
| [2025-02-25 11:08:13,993][00253] Fps is (10 sec: 4096.8, 60 sec: 3891.2, 300 sec: 3762.8). Total num frames: 3227648. Throughput: 0: 973.7. Samples: 806974. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-25 11:08:13,996][00253] Avg episode reward: [(0, '26.378')] | |
| [2025-02-25 11:08:14,006][02481] Saving new best policy, reward=26.378! | |
| [2025-02-25 11:08:15,685][02495] Updated weights for policy 0, policy_version 790 (0.0017) | |
| [2025-02-25 11:08:18,993][00253] Fps is (10 sec: 4095.8, 60 sec: 3822.9, 300 sec: 3762.8). Total num frames: 3244032. Throughput: 0: 964.7. Samples: 809792. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:08:18,995][00253] Avg episode reward: [(0, '26.240')] | |
| [2025-02-25 11:08:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3776.7). Total num frames: 3264512. Throughput: 0: 969.4. Samples: 815042. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:08:23,994][00253] Avg episode reward: [(0, '23.797')] | |
| [2025-02-25 11:08:26,631][02495] Updated weights for policy 0, policy_version 800 (0.0015) | |
| [2025-02-25 11:08:28,993][00253] Fps is (10 sec: 4096.2, 60 sec: 3891.2, 300 sec: 3776.7). Total num frames: 3284992. Throughput: 0: 974.2. Samples: 821626. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:08:28,994][00253] Avg episode reward: [(0, '23.966')] | |
| [2025-02-25 11:08:33,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3823.1, 300 sec: 3776.7). Total num frames: 3301376. Throughput: 0: 956.2. Samples: 824058. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:08:33,994][00253] Avg episode reward: [(0, '24.223')] | |
| [2025-02-25 11:08:37,629][02495] Updated weights for policy 0, policy_version 810 (0.0014) | |
| [2025-02-25 11:08:38,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3776.7). Total num frames: 3321856. Throughput: 0: 974.2. Samples: 829752. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:08:38,994][00253] Avg episode reward: [(0, '22.620')] | |
| [2025-02-25 11:08:43,995][00253] Fps is (10 sec: 4095.1, 60 sec: 3891.1, 300 sec: 3776.6). Total num frames: 3342336. Throughput: 0: 972.5. Samples: 836284. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:08:43,998][00253] Avg episode reward: [(0, '21.001')] | |
| [2025-02-25 11:08:48,458][02495] Updated weights for policy 0, policy_version 820 (0.0019) | |
| [2025-02-25 11:08:48,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3776.7). Total num frames: 3358720. Throughput: 0: 946.8. Samples: 838370. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:08:48,994][00253] Avg episode reward: [(0, '22.384')] | |
| [2025-02-25 11:08:53,993][00253] Fps is (10 sec: 3687.2, 60 sec: 3891.2, 300 sec: 3776.7). Total num frames: 3379200. Throughput: 0: 975.3. Samples: 844464. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:08:53,994][00253] Avg episode reward: [(0, '23.970')] | |
| [2025-02-25 11:08:57,779][02495] Updated weights for policy 0, policy_version 830 (0.0021) | |
| [2025-02-25 11:08:58,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3776.7). Total num frames: 3399680. Throughput: 0: 970.3. Samples: 850638. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:08:58,997][00253] Avg episode reward: [(0, '22.289')] | |
| [2025-02-25 11:09:03,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3823.1, 300 sec: 3776.7). Total num frames: 3416064. Throughput: 0: 952.0. Samples: 852632. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:09:03,994][00253] Avg episode reward: [(0, '22.507')] | |
| [2025-02-25 11:09:08,680][02495] Updated weights for policy 0, policy_version 840 (0.0014) | |
| [2025-02-25 11:09:08,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3790.5). Total num frames: 3440640. Throughput: 0: 983.0. Samples: 859276. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:09:08,999][00253] Avg episode reward: [(0, '22.855')] | |
| [2025-02-25 11:09:13,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3776.7). Total num frames: 3457024. Throughput: 0: 959.4. Samples: 864798. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:09:13,994][00253] Avg episode reward: [(0, '22.656')] | |
| [2025-02-25 11:09:18,998][00253] Fps is (10 sec: 3684.5, 60 sec: 3890.9, 300 sec: 3790.5). Total num frames: 3477504. Throughput: 0: 960.3. Samples: 867276. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:09:18,999][00253] Avg episode reward: [(0, '19.858')] | |
| [2025-02-25 11:09:19,006][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000849_3477504.pth... | |
| [2025-02-25 11:09:19,137][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000624_2555904.pth | |
| [2025-02-25 11:09:19,745][02495] Updated weights for policy 0, policy_version 850 (0.0014) | |
| [2025-02-25 11:09:23,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3790.5). Total num frames: 3497984. Throughput: 0: 978.5. Samples: 873784. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:09:23,998][00253] Avg episode reward: [(0, '19.533')] | |
| [2025-02-25 11:09:28,995][00253] Fps is (10 sec: 3687.5, 60 sec: 3822.8, 300 sec: 3776.7). Total num frames: 3514368. Throughput: 0: 952.2. Samples: 879134. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:09:28,996][00253] Avg episode reward: [(0, '19.147')] | |
| [2025-02-25 11:09:30,639][02495] Updated weights for policy 0, policy_version 860 (0.0014) | |
| [2025-02-25 11:09:33,993][00253] Fps is (10 sec: 3686.3, 60 sec: 3891.2, 300 sec: 3790.5). Total num frames: 3534848. Throughput: 0: 971.5. Samples: 882086. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:09:33,997][00253] Avg episode reward: [(0, '19.534')] | |
| [2025-02-25 11:09:38,995][00253] Fps is (10 sec: 4505.4, 60 sec: 3959.3, 300 sec: 3818.3). Total num frames: 3559424. Throughput: 0: 982.3. Samples: 888668. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:09:39,001][00253] Avg episode reward: [(0, '18.233')] | |
| [2025-02-25 11:09:40,105][02495] Updated weights for policy 0, policy_version 870 (0.0014) | |
| [2025-02-25 11:09:43,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3823.1, 300 sec: 3804.4). Total num frames: 3571712. Throughput: 0: 952.8. Samples: 893516. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:09:43,998][00253] Avg episode reward: [(0, '18.955')] | |
| [2025-02-25 11:09:48,993][00253] Fps is (10 sec: 3277.6, 60 sec: 3891.2, 300 sec: 3804.4). Total num frames: 3592192. Throughput: 0: 979.1. Samples: 896690. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:09:48,994][00253] Avg episode reward: [(0, '19.591')] | |
| [2025-02-25 11:09:50,782][02495] Updated weights for policy 0, policy_version 880 (0.0014) | |
| [2025-02-25 11:09:53,993][00253] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3846.1). Total num frames: 3616768. Throughput: 0: 979.5. Samples: 903352. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:09:53,994][00253] Avg episode reward: [(0, '19.750')] | |
| [2025-02-25 11:09:58,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 3633152. Throughput: 0: 965.8. Samples: 908258. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:09:58,997][00253] Avg episode reward: [(0, '18.779')] | |
| [2025-02-25 11:10:01,568][02495] Updated weights for policy 0, policy_version 890 (0.0018) | |
| [2025-02-25 11:10:03,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3846.1). Total num frames: 3653632. Throughput: 0: 984.1. Samples: 911556. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:10:03,998][00253] Avg episode reward: [(0, '19.448')] | |
| [2025-02-25 11:10:08,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 3674112. Throughput: 0: 987.6. Samples: 918224. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:10:08,998][00253] Avg episode reward: [(0, '19.866')] | |
| [2025-02-25 11:10:12,573][02495] Updated weights for policy 0, policy_version 900 (0.0019) | |
| [2025-02-25 11:10:13,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 3690496. Throughput: 0: 974.7. Samples: 922992. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:10:13,994][00253] Avg episode reward: [(0, '19.667')] | |
| [2025-02-25 11:10:18,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.5, 300 sec: 3846.1). Total num frames: 3710976. Throughput: 0: 982.3. Samples: 926290. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:10:18,997][00253] Avg episode reward: [(0, '20.624')] | |
| [2025-02-25 11:10:22,150][02495] Updated weights for policy 0, policy_version 910 (0.0013) | |
| [2025-02-25 11:10:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 3727360. Throughput: 0: 969.7. Samples: 932300. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:10:23,995][00253] Avg episode reward: [(0, '21.400')] | |
| [2025-02-25 11:10:28,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3891.3, 300 sec: 3846.1). Total num frames: 3747840. Throughput: 0: 980.5. Samples: 937640. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:10:28,994][00253] Avg episode reward: [(0, '22.785')] | |
| [2025-02-25 11:10:33,114][02495] Updated weights for policy 0, policy_version 920 (0.0013) | |
| [2025-02-25 11:10:33,993][00253] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3860.0). Total num frames: 3772416. Throughput: 0: 981.5. Samples: 940858. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:10:33,997][00253] Avg episode reward: [(0, '23.453')] | |
| [2025-02-25 11:10:38,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.8, 300 sec: 3846.1). Total num frames: 3784704. Throughput: 0: 957.9. Samples: 946458. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:10:38,994][00253] Avg episode reward: [(0, '23.502')] | |
| [2025-02-25 11:10:43,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 3805184. Throughput: 0: 967.9. Samples: 951814. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:10:43,994][00253] Avg episode reward: [(0, '25.003')] | |
| [2025-02-25 11:10:44,460][02495] Updated weights for policy 0, policy_version 930 (0.0013) | |
| [2025-02-25 11:10:48,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 3825664. Throughput: 0: 961.6. Samples: 954830. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:10:48,994][00253] Avg episode reward: [(0, '25.429')] | |
| [2025-02-25 11:10:53,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3846.2). Total num frames: 3842048. Throughput: 0: 923.5. Samples: 959780. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:10:53,994][00253] Avg episode reward: [(0, '25.538')] | |
| [2025-02-25 11:10:55,921][02495] Updated weights for policy 0, policy_version 940 (0.0012) | |
| [2025-02-25 11:10:58,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 3862528. Throughput: 0: 947.9. Samples: 965648. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:10:58,994][00253] Avg episode reward: [(0, '23.991')] | |
| [2025-02-25 11:11:03,994][00253] Fps is (10 sec: 4095.7, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 3883008. Throughput: 0: 944.9. Samples: 968810. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:11:03,998][00253] Avg episode reward: [(0, '22.875')] | |
| [2025-02-25 11:11:07,411][02495] Updated weights for policy 0, policy_version 950 (0.0017) | |
| [2025-02-25 11:11:08,993][00253] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3832.2). Total num frames: 3895296. Throughput: 0: 912.7. Samples: 973370. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:11:08,998][00253] Avg episode reward: [(0, '23.069')] | |
| [2025-02-25 11:11:13,993][00253] Fps is (10 sec: 3277.1, 60 sec: 3754.7, 300 sec: 3832.2). Total num frames: 3915776. Throughput: 0: 934.0. Samples: 979668. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:11:13,997][00253] Avg episode reward: [(0, '20.815')] | |
| [2025-02-25 11:11:16,922][02495] Updated weights for policy 0, policy_version 960 (0.0019) | |
| [2025-02-25 11:11:18,997][00253] Fps is (10 sec: 4094.4, 60 sec: 3754.4, 300 sec: 3832.2). Total num frames: 3936256. Throughput: 0: 935.6. Samples: 982962. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) | |
| [2025-02-25 11:11:19,002][00253] Avg episode reward: [(0, '23.015')] | |
| [2025-02-25 11:11:19,018][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000961_3936256.pth... | |
| [2025-02-25 11:11:19,172][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000736_3014656.pth | |
| [2025-02-25 11:11:23,993][00253] Fps is (10 sec: 3686.4, 60 sec: 3754.7, 300 sec: 3832.2). Total num frames: 3952640. Throughput: 0: 918.5. Samples: 987790. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:11:23,999][00253] Avg episode reward: [(0, '22.532')] | |
| [2025-02-25 11:11:27,741][02495] Updated weights for policy 0, policy_version 970 (0.0016) | |
| [2025-02-25 11:11:28,993][00253] Fps is (10 sec: 4097.7, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 3977216. Throughput: 0: 948.1. Samples: 994480. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) | |
| [2025-02-25 11:11:29,000][00253] Avg episode reward: [(0, '24.311')] | |
| [2025-02-25 11:11:33,993][00253] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3832.2). Total num frames: 3993600. Throughput: 0: 950.1. Samples: 997586. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:11:33,994][00253] Avg episode reward: [(0, '23.040')] | |
| [2025-02-25 11:11:36,659][02481] Stopping Batcher_0... | |
| [2025-02-25 11:11:36,661][02481] Loop batcher_evt_loop terminating... | |
| [2025-02-25 11:11:36,661][00253] Component Batcher_0 stopped! | |
| [2025-02-25 11:11:36,663][00253] Component RolloutWorker_w0 process died already! Don't wait for it. | |
| [2025-02-25 11:11:36,664][00253] Component RolloutWorker_w5 process died already! Don't wait for it. | |
| [2025-02-25 11:11:36,666][00253] Component RolloutWorker_w7 process died already! Don't wait for it. | |
| [2025-02-25 11:11:36,661][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-25 11:11:36,709][02495] Weights refcount: 2 0 | |
| [2025-02-25 11:11:36,712][00253] Component InferenceWorker_p0-w0 stopped! | |
| [2025-02-25 11:11:36,713][02495] Stopping InferenceWorker_p0-w0... | |
| [2025-02-25 11:11:36,714][02495] Loop inference_proc0-0_evt_loop terminating... | |
| [2025-02-25 11:11:36,785][02481] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000849_3477504.pth | |
| [2025-02-25 11:11:36,810][02481] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-25 11:11:36,983][00253] Component LearnerWorker_p0 stopped! | |
| [2025-02-25 11:11:36,984][02481] Stopping LearnerWorker_p0... | |
| [2025-02-25 11:11:36,985][02481] Loop learner_proc0_evt_loop terminating... | |
| [2025-02-25 11:11:37,017][02497] Stopping RolloutWorker_w2... | |
| [2025-02-25 11:11:37,017][00253] Component RolloutWorker_w2 stopped! | |
| [2025-02-25 11:11:37,019][00253] Component RolloutWorker_w3 stopped! | |
| [2025-02-25 11:11:37,020][02498] Stopping RolloutWorker_w3... | |
| [2025-02-25 11:11:37,021][02498] Loop rollout_proc3_evt_loop terminating... | |
| [2025-02-25 11:11:37,018][02497] Loop rollout_proc2_evt_loop terminating... | |
| [2025-02-25 11:11:37,035][02499] Stopping RolloutWorker_w4... | |
| [2025-02-25 11:11:37,035][00253] Component RolloutWorker_w4 stopped! | |
| [2025-02-25 11:11:37,044][02499] Loop rollout_proc4_evt_loop terminating... | |
| [2025-02-25 11:11:37,074][02501] Stopping RolloutWorker_w6... | |
| [2025-02-25 11:11:37,074][00253] Component RolloutWorker_w6 stopped! | |
| [2025-02-25 11:11:37,076][00253] Component RolloutWorker_w1 stopped! | |
| [2025-02-25 11:11:37,077][00253] Waiting for process learner_proc0 to stop... | |
| [2025-02-25 11:11:37,077][02496] Stopping RolloutWorker_w1... | |
| [2025-02-25 11:11:37,079][02496] Loop rollout_proc1_evt_loop terminating... | |
| [2025-02-25 11:11:37,088][02501] Loop rollout_proc6_evt_loop terminating... | |
| [2025-02-25 11:11:38,521][00253] Waiting for process inference_proc0-0 to join... | |
| [2025-02-25 11:11:38,522][00253] Waiting for process rollout_proc0 to join... | |
| [2025-02-25 11:11:38,524][00253] Waiting for process rollout_proc1 to join... | |
| [2025-02-25 11:11:39,586][00253] Waiting for process rollout_proc2 to join... | |
| [2025-02-25 11:11:39,725][00253] Waiting for process rollout_proc3 to join... | |
| [2025-02-25 11:11:39,730][00253] Waiting for process rollout_proc4 to join... | |
| [2025-02-25 11:11:39,731][00253] Waiting for process rollout_proc5 to join... | |
| [2025-02-25 11:11:39,733][00253] Waiting for process rollout_proc6 to join... | |
| [2025-02-25 11:11:39,734][00253] Waiting for process rollout_proc7 to join... | |
| [2025-02-25 11:11:39,736][00253] Batcher 0 profile tree view: | |
| batching: 23.1869, releasing_batches: 0.0259 | |
| [2025-02-25 11:11:39,739][00253] InferenceWorker_p0-w0 profile tree view: | |
| wait_policy: 0.0000 | |
| wait_policy_total: 416.6379 | |
| update_model: 9.2502 | |
| weight_update: 0.0021 | |
| one_step: 0.0038 | |
| handle_policy_step: 607.7302 | |
| deserialize: 14.5380, stack: 3.6101, obs_to_device_normalize: 135.5190, forward: 320.5610, send_messages: 22.6079 | |
| prepare_outputs: 85.0886 | |
| to_cpu: 53.3036 | |
| [2025-02-25 11:11:39,740][00253] Learner 0 profile tree view: | |
| misc: 0.0040, prepare_batch: 12.3533 | |
| train: 68.2608 | |
| epoch_init: 0.0049, minibatch_init: 0.0059, losses_postprocess: 0.6598, kl_divergence: 0.5074, after_optimizer: 32.7101 | |
| calculate_losses: 23.3576 | |
| losses_init: 0.0035, forward_head: 1.2904, bptt_initial: 15.7890, tail: 0.9865, advantages_returns: 0.2645, losses: 3.0385 | |
| bptt: 1.7456 | |
| bptt_forward_core: 1.6742 | |
| update: 10.4858 | |
| clip: 0.8527 | |
| [2025-02-25 11:11:39,741][00253] Loop Runner_EvtLoop terminating... | |
| [2025-02-25 11:11:39,741][00253] Runner profile tree view: | |
| main_loop: 1094.9160 | |
| [2025-02-25 11:11:39,742][00253] Collected {0: 4005888}, FPS: 3658.6 | |
| [2025-02-25 11:11:40,211][00253] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-25 11:11:40,212][00253] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-25 11:11:40,213][00253] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-25 11:11:40,215][00253] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-25 11:11:40,215][00253] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:11:40,216][00253] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-25 11:11:40,217][00253] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:11:40,218][00253] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-25 11:11:40,219][00253] Adding new argument 'push_to_hub'=False that is not in the saved config file! | |
| [2025-02-25 11:11:40,220][00253] Adding new argument 'hf_repository'=None that is not in the saved config file! | |
| [2025-02-25 11:11:40,221][00253] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-25 11:11:40,222][00253] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-25 11:11:40,223][00253] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-25 11:11:40,224][00253] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-25 11:11:40,225][00253] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-25 11:11:40,254][00253] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:11:40,257][00253] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 11:11:40,258][00253] RunningMeanStd input shape: (1,) | |
| [2025-02-25 11:11:40,271][00253] ConvEncoder: input_channels=3 | |
| [2025-02-25 11:11:40,369][00253] Conv encoder output size: 512 | |
| [2025-02-25 11:11:40,370][00253] Policy head output size: 512 | |
| [2025-02-25 11:11:40,546][00253] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-25 11:11:41,334][00253] Num frames 100... | |
| [2025-02-25 11:11:41,468][00253] Num frames 200... | |
| [2025-02-25 11:11:41,594][00253] Num frames 300... | |
| [2025-02-25 11:11:41,719][00253] Num frames 400... | |
| [2025-02-25 11:11:41,842][00253] Num frames 500... | |
| [2025-02-25 11:11:41,967][00253] Num frames 600... | |
| [2025-02-25 11:11:42,093][00253] Num frames 700... | |
| [2025-02-25 11:11:42,227][00253] Avg episode rewards: #0: 14.590, true rewards: #0: 7.590 | |
| [2025-02-25 11:11:42,228][00253] Avg episode reward: 14.590, avg true_objective: 7.590 | |
| [2025-02-25 11:11:42,282][00253] Num frames 800... | |
| [2025-02-25 11:11:42,437][00253] Num frames 900... | |
| [2025-02-25 11:11:42,570][00253] Num frames 1000... | |
| [2025-02-25 11:11:42,702][00253] Num frames 1100... | |
| [2025-02-25 11:11:42,831][00253] Num frames 1200... | |
| [2025-02-25 11:11:42,958][00253] Num frames 1300... | |
| [2025-02-25 11:11:43,083][00253] Num frames 1400... | |
| [2025-02-25 11:11:43,212][00253] Num frames 1500... | |
| [2025-02-25 11:11:43,340][00253] Num frames 1600... | |
| [2025-02-25 11:11:43,469][00253] Num frames 1700... | |
| [2025-02-25 11:11:43,606][00253] Num frames 1800... | |
| [2025-02-25 11:11:43,737][00253] Num frames 1900... | |
| [2025-02-25 11:11:43,862][00253] Num frames 2000... | |
| [2025-02-25 11:11:43,988][00253] Num frames 2100... | |
| [2025-02-25 11:11:44,073][00253] Avg episode rewards: #0: 24.620, true rewards: #0: 10.620 | |
| [2025-02-25 11:11:44,074][00253] Avg episode reward: 24.620, avg true_objective: 10.620 | |
| [2025-02-25 11:11:44,171][00253] Num frames 2200... | |
| [2025-02-25 11:11:44,296][00253] Num frames 2300... | |
| [2025-02-25 11:11:44,424][00253] Num frames 2400... | |
| [2025-02-25 11:11:44,560][00253] Num frames 2500... | |
| [2025-02-25 11:11:44,688][00253] Num frames 2600... | |
| [2025-02-25 11:11:44,814][00253] Num frames 2700... | |
| [2025-02-25 11:11:44,942][00253] Num frames 2800... | |
| [2025-02-25 11:11:45,067][00253] Num frames 2900... | |
| [2025-02-25 11:11:45,197][00253] Num frames 3000... | |
| [2025-02-25 11:11:45,377][00253] Num frames 3100... | |
| [2025-02-25 11:11:45,560][00253] Num frames 3200... | |
| [2025-02-25 11:11:45,728][00253] Num frames 3300... | |
| [2025-02-25 11:11:45,852][00253] Avg episode rewards: #0: 26.133, true rewards: #0: 11.133 | |
| [2025-02-25 11:11:45,853][00253] Avg episode reward: 26.133, avg true_objective: 11.133 | |
| [2025-02-25 11:11:45,955][00253] Num frames 3400... | |
| [2025-02-25 11:11:46,125][00253] Num frames 3500... | |
| [2025-02-25 11:11:46,293][00253] Num frames 3600... | |
| [2025-02-25 11:11:46,462][00253] Num frames 3700... | |
| [2025-02-25 11:11:46,648][00253] Num frames 3800... | |
| [2025-02-25 11:11:46,825][00253] Num frames 3900... | |
| [2025-02-25 11:11:47,001][00253] Num frames 4000... | |
| [2025-02-25 11:11:47,178][00253] Num frames 4100... | |
| [2025-02-25 11:11:47,338][00253] Num frames 4200... | |
| [2025-02-25 11:11:47,466][00253] Num frames 4300... | |
| [2025-02-25 11:11:47,594][00253] Num frames 4400... | |
| [2025-02-25 11:11:47,728][00253] Num frames 4500... | |
| [2025-02-25 11:11:47,855][00253] Num frames 4600... | |
| [2025-02-25 11:11:47,982][00253] Num frames 4700... | |
| [2025-02-25 11:11:48,108][00253] Num frames 4800... | |
| [2025-02-25 11:11:48,238][00253] Num frames 4900... | |
| [2025-02-25 11:11:48,368][00253] Num frames 5000... | |
| [2025-02-25 11:11:48,431][00253] Avg episode rewards: #0: 31.012, true rewards: #0: 12.512 | |
| [2025-02-25 11:11:48,432][00253] Avg episode reward: 31.012, avg true_objective: 12.512 | |
| [2025-02-25 11:11:48,552][00253] Num frames 5100... | |
| [2025-02-25 11:11:48,686][00253] Num frames 5200... | |
| [2025-02-25 11:11:48,811][00253] Num frames 5300... | |
| [2025-02-25 11:11:48,938][00253] Num frames 5400... | |
| [2025-02-25 11:11:49,063][00253] Num frames 5500... | |
| [2025-02-25 11:11:49,195][00253] Num frames 5600... | |
| [2025-02-25 11:11:49,321][00253] Num frames 5700... | |
| [2025-02-25 11:11:49,448][00253] Num frames 5800... | |
| [2025-02-25 11:11:49,603][00253] Avg episode rewards: #0: 28.360, true rewards: #0: 11.760 | |
| [2025-02-25 11:11:49,603][00253] Avg episode reward: 28.360, avg true_objective: 11.760 | |
| [2025-02-25 11:11:49,630][00253] Num frames 5900... | |
| [2025-02-25 11:11:49,768][00253] Num frames 6000... | |
| [2025-02-25 11:11:49,896][00253] Num frames 6100... | |
| [2025-02-25 11:11:50,022][00253] Num frames 6200... | |
| [2025-02-25 11:11:50,147][00253] Num frames 6300... | |
| [2025-02-25 11:11:50,276][00253] Num frames 6400... | |
| [2025-02-25 11:11:50,406][00253] Num frames 6500... | |
| [2025-02-25 11:11:50,533][00253] Num frames 6600... | |
| [2025-02-25 11:11:50,609][00253] Avg episode rewards: #0: 26.693, true rewards: #0: 11.027 | |
| [2025-02-25 11:11:50,610][00253] Avg episode reward: 26.693, avg true_objective: 11.027 | |
| [2025-02-25 11:11:50,728][00253] Num frames 6700... | |
| [2025-02-25 11:11:50,855][00253] Num frames 6800... | |
| [2025-02-25 11:11:50,983][00253] Num frames 6900... | |
| [2025-02-25 11:11:51,118][00253] Num frames 7000... | |
| [2025-02-25 11:11:51,256][00253] Num frames 7100... | |
| [2025-02-25 11:11:51,386][00253] Num frames 7200... | |
| [2025-02-25 11:11:51,516][00253] Num frames 7300... | |
| [2025-02-25 11:11:51,647][00253] Num frames 7400... | |
| [2025-02-25 11:11:51,785][00253] Num frames 7500... | |
| [2025-02-25 11:11:51,914][00253] Num frames 7600... | |
| [2025-02-25 11:11:52,040][00253] Num frames 7700... | |
| [2025-02-25 11:11:52,171][00253] Num frames 7800... | |
| [2025-02-25 11:11:52,298][00253] Num frames 7900... | |
| [2025-02-25 11:11:52,427][00253] Num frames 8000... | |
| [2025-02-25 11:11:52,558][00253] Num frames 8100... | |
| [2025-02-25 11:11:52,690][00253] Num frames 8200... | |
| [2025-02-25 11:11:52,825][00253] Num frames 8300... | |
| [2025-02-25 11:11:52,952][00253] Num frames 8400... | |
| [2025-02-25 11:11:53,083][00253] Num frames 8500... | |
| [2025-02-25 11:11:53,212][00253] Num frames 8600... | |
| [2025-02-25 11:11:53,341][00253] Num frames 8700... | |
| [2025-02-25 11:11:53,417][00253] Avg episode rewards: #0: 32.308, true rewards: #0: 12.451 | |
| [2025-02-25 11:11:53,418][00253] Avg episode reward: 32.308, avg true_objective: 12.451 | |
| [2025-02-25 11:11:53,525][00253] Num frames 8800... | |
| [2025-02-25 11:11:53,656][00253] Num frames 8900... | |
| [2025-02-25 11:11:53,790][00253] Num frames 9000... | |
| [2025-02-25 11:11:53,918][00253] Num frames 9100... | |
| [2025-02-25 11:11:54,044][00253] Num frames 9200... | |
| [2025-02-25 11:11:54,171][00253] Num frames 9300... | |
| [2025-02-25 11:11:54,298][00253] Num frames 9400... | |
| [2025-02-25 11:11:54,418][00253] Avg episode rewards: #0: 30.065, true rewards: #0: 11.815 | |
| [2025-02-25 11:11:54,419][00253] Avg episode reward: 30.065, avg true_objective: 11.815 | |
| [2025-02-25 11:11:54,480][00253] Num frames 9500... | |
| [2025-02-25 11:11:54,608][00253] Num frames 9600... | |
| [2025-02-25 11:11:54,738][00253] Num frames 9700... | |
| [2025-02-25 11:11:54,872][00253] Num frames 9800... | |
| [2025-02-25 11:11:54,974][00253] Avg episode rewards: #0: 27.151, true rewards: #0: 10.929 | |
| [2025-02-25 11:11:54,975][00253] Avg episode reward: 27.151, avg true_objective: 10.929 | |
| [2025-02-25 11:11:55,059][00253] Num frames 9900... | |
| [2025-02-25 11:11:55,190][00253] Num frames 10000... | |
| [2025-02-25 11:11:55,319][00253] Num frames 10100... | |
| [2025-02-25 11:11:55,448][00253] Num frames 10200... | |
| [2025-02-25 11:11:55,581][00253] Num frames 10300... | |
| [2025-02-25 11:11:55,715][00253] Num frames 10400... | |
| [2025-02-25 11:11:55,848][00253] Num frames 10500... | |
| [2025-02-25 11:11:55,975][00253] Num frames 10600... | |
| [2025-02-25 11:11:56,108][00253] Num frames 10700... | |
| [2025-02-25 11:11:56,236][00253] Num frames 10800... | |
| [2025-02-25 11:11:56,365][00253] Num frames 10900... | |
| [2025-02-25 11:11:56,492][00253] Num frames 11000... | |
| [2025-02-25 11:11:56,621][00253] Num frames 11100... | |
| [2025-02-25 11:11:56,761][00253] Num frames 11200... | |
| [2025-02-25 11:11:56,899][00253] Num frames 11300... | |
| [2025-02-25 11:11:57,029][00253] Num frames 11400... | |
| [2025-02-25 11:11:57,158][00253] Num frames 11500... | |
| [2025-02-25 11:11:57,294][00253] Num frames 11600... | |
| [2025-02-25 11:11:57,482][00253] Num frames 11700... | |
| [2025-02-25 11:11:57,698][00253] Avg episode rewards: #0: 30.292, true rewards: #0: 11.792 | |
| [2025-02-25 11:11:57,699][00253] Avg episode reward: 30.292, avg true_objective: 11.792 | |
| [2025-02-25 11:13:08,395][00253] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |
| [2025-02-25 11:39:47,991][00253] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-25 11:39:47,992][00253] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-25 11:39:47,993][00253] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-25 11:39:47,993][00253] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-25 11:39:47,994][00253] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:39:47,995][00253] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-25 11:39:47,996][00253] Adding new argument 'max_num_frames'=100000 that is not in the saved config file! | |
| [2025-02-25 11:39:47,997][00253] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-25 11:39:47,998][00253] Adding new argument 'push_to_hub'=True that is not in the saved config file! | |
| [2025-02-25 11:39:47,998][00253] Adding new argument 'hf_repository'='sidsriv/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file! | |
| [2025-02-25 11:39:47,999][00253] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-25 11:39:48,000][00253] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-25 11:39:48,001][00253] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-25 11:39:48,002][00253] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-25 11:39:48,003][00253] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-25 11:39:48,029][00253] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 11:39:48,030][00253] RunningMeanStd input shape: (1,) | |
| [2025-02-25 11:39:48,041][00253] ConvEncoder: input_channels=3 | |
| [2025-02-25 11:39:48,074][00253] Conv encoder output size: 512 | |
| [2025-02-25 11:39:48,075][00253] Policy head output size: 512 | |
| [2025-02-25 11:39:48,092][00253] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-25 11:39:48,521][00253] Num frames 100... | |
| [2025-02-25 11:39:48,658][00253] Num frames 200... | |
| [2025-02-25 11:39:48,790][00253] Num frames 300... | |
| [2025-02-25 11:39:48,914][00253] Num frames 400... | |
| [2025-02-25 11:39:49,070][00253] Avg episode rewards: #0: 7.800, true rewards: #0: 4.800 | |
| [2025-02-25 11:39:49,071][00253] Avg episode reward: 7.800, avg true_objective: 4.800 | |
| [2025-02-25 11:39:49,099][00253] Num frames 500... | |
| [2025-02-25 11:39:49,225][00253] Num frames 600... | |
| [2025-02-25 11:39:49,354][00253] Num frames 700... | |
| [2025-02-25 11:39:49,480][00253] Num frames 800... | |
| [2025-02-25 11:39:49,609][00253] Num frames 900... | |
| [2025-02-25 11:39:49,744][00253] Num frames 1000... | |
| [2025-02-25 11:39:49,875][00253] Num frames 1100... | |
| [2025-02-25 11:39:50,004][00253] Num frames 1200... | |
| [2025-02-25 11:39:50,129][00253] Num frames 1300... | |
| [2025-02-25 11:39:50,258][00253] Num frames 1400... | |
| [2025-02-25 11:39:50,385][00253] Num frames 1500... | |
| [2025-02-25 11:39:50,515][00253] Num frames 1600... | |
| [2025-02-25 11:39:50,644][00253] Num frames 1700... | |
| [2025-02-25 11:39:50,835][00253] Avg episode rewards: #0: 23.490, true rewards: #0: 8.990 | |
| [2025-02-25 11:39:50,836][00253] Avg episode reward: 23.490, avg true_objective: 8.990 | |
| [2025-02-25 11:39:50,841][00253] Num frames 1800... | |
| [2025-02-25 11:39:50,967][00253] Num frames 1900... | |
| [2025-02-25 11:39:51,095][00253] Num frames 2000... | |
| [2025-02-25 11:39:51,225][00253] Num frames 2100... | |
| [2025-02-25 11:39:51,357][00253] Num frames 2200... | |
| [2025-02-25 11:39:51,488][00253] Num frames 2300... | |
| [2025-02-25 11:39:51,627][00253] Num frames 2400... | |
| [2025-02-25 11:39:51,769][00253] Num frames 2500... | |
| [2025-02-25 11:39:51,897][00253] Num frames 2600... | |
| [2025-02-25 11:39:52,026][00253] Num frames 2700... | |
| [2025-02-25 11:39:52,157][00253] Num frames 2800... | |
| [2025-02-25 11:39:52,288][00253] Num frames 2900... | |
| [2025-02-25 11:39:52,413][00253] Num frames 3000... | |
| [2025-02-25 11:39:52,540][00253] Num frames 3100... | |
| [2025-02-25 11:39:52,671][00253] Num frames 3200... | |
| [2025-02-25 11:39:52,804][00253] Num frames 3300... | |
| [2025-02-25 11:39:52,935][00253] Num frames 3400... | |
| [2025-02-25 11:39:53,062][00253] Num frames 3500... | |
| [2025-02-25 11:39:53,190][00253] Num frames 3600... | |
| [2025-02-25 11:39:53,317][00253] Avg episode rewards: #0: 31.180, true rewards: #0: 12.180 | |
| [2025-02-25 11:39:53,318][00253] Avg episode reward: 31.180, avg true_objective: 12.180 | |
| [2025-02-25 11:39:53,377][00253] Num frames 3700... | |
| [2025-02-25 11:39:53,501][00253] Num frames 3800... | |
| [2025-02-25 11:39:53,627][00253] Num frames 3900... | |
| [2025-02-25 11:39:53,757][00253] Num frames 4000... | |
| [2025-02-25 11:39:53,886][00253] Num frames 4100... | |
| [2025-02-25 11:39:54,010][00253] Num frames 4200... | |
| [2025-02-25 11:39:54,144][00253] Avg episode rewards: #0: 26.155, true rewards: #0: 10.655 | |
| [2025-02-25 11:39:54,145][00253] Avg episode reward: 26.155, avg true_objective: 10.655 | |
| [2025-02-25 11:39:54,193][00253] Num frames 4300... | |
| [2025-02-25 11:39:54,318][00253] Num frames 4400... | |
| [2025-02-25 11:39:54,446][00253] Num frames 4500... | |
| [2025-02-25 11:39:54,571][00253] Num frames 4600... | |
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| [2025-02-25 11:39:54,835][00253] Num frames 4800... | |
| [2025-02-25 11:39:54,957][00253] Num frames 4900... | |
| [2025-02-25 11:39:55,081][00253] Num frames 5000... | |
| [2025-02-25 11:39:55,206][00253] Num frames 5100... | |
| [2025-02-25 11:39:55,336][00253] Num frames 5200... | |
| [2025-02-25 11:39:55,463][00253] Avg episode rewards: #0: 25.108, true rewards: #0: 10.508 | |
| [2025-02-25 11:39:55,464][00253] Avg episode reward: 25.108, avg true_objective: 10.508 | |
| [2025-02-25 11:39:55,528][00253] Num frames 5300... | |
| [2025-02-25 11:39:55,693][00253] Avg episode rewards: #0: 21.137, true rewards: #0: 8.970 | |
| [2025-02-25 11:39:55,694][00253] Avg episode reward: 21.137, avg true_objective: 8.970 | |
| [2025-02-25 11:39:55,720][00253] Num frames 5400... | |
| [2025-02-25 11:39:55,857][00253] Num frames 5500... | |
| [2025-02-25 11:39:55,988][00253] Num frames 5600... | |
| [2025-02-25 11:39:56,130][00253] Num frames 5700... | |
| [2025-02-25 11:39:56,309][00253] Num frames 5800... | |
| [2025-02-25 11:39:56,476][00253] Num frames 5900... | |
| [2025-02-25 11:39:56,656][00253] Num frames 6000... | |
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| [2025-02-25 11:39:56,996][00253] Num frames 6200... | |
| [2025-02-25 11:39:57,166][00253] Num frames 6300... | |
| [2025-02-25 11:39:57,333][00253] Num frames 6400... | |
| [2025-02-25 11:39:57,506][00253] Num frames 6500... | |
| [2025-02-25 11:39:57,604][00253] Avg episode rewards: #0: 22.744, true rewards: #0: 9.316 | |
| [2025-02-25 11:39:57,605][00253] Avg episode reward: 22.744, avg true_objective: 9.316 | |
| [2025-02-25 11:39:57,748][00253] Num frames 6600... | |
| [2025-02-25 11:39:57,930][00253] Num frames 6700... | |
| [2025-02-25 11:39:58,119][00253] Num frames 6800... | |
| [2025-02-25 11:39:58,295][00253] Num frames 6900... | |
| [2025-02-25 11:39:58,425][00253] Num frames 7000... | |
| [2025-02-25 11:39:58,553][00253] Num frames 7100... | |
| [2025-02-25 11:39:58,688][00253] Num frames 7200... | |
| [2025-02-25 11:39:58,816][00253] Num frames 7300... | |
| [2025-02-25 11:39:58,947][00253] Num frames 7400... | |
| [2025-02-25 11:39:59,074][00253] Num frames 7500... | |
| [2025-02-25 11:39:59,146][00253] Avg episode rewards: #0: 22.266, true rewards: #0: 9.391 | |
| [2025-02-25 11:39:59,147][00253] Avg episode reward: 22.266, avg true_objective: 9.391 | |
| [2025-02-25 11:39:59,261][00253] Num frames 7600... | |
| [2025-02-25 11:39:59,389][00253] Num frames 7700... | |
| [2025-02-25 11:39:59,515][00253] Num frames 7800... | |
| [2025-02-25 11:39:59,647][00253] Num frames 7900... | |
| [2025-02-25 11:39:59,774][00253] Num frames 8000... | |
| [2025-02-25 11:39:59,899][00253] Num frames 8100... | |
| [2025-02-25 11:40:00,031][00253] Num frames 8200... | |
| [2025-02-25 11:40:00,165][00253] Num frames 8300... | |
| [2025-02-25 11:40:00,294][00253] Num frames 8400... | |
| [2025-02-25 11:40:00,372][00253] Avg episode rewards: #0: 22.353, true rewards: #0: 9.353 | |
| [2025-02-25 11:40:00,372][00253] Avg episode reward: 22.353, avg true_objective: 9.353 | |
| [2025-02-25 11:40:00,478][00253] Num frames 8500... | |
| [2025-02-25 11:40:00,611][00253] Num frames 8600... | |
| [2025-02-25 11:40:00,746][00253] Num frames 8700... | |
| [2025-02-25 11:40:00,878][00253] Num frames 8800... | |
| [2025-02-25 11:40:01,016][00253] Num frames 8900... | |
| [2025-02-25 11:40:01,144][00253] Num frames 9000... | |
| [2025-02-25 11:40:01,274][00253] Num frames 9100... | |
| [2025-02-25 11:40:01,406][00253] Num frames 9200... | |
| [2025-02-25 11:40:01,541][00253] Num frames 9300... | |
| [2025-02-25 11:40:01,672][00253] Num frames 9400... | |
| [2025-02-25 11:40:01,800][00253] Num frames 9500... | |
| [2025-02-25 11:40:01,928][00253] Num frames 9600... | |
| [2025-02-25 11:40:02,065][00253] Num frames 9700... | |
| [2025-02-25 11:40:02,191][00253] Num frames 9800... | |
| [2025-02-25 11:40:02,321][00253] Num frames 9900... | |
| [2025-02-25 11:40:02,448][00253] Num frames 10000... | |
| [2025-02-25 11:40:02,580][00253] Num frames 10100... | |
| [2025-02-25 11:40:02,710][00253] Num frames 10200... | |
| [2025-02-25 11:40:02,838][00253] Num frames 10300... | |
| [2025-02-25 11:40:02,964][00253] Num frames 10400... | |
| [2025-02-25 11:40:03,100][00253] Num frames 10500... | |
| [2025-02-25 11:40:03,179][00253] Avg episode rewards: #0: 25.618, true rewards: #0: 10.518 | |
| [2025-02-25 11:40:03,180][00253] Avg episode reward: 25.618, avg true_objective: 10.518 | |
| [2025-02-25 11:41:07,981][00253] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |
| [2025-02-25 11:41:16,978][00253] The model has been pushed to https://huggingface.co/sidsriv/rl_course_vizdoom_health_gathering_supreme | |
| [2025-02-25 11:42:22,274][00253] Loading legacy config file train_dir/doom_health_gathering_supreme_2222/cfg.json instead of train_dir/doom_health_gathering_supreme_2222/config.json | |
| [2025-02-25 11:42:22,276][00253] Loading existing experiment configuration from train_dir/doom_health_gathering_supreme_2222/config.json | |
| [2025-02-25 11:42:22,277][00253] Overriding arg 'experiment' with value 'doom_health_gathering_supreme_2222' passed from command line | |
| [2025-02-25 11:42:22,279][00253] Overriding arg 'train_dir' with value 'train_dir' passed from command line | |
| [2025-02-25 11:42:22,280][00253] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-25 11:42:22,280][00253] Adding new argument 'lr_adaptive_min'=1e-06 that is not in the saved config file! | |
| [2025-02-25 11:42:22,282][00253] Adding new argument 'lr_adaptive_max'=0.01 that is not in the saved config file! | |
| [2025-02-25 11:42:22,283][00253] Adding new argument 'env_gpu_observations'=True that is not in the saved config file! | |
| [2025-02-25 11:42:22,284][00253] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-25 11:42:22,286][00253] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-25 11:42:22,287][00253] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:42:22,287][00253] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-25 11:42:22,288][00253] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:42:22,290][00253] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-25 11:42:22,291][00253] Adding new argument 'push_to_hub'=False that is not in the saved config file! | |
| [2025-02-25 11:42:22,291][00253] Adding new argument 'hf_repository'=None that is not in the saved config file! | |
| [2025-02-25 11:42:22,294][00253] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-25 11:42:22,294][00253] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-25 11:42:22,295][00253] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-25 11:42:22,298][00253] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-25 11:42:22,299][00253] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-25 11:42:22,340][00253] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 11:42:22,342][00253] RunningMeanStd input shape: (1,) | |
| [2025-02-25 11:42:22,357][00253] ConvEncoder: input_channels=3 | |
| [2025-02-25 11:42:22,422][00253] Conv encoder output size: 512 | |
| [2025-02-25 11:42:22,423][00253] Policy head output size: 512 | |
| [2025-02-25 11:42:22,456][00253] Loading state from checkpoint train_dir/doom_health_gathering_supreme_2222/checkpoint_p0/checkpoint_000539850_4422451200.pth... | |
| [2025-02-25 11:42:23,143][00253] Num frames 100... | |
| [2025-02-25 11:42:23,333][00253] Num frames 200... | |
| [2025-02-25 11:42:23,463][00253] Num frames 300... | |
| [2025-02-25 11:42:23,590][00253] Num frames 400... | |
| [2025-02-25 11:42:23,733][00253] Num frames 500... | |
| [2025-02-25 11:42:23,863][00253] Num frames 600... | |
| [2025-02-25 11:42:23,997][00253] Num frames 700... | |
| [2025-02-25 11:42:24,124][00253] Num frames 800... | |
| [2025-02-25 11:42:24,251][00253] Num frames 900... | |
| [2025-02-25 11:42:24,380][00253] Num frames 1000... | |
| [2025-02-25 11:42:24,512][00253] Num frames 1100... | |
| [2025-02-25 11:42:24,641][00253] Num frames 1200... | |
| [2025-02-25 11:42:24,774][00253] Num frames 1300... | |
| [2025-02-25 11:42:24,900][00253] Num frames 1400... | |
| [2025-02-25 11:42:25,038][00253] Num frames 1500... | |
| [2025-02-25 11:42:25,165][00253] Num frames 1600... | |
| [2025-02-25 11:42:25,295][00253] Num frames 1700... | |
| [2025-02-25 11:42:25,423][00253] Num frames 1800... | |
| [2025-02-25 11:42:25,550][00253] Num frames 1900... | |
| [2025-02-25 11:42:25,687][00253] Num frames 2000... | |
| [2025-02-25 11:42:25,822][00253] Num frames 2100... | |
| [2025-02-25 11:42:25,874][00253] Avg episode rewards: #0: 67.999, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:25,875][00253] Avg episode reward: 67.999, avg true_objective: 21.000 | |
| [2025-02-25 11:42:26,004][00253] Num frames 2200... | |
| [2025-02-25 11:42:26,139][00253] Num frames 2300... | |
| [2025-02-25 11:42:26,270][00253] Num frames 2400... | |
| [2025-02-25 11:42:26,396][00253] Num frames 2500... | |
| [2025-02-25 11:42:26,524][00253] Num frames 2600... | |
| [2025-02-25 11:42:26,656][00253] Num frames 2700... | |
| [2025-02-25 11:42:26,786][00253] Num frames 2800... | |
| [2025-02-25 11:42:26,912][00253] Num frames 2900... | |
| [2025-02-25 11:42:27,042][00253] Num frames 3000... | |
| [2025-02-25 11:42:27,183][00253] Num frames 3100... | |
| [2025-02-25 11:42:27,318][00253] Num frames 3200... | |
| [2025-02-25 11:42:27,446][00253] Num frames 3300... | |
| [2025-02-25 11:42:27,574][00253] Num frames 3400... | |
| [2025-02-25 11:42:27,702][00253] Num frames 3500... | |
| [2025-02-25 11:42:27,830][00253] Num frames 3600... | |
| [2025-02-25 11:42:27,961][00253] Num frames 3700... | |
| [2025-02-25 11:42:28,101][00253] Num frames 3800... | |
| [2025-02-25 11:42:28,228][00253] Num frames 3900... | |
| [2025-02-25 11:42:28,359][00253] Num frames 4000... | |
| [2025-02-25 11:42:28,488][00253] Num frames 4100... | |
| [2025-02-25 11:42:28,618][00253] Num frames 4200... | |
| [2025-02-25 11:42:28,670][00253] Avg episode rewards: #0: 67.499, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:28,671][00253] Avg episode reward: 67.499, avg true_objective: 21.000 | |
| [2025-02-25 11:42:28,806][00253] Num frames 4300... | |
| [2025-02-25 11:42:28,937][00253] Num frames 4400... | |
| [2025-02-25 11:42:29,064][00253] Num frames 4500... | |
| [2025-02-25 11:42:29,200][00253] Num frames 4600... | |
| [2025-02-25 11:42:29,333][00253] Num frames 4700... | |
| [2025-02-25 11:42:29,466][00253] Num frames 4800... | |
| [2025-02-25 11:42:29,602][00253] Num frames 4900... | |
| [2025-02-25 11:42:29,749][00253] Num frames 5000... | |
| [2025-02-25 11:42:29,896][00253] Num frames 5100... | |
| [2025-02-25 11:42:30,024][00253] Num frames 5200... | |
| [2025-02-25 11:42:30,161][00253] Num frames 5300... | |
| [2025-02-25 11:42:30,291][00253] Num frames 5400... | |
| [2025-02-25 11:42:30,420][00253] Num frames 5500... | |
| [2025-02-25 11:42:30,547][00253] Num frames 5600... | |
| [2025-02-25 11:42:30,682][00253] Num frames 5700... | |
| [2025-02-25 11:42:30,813][00253] Num frames 5800... | |
| [2025-02-25 11:42:30,943][00253] Num frames 5900... | |
| [2025-02-25 11:42:31,074][00253] Num frames 6000... | |
| [2025-02-25 11:42:31,214][00253] Num frames 6100... | |
| [2025-02-25 11:42:31,352][00253] Num frames 6200... | |
| [2025-02-25 11:42:31,487][00253] Num frames 6300... | |
| [2025-02-25 11:42:31,539][00253] Avg episode rewards: #0: 67.332, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:31,540][00253] Avg episode reward: 67.332, avg true_objective: 21.000 | |
| [2025-02-25 11:42:31,672][00253] Num frames 6400... | |
| [2025-02-25 11:42:31,802][00253] Num frames 6500... | |
| [2025-02-25 11:42:31,931][00253] Num frames 6600... | |
| [2025-02-25 11:42:32,061][00253] Num frames 6700... | |
| [2025-02-25 11:42:32,199][00253] Num frames 6800... | |
| [2025-02-25 11:42:32,336][00253] Num frames 6900... | |
| [2025-02-25 11:42:32,484][00253] Num frames 7000... | |
| [2025-02-25 11:42:32,625][00253] Num frames 7100... | |
| [2025-02-25 11:42:32,755][00253] Num frames 7200... | |
| [2025-02-25 11:42:32,882][00253] Num frames 7300... | |
| [2025-02-25 11:42:33,022][00253] Num frames 7400... | |
| [2025-02-25 11:42:33,167][00253] Num frames 7500... | |
| [2025-02-25 11:42:33,310][00253] Num frames 7600... | |
| [2025-02-25 11:42:33,490][00253] Num frames 7700... | |
| [2025-02-25 11:42:33,666][00253] Num frames 7800... | |
| [2025-02-25 11:42:33,838][00253] Num frames 7900... | |
| [2025-02-25 11:42:34,012][00253] Num frames 8000... | |
| [2025-02-25 11:42:34,180][00253] Num frames 8100... | |
| [2025-02-25 11:42:34,359][00253] Num frames 8200... | |
| [2025-02-25 11:42:34,530][00253] Num frames 8300... | |
| [2025-02-25 11:42:34,715][00253] Num frames 8400... | |
| [2025-02-25 11:42:34,769][00253] Avg episode rewards: #0: 66.999, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:34,771][00253] Avg episode reward: 66.999, avg true_objective: 21.000 | |
| [2025-02-25 11:42:34,950][00253] Num frames 8500... | |
| [2025-02-25 11:42:35,127][00253] Num frames 8600... | |
| [2025-02-25 11:42:35,317][00253] Num frames 8700... | |
| [2025-02-25 11:42:35,495][00253] Num frames 8800... | |
| [2025-02-25 11:42:35,623][00253] Num frames 8900... | |
| [2025-02-25 11:42:35,766][00253] Num frames 9000... | |
| [2025-02-25 11:42:35,894][00253] Num frames 9100... | |
| [2025-02-25 11:42:36,023][00253] Num frames 9200... | |
| [2025-02-25 11:42:36,154][00253] Num frames 9300... | |
| [2025-02-25 11:42:36,284][00253] Num frames 9400... | |
| [2025-02-25 11:42:36,419][00253] Num frames 9500... | |
| [2025-02-25 11:42:36,547][00253] Num frames 9600... | |
| [2025-02-25 11:42:36,679][00253] Num frames 9700... | |
| [2025-02-25 11:42:36,812][00253] Num frames 9800... | |
| [2025-02-25 11:42:36,940][00253] Num frames 9900... | |
| [2025-02-25 11:42:37,069][00253] Num frames 10000... | |
| [2025-02-25 11:42:37,202][00253] Num frames 10100... | |
| [2025-02-25 11:42:37,334][00253] Num frames 10200... | |
| [2025-02-25 11:42:37,472][00253] Num frames 10300... | |
| [2025-02-25 11:42:37,603][00253] Num frames 10400... | |
| [2025-02-25 11:42:37,737][00253] Num frames 10500... | |
| [2025-02-25 11:42:37,790][00253] Avg episode rewards: #0: 65.399, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:37,790][00253] Avg episode reward: 65.399, avg true_objective: 21.000 | |
| [2025-02-25 11:42:37,919][00253] Num frames 10600... | |
| [2025-02-25 11:42:38,047][00253] Num frames 10700... | |
| [2025-02-25 11:42:38,177][00253] Num frames 10800... | |
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| [2025-02-25 11:42:40,583][00253] Num frames 12600... | |
| [2025-02-25 11:42:40,634][00253] Avg episode rewards: #0: 65.332, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:40,635][00253] Avg episode reward: 65.332, avg true_objective: 21.000 | |
| [2025-02-25 11:42:40,776][00253] Num frames 12700... | |
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| [2025-02-25 11:42:43,390][00253] Num frames 14700... | |
| [2025-02-25 11:42:43,442][00253] Avg episode rewards: #0: 65.856, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:43,443][00253] Avg episode reward: 65.856, avg true_objective: 21.000 | |
| [2025-02-25 11:42:43,582][00253] Num frames 14800... | |
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| [2025-02-25 11:42:46,554][00253] Avg episode rewards: #0: 65.124, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:46,555][00253] Avg episode reward: 65.124, avg true_objective: 21.000 | |
| [2025-02-25 11:42:46,749][00253] Num frames 16900... | |
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| [2025-02-25 11:42:49,637][00253] Num frames 18900... | |
| [2025-02-25 11:42:49,689][00253] Avg episode rewards: #0: 65.110, true rewards: #0: 21.000 | |
| [2025-02-25 11:42:49,690][00253] Avg episode reward: 65.110, avg true_objective: 21.000 | |
| [2025-02-25 11:42:49,824][00253] Num frames 19000... | |
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| [2025-02-25 11:42:51,003][00253] Num frames 19900... | |
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| [2025-02-25 11:42:51,260][00253] Num frames 20100... | |
| [2025-02-25 11:42:51,356][00253] Avg episode rewards: #0: 62.131, true rewards: #0: 20.132 | |
| [2025-02-25 11:42:51,357][00253] Avg episode reward: 62.131, avg true_objective: 20.132 | |
| [2025-02-25 11:44:51,551][00253] Replay video saved to train_dir/doom_health_gathering_supreme_2222/replay.mp4! | |
| [2025-02-25 11:45:50,351][00253] Environment doom_basic already registered, overwriting... | |
| [2025-02-25 11:45:50,353][00253] Environment doom_two_colors_easy already registered, overwriting... | |
| [2025-02-25 11:45:50,353][00253] Environment doom_two_colors_hard already registered, overwriting... | |
| [2025-02-25 11:45:50,354][00253] Environment doom_dm already registered, overwriting... | |
| [2025-02-25 11:45:50,355][00253] Environment doom_dwango5 already registered, overwriting... | |
| [2025-02-25 11:45:50,356][00253] Environment doom_my_way_home_flat_actions already registered, overwriting... | |
| [2025-02-25 11:45:50,356][00253] Environment doom_defend_the_center_flat_actions already registered, overwriting... | |
| [2025-02-25 11:45:50,359][00253] Environment doom_my_way_home already registered, overwriting... | |
| [2025-02-25 11:45:50,360][00253] Environment doom_deadly_corridor already registered, overwriting... | |
| [2025-02-25 11:45:50,361][00253] Environment doom_defend_the_center already registered, overwriting... | |
| [2025-02-25 11:45:50,361][00253] Environment doom_defend_the_line already registered, overwriting... | |
| [2025-02-25 11:45:50,363][00253] Environment doom_health_gathering already registered, overwriting... | |
| [2025-02-25 11:45:50,364][00253] Environment doom_health_gathering_supreme already registered, overwriting... | |
| [2025-02-25 11:45:50,365][00253] Environment doom_battle already registered, overwriting... | |
| [2025-02-25 11:45:50,366][00253] Environment doom_battle2 already registered, overwriting... | |
| [2025-02-25 11:45:50,367][00253] Environment doom_duel_bots already registered, overwriting... | |
| [2025-02-25 11:45:50,368][00253] Environment doom_deathmatch_bots already registered, overwriting... | |
| [2025-02-25 11:45:50,369][00253] Environment doom_duel already registered, overwriting... | |
| [2025-02-25 11:45:50,370][00253] Environment doom_deathmatch_full already registered, overwriting... | |
| [2025-02-25 11:45:50,372][00253] Environment doom_benchmark already registered, overwriting... | |
| [2025-02-25 11:45:50,372][00253] register_encoder_factory: <function make_vizdoom_encoder at 0x78731f77e0c0> | |
| [2025-02-25 11:46:37,319][00253] Environment doom_basic already registered, overwriting... | |
| [2025-02-25 11:46:37,320][00253] Environment doom_two_colors_easy already registered, overwriting... | |
| [2025-02-25 11:46:37,321][00253] Environment doom_two_colors_hard already registered, overwriting... | |
| [2025-02-25 11:46:37,322][00253] Environment doom_dm already registered, overwriting... | |
| [2025-02-25 11:46:37,323][00253] Environment doom_dwango5 already registered, overwriting... | |
| [2025-02-25 11:46:37,324][00253] Environment doom_my_way_home_flat_actions already registered, overwriting... | |
| [2025-02-25 11:46:37,324][00253] Environment doom_defend_the_center_flat_actions already registered, overwriting... | |
| [2025-02-25 11:46:37,325][00253] Environment doom_my_way_home already registered, overwriting... | |
| [2025-02-25 11:46:37,326][00253] Environment doom_deadly_corridor already registered, overwriting... | |
| [2025-02-25 11:46:37,327][00253] Environment doom_defend_the_center already registered, overwriting... | |
| [2025-02-25 11:46:37,327][00253] Environment doom_defend_the_line already registered, overwriting... | |
| [2025-02-25 11:46:37,328][00253] Environment doom_health_gathering already registered, overwriting... | |
| [2025-02-25 11:46:37,329][00253] Environment doom_health_gathering_supreme already registered, overwriting... | |
| [2025-02-25 11:46:37,330][00253] Environment doom_battle already registered, overwriting... | |
| [2025-02-25 11:46:37,331][00253] Environment doom_battle2 already registered, overwriting... | |
| [2025-02-25 11:46:37,332][00253] Environment doom_duel_bots already registered, overwriting... | |
| [2025-02-25 11:46:37,333][00253] Environment doom_deathmatch_bots already registered, overwriting... | |
| [2025-02-25 11:46:37,334][00253] Environment doom_duel already registered, overwriting... | |
| [2025-02-25 11:46:37,334][00253] Environment doom_deathmatch_full already registered, overwriting... | |
| [2025-02-25 11:46:37,335][00253] Environment doom_benchmark already registered, overwriting... | |
| [2025-02-25 11:46:37,336][00253] register_encoder_factory: <function make_vizdoom_encoder at 0x78731f77e0c0> | |
| [2025-02-25 11:46:37,349][00253] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-25 11:46:37,351][00253] Overriding arg 'train_for_env_steps' with value 5000000 passed from command line | |
| [2025-02-25 11:46:37,357][00253] Experiment dir /content/train_dir/default_experiment already exists! | |
| [2025-02-25 11:46:37,358][00253] Resuming existing experiment from /content/train_dir/default_experiment... | |
| [2025-02-25 11:46:37,359][00253] Weights and Biases integration disabled | |
| [2025-02-25 11:46:37,362][00253] Environment var CUDA_VISIBLE_DEVICES is 0 | |
| [2025-02-25 11:46:39,467][00253] Starting experiment with the following configuration: | |
| help=False | |
| algo=APPO | |
| env=doom_health_gathering_supreme | |
| experiment=default_experiment | |
| train_dir=/content/train_dir | |
| restart_behavior=resume | |
| device=gpu | |
| seed=None | |
| num_policies=1 | |
| async_rl=True | |
| serial_mode=False | |
| batched_sampling=False | |
| num_batches_to_accumulate=2 | |
| worker_num_splits=2 | |
| policy_workers_per_policy=1 | |
| max_policy_lag=1000 | |
| num_workers=8 | |
| num_envs_per_worker=4 | |
| batch_size=1024 | |
| num_batches_per_epoch=1 | |
| num_epochs=1 | |
| rollout=32 | |
| recurrence=32 | |
| shuffle_minibatches=False | |
| gamma=0.99 | |
| reward_scale=1.0 | |
| reward_clip=1000.0 | |
| value_bootstrap=False | |
| normalize_returns=True | |
| exploration_loss_coeff=0.001 | |
| value_loss_coeff=0.5 | |
| kl_loss_coeff=0.0 | |
| exploration_loss=symmetric_kl | |
| gae_lambda=0.95 | |
| ppo_clip_ratio=0.1 | |
| ppo_clip_value=0.2 | |
| with_vtrace=False | |
| vtrace_rho=1.0 | |
| vtrace_c=1.0 | |
| optimizer=adam | |
| adam_eps=1e-06 | |
| adam_beta1=0.9 | |
| adam_beta2=0.999 | |
| max_grad_norm=4.0 | |
| learning_rate=0.0001 | |
| lr_schedule=constant | |
| lr_schedule_kl_threshold=0.008 | |
| lr_adaptive_min=1e-06 | |
| lr_adaptive_max=0.01 | |
| obs_subtract_mean=0.0 | |
| obs_scale=255.0 | |
| normalize_input=True | |
| normalize_input_keys=None | |
| decorrelate_experience_max_seconds=0 | |
| decorrelate_envs_on_one_worker=True | |
| actor_worker_gpus=[] | |
| set_workers_cpu_affinity=True | |
| force_envs_single_thread=False | |
| default_niceness=0 | |
| log_to_file=True | |
| experiment_summaries_interval=10 | |
| flush_summaries_interval=30 | |
| stats_avg=100 | |
| summaries_use_frameskip=True | |
| heartbeat_interval=20 | |
| heartbeat_reporting_interval=600 | |
| train_for_env_steps=5000000 | |
| train_for_seconds=10000000000 | |
| save_every_sec=120 | |
| keep_checkpoints=2 | |
| load_checkpoint_kind=latest | |
| save_milestones_sec=-1 | |
| save_best_every_sec=5 | |
| save_best_metric=reward | |
| save_best_after=100000 | |
| benchmark=False | |
| encoder_mlp_layers=[512, 512] | |
| encoder_conv_architecture=convnet_simple | |
| encoder_conv_mlp_layers=[512] | |
| use_rnn=True | |
| rnn_size=512 | |
| rnn_type=gru | |
| rnn_num_layers=1 | |
| decoder_mlp_layers=[] | |
| nonlinearity=elu | |
| policy_initialization=orthogonal | |
| policy_init_gain=1.0 | |
| actor_critic_share_weights=True | |
| adaptive_stddev=True | |
| continuous_tanh_scale=0.0 | |
| initial_stddev=1.0 | |
| use_env_info_cache=False | |
| env_gpu_actions=False | |
| env_gpu_observations=True | |
| env_frameskip=4 | |
| env_framestack=1 | |
| pixel_format=CHW | |
| use_record_episode_statistics=False | |
| with_wandb=False | |
| wandb_user=None | |
| wandb_project=sample_factory | |
| wandb_group=None | |
| wandb_job_type=SF | |
| wandb_tags=[] | |
| with_pbt=False | |
| pbt_mix_policies_in_one_env=True | |
| pbt_period_env_steps=5000000 | |
| pbt_start_mutation=20000000 | |
| pbt_replace_fraction=0.3 | |
| pbt_mutation_rate=0.15 | |
| pbt_replace_reward_gap=0.1 | |
| pbt_replace_reward_gap_absolute=1e-06 | |
| pbt_optimize_gamma=False | |
| pbt_target_objective=true_objective | |
| pbt_perturb_min=1.1 | |
| pbt_perturb_max=1.5 | |
| num_agents=-1 | |
| num_humans=0 | |
| num_bots=-1 | |
| start_bot_difficulty=None | |
| timelimit=None | |
| res_w=128 | |
| res_h=72 | |
| wide_aspect_ratio=False | |
| eval_env_frameskip=1 | |
| fps=35 | |
| command_line=--env=doom_health_gathering_supreme --num_workers=8 --num_envs_per_worker=4 --train_for_env_steps=4000000 | |
| cli_args={'env': 'doom_health_gathering_supreme', 'num_workers': 8, 'num_envs_per_worker': 4, 'train_for_env_steps': 4000000} | |
| git_hash=unknown | |
| git_repo_name=not a git repository | |
| [2025-02-25 11:46:39,468][00253] Saving configuration to /content/train_dir/default_experiment/config.json... | |
| [2025-02-25 11:46:39,470][00253] Rollout worker 0 uses device cpu | |
| [2025-02-25 11:46:39,471][00253] Rollout worker 1 uses device cpu | |
| [2025-02-25 11:46:39,472][00253] Rollout worker 2 uses device cpu | |
| [2025-02-25 11:46:39,473][00253] Rollout worker 3 uses device cpu | |
| [2025-02-25 11:46:39,474][00253] Rollout worker 4 uses device cpu | |
| [2025-02-25 11:46:39,475][00253] Rollout worker 5 uses device cpu | |
| [2025-02-25 11:46:39,475][00253] Rollout worker 6 uses device cpu | |
| [2025-02-25 11:46:39,476][00253] Rollout worker 7 uses device cpu | |
| [2025-02-25 11:46:39,547][00253] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 11:46:39,548][00253] InferenceWorker_p0-w0: min num requests: 2 | |
| [2025-02-25 11:46:39,580][00253] Starting all processes... | |
| [2025-02-25 11:46:39,580][00253] Starting process learner_proc0 | |
| [2025-02-25 11:46:39,632][00253] Starting all processes... | |
| [2025-02-25 11:46:39,642][00253] Starting process inference_proc0-0 | |
| [2025-02-25 11:46:39,642][00253] Starting process rollout_proc0 | |
| [2025-02-25 11:46:39,643][00253] Starting process rollout_proc1 | |
| [2025-02-25 11:46:39,644][00253] Starting process rollout_proc2 | |
| [2025-02-25 11:46:39,644][00253] Starting process rollout_proc3 | |
| [2025-02-25 11:46:39,644][00253] Starting process rollout_proc4 | |
| [2025-02-25 11:46:39,644][00253] Starting process rollout_proc5 | |
| [2025-02-25 11:46:39,644][00253] Starting process rollout_proc6 | |
| [2025-02-25 11:46:39,644][00253] Starting process rollout_proc7 | |
| [2025-02-25 11:46:54,869][17585] Worker 7 uses CPU cores [1] | |
| [2025-02-25 11:46:55,122][17580] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 11:46:55,126][17580] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 | |
| [2025-02-25 11:46:55,170][17581] Worker 3 uses CPU cores [1] | |
| [2025-02-25 11:46:55,233][17580] Num visible devices: 1 | |
| [2025-02-25 11:46:55,301][17583] Worker 5 uses CPU cores [1] | |
| [2025-02-25 11:46:55,303][17564] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 11:46:55,306][17564] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 | |
| [2025-02-25 11:46:55,350][17582] Worker 4 uses CPU cores [0] | |
| [2025-02-25 11:46:55,362][17564] Num visible devices: 1 | |
| [2025-02-25 11:46:55,392][17564] Starting seed is not provided | |
| [2025-02-25 11:46:55,393][17564] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 11:46:55,393][17564] Initializing actor-critic model on device cuda:0 | |
| [2025-02-25 11:46:55,394][17564] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 11:46:55,396][17564] RunningMeanStd input shape: (1,) | |
| [2025-02-25 11:46:55,452][17564] ConvEncoder: input_channels=3 | |
| [2025-02-25 11:46:55,513][17577] Worker 0 uses CPU cores [0] | |
| [2025-02-25 11:46:55,530][17584] Worker 6 uses CPU cores [0] | |
| [2025-02-25 11:46:55,539][17578] Worker 1 uses CPU cores [1] | |
| [2025-02-25 11:46:55,539][17579] Worker 2 uses CPU cores [0] | |
| [2025-02-25 11:46:55,632][17564] Conv encoder output size: 512 | |
| [2025-02-25 11:46:55,632][17564] Policy head output size: 512 | |
| [2025-02-25 11:46:55,651][17564] Created Actor Critic model with architecture: | |
| [2025-02-25 11:46:55,651][17564] ActorCriticSharedWeights( | |
| (obs_normalizer): ObservationNormalizer( | |
| (running_mean_std): RunningMeanStdDictInPlace( | |
| (running_mean_std): ModuleDict( | |
| (obs): RunningMeanStdInPlace() | |
| ) | |
| ) | |
| ) | |
| (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace) | |
| (encoder): VizdoomEncoder( | |
| (basic_encoder): ConvEncoder( | |
| (enc): RecursiveScriptModule( | |
| original_name=ConvEncoderImpl | |
| (conv_head): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Conv2d) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| (2): RecursiveScriptModule(original_name=Conv2d) | |
| (3): RecursiveScriptModule(original_name=ELU) | |
| (4): RecursiveScriptModule(original_name=Conv2d) | |
| (5): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| (mlp_layers): RecursiveScriptModule( | |
| original_name=Sequential | |
| (0): RecursiveScriptModule(original_name=Linear) | |
| (1): RecursiveScriptModule(original_name=ELU) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (core): ModelCoreRNN( | |
| (core): GRU(512, 512) | |
| ) | |
| (decoder): MlpDecoder( | |
| (mlp): Identity() | |
| ) | |
| (critic_linear): Linear(in_features=512, out_features=1, bias=True) | |
| (action_parameterization): ActionParameterizationDefault( | |
| (distribution_linear): Linear(in_features=512, out_features=5, bias=True) | |
| ) | |
| ) | |
| [2025-02-25 11:46:55,818][17564] Using optimizer <class 'torch.optim.adam.Adam'> | |
| [2025-02-25 11:46:56,755][17564] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... | |
| [2025-02-25 11:46:56,796][17564] Loading model from checkpoint | |
| [2025-02-25 11:46:56,798][17564] Loaded experiment state at self.train_step=978, self.env_steps=4005888 | |
| [2025-02-25 11:46:56,798][17564] Initialized policy 0 weights for model version 978 | |
| [2025-02-25 11:46:56,801][17564] LearnerWorker_p0 finished initialization! | |
| [2025-02-25 11:46:56,802][17564] Using GPUs [0] for process 0 (actually maps to GPUs [0]) | |
| [2025-02-25 11:46:56,952][17580] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 11:46:56,953][17580] RunningMeanStd input shape: (1,) | |
| [2025-02-25 11:46:56,966][17580] ConvEncoder: input_channels=3 | |
| [2025-02-25 11:46:57,066][17580] Conv encoder output size: 512 | |
| [2025-02-25 11:46:57,067][17580] Policy head output size: 512 | |
| [2025-02-25 11:46:57,108][00253] Inference worker 0-0 is ready! | |
| [2025-02-25 11:46:57,109][00253] All inference workers are ready! Signal rollout workers to start! | |
| [2025-02-25 11:46:57,362][00253] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 4005888. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-25 11:46:57,396][17585] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:57,392][17578] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:57,397][17581] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:57,425][17583] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:57,431][17579] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:57,490][17582] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:57,503][17577] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:57,540][17584] Doom resolution: 160x120, resize resolution: (128, 72) | |
| [2025-02-25 11:46:58,139][17579] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:46:58,883][17579] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:46:59,003][17582] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:46:59,069][17578] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:46:59,075][17585] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:46:59,080][17581] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:46:59,083][17583] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:46:59,540][00253] Heartbeat connected on Batcher_0 | |
| [2025-02-25 11:46:59,543][00253] Heartbeat connected on LearnerWorker_p0 | |
| [2025-02-25 11:46:59,599][00253] Heartbeat connected on InferenceWorker_p0-w0 | |
| [2025-02-25 11:46:59,825][17577] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:46:59,904][17584] Decorrelating experience for 0 frames... | |
| [2025-02-25 11:47:00,735][17585] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:47:00,738][17578] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:47:00,741][17581] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:47:00,753][17583] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:47:01,101][17577] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:47:01,302][17584] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:47:02,351][17582] Decorrelating experience for 32 frames... | |
| [2025-02-25 11:47:02,363][00253] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 4005888. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-25 11:47:03,284][17578] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:03,291][17585] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:03,350][17583] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:03,591][17577] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:04,547][17584] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:05,100][17582] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:05,625][17581] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:05,628][17578] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:05,703][17577] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:05,706][17583] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:05,929][00253] Heartbeat connected on RolloutWorker_w0 | |
| [2025-02-25 11:47:05,932][00253] Heartbeat connected on RolloutWorker_w1 | |
| [2025-02-25 11:47:05,965][00253] Heartbeat connected on RolloutWorker_w5 | |
| [2025-02-25 11:47:06,426][17579] Decorrelating experience for 64 frames... | |
| [2025-02-25 11:47:06,563][17584] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:06,734][00253] Heartbeat connected on RolloutWorker_w6 | |
| [2025-02-25 11:47:06,790][17582] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:06,904][00253] Heartbeat connected on RolloutWorker_w4 | |
| [2025-02-25 11:47:06,997][17585] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:07,277][00253] Heartbeat connected on RolloutWorker_w7 | |
| [2025-02-25 11:47:07,362][00253] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 4005888. Throughput: 0: 2.2. Samples: 22. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) | |
| [2025-02-25 11:47:07,868][17581] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:08,211][00253] Heartbeat connected on RolloutWorker_w3 | |
| [2025-02-25 11:47:10,000][17564] Signal inference workers to stop experience collection... | |
| [2025-02-25 11:47:10,017][17580] InferenceWorker_p0-w0: stopping experience collection | |
| [2025-02-25 11:47:10,198][17579] Decorrelating experience for 96 frames... | |
| [2025-02-25 11:47:10,260][00253] Heartbeat connected on RolloutWorker_w2 | |
| [2025-02-25 11:47:11,582][17564] Signal inference workers to resume experience collection... | |
| [2025-02-25 11:47:11,584][17580] InferenceWorker_p0-w0: resuming experience collection | |
| [2025-02-25 11:47:12,362][00253] Fps is (10 sec: 819.2, 60 sec: 546.1, 300 sec: 546.1). Total num frames: 4014080. Throughput: 0: 194.5. Samples: 2918. Policy #0 lag: (min: 0.0, avg: 0.0, max: 0.0) | |
| [2025-02-25 11:47:12,364][00253] Avg episode reward: [(0, '3.503')] | |
| [2025-02-25 11:47:17,365][00253] Fps is (10 sec: 2457.0, 60 sec: 1228.6, 300 sec: 1228.6). Total num frames: 4030464. Throughput: 0: 311.5. Samples: 6230. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:47:17,366][00253] Avg episode reward: [(0, '11.000')] | |
| [2025-02-25 11:47:21,316][17580] Updated weights for policy 0, policy_version 988 (0.0023) | |
| [2025-02-25 11:47:22,362][00253] Fps is (10 sec: 3686.4, 60 sec: 1802.2, 300 sec: 1802.2). Total num frames: 4050944. Throughput: 0: 428.3. Samples: 10708. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:47:22,364][00253] Avg episode reward: [(0, '13.334')] | |
| [2025-02-25 11:47:27,362][00253] Fps is (10 sec: 4097.1, 60 sec: 2184.5, 300 sec: 2184.5). Total num frames: 4071424. Throughput: 0: 594.2. Samples: 17826. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-25 11:47:27,367][00253] Avg episode reward: [(0, '17.900')] | |
| [2025-02-25 11:47:30,065][17580] Updated weights for policy 0, policy_version 998 (0.0031) | |
| [2025-02-25 11:47:32,362][00253] Fps is (10 sec: 4096.0, 60 sec: 2457.6, 300 sec: 2457.6). Total num frames: 4091904. Throughput: 0: 604.9. Samples: 21170. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) | |
| [2025-02-25 11:47:32,364][00253] Avg episode reward: [(0, '18.509')] | |
| [2025-02-25 11:47:37,362][00253] Fps is (10 sec: 4095.9, 60 sec: 2662.4, 300 sec: 2662.4). Total num frames: 4112384. Throughput: 0: 644.7. Samples: 25790. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-25 11:47:37,364][00253] Avg episode reward: [(0, '20.950')] | |
| [2025-02-25 11:47:40,894][17580] Updated weights for policy 0, policy_version 1008 (0.0025) | |
| [2025-02-25 11:47:42,362][00253] Fps is (10 sec: 4096.0, 60 sec: 2821.7, 300 sec: 2821.7). Total num frames: 4132864. Throughput: 0: 728.2. Samples: 32770. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:47:42,364][00253] Avg episode reward: [(0, '22.680')] | |
| [2025-02-25 11:47:47,362][00253] Fps is (10 sec: 4096.0, 60 sec: 2949.1, 300 sec: 2949.1). Total num frames: 4153344. Throughput: 0: 803.2. Samples: 36142. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-25 11:47:47,366][00253] Avg episode reward: [(0, '24.587')] | |
| [2025-02-25 11:47:51,382][17580] Updated weights for policy 0, policy_version 1018 (0.0012) | |
| [2025-02-25 11:47:52,362][00253] Fps is (10 sec: 4096.0, 60 sec: 3053.4, 300 sec: 3053.4). Total num frames: 4173824. Throughput: 0: 914.2. Samples: 41160. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:47:52,364][00253] Avg episode reward: [(0, '23.748')] | |
| [2025-02-25 11:47:57,362][00253] Fps is (10 sec: 4096.0, 60 sec: 3140.3, 300 sec: 3140.3). Total num frames: 4194304. Throughput: 0: 1009.0. Samples: 48322. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:47:57,364][00253] Avg episode reward: [(0, '21.631')] | |
| [2025-02-25 11:48:00,548][17580] Updated weights for policy 0, policy_version 1028 (0.0016) | |
| [2025-02-25 11:48:02,366][00253] Fps is (10 sec: 4094.6, 60 sec: 3481.4, 300 sec: 3213.6). Total num frames: 4214784. Throughput: 0: 1007.0. Samples: 51548. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:48:02,367][00253] Avg episode reward: [(0, '21.563')] | |
| [2025-02-25 11:48:07,362][00253] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3276.8). Total num frames: 4235264. Throughput: 0: 1023.4. Samples: 56762. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-25 11:48:07,364][00253] Avg episode reward: [(0, '21.758')] | |
| [2025-02-25 11:48:10,823][17580] Updated weights for policy 0, policy_version 1038 (0.0023) | |
| [2025-02-25 11:48:12,362][00253] Fps is (10 sec: 4097.4, 60 sec: 4027.7, 300 sec: 3331.4). Total num frames: 4255744. Throughput: 0: 1018.6. Samples: 63662. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-25 11:48:12,364][00253] Avg episode reward: [(0, '22.400')] | |
| [2025-02-25 11:48:17,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.2, 300 sec: 3379.2). Total num frames: 4276224. Throughput: 0: 1011.5. Samples: 66688. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-25 11:48:17,364][00253] Avg episode reward: [(0, '21.868')] | |
| [2025-02-25 11:48:21,318][17580] Updated weights for policy 0, policy_version 1048 (0.0023) | |
| [2025-02-25 11:48:22,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3421.4). Total num frames: 4296704. Throughput: 0: 1026.9. Samples: 72002. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:48:22,366][00253] Avg episode reward: [(0, '24.206')] | |
| [2025-02-25 11:48:27,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3458.8). Total num frames: 4317184. Throughput: 0: 1029.0. Samples: 79074. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) | |
| [2025-02-25 11:48:27,364][00253] Avg episode reward: [(0, '25.427')] | |
| [2025-02-25 11:48:30,644][17580] Updated weights for policy 0, policy_version 1058 (0.0014) | |
| [2025-02-25 11:48:32,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3492.4). Total num frames: 4337664. Throughput: 0: 1021.1. Samples: 82090. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:48:32,364][00253] Avg episode reward: [(0, '25.260')] | |
| [2025-02-25 11:48:37,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3522.6). Total num frames: 4358144. Throughput: 0: 1031.5. Samples: 87578. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-25 11:48:37,366][00253] Avg episode reward: [(0, '26.071')] | |
| [2025-02-25 11:48:37,373][17564] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001064_4358144.pth... | |
| [2025-02-25 11:48:37,503][17564] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000961_3936256.pth | |
| [2025-02-25 11:48:40,780][17580] Updated weights for policy 0, policy_version 1068 (0.0017) | |
| [2025-02-25 11:48:42,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3549.9). Total num frames: 4378624. Throughput: 0: 1024.8. Samples: 94436. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:48:42,365][00253] Avg episode reward: [(0, '26.693')] | |
| [2025-02-25 11:48:42,405][17564] Saving new best policy, reward=26.693! | |
| [2025-02-25 11:48:47,362][00253] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3537.5). Total num frames: 4395008. Throughput: 0: 1013.3. Samples: 97142. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-25 11:48:47,364][00253] Avg episode reward: [(0, '25.657')] | |
| [2025-02-25 11:48:51,460][17580] Updated weights for policy 0, policy_version 1078 (0.0013) | |
| [2025-02-25 11:48:52,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3597.4). Total num frames: 4419584. Throughput: 0: 1017.7. Samples: 102560. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:48:52,366][00253] Avg episode reward: [(0, '24.664')] | |
| [2025-02-25 11:48:57,362][00253] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3618.1). Total num frames: 4440064. Throughput: 0: 1021.3. Samples: 109620. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:48:57,367][00253] Avg episode reward: [(0, '24.927')] | |
| [2025-02-25 11:49:01,365][17580] Updated weights for policy 0, policy_version 1088 (0.0023) | |
| [2025-02-25 11:49:02,362][00253] Fps is (10 sec: 3686.3, 60 sec: 4028.0, 300 sec: 3604.5). Total num frames: 4456448. Throughput: 0: 1013.2. Samples: 112282. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:49:02,367][00253] Avg episode reward: [(0, '25.261')] | |
| [2025-02-25 11:49:07,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3654.9). Total num frames: 4481024. Throughput: 0: 1025.2. Samples: 118138. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-25 11:49:07,364][00253] Avg episode reward: [(0, '24.910')] | |
| [2025-02-25 11:49:10,712][17580] Updated weights for policy 0, policy_version 1098 (0.0034) | |
| [2025-02-25 11:49:12,362][00253] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3671.2). Total num frames: 4501504. Throughput: 0: 1022.9. Samples: 125104. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-25 11:49:12,368][00253] Avg episode reward: [(0, '24.702')] | |
| [2025-02-25 11:49:17,362][00253] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3657.1). Total num frames: 4517888. Throughput: 0: 1010.8. Samples: 127576. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:49:17,367][00253] Avg episode reward: [(0, '24.266')] | |
| [2025-02-25 11:49:21,328][17580] Updated weights for policy 0, policy_version 1108 (0.0014) | |
| [2025-02-25 11:49:22,363][00253] Fps is (10 sec: 4095.9, 60 sec: 4096.0, 300 sec: 3700.5). Total num frames: 4542464. Throughput: 0: 1019.4. Samples: 133452. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:49:22,364][00253] Avg episode reward: [(0, '24.419')] | |
| [2025-02-25 11:49:27,362][00253] Fps is (10 sec: 4915.2, 60 sec: 4164.3, 300 sec: 3741.0). Total num frames: 4567040. Throughput: 0: 1026.7. Samples: 140638. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:49:27,364][00253] Avg episode reward: [(0, '22.227')] | |
| [2025-02-25 11:49:31,382][17580] Updated weights for policy 0, policy_version 1118 (0.0025) | |
| [2025-02-25 11:49:32,362][00253] Fps is (10 sec: 3686.5, 60 sec: 4027.7, 300 sec: 3699.6). Total num frames: 4579328. Throughput: 0: 1017.5. Samples: 142928. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) | |
| [2025-02-25 11:49:32,366][00253] Avg episode reward: [(0, '22.520')] | |
| [2025-02-25 11:49:37,362][00253] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 3737.6). Total num frames: 4603904. Throughput: 0: 1031.9. Samples: 148994. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:49:37,367][00253] Avg episode reward: [(0, '24.939')] | |
| [2025-02-25 11:49:40,704][17580] Updated weights for policy 0, policy_version 1128 (0.0012) | |
| [2025-02-25 11:49:42,362][00253] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3748.5). Total num frames: 4624384. Throughput: 0: 1025.3. Samples: 155760. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:49:42,364][00253] Avg episode reward: [(0, '26.329')] | |
| [2025-02-25 11:49:47,362][00253] Fps is (10 sec: 3686.4, 60 sec: 4096.0, 300 sec: 3734.6). Total num frames: 4640768. Throughput: 0: 1012.0. Samples: 157824. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-25 11:49:47,366][00253] Avg episode reward: [(0, '27.561')] | |
| [2025-02-25 11:49:47,373][17564] Saving new best policy, reward=27.561! | |
| [2025-02-25 11:49:51,562][17580] Updated weights for policy 0, policy_version 1138 (0.0020) | |
| [2025-02-25 11:49:52,362][00253] Fps is (10 sec: 3686.4, 60 sec: 4027.7, 300 sec: 3744.9). Total num frames: 4661248. Throughput: 0: 1016.8. Samples: 163892. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:49:52,366][00253] Avg episode reward: [(0, '27.878')] | |
| [2025-02-25 11:49:52,369][17564] Saving new best policy, reward=27.878! | |
| [2025-02-25 11:49:57,362][00253] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3777.4). Total num frames: 4685824. Throughput: 0: 1013.2. Samples: 170698. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-25 11:49:57,364][00253] Avg episode reward: [(0, '27.262')] | |
| [2025-02-25 11:50:02,204][17580] Updated weights for policy 0, policy_version 1148 (0.0018) | |
| [2025-02-25 11:50:02,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3763.9). Total num frames: 4702208. Throughput: 0: 1006.0. Samples: 172846. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:50:02,364][00253] Avg episode reward: [(0, '25.002')] | |
| [2025-02-25 11:50:07,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3794.2). Total num frames: 4726784. Throughput: 0: 1021.0. Samples: 179396. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:50:07,364][00253] Avg episode reward: [(0, '23.084')] | |
| [2025-02-25 11:50:11,014][17580] Updated weights for policy 0, policy_version 1158 (0.0016) | |
| [2025-02-25 11:50:12,362][00253] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3801.9). Total num frames: 4747264. Throughput: 0: 1008.6. Samples: 186024. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-25 11:50:12,366][00253] Avg episode reward: [(0, '22.714')] | |
| [2025-02-25 11:50:17,363][00253] Fps is (10 sec: 3686.3, 60 sec: 4096.0, 300 sec: 3788.8). Total num frames: 4763648. Throughput: 0: 1005.1. Samples: 188158. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:50:17,366][00253] Avg episode reward: [(0, '20.972')] | |
| [2025-02-25 11:50:21,487][17580] Updated weights for policy 0, policy_version 1168 (0.0021) | |
| [2025-02-25 11:50:22,362][00253] Fps is (10 sec: 3686.4, 60 sec: 4027.8, 300 sec: 3796.3). Total num frames: 4784128. Throughput: 0: 1015.7. Samples: 194702. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:50:22,364][00253] Avg episode reward: [(0, '22.173')] | |
| [2025-02-25 11:50:27,365][00253] Fps is (10 sec: 4504.6, 60 sec: 4027.6, 300 sec: 3822.9). Total num frames: 4808704. Throughput: 0: 1015.0. Samples: 201436. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) | |
| [2025-02-25 11:50:27,366][00253] Avg episode reward: [(0, '24.252')] | |
| [2025-02-25 11:50:32,042][17580] Updated weights for policy 0, policy_version 1178 (0.0015) | |
| [2025-02-25 11:50:32,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4096.0, 300 sec: 3810.2). Total num frames: 4825088. Throughput: 0: 1016.9. Samples: 203586. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:50:32,364][00253] Avg episode reward: [(0, '24.198')] | |
| [2025-02-25 11:50:37,362][00253] Fps is (10 sec: 4096.9, 60 sec: 4096.0, 300 sec: 3835.3). Total num frames: 4849664. Throughput: 0: 1033.2. Samples: 210384. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:50:37,364][00253] Avg episode reward: [(0, '25.479')] | |
| [2025-02-25 11:50:37,375][17564] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001184_4849664.pth... | |
| [2025-02-25 11:50:37,496][17564] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth | |
| [2025-02-25 11:50:40,607][17580] Updated weights for policy 0, policy_version 1188 (0.0016) | |
| [2025-02-25 11:50:42,362][00253] Fps is (10 sec: 4505.6, 60 sec: 4096.0, 300 sec: 3841.1). Total num frames: 4870144. Throughput: 0: 1022.5. Samples: 216710. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:50:42,365][00253] Avg episode reward: [(0, '26.605')] | |
| [2025-02-25 11:50:47,363][00253] Fps is (10 sec: 3686.3, 60 sec: 4096.0, 300 sec: 3828.9). Total num frames: 4886528. Throughput: 0: 1021.1. Samples: 218796. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) | |
| [2025-02-25 11:50:47,364][00253] Avg episode reward: [(0, '27.327')] | |
| [2025-02-25 11:50:51,367][17580] Updated weights for policy 0, policy_version 1198 (0.0020) | |
| [2025-02-25 11:50:52,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4164.3, 300 sec: 3852.0). Total num frames: 4911104. Throughput: 0: 1025.9. Samples: 225562. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:50:52,364][00253] Avg episode reward: [(0, '26.914')] | |
| [2025-02-25 11:50:57,362][00253] Fps is (10 sec: 4096.2, 60 sec: 4027.7, 300 sec: 3840.0). Total num frames: 4927488. Throughput: 0: 1013.7. Samples: 231642. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:50:57,364][00253] Avg episode reward: [(0, '26.968')] | |
| [2025-02-25 11:51:02,363][00253] Fps is (10 sec: 3276.6, 60 sec: 4027.7, 300 sec: 3828.5). Total num frames: 4943872. Throughput: 0: 1012.3. Samples: 233712. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) | |
| [2025-02-25 11:51:02,367][00253] Avg episode reward: [(0, '26.247')] | |
| [2025-02-25 11:51:02,452][17580] Updated weights for policy 0, policy_version 1208 (0.0013) | |
| [2025-02-25 11:51:07,362][00253] Fps is (10 sec: 4096.0, 60 sec: 4027.7, 300 sec: 3850.2). Total num frames: 4968448. Throughput: 0: 1020.0. Samples: 240602. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:51:07,367][00253] Avg episode reward: [(0, '25.653')] | |
| [2025-02-25 11:51:11,647][17580] Updated weights for policy 0, policy_version 1218 (0.0020) | |
| [2025-02-25 11:51:12,362][00253] Fps is (10 sec: 4505.8, 60 sec: 4027.7, 300 sec: 3855.1). Total num frames: 4988928. Throughput: 0: 1008.8. Samples: 246830. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) | |
| [2025-02-25 11:51:12,363][00253] Avg episode reward: [(0, '24.840')] | |
| [2025-02-25 11:51:16,535][00253] Component Batcher_0 stopped! | |
| [2025-02-25 11:51:16,534][17564] Stopping Batcher_0... | |
| [2025-02-25 11:51:16,540][17564] Loop batcher_evt_loop terminating... | |
| [2025-02-25 11:51:16,542][17564] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001222_5005312.pth... | |
| [2025-02-25 11:51:16,602][17580] Weights refcount: 2 0 | |
| [2025-02-25 11:51:16,606][00253] Component InferenceWorker_p0-w0 stopped! | |
| [2025-02-25 11:51:16,607][17580] Stopping InferenceWorker_p0-w0... | |
| [2025-02-25 11:51:16,607][17580] Loop inference_proc0-0_evt_loop terminating... | |
| [2025-02-25 11:51:16,663][17564] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001064_4358144.pth | |
| [2025-02-25 11:51:16,676][17564] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001222_5005312.pth... | |
| [2025-02-25 11:51:16,865][00253] Component LearnerWorker_p0 stopped! | |
| [2025-02-25 11:51:16,868][17564] Stopping LearnerWorker_p0... | |
| [2025-02-25 11:51:16,869][17564] Loop learner_proc0_evt_loop terminating... | |
| [2025-02-25 11:51:16,933][00253] Component RolloutWorker_w6 stopped! | |
| [2025-02-25 11:51:16,936][17584] Stopping RolloutWorker_w6... | |
| [2025-02-25 11:51:16,937][17584] Loop rollout_proc6_evt_loop terminating... | |
| [2025-02-25 11:51:16,942][00253] Component RolloutWorker_w2 stopped! | |
| [2025-02-25 11:51:16,945][17579] Stopping RolloutWorker_w2... | |
| [2025-02-25 11:51:16,946][17579] Loop rollout_proc2_evt_loop terminating... | |
| [2025-02-25 11:51:16,970][00253] Component RolloutWorker_w4 stopped! | |
| [2025-02-25 11:51:16,974][17582] Stopping RolloutWorker_w4... | |
| [2025-02-25 11:51:16,981][00253] Component RolloutWorker_w0 stopped! | |
| [2025-02-25 11:51:16,980][17582] Loop rollout_proc4_evt_loop terminating... | |
| [2025-02-25 11:51:16,984][17577] Stopping RolloutWorker_w0... | |
| [2025-02-25 11:51:16,987][17577] Loop rollout_proc0_evt_loop terminating... | |
| [2025-02-25 11:51:17,044][17585] Stopping RolloutWorker_w7... | |
| [2025-02-25 11:51:17,044][00253] Component RolloutWorker_w7 stopped! | |
| [2025-02-25 11:51:17,049][17585] Loop rollout_proc7_evt_loop terminating... | |
| [2025-02-25 11:51:17,065][17578] Stopping RolloutWorker_w1... | |
| [2025-02-25 11:51:17,065][00253] Component RolloutWorker_w1 stopped! | |
| [2025-02-25 11:51:17,076][17578] Loop rollout_proc1_evt_loop terminating... | |
| [2025-02-25 11:51:17,121][17583] Stopping RolloutWorker_w5... | |
| [2025-02-25 11:51:17,124][17583] Loop rollout_proc5_evt_loop terminating... | |
| [2025-02-25 11:51:17,120][00253] Component RolloutWorker_w5 stopped! | |
| [2025-02-25 11:51:17,130][17581] Stopping RolloutWorker_w3... | |
| [2025-02-25 11:51:17,133][17581] Loop rollout_proc3_evt_loop terminating... | |
| [2025-02-25 11:51:17,130][00253] Component RolloutWorker_w3 stopped! | |
| [2025-02-25 11:51:17,134][00253] Waiting for process learner_proc0 to stop... | |
| [2025-02-25 11:51:18,616][00253] Waiting for process inference_proc0-0 to join... | |
| [2025-02-25 11:51:18,624][00253] Waiting for process rollout_proc0 to join... | |
| [2025-02-25 11:51:20,820][00253] Waiting for process rollout_proc1 to join... | |
| [2025-02-25 11:51:20,821][00253] Waiting for process rollout_proc2 to join... | |
| [2025-02-25 11:51:20,822][00253] Waiting for process rollout_proc3 to join... | |
| [2025-02-25 11:51:20,823][00253] Waiting for process rollout_proc4 to join... | |
| [2025-02-25 11:51:20,827][00253] Waiting for process rollout_proc5 to join... | |
| [2025-02-25 11:51:20,828][00253] Waiting for process rollout_proc6 to join... | |
| [2025-02-25 11:51:20,830][00253] Waiting for process rollout_proc7 to join... | |
| [2025-02-25 11:51:20,832][00253] Batcher 0 profile tree view: | |
| batching: 6.4342, releasing_batches: 0.0085 | |
| [2025-02-25 11:51:20,833][00253] InferenceWorker_p0-w0 profile tree view: | |
| wait_policy: 0.0000 | |
| wait_policy_total: 105.6020 | |
| update_model: 1.9869 | |
| weight_update: 0.0021 | |
| one_step: 0.0024 | |
| handle_policy_step: 141.4189 | |
| deserialize: 3.3648, stack: 0.7280, obs_to_device_normalize: 30.2036, forward: 72.8299, send_messages: 6.6535 | |
| prepare_outputs: 21.6085 | |
| to_cpu: 13.5659 | |
| [2025-02-25 11:51:20,834][00253] Learner 0 profile tree view: | |
| misc: 0.0010, prepare_batch: 4.2601 | |
| train: 19.6231 | |
| epoch_init: 0.0011, minibatch_init: 0.0014, losses_postprocess: 0.1365, kl_divergence: 0.1306, after_optimizer: 0.8301 | |
| calculate_losses: 6.4572 | |
| losses_init: 0.0008, forward_head: 0.6584, bptt_initial: 4.0425, tail: 0.2969, advantages_returns: 0.0550, losses: 0.8797 | |
| bptt: 0.4738 | |
| bptt_forward_core: 0.4551 | |
| update: 11.8830 | |
| clip: 0.2334 | |
| [2025-02-25 11:51:20,834][00253] RolloutWorker_w0 profile tree view: | |
| wait_for_trajectories: 0.0757, enqueue_policy_requests: 25.4344, env_step: 197.0858, overhead: 2.9988, complete_rollouts: 1.2629 | |
| save_policy_outputs: 4.6291 | |
| split_output_tensors: 1.7869 | |
| [2025-02-25 11:51:20,836][00253] RolloutWorker_w7 profile tree view: | |
| wait_for_trajectories: 0.0536, enqueue_policy_requests: 22.4654, env_step: 198.3978, overhead: 2.7616, complete_rollouts: 2.1799 | |
| save_policy_outputs: 4.5091 | |
| split_output_tensors: 1.6912 | |
| [2025-02-25 11:51:20,838][00253] Loop Runner_EvtLoop terminating... | |
| [2025-02-25 11:51:20,839][00253] Runner profile tree view: | |
| main_loop: 281.2592 | |
| [2025-02-25 11:51:20,841][00253] Collected {0: 5005312}, FPS: 3553.4 | |
| [2025-02-25 11:51:20,857][00253] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-25 11:51:20,858][00253] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-25 11:51:20,858][00253] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-25 11:51:20,859][00253] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-25 11:51:20,860][00253] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:51:20,861][00253] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-25 11:51:20,861][00253] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:51:20,862][00253] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-25 11:51:20,863][00253] Adding new argument 'push_to_hub'=False that is not in the saved config file! | |
| [2025-02-25 11:51:20,863][00253] Adding new argument 'hf_repository'=None that is not in the saved config file! | |
| [2025-02-25 11:51:20,864][00253] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-25 11:51:20,865][00253] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-25 11:51:20,866][00253] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-25 11:51:20,866][00253] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-25 11:51:20,867][00253] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-25 11:51:20,901][00253] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 11:51:20,902][00253] RunningMeanStd input shape: (1,) | |
| [2025-02-25 11:51:20,915][00253] ConvEncoder: input_channels=3 | |
| [2025-02-25 11:51:20,950][00253] Conv encoder output size: 512 | |
| [2025-02-25 11:51:20,950][00253] Policy head output size: 512 | |
| [2025-02-25 11:51:20,970][00253] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001222_5005312.pth... | |
| [2025-02-25 11:51:21,600][00253] Num frames 100... | |
| [2025-02-25 11:51:21,742][00253] Num frames 200... | |
| [2025-02-25 11:51:21,867][00253] Num frames 300... | |
| [2025-02-25 11:51:21,993][00253] Num frames 400... | |
| [2025-02-25 11:51:22,119][00253] Num frames 500... | |
| [2025-02-25 11:51:22,245][00253] Num frames 600... | |
| [2025-02-25 11:51:22,380][00253] Num frames 700... | |
| [2025-02-25 11:51:22,507][00253] Num frames 800... | |
| [2025-02-25 11:51:22,683][00253] Avg episode rewards: #0: 17.960, true rewards: #0: 8.960 | |
| [2025-02-25 11:51:22,684][00253] Avg episode reward: 17.960, avg true_objective: 8.960 | |
| [2025-02-25 11:51:22,693][00253] Num frames 900... | |
| [2025-02-25 11:51:22,819][00253] Num frames 1000... | |
| [2025-02-25 11:51:22,944][00253] Num frames 1100... | |
| [2025-02-25 11:51:23,070][00253] Num frames 1200... | |
| [2025-02-25 11:51:23,199][00253] Num frames 1300... | |
| [2025-02-25 11:51:23,330][00253] Num frames 1400... | |
| [2025-02-25 11:51:23,462][00253] Num frames 1500... | |
| [2025-02-25 11:51:23,587][00253] Num frames 1600... | |
| [2025-02-25 11:51:23,715][00253] Num frames 1700... | |
| [2025-02-25 11:51:23,854][00253] Num frames 1800... | |
| [2025-02-25 11:51:23,980][00253] Num frames 1900... | |
| [2025-02-25 11:51:24,107][00253] Num frames 2000... | |
| [2025-02-25 11:51:24,235][00253] Num frames 2100... | |
| [2025-02-25 11:51:24,370][00253] Num frames 2200... | |
| [2025-02-25 11:51:24,501][00253] Num frames 2300... | |
| [2025-02-25 11:51:24,629][00253] Num frames 2400... | |
| [2025-02-25 11:51:24,788][00253] Avg episode rewards: #0: 27.390, true rewards: #0: 12.390 | |
| [2025-02-25 11:51:24,789][00253] Avg episode reward: 27.390, avg true_objective: 12.390 | |
| [2025-02-25 11:51:24,821][00253] Num frames 2500... | |
| [2025-02-25 11:51:24,948][00253] Num frames 2600... | |
| [2025-02-25 11:51:25,076][00253] Num frames 2700... | |
| [2025-02-25 11:51:25,202][00253] Num frames 2800... | |
| [2025-02-25 11:51:25,368][00253] Num frames 2900... | |
| [2025-02-25 11:51:25,553][00253] Num frames 3000... | |
| [2025-02-25 11:51:25,723][00253] Num frames 3100... | |
| [2025-02-25 11:51:25,888][00253] Num frames 3200... | |
| [2025-02-25 11:51:26,052][00253] Num frames 3300... | |
| [2025-02-25 11:51:26,178][00253] Avg episode rewards: #0: 24.140, true rewards: #0: 11.140 | |
| [2025-02-25 11:51:26,179][00253] Avg episode reward: 24.140, avg true_objective: 11.140 | |
| [2025-02-25 11:51:26,277][00253] Num frames 3400... | |
| [2025-02-25 11:51:26,450][00253] Num frames 3500... | |
| [2025-02-25 11:51:26,618][00253] Num frames 3600... | |
| [2025-02-25 11:51:26,794][00253] Num frames 3700... | |
| [2025-02-25 11:51:26,964][00253] Num frames 3800... | |
| [2025-02-25 11:51:27,149][00253] Num frames 3900... | |
| [2025-02-25 11:51:27,328][00253] Num frames 4000... | |
| [2025-02-25 11:51:27,486][00253] Num frames 4100... | |
| [2025-02-25 11:51:27,613][00253] Num frames 4200... | |
| [2025-02-25 11:51:27,743][00253] Num frames 4300... | |
| [2025-02-25 11:51:27,869][00253] Num frames 4400... | |
| [2025-02-25 11:51:27,996][00253] Num frames 4500... | |
| [2025-02-25 11:51:28,120][00253] Num frames 4600... | |
| [2025-02-25 11:51:28,248][00253] Num frames 4700... | |
| [2025-02-25 11:51:28,378][00253] Num frames 4800... | |
| [2025-02-25 11:51:28,516][00253] Num frames 4900... | |
| [2025-02-25 11:51:28,584][00253] Avg episode rewards: #0: 27.525, true rewards: #0: 12.275 | |
| [2025-02-25 11:51:28,585][00253] Avg episode reward: 27.525, avg true_objective: 12.275 | |
| [2025-02-25 11:51:28,707][00253] Num frames 5000... | |
| [2025-02-25 11:51:28,837][00253] Num frames 5100... | |
| [2025-02-25 11:51:28,964][00253] Num frames 5200... | |
| [2025-02-25 11:51:29,092][00253] Num frames 5300... | |
| [2025-02-25 11:51:29,220][00253] Num frames 5400... | |
| [2025-02-25 11:51:29,348][00253] Num frames 5500... | |
| [2025-02-25 11:51:29,477][00253] Num frames 5600... | |
| [2025-02-25 11:51:29,639][00253] Avg episode rewards: #0: 25.556, true rewards: #0: 11.356 | |
| [2025-02-25 11:51:29,641][00253] Avg episode reward: 25.556, avg true_objective: 11.356 | |
| [2025-02-25 11:51:29,674][00253] Num frames 5700... | |
| [2025-02-25 11:51:29,799][00253] Num frames 5800... | |
| [2025-02-25 11:51:29,924][00253] Num frames 5900... | |
| [2025-02-25 11:51:30,052][00253] Num frames 6000... | |
| [2025-02-25 11:51:30,182][00253] Num frames 6100... | |
| [2025-02-25 11:51:30,314][00253] Num frames 6200... | |
| [2025-02-25 11:51:30,447][00253] Num frames 6300... | |
| [2025-02-25 11:51:30,584][00253] Num frames 6400... | |
| [2025-02-25 11:51:30,718][00253] Num frames 6500... | |
| [2025-02-25 11:51:30,851][00253] Avg episode rewards: #0: 24.432, true rewards: #0: 10.932 | |
| [2025-02-25 11:51:30,852][00253] Avg episode reward: 24.432, avg true_objective: 10.932 | |
| [2025-02-25 11:51:30,907][00253] Num frames 6600... | |
| [2025-02-25 11:51:31,037][00253] Num frames 6700... | |
| [2025-02-25 11:51:31,166][00253] Num frames 6800... | |
| [2025-02-25 11:51:31,293][00253] Num frames 6900... | |
| [2025-02-25 11:51:31,429][00253] Num frames 7000... | |
| [2025-02-25 11:51:31,560][00253] Num frames 7100... | |
| [2025-02-25 11:51:31,698][00253] Num frames 7200... | |
| [2025-02-25 11:51:31,825][00253] Num frames 7300... | |
| [2025-02-25 11:51:31,952][00253] Num frames 7400... | |
| [2025-02-25 11:51:32,079][00253] Num frames 7500... | |
| [2025-02-25 11:51:32,206][00253] Num frames 7600... | |
| [2025-02-25 11:51:32,335][00253] Num frames 7700... | |
| [2025-02-25 11:51:32,467][00253] Num frames 7800... | |
| [2025-02-25 11:51:32,532][00253] Avg episode rewards: #0: 25.439, true rewards: #0: 11.153 | |
| [2025-02-25 11:51:32,533][00253] Avg episode reward: 25.439, avg true_objective: 11.153 | |
| [2025-02-25 11:51:32,665][00253] Num frames 7900... | |
| [2025-02-25 11:51:32,795][00253] Num frames 8000... | |
| [2025-02-25 11:51:32,925][00253] Num frames 8100... | |
| [2025-02-25 11:51:33,054][00253] Num frames 8200... | |
| [2025-02-25 11:51:33,184][00253] Num frames 8300... | |
| [2025-02-25 11:51:33,316][00253] Num frames 8400... | |
| [2025-02-25 11:51:33,453][00253] Num frames 8500... | |
| [2025-02-25 11:51:33,584][00253] Num frames 8600... | |
| [2025-02-25 11:51:33,726][00253] Num frames 8700... | |
| [2025-02-25 11:51:33,856][00253] Num frames 8800... | |
| [2025-02-25 11:51:33,993][00253] Num frames 8900... | |
| [2025-02-25 11:51:34,121][00253] Num frames 9000... | |
| [2025-02-25 11:51:34,248][00253] Num frames 9100... | |
| [2025-02-25 11:51:34,377][00253] Num frames 9200... | |
| [2025-02-25 11:51:34,508][00253] Num frames 9300... | |
| [2025-02-25 11:51:34,637][00253] Num frames 9400... | |
| [2025-02-25 11:51:34,777][00253] Num frames 9500... | |
| [2025-02-25 11:51:34,841][00253] Avg episode rewards: #0: 28.132, true rewards: #0: 11.882 | |
| [2025-02-25 11:51:34,842][00253] Avg episode reward: 28.132, avg true_objective: 11.882 | |
| [2025-02-25 11:51:34,960][00253] Num frames 9600... | |
| [2025-02-25 11:51:35,088][00253] Num frames 9700... | |
| [2025-02-25 11:51:35,216][00253] Num frames 9800... | |
| [2025-02-25 11:51:35,346][00253] Num frames 9900... | |
| [2025-02-25 11:51:35,477][00253] Num frames 10000... | |
| [2025-02-25 11:51:35,605][00253] Num frames 10100... | |
| [2025-02-25 11:51:35,747][00253] Num frames 10200... | |
| [2025-02-25 11:51:35,878][00253] Num frames 10300... | |
| [2025-02-25 11:51:36,009][00253] Num frames 10400... | |
| [2025-02-25 11:51:36,138][00253] Num frames 10500... | |
| [2025-02-25 11:51:36,265][00253] Num frames 10600... | |
| [2025-02-25 11:51:36,354][00253] Avg episode rewards: #0: 27.473, true rewards: #0: 11.807 | |
| [2025-02-25 11:51:36,355][00253] Avg episode reward: 27.473, avg true_objective: 11.807 | |
| [2025-02-25 11:51:36,449][00253] Num frames 10700... | |
| [2025-02-25 11:51:36,578][00253] Num frames 10800... | |
| [2025-02-25 11:51:36,708][00253] Num frames 10900... | |
| [2025-02-25 11:51:36,841][00253] Num frames 11000... | |
| [2025-02-25 11:51:36,964][00253] Num frames 11100... | |
| [2025-02-25 11:51:37,093][00253] Num frames 11200... | |
| [2025-02-25 11:51:37,220][00253] Num frames 11300... | |
| [2025-02-25 11:51:37,355][00253] Num frames 11400... | |
| [2025-02-25 11:51:37,520][00253] Num frames 11500... | |
| [2025-02-25 11:51:37,698][00253] Num frames 11600... | |
| [2025-02-25 11:51:37,879][00253] Num frames 11700... | |
| [2025-02-25 11:51:38,046][00253] Num frames 11800... | |
| [2025-02-25 11:51:38,217][00253] Num frames 11900... | |
| [2025-02-25 11:51:38,391][00253] Num frames 12000... | |
| [2025-02-25 11:51:38,562][00253] Num frames 12100... | |
| [2025-02-25 11:51:38,738][00253] Num frames 12200... | |
| [2025-02-25 11:51:38,929][00253] Num frames 12300... | |
| [2025-02-25 11:51:39,100][00253] Num frames 12400... | |
| [2025-02-25 11:51:39,296][00253] Num frames 12500... | |
| [2025-02-25 11:51:39,480][00253] Num frames 12600... | |
| [2025-02-25 11:51:39,669][00253] Num frames 12700... | |
| [2025-02-25 11:51:39,759][00253] Avg episode rewards: #0: 30.326, true rewards: #0: 12.726 | |
| [2025-02-25 11:51:39,760][00253] Avg episode reward: 30.326, avg true_objective: 12.726 | |
| [2025-02-25 11:52:54,804][00253] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |
| [2025-02-25 11:52:55,588][00253] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json | |
| [2025-02-25 11:52:55,591][00253] Overriding arg 'num_workers' with value 1 passed from command line | |
| [2025-02-25 11:52:55,593][00253] Adding new argument 'no_render'=True that is not in the saved config file! | |
| [2025-02-25 11:52:55,595][00253] Adding new argument 'save_video'=True that is not in the saved config file! | |
| [2025-02-25 11:52:55,596][00253] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! | |
| [2025-02-25 11:52:55,598][00253] Adding new argument 'video_name'=None that is not in the saved config file! | |
| [2025-02-25 11:52:55,599][00253] Adding new argument 'max_num_frames'=100000 that is not in the saved config file! | |
| [2025-02-25 11:52:55,601][00253] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! | |
| [2025-02-25 11:52:55,602][00253] Adding new argument 'push_to_hub'=True that is not in the saved config file! | |
| [2025-02-25 11:52:55,604][00253] Adding new argument 'hf_repository'='sidsriv/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file! | |
| [2025-02-25 11:52:55,605][00253] Adding new argument 'policy_index'=0 that is not in the saved config file! | |
| [2025-02-25 11:52:55,606][00253] Adding new argument 'eval_deterministic'=False that is not in the saved config file! | |
| [2025-02-25 11:52:55,608][00253] Adding new argument 'train_script'=None that is not in the saved config file! | |
| [2025-02-25 11:52:55,609][00253] Adding new argument 'enjoy_script'=None that is not in the saved config file! | |
| [2025-02-25 11:52:55,611][00253] Using frameskip 1 and render_action_repeat=4 for evaluation | |
| [2025-02-25 11:52:55,666][00253] RunningMeanStd input shape: (3, 72, 128) | |
| [2025-02-25 11:52:55,670][00253] RunningMeanStd input shape: (1,) | |
| [2025-02-25 11:52:55,700][00253] ConvEncoder: input_channels=3 | |
| [2025-02-25 11:52:55,784][00253] Conv encoder output size: 512 | |
| [2025-02-25 11:52:55,785][00253] Policy head output size: 512 | |
| [2025-02-25 11:52:55,822][00253] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001222_5005312.pth... | |
| [2025-02-25 11:52:56,554][00253] Num frames 100... | |
| [2025-02-25 11:52:56,748][00253] Num frames 200... | |
| [2025-02-25 11:52:56,913][00253] Num frames 300... | |
| [2025-02-25 11:52:57,070][00253] Num frames 400... | |
| [2025-02-25 11:52:57,228][00253] Num frames 500... | |
| [2025-02-25 11:52:57,396][00253] Num frames 600... | |
| [2025-02-25 11:52:57,550][00253] Num frames 700... | |
| [2025-02-25 11:52:57,724][00253] Num frames 800... | |
| [2025-02-25 11:52:57,884][00253] Num frames 900... | |
| [2025-02-25 11:52:58,094][00253] Avg episode rewards: #0: 17.920, true rewards: #0: 9.920 | |
| [2025-02-25 11:52:58,095][00253] Avg episode reward: 17.920, avg true_objective: 9.920 | |
| [2025-02-25 11:52:58,109][00253] Num frames 1000... | |
| [2025-02-25 11:52:58,264][00253] Num frames 1100... | |
| [2025-02-25 11:52:58,420][00253] Num frames 1200... | |
| [2025-02-25 11:52:58,578][00253] Num frames 1300... | |
| [2025-02-25 11:52:58,753][00253] Num frames 1400... | |
| [2025-02-25 11:52:58,915][00253] Num frames 1500... | |
| [2025-02-25 11:52:59,082][00253] Num frames 1600... | |
| [2025-02-25 11:52:59,293][00253] Avg episode rewards: #0: 15.980, true rewards: #0: 8.480 | |
| [2025-02-25 11:52:59,294][00253] Avg episode reward: 15.980, avg true_objective: 8.480 | |
| [2025-02-25 11:52:59,304][00253] Num frames 1700... | |
| [2025-02-25 11:52:59,484][00253] Num frames 1800... | |
| [2025-02-25 11:52:59,676][00253] Num frames 1900... | |
| [2025-02-25 11:52:59,843][00253] Num frames 2000... | |
| [2025-02-25 11:53:00,021][00253] Num frames 2100... | |
| [2025-02-25 11:53:00,155][00253] Num frames 2200... | |
| [2025-02-25 11:53:00,284][00253] Num frames 2300... | |
| [2025-02-25 11:53:00,416][00253] Num frames 2400... | |
| [2025-02-25 11:53:00,547][00253] Num frames 2500... | |
| [2025-02-25 11:53:00,708][00253] Num frames 2600... | |
| [2025-02-25 11:53:00,836][00253] Num frames 2700... | |
| [2025-02-25 11:53:00,962][00253] Num frames 2800... | |
| [2025-02-25 11:53:01,091][00253] Num frames 2900... | |
| [2025-02-25 11:53:01,203][00253] Avg episode rewards: #0: 20.147, true rewards: #0: 9.813 | |
| [2025-02-25 11:53:01,204][00253] Avg episode reward: 20.147, avg true_objective: 9.813 | |
| [2025-02-25 11:53:01,278][00253] Num frames 3000... | |
| [2025-02-25 11:53:01,405][00253] Num frames 3100... | |
| [2025-02-25 11:53:01,531][00253] Num frames 3200... | |
| [2025-02-25 11:53:01,664][00253] Num frames 3300... | |
| [2025-02-25 11:53:01,800][00253] Num frames 3400... | |
| [2025-02-25 11:53:01,927][00253] Num frames 3500... | |
| [2025-02-25 11:53:02,055][00253] Num frames 3600... | |
| [2025-02-25 11:53:02,188][00253] Num frames 3700... | |
| [2025-02-25 11:53:02,315][00253] Num frames 3800... | |
| [2025-02-25 11:53:02,446][00253] Num frames 3900... | |
| [2025-02-25 11:53:02,577][00253] Num frames 4000... | |
| [2025-02-25 11:53:02,673][00253] Avg episode rewards: #0: 21.080, true rewards: #0: 10.080 | |
| [2025-02-25 11:53:02,674][00253] Avg episode reward: 21.080, avg true_objective: 10.080 | |
| [2025-02-25 11:53:02,769][00253] Num frames 4100... | |
| [2025-02-25 11:53:02,894][00253] Num frames 4200... | |
| [2025-02-25 11:53:03,027][00253] Num frames 4300... | |
| [2025-02-25 11:53:03,156][00253] Num frames 4400... | |
| [2025-02-25 11:53:03,281][00253] Num frames 4500... | |
| [2025-02-25 11:53:03,409][00253] Num frames 4600... | |
| [2025-02-25 11:53:03,474][00253] Avg episode rewards: #0: 19.216, true rewards: #0: 9.216 | |
| [2025-02-25 11:53:03,475][00253] Avg episode reward: 19.216, avg true_objective: 9.216 | |
| [2025-02-25 11:53:03,593][00253] Num frames 4700... | |
| [2025-02-25 11:53:03,727][00253] Num frames 4800... | |
| [2025-02-25 11:53:03,876][00253] Num frames 4900... | |
| [2025-02-25 11:53:04,022][00253] Num frames 5000... | |
| [2025-02-25 11:53:04,161][00253] Num frames 5100... | |
| [2025-02-25 11:53:04,305][00253] Num frames 5200... | |
| [2025-02-25 11:53:04,450][00253] Num frames 5300... | |
| [2025-02-25 11:53:04,601][00253] Num frames 5400... | |
| [2025-02-25 11:53:04,745][00253] Num frames 5500... | |
| [2025-02-25 11:53:04,886][00253] Num frames 5600... | |
| [2025-02-25 11:53:05,022][00253] Num frames 5700... | |
| [2025-02-25 11:53:05,166][00253] Num frames 5800... | |
| [2025-02-25 11:53:05,302][00253] Num frames 5900... | |
| [2025-02-25 11:53:05,428][00253] Num frames 6000... | |
| [2025-02-25 11:53:05,573][00253] Num frames 6100... | |
| [2025-02-25 11:53:05,735][00253] Avg episode rewards: #0: 22.793, true rewards: #0: 10.293 | |
| [2025-02-25 11:53:05,736][00253] Avg episode reward: 22.793, avg true_objective: 10.293 | |
| [2025-02-25 11:53:05,771][00253] Num frames 6200... | |
| [2025-02-25 11:53:05,913][00253] Num frames 6300... | |
| [2025-02-25 11:53:06,153][00253] Num frames 6400... | |
| [2025-02-25 11:53:06,380][00253] Num frames 6500... | |
| [2025-02-25 11:53:06,549][00253] Num frames 6600... | |
| [2025-02-25 11:53:06,727][00253] Num frames 6700... | |
| [2025-02-25 11:53:06,914][00253] Num frames 6800... | |
| [2025-02-25 11:53:07,082][00253] Num frames 6900... | |
| [2025-02-25 11:53:07,255][00253] Num frames 7000... | |
| [2025-02-25 11:53:07,449][00253] Num frames 7100... | |
| [2025-02-25 11:53:07,633][00253] Num frames 7200... | |
| [2025-02-25 11:53:07,809][00253] Num frames 7300... | |
| [2025-02-25 11:53:07,998][00253] Num frames 7400... | |
| [2025-02-25 11:53:08,208][00253] Num frames 7500... | |
| [2025-02-25 11:53:08,350][00253] Num frames 7600... | |
| [2025-02-25 11:53:08,490][00253] Num frames 7700... | |
| [2025-02-25 11:53:08,627][00253] Num frames 7800... | |
| [2025-02-25 11:53:08,769][00253] Num frames 7900... | |
| [2025-02-25 11:53:08,905][00253] Num frames 8000... | |
| [2025-02-25 11:53:08,957][00253] Avg episode rewards: #0: 27.000, true rewards: #0: 11.429 | |
| [2025-02-25 11:53:08,959][00253] Avg episode reward: 27.000, avg true_objective: 11.429 | |
| [2025-02-25 11:53:09,089][00253] Num frames 8100... | |
| [2025-02-25 11:53:09,217][00253] Num frames 8200... | |
| [2025-02-25 11:53:09,346][00253] Num frames 8300... | |
| [2025-02-25 11:53:09,477][00253] Num frames 8400... | |
| [2025-02-25 11:53:09,604][00253] Num frames 8500... | |
| [2025-02-25 11:53:09,737][00253] Num frames 8600... | |
| [2025-02-25 11:53:09,864][00253] Num frames 8700... | |
| [2025-02-25 11:53:10,000][00253] Num frames 8800... | |
| [2025-02-25 11:53:10,160][00253] Num frames 8900... | |
| [2025-02-25 11:53:10,288][00253] Num frames 9000... | |
| [2025-02-25 11:53:10,418][00253] Num frames 9100... | |
| [2025-02-25 11:53:10,552][00253] Num frames 9200... | |
| [2025-02-25 11:53:10,694][00253] Num frames 9300... | |
| [2025-02-25 11:53:10,831][00253] Num frames 9400... | |
| [2025-02-25 11:53:10,961][00253] Num frames 9500... | |
| [2025-02-25 11:53:11,024][00253] Avg episode rewards: #0: 29.002, true rewards: #0: 11.877 | |
| [2025-02-25 11:53:11,025][00253] Avg episode reward: 29.002, avg true_objective: 11.877 | |
| [2025-02-25 11:53:11,150][00253] Num frames 9600... | |
| [2025-02-25 11:53:11,280][00253] Num frames 9700... | |
| [2025-02-25 11:53:11,405][00253] Num frames 9800... | |
| [2025-02-25 11:53:11,535][00253] Num frames 9900... | |
| [2025-02-25 11:53:11,666][00253] Num frames 10000... | |
| [2025-02-25 11:53:11,793][00253] Num frames 10100... | |
| [2025-02-25 11:53:11,915][00253] Num frames 10200... | |
| [2025-02-25 11:53:12,051][00253] Num frames 10300... | |
| [2025-02-25 11:53:12,168][00253] Avg episode rewards: #0: 27.718, true rewards: #0: 11.496 | |
| [2025-02-25 11:53:12,170][00253] Avg episode reward: 27.718, avg true_objective: 11.496 | |
| [2025-02-25 11:53:12,252][00253] Num frames 10400... | |
| [2025-02-25 11:53:12,399][00253] Num frames 10500... | |
| [2025-02-25 11:53:12,528][00253] Num frames 10600... | |
| [2025-02-25 11:53:12,657][00253] Num frames 10700... | |
| [2025-02-25 11:53:12,788][00253] Num frames 10800... | |
| [2025-02-25 11:53:12,921][00253] Num frames 10900... | |
| [2025-02-25 11:53:13,056][00253] Num frames 11000... | |
| [2025-02-25 11:53:13,182][00253] Num frames 11100... | |
| [2025-02-25 11:53:13,311][00253] Num frames 11200... | |
| [2025-02-25 11:53:13,441][00253] Num frames 11300... | |
| [2025-02-25 11:53:13,567][00253] Num frames 11400... | |
| [2025-02-25 11:53:13,752][00253] Avg episode rewards: #0: 27.298, true rewards: #0: 11.498 | |
| [2025-02-25 11:53:13,754][00253] Avg episode reward: 27.298, avg true_objective: 11.498 | |
| [2025-02-25 11:53:13,758][00253] Num frames 11500... | |
| [2025-02-25 11:54:23,647][00253] Replay video saved to /content/train_dir/default_experiment/replay.mp4! | |