[2023-02-23 20:07:09,899][00631] Saving configuration to /content/train_dir/default_experiment/config.json... [2023-02-23 20:07:09,904][00631] Rollout worker 0 uses device cpu [2023-02-23 20:07:09,905][00631] Rollout worker 1 uses device cpu [2023-02-23 20:07:09,909][00631] Rollout worker 2 uses device cpu [2023-02-23 20:07:09,910][00631] Rollout worker 3 uses device cpu [2023-02-23 20:07:09,914][00631] Rollout worker 4 uses device cpu [2023-02-23 20:07:09,917][00631] Rollout worker 5 uses device cpu [2023-02-23 20:07:09,918][00631] Rollout worker 6 uses device cpu [2023-02-23 20:07:09,922][00631] Rollout worker 7 uses device cpu [2023-02-23 20:07:10,107][00631] Using GPUs [0] for process 0 (actually maps to GPUs [0]) [2023-02-23 20:07:10,109][00631] InferenceWorker_p0-w0: min num requests: 2 [2023-02-23 20:07:10,141][00631] Starting all processes... [2023-02-23 20:07:10,143][00631] Starting process learner_proc0 [2023-02-23 20:07:10,205][00631] Starting all processes... [2023-02-23 20:07:10,214][00631] Starting process inference_proc0-0 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc0 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc1 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc2 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc3 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc4 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc5 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc6 [2023-02-23 20:07:10,215][00631] Starting process rollout_proc7 [2023-02-23 20:07:23,376][10905] Worker 6 uses CPU cores [0] [2023-02-23 20:07:23,521][10899] Worker 0 uses CPU cores [0] [2023-02-23 20:07:23,659][10900] Worker 1 uses CPU cores [1] [2023-02-23 20:07:23,824][10906] Worker 7 uses CPU cores [1] [2023-02-23 20:07:23,854][10884] Using GPUs [0] for process 0 (actually maps to GPUs [0]) [2023-02-23 20:07:23,854][10884] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0 [2023-02-23 20:07:23,867][10904] Worker 5 uses CPU cores [1] [2023-02-23 20:07:24,010][10902] Worker 3 uses CPU cores [1] [2023-02-23 20:07:24,014][10898] Using GPUs [0] for process 0 (actually maps to GPUs [0]) [2023-02-23 20:07:24,015][10898] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0 [2023-02-23 20:07:24,056][10901] Worker 2 uses CPU cores [0] [2023-02-23 20:07:24,128][10903] Worker 4 uses CPU cores [0] [2023-02-23 20:07:24,580][10898] Num visible devices: 1 [2023-02-23 20:07:24,580][10884] Num visible devices: 1 [2023-02-23 20:07:24,596][10884] Starting seed is not provided [2023-02-23 20:07:24,598][10884] Using GPUs [0] for process 0 (actually maps to GPUs [0]) [2023-02-23 20:07:24,599][10884] Initializing actor-critic model on device cuda:0 [2023-02-23 20:07:24,600][10884] RunningMeanStd input shape: (3, 72, 128) [2023-02-23 20:07:24,603][10884] RunningMeanStd input shape: (1,) [2023-02-23 20:07:24,649][10884] ConvEncoder: input_channels=3 [2023-02-23 20:07:25,151][10884] Conv encoder output size: 512 [2023-02-23 20:07:25,151][10884] Policy head output size: 512 [2023-02-23 20:07:25,227][10884] Created Actor Critic model with architecture: [2023-02-23 20:07:25,228][10884] 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) ) ) [2023-02-23 20:07:30,100][00631] Heartbeat connected on Batcher_0 [2023-02-23 20:07:30,108][00631] Heartbeat connected on InferenceWorker_p0-w0 [2023-02-23 20:07:30,117][00631] Heartbeat connected on RolloutWorker_w0 [2023-02-23 20:07:30,122][00631] Heartbeat connected on RolloutWorker_w1 [2023-02-23 20:07:30,125][00631] Heartbeat connected on RolloutWorker_w2 [2023-02-23 20:07:30,129][00631] Heartbeat connected on RolloutWorker_w3 [2023-02-23 20:07:30,133][00631] Heartbeat connected on RolloutWorker_w4 [2023-02-23 20:07:30,134][00631] Heartbeat connected on RolloutWorker_w5 [2023-02-23 20:07:30,137][00631] Heartbeat connected on RolloutWorker_w6 [2023-02-23 20:07:30,141][00631] Heartbeat connected on RolloutWorker_w7 [2023-02-23 20:07:32,608][10884] Using optimizer [2023-02-23 20:07:32,609][10884] No checkpoints found [2023-02-23 20:07:32,609][10884] Did not load from checkpoint, starting from scratch! [2023-02-23 20:07:32,610][10884] Initialized policy 0 weights for model version 0 [2023-02-23 20:07:32,614][10884] Using GPUs [0] for process 0 (actually maps to GPUs [0]) [2023-02-23 20:07:32,622][10884] LearnerWorker_p0 finished initialization! [2023-02-23 20:07:32,623][00631] Heartbeat connected on LearnerWorker_p0 [2023-02-23 20:07:32,731][10898] RunningMeanStd input shape: (3, 72, 128) [2023-02-23 20:07:32,734][10898] RunningMeanStd input shape: (1,) [2023-02-23 20:07:32,747][10898] ConvEncoder: input_channels=3 [2023-02-23 20:07:32,855][10898] Conv encoder output size: 512 [2023-02-23 20:07:32,856][10898] Policy head output size: 512 [2023-02-23 20:07:35,197][00631] 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) [2023-02-23 20:07:35,879][00631] Inference worker 0-0 is ready! [2023-02-23 20:07:35,883][00631] All inference workers are ready! Signal rollout workers to start! [2023-02-23 20:07:36,064][10905] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:36,079][10902] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:36,102][10906] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:36,108][10900] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:36,111][10904] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:36,108][10899] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:36,153][10903] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:36,173][10901] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:07:37,213][10902] Decorrelating experience for 0 frames... [2023-02-23 20:07:37,212][10906] Decorrelating experience for 0 frames... [2023-02-23 20:07:38,051][10905] Decorrelating experience for 0 frames... [2023-02-23 20:07:38,063][10899] Decorrelating experience for 0 frames... [2023-02-23 20:07:38,065][10903] Decorrelating experience for 0 frames... [2023-02-23 20:07:39,245][10900] Decorrelating experience for 0 frames... [2023-02-23 20:07:39,270][10906] Decorrelating experience for 32 frames... [2023-02-23 20:07:39,275][10902] Decorrelating experience for 32 frames... [2023-02-23 20:07:39,733][10901] Decorrelating experience for 0 frames... [2023-02-23 20:07:40,197][00631] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) [2023-02-23 20:07:40,350][10903] Decorrelating experience for 32 frames... [2023-02-23 20:07:40,361][10905] Decorrelating experience for 32 frames... [2023-02-23 20:07:40,477][10900] Decorrelating experience for 32 frames... [2023-02-23 20:07:40,746][10902] Decorrelating experience for 64 frames... [2023-02-23 20:07:40,770][10906] Decorrelating experience for 64 frames... [2023-02-23 20:07:41,084][10901] Decorrelating experience for 32 frames... [2023-02-23 20:07:41,103][10899] Decorrelating experience for 32 frames... [2023-02-23 20:07:41,623][10904] Decorrelating experience for 0 frames... [2023-02-23 20:07:41,643][10903] Decorrelating experience for 64 frames... [2023-02-23 20:07:41,893][10901] Decorrelating experience for 64 frames... [2023-02-23 20:07:41,937][10902] Decorrelating experience for 96 frames... [2023-02-23 20:07:42,383][10899] Decorrelating experience for 64 frames... [2023-02-23 20:07:42,409][10906] Decorrelating experience for 96 frames... [2023-02-23 20:07:43,085][10904] Decorrelating experience for 32 frames... [2023-02-23 20:07:43,165][10900] Decorrelating experience for 64 frames... [2023-02-23 20:07:43,223][10905] Decorrelating experience for 64 frames... [2023-02-23 20:07:43,287][10899] Decorrelating experience for 96 frames... [2023-02-23 20:07:44,376][10901] Decorrelating experience for 96 frames... [2023-02-23 20:07:44,539][10903] Decorrelating experience for 96 frames... [2023-02-23 20:07:44,593][10900] Decorrelating experience for 96 frames... [2023-02-23 20:07:44,638][10905] Decorrelating experience for 96 frames... [2023-02-23 20:07:44,702][10904] Decorrelating experience for 64 frames... [2023-02-23 20:07:45,140][10904] Decorrelating experience for 96 frames... [2023-02-23 20:07:45,197][00631] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) [2023-02-23 20:07:48,472][10884] Signal inference workers to stop experience collection... [2023-02-23 20:07:48,496][10898] InferenceWorker_p0-w0: stopping experience collection [2023-02-23 20:07:50,197][00631] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 121.1. Samples: 1816. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0) [2023-02-23 20:07:50,199][00631] Avg episode reward: [(0, '1.838')] [2023-02-23 20:07:51,154][10884] Signal inference workers to resume experience collection... [2023-02-23 20:07:51,155][10898] InferenceWorker_p0-w0: resuming experience collection [2023-02-23 20:07:55,197][00631] Fps is (10 sec: 1228.8, 60 sec: 614.4, 300 sec: 614.4). Total num frames: 12288. Throughput: 0: 157.2. Samples: 3144. Policy #0 lag: (min: 1.0, avg: 1.0, max: 1.0) [2023-02-23 20:07:55,207][00631] Avg episode reward: [(0, '2.943')] [2023-02-23 20:08:00,197][00631] Fps is (10 sec: 2867.1, 60 sec: 1146.9, 300 sec: 1146.9). Total num frames: 28672. Throughput: 0: 298.8. Samples: 7470. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) [2023-02-23 20:08:00,199][00631] Avg episode reward: [(0, '3.638')] [2023-02-23 20:08:03,235][10898] Updated weights for policy 0, policy_version 10 (0.0013) [2023-02-23 20:08:05,197][00631] Fps is (10 sec: 3686.4, 60 sec: 1638.4, 300 sec: 1638.4). Total num frames: 49152. Throughput: 0: 351.5. Samples: 10546. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:08:05,203][00631] Avg episode reward: [(0, '4.272')] [2023-02-23 20:08:10,197][00631] Fps is (10 sec: 3686.4, 60 sec: 1872.4, 300 sec: 1872.4). Total num frames: 65536. Throughput: 0: 475.9. Samples: 16658. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:08:10,204][00631] Avg episode reward: [(0, '4.529')] [2023-02-23 20:08:14,880][10898] Updated weights for policy 0, policy_version 20 (0.0015) [2023-02-23 20:08:15,200][00631] Fps is (10 sec: 3275.7, 60 sec: 2047.8, 300 sec: 2047.8). Total num frames: 81920. Throughput: 0: 516.6. Samples: 20664. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) [2023-02-23 20:08:15,205][00631] Avg episode reward: [(0, '4.487')] [2023-02-23 20:08:20,197][00631] Fps is (10 sec: 2867.3, 60 sec: 2093.5, 300 sec: 2093.5). Total num frames: 94208. Throughput: 0: 496.9. Samples: 22360. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) [2023-02-23 20:08:20,200][00631] Avg episode reward: [(0, '4.356')] [2023-02-23 20:08:25,197][00631] Fps is (10 sec: 3277.9, 60 sec: 2293.8, 300 sec: 2293.8). Total num frames: 114688. Throughput: 0: 621.7. Samples: 27978. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0) [2023-02-23 20:08:25,200][00631] Avg episode reward: [(0, '4.441')] [2023-02-23 20:08:25,214][10884] Saving new best policy, reward=4.441! [2023-02-23 20:08:26,759][10898] Updated weights for policy 0, policy_version 30 (0.0048) [2023-02-23 20:08:30,197][00631] Fps is (10 sec: 4095.9, 60 sec: 2457.6, 300 sec: 2457.6). Total num frames: 135168. Throughput: 0: 762.4. Samples: 34310. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) [2023-02-23 20:08:30,208][00631] Avg episode reward: [(0, '4.576')] [2023-02-23 20:08:30,211][10884] Saving new best policy, reward=4.576! [2023-02-23 20:08:35,199][00631] Fps is (10 sec: 3276.1, 60 sec: 2457.5, 300 sec: 2457.5). Total num frames: 147456. Throughput: 0: 765.1. Samples: 36248. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:08:35,206][00631] Avg episode reward: [(0, '4.420')] [2023-02-23 20:08:40,169][10898] Updated weights for policy 0, policy_version 40 (0.0032) [2023-02-23 20:08:40,198][00631] Fps is (10 sec: 2867.2, 60 sec: 2730.6, 300 sec: 2520.6). Total num frames: 163840. Throughput: 0: 825.3. Samples: 40284. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) [2023-02-23 20:08:40,201][00631] Avg episode reward: [(0, '4.371')] [2023-02-23 20:08:45,197][00631] Fps is (10 sec: 3277.4, 60 sec: 3003.7, 300 sec: 2574.6). Total num frames: 180224. Throughput: 0: 854.0. Samples: 45900. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:08:45,203][00631] Avg episode reward: [(0, '4.508')] [2023-02-23 20:08:50,197][00631] Fps is (10 sec: 3686.6, 60 sec: 3345.1, 300 sec: 2676.1). Total num frames: 200704. Throughput: 0: 856.6. Samples: 49092. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) [2023-02-23 20:08:50,200][00631] Avg episode reward: [(0, '4.616')] [2023-02-23 20:08:50,202][10884] Saving new best policy, reward=4.616! [2023-02-23 20:08:50,460][10898] Updated weights for policy 0, policy_version 50 (0.0019) [2023-02-23 20:08:55,199][00631] Fps is (10 sec: 3685.6, 60 sec: 3413.2, 300 sec: 2713.5). Total num frames: 217088. Throughput: 0: 836.6. Samples: 54308. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:08:55,203][00631] Avg episode reward: [(0, '4.502')] [2023-02-23 20:09:00,198][00631] Fps is (10 sec: 2867.0, 60 sec: 3345.1, 300 sec: 2698.5). Total num frames: 229376. Throughput: 0: 839.4. Samples: 58436. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:09:00,207][00631] Avg episode reward: [(0, '4.571')] [2023-02-23 20:09:04,138][10898] Updated weights for policy 0, policy_version 60 (0.0016) [2023-02-23 20:09:05,197][00631] Fps is (10 sec: 3277.5, 60 sec: 3345.1, 300 sec: 2776.2). Total num frames: 249856. Throughput: 0: 853.1. Samples: 60748. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:09:05,203][00631] Avg episode reward: [(0, '4.345')] [2023-02-23 20:09:05,216][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000061_249856.pth... [2023-02-23 20:09:10,197][00631] Fps is (10 sec: 4096.2, 60 sec: 3413.3, 300 sec: 2845.6). Total num frames: 270336. Throughput: 0: 871.8. Samples: 67208. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:09:10,203][00631] Avg episode reward: [(0, '4.530')] [2023-02-23 20:09:14,370][10898] Updated weights for policy 0, policy_version 70 (0.0022) [2023-02-23 20:09:15,200][00631] Fps is (10 sec: 3685.2, 60 sec: 3413.3, 300 sec: 2867.1). Total num frames: 286720. Throughput: 0: 850.1. Samples: 72568. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:09:15,206][00631] Avg episode reward: [(0, '4.589')] [2023-02-23 20:09:20,202][00631] Fps is (10 sec: 3275.1, 60 sec: 3481.3, 300 sec: 2886.6). Total num frames: 303104. Throughput: 0: 852.0. Samples: 74592. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:09:20,211][00631] Avg episode reward: [(0, '4.404')] [2023-02-23 20:09:25,197][00631] Fps is (10 sec: 3277.9, 60 sec: 3413.3, 300 sec: 2904.4). Total num frames: 319488. Throughput: 0: 860.7. Samples: 79016. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:09:25,200][00631] Avg episode reward: [(0, '4.316')] [2023-02-23 20:09:27,001][10898] Updated weights for policy 0, policy_version 80 (0.0036) [2023-02-23 20:09:30,197][00631] Fps is (10 sec: 3688.3, 60 sec: 3413.3, 300 sec: 2956.2). Total num frames: 339968. Throughput: 0: 876.9. Samples: 85360. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:09:30,205][00631] Avg episode reward: [(0, '4.337')] [2023-02-23 20:09:35,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.7, 300 sec: 2969.6). Total num frames: 356352. Throughput: 0: 874.4. Samples: 88440. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:09:35,207][00631] Avg episode reward: [(0, '4.448')] [2023-02-23 20:09:38,850][10898] Updated weights for policy 0, policy_version 90 (0.0017) [2023-02-23 20:09:40,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.4, 300 sec: 2949.1). Total num frames: 368640. Throughput: 0: 852.4. Samples: 92662. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:09:40,203][00631] Avg episode reward: [(0, '4.534')] [2023-02-23 20:09:45,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 2961.7). Total num frames: 385024. Throughput: 0: 855.7. Samples: 96944. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:09:45,205][00631] Avg episode reward: [(0, '4.616')] [2023-02-23 20:09:50,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3003.7). Total num frames: 405504. Throughput: 0: 873.1. Samples: 100038. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:09:50,200][00631] Avg episode reward: [(0, '4.444')] [2023-02-23 20:09:50,756][10898] Updated weights for policy 0, policy_version 100 (0.0015) [2023-02-23 20:09:55,197][00631] Fps is (10 sec: 4096.1, 60 sec: 3481.7, 300 sec: 3042.7). Total num frames: 425984. Throughput: 0: 872.4. Samples: 106464. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:09:55,199][00631] Avg episode reward: [(0, '4.345')] [2023-02-23 20:10:00,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3050.8). Total num frames: 442368. Throughput: 0: 849.7. Samples: 110802. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:10:00,204][00631] Avg episode reward: [(0, '4.354')] [2023-02-23 20:10:03,245][10898] Updated weights for policy 0, policy_version 110 (0.0027) [2023-02-23 20:10:05,198][00631] Fps is (10 sec: 2866.9, 60 sec: 3413.3, 300 sec: 3031.0). Total num frames: 454656. Throughput: 0: 850.3. Samples: 112852. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:10:05,208][00631] Avg episode reward: [(0, '4.361')] [2023-02-23 20:10:10,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3065.4). Total num frames: 475136. Throughput: 0: 875.2. Samples: 118398. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:10:10,200][00631] Avg episode reward: [(0, '4.567')] [2023-02-23 20:10:13,829][10898] Updated weights for policy 0, policy_version 120 (0.0013) [2023-02-23 20:10:15,197][00631] Fps is (10 sec: 4096.4, 60 sec: 3481.8, 300 sec: 3097.6). Total num frames: 495616. Throughput: 0: 872.6. Samples: 124628. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:10:15,200][00631] Avg episode reward: [(0, '4.658')] [2023-02-23 20:10:15,212][10884] Saving new best policy, reward=4.658! [2023-02-23 20:10:20,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.6, 300 sec: 3078.2). Total num frames: 507904. Throughput: 0: 850.3. Samples: 126704. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:10:20,205][00631] Avg episode reward: [(0, '4.765')] [2023-02-23 20:10:20,214][10884] Saving new best policy, reward=4.765! [2023-02-23 20:10:25,197][00631] Fps is (10 sec: 2457.5, 60 sec: 3345.1, 300 sec: 3059.9). Total num frames: 520192. Throughput: 0: 844.5. Samples: 130664. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:10:25,201][00631] Avg episode reward: [(0, '4.671')] [2023-02-23 20:10:27,821][10898] Updated weights for policy 0, policy_version 130 (0.0022) [2023-02-23 20:10:30,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3345.1, 300 sec: 3089.6). Total num frames: 540672. Throughput: 0: 868.4. Samples: 136020. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:10:30,201][00631] Avg episode reward: [(0, '4.472')] [2023-02-23 20:10:35,201][00631] Fps is (10 sec: 3275.6, 60 sec: 3276.6, 300 sec: 3071.9). Total num frames: 552960. Throughput: 0: 845.4. Samples: 138084. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:10:35,215][00631] Avg episode reward: [(0, '4.431')] [2023-02-23 20:10:40,198][00631] Fps is (10 sec: 2457.5, 60 sec: 3276.8, 300 sec: 3055.4). Total num frames: 565248. Throughput: 0: 784.3. Samples: 141758. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:10:40,201][00631] Avg episode reward: [(0, '4.522')] [2023-02-23 20:10:42,980][10898] Updated weights for policy 0, policy_version 140 (0.0016) [2023-02-23 20:10:45,197][00631] Fps is (10 sec: 2458.5, 60 sec: 3208.5, 300 sec: 3039.7). Total num frames: 577536. Throughput: 0: 763.6. Samples: 145162. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:10:45,199][00631] Avg episode reward: [(0, '4.514')] [2023-02-23 20:10:50,203][00631] Fps is (10 sec: 2456.2, 60 sec: 3071.7, 300 sec: 3024.6). Total num frames: 589824. Throughput: 0: 763.0. Samples: 147192. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:10:50,209][00631] Avg episode reward: [(0, '4.530')] [2023-02-23 20:10:55,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3072.0, 300 sec: 3051.5). Total num frames: 610304. Throughput: 0: 768.0. Samples: 152958. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:10:55,203][00631] Avg episode reward: [(0, '4.299')] [2023-02-23 20:10:55,221][10898] Updated weights for policy 0, policy_version 150 (0.0014) [2023-02-23 20:11:00,197][00631] Fps is (10 sec: 4508.5, 60 sec: 3208.5, 300 sec: 3097.0). Total num frames: 634880. Throughput: 0: 770.0. Samples: 159280. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:11:00,202][00631] Avg episode reward: [(0, '4.356')] [2023-02-23 20:11:05,202][00631] Fps is (10 sec: 3684.6, 60 sec: 3208.3, 300 sec: 3081.7). Total num frames: 647168. Throughput: 0: 768.7. Samples: 161298. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:11:05,207][00631] Avg episode reward: [(0, '4.429')] [2023-02-23 20:11:05,225][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000158_647168.pth... [2023-02-23 20:11:07,728][10898] Updated weights for policy 0, policy_version 160 (0.0017) [2023-02-23 20:11:10,197][00631] Fps is (10 sec: 2457.5, 60 sec: 3072.0, 300 sec: 3067.2). Total num frames: 659456. Throughput: 0: 768.6. Samples: 165252. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:11:10,203][00631] Avg episode reward: [(0, '4.523')] [2023-02-23 20:11:15,197][00631] Fps is (10 sec: 3278.4, 60 sec: 3072.0, 300 sec: 3090.6). Total num frames: 679936. Throughput: 0: 776.7. Samples: 170970. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:11:15,202][00631] Avg episode reward: [(0, '4.324')] [2023-02-23 20:11:18,130][10898] Updated weights for policy 0, policy_version 170 (0.0018) [2023-02-23 20:11:20,197][00631] Fps is (10 sec: 4505.7, 60 sec: 3276.8, 300 sec: 3131.2). Total num frames: 704512. Throughput: 0: 804.4. Samples: 174278. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:11:20,199][00631] Avg episode reward: [(0, '4.448')] [2023-02-23 20:11:25,197][00631] Fps is (10 sec: 3686.3, 60 sec: 3276.8, 300 sec: 3116.5). Total num frames: 716800. Throughput: 0: 840.7. Samples: 179588. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:11:25,201][00631] Avg episode reward: [(0, '4.455')] [2023-02-23 20:11:30,200][00631] Fps is (10 sec: 2456.9, 60 sec: 3140.1, 300 sec: 3102.5). Total num frames: 729088. Throughput: 0: 856.6. Samples: 183712. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:11:30,203][00631] Avg episode reward: [(0, '4.417')] [2023-02-23 20:11:31,780][10898] Updated weights for policy 0, policy_version 180 (0.0019) [2023-02-23 20:11:35,197][00631] Fps is (10 sec: 3276.9, 60 sec: 3277.0, 300 sec: 3123.2). Total num frames: 749568. Throughput: 0: 866.4. Samples: 186174. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:11:35,205][00631] Avg episode reward: [(0, '4.640')] [2023-02-23 20:11:40,197][00631] Fps is (10 sec: 4097.1, 60 sec: 3413.4, 300 sec: 3143.1). Total num frames: 770048. Throughput: 0: 879.9. Samples: 192552. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:11:40,203][00631] Avg episode reward: [(0, '4.894')] [2023-02-23 20:11:40,277][10884] Saving new best policy, reward=4.894! [2023-02-23 20:11:41,344][10898] Updated weights for policy 0, policy_version 190 (0.0023) [2023-02-23 20:11:45,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3145.7). Total num frames: 786432. Throughput: 0: 853.8. Samples: 197702. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:11:45,204][00631] Avg episode reward: [(0, '4.931')] [2023-02-23 20:11:45,213][10884] Saving new best policy, reward=4.931! [2023-02-23 20:11:50,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3550.2, 300 sec: 3148.3). Total num frames: 802816. Throughput: 0: 851.9. Samples: 199628. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:11:50,204][00631] Avg episode reward: [(0, '4.898')] [2023-02-23 20:11:54,983][10898] Updated weights for policy 0, policy_version 200 (0.0012) [2023-02-23 20:11:55,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3150.8). Total num frames: 819200. Throughput: 0: 865.0. Samples: 204176. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:11:55,205][00631] Avg episode reward: [(0, '4.655')] [2023-02-23 20:12:00,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3168.6). Total num frames: 839680. Throughput: 0: 881.2. Samples: 210626. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:12:00,199][00631] Avg episode reward: [(0, '4.388')] [2023-02-23 20:12:05,200][00631] Fps is (10 sec: 3685.2, 60 sec: 3481.7, 300 sec: 3170.6). Total num frames: 856064. Throughput: 0: 878.8. Samples: 213826. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:12:05,203][00631] Avg episode reward: [(0, '4.440')] [2023-02-23 20:12:05,646][10898] Updated weights for policy 0, policy_version 210 (0.0017) [2023-02-23 20:12:10,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3172.5). Total num frames: 872448. Throughput: 0: 852.6. Samples: 217954. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:12:10,207][00631] Avg episode reward: [(0, '4.498')] [2023-02-23 20:12:15,197][00631] Fps is (10 sec: 2868.1, 60 sec: 3413.3, 300 sec: 3159.8). Total num frames: 884736. Throughput: 0: 858.1. Samples: 222326. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:12:15,205][00631] Avg episode reward: [(0, '4.423')] [2023-02-23 20:12:18,321][10898] Updated weights for policy 0, policy_version 220 (0.0021) [2023-02-23 20:12:20,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3190.6). Total num frames: 909312. Throughput: 0: 875.2. Samples: 225558. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:12:20,200][00631] Avg episode reward: [(0, '4.270')] [2023-02-23 20:12:25,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3192.1). Total num frames: 925696. Throughput: 0: 876.8. Samples: 232008. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:12:25,208][00631] Avg episode reward: [(0, '4.430')] [2023-02-23 20:12:29,701][10898] Updated weights for policy 0, policy_version 230 (0.0018) [2023-02-23 20:12:30,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3193.5). Total num frames: 942080. Throughput: 0: 853.4. Samples: 236106. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:12:30,200][00631] Avg episode reward: [(0, '4.580')] [2023-02-23 20:12:35,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3235.1). Total num frames: 954368. Throughput: 0: 854.5. Samples: 238080. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:12:35,200][00631] Avg episode reward: [(0, '4.619')] [2023-02-23 20:12:40,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3304.6). Total num frames: 974848. Throughput: 0: 878.0. Samples: 243684. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:12:40,199][00631] Avg episode reward: [(0, '4.610')] [2023-02-23 20:12:41,351][10898] Updated weights for policy 0, policy_version 240 (0.0015) [2023-02-23 20:12:45,202][00631] Fps is (10 sec: 4093.8, 60 sec: 3481.3, 300 sec: 3373.9). Total num frames: 995328. Throughput: 0: 875.1. Samples: 250010. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:12:45,208][00631] Avg episode reward: [(0, '4.291')] [2023-02-23 20:12:50,199][00631] Fps is (10 sec: 3685.8, 60 sec: 3481.5, 300 sec: 3387.9). Total num frames: 1011712. Throughput: 0: 852.0. Samples: 252164. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:12:50,201][00631] Avg episode reward: [(0, '4.396')] [2023-02-23 20:12:54,572][10898] Updated weights for policy 0, policy_version 250 (0.0036) [2023-02-23 20:12:55,197][00631] Fps is (10 sec: 2868.7, 60 sec: 3413.3, 300 sec: 3374.0). Total num frames: 1024000. Throughput: 0: 850.5. Samples: 256226. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:12:55,200][00631] Avg episode reward: [(0, '4.492')] [2023-02-23 20:13:00,197][00631] Fps is (10 sec: 3277.3, 60 sec: 3413.3, 300 sec: 3374.0). Total num frames: 1044480. Throughput: 0: 874.1. Samples: 261662. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:13:00,200][00631] Avg episode reward: [(0, '4.709')] [2023-02-23 20:13:04,689][10898] Updated weights for policy 0, policy_version 260 (0.0019) [2023-02-23 20:13:05,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.8, 300 sec: 3387.9). Total num frames: 1064960. Throughput: 0: 871.6. Samples: 264778. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:13:05,202][00631] Avg episode reward: [(0, '4.515')] [2023-02-23 20:13:05,225][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000260_1064960.pth... [2023-02-23 20:13:05,375][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000061_249856.pth [2023-02-23 20:13:10,199][00631] Fps is (10 sec: 3685.7, 60 sec: 3481.5, 300 sec: 3387.9). Total num frames: 1081344. Throughput: 0: 845.4. Samples: 270052. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:13:10,211][00631] Avg episode reward: [(0, '4.467')] [2023-02-23 20:13:15,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3387.9). Total num frames: 1093632. Throughput: 0: 845.5. Samples: 274154. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:13:15,204][00631] Avg episode reward: [(0, '4.494')] [2023-02-23 20:13:18,419][10898] Updated weights for policy 0, policy_version 270 (0.0014) [2023-02-23 20:13:20,197][00631] Fps is (10 sec: 3277.5, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 1114112. Throughput: 0: 856.3. Samples: 276614. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:13:20,199][00631] Avg episode reward: [(0, '4.476')] [2023-02-23 20:13:25,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3387.9). Total num frames: 1134592. Throughput: 0: 877.5. Samples: 283172. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:13:25,200][00631] Avg episode reward: [(0, '4.752')] [2023-02-23 20:13:27,924][10898] Updated weights for policy 0, policy_version 280 (0.0014) [2023-02-23 20:13:30,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 1150976. Throughput: 0: 857.2. Samples: 288578. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:13:30,202][00631] Avg episode reward: [(0, '4.749')] [2023-02-23 20:13:35,197][00631] Fps is (10 sec: 2867.1, 60 sec: 3481.6, 300 sec: 3387.9). Total num frames: 1163264. Throughput: 0: 855.2. Samples: 290648. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:13:35,200][00631] Avg episode reward: [(0, '4.833')] [2023-02-23 20:13:40,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 1183744. Throughput: 0: 866.5. Samples: 295220. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:13:40,203][00631] Avg episode reward: [(0, '5.153')] [2023-02-23 20:13:40,208][10884] Saving new best policy, reward=5.153! [2023-02-23 20:13:41,094][10898] Updated weights for policy 0, policy_version 290 (0.0037) [2023-02-23 20:13:45,197][00631] Fps is (10 sec: 4096.1, 60 sec: 3481.9, 300 sec: 3401.8). Total num frames: 1204224. Throughput: 0: 885.9. Samples: 301526. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:13:45,200][00631] Avg episode reward: [(0, '4.909')] [2023-02-23 20:13:50,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.7, 300 sec: 3401.8). Total num frames: 1220608. Throughput: 0: 889.6. Samples: 304812. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:13:50,200][00631] Avg episode reward: [(0, '4.702')] [2023-02-23 20:13:51,928][10898] Updated weights for policy 0, policy_version 300 (0.0020) [2023-02-23 20:13:55,202][00631] Fps is (10 sec: 3275.1, 60 sec: 3549.6, 300 sec: 3415.6). Total num frames: 1236992. Throughput: 0: 866.0. Samples: 309026. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:13:55,213][00631] Avg episode reward: [(0, '4.725')] [2023-02-23 20:14:00,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 1253376. Throughput: 0: 876.8. Samples: 313610. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:14:00,204][00631] Avg episode reward: [(0, '4.865')] [2023-02-23 20:14:03,885][10898] Updated weights for policy 0, policy_version 310 (0.0016) [2023-02-23 20:14:05,197][00631] Fps is (10 sec: 3688.3, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 1273856. Throughput: 0: 895.0. Samples: 316888. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:14:05,204][00631] Avg episode reward: [(0, '5.020')] [2023-02-23 20:14:10,197][00631] Fps is (10 sec: 4096.1, 60 sec: 3550.0, 300 sec: 3415.7). Total num frames: 1294336. Throughput: 0: 893.0. Samples: 323358. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:14:10,201][00631] Avg episode reward: [(0, '4.917')] [2023-02-23 20:14:15,198][00631] Fps is (10 sec: 3276.5, 60 sec: 3549.8, 300 sec: 3401.8). Total num frames: 1306624. Throughput: 0: 863.1. Samples: 327418. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:14:15,208][00631] Avg episode reward: [(0, '4.619')] [2023-02-23 20:14:16,248][10898] Updated weights for policy 0, policy_version 320 (0.0018) [2023-02-23 20:14:20,197][00631] Fps is (10 sec: 2457.6, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 1318912. Throughput: 0: 862.2. Samples: 329448. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:14:20,200][00631] Avg episode reward: [(0, '5.008')] [2023-02-23 20:14:25,197][00631] Fps is (10 sec: 3277.1, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 1339392. Throughput: 0: 886.8. Samples: 335124. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:14:25,200][00631] Avg episode reward: [(0, '5.163')] [2023-02-23 20:14:25,258][10884] Saving new best policy, reward=5.163! [2023-02-23 20:14:27,147][10898] Updated weights for policy 0, policy_version 330 (0.0015) [2023-02-23 20:14:30,197][00631] Fps is (10 sec: 4505.6, 60 sec: 3549.9, 300 sec: 3415.6). Total num frames: 1363968. Throughput: 0: 889.3. Samples: 341544. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:14:30,200][00631] Avg episode reward: [(0, '5.168')] [2023-02-23 20:14:30,205][10884] Saving new best policy, reward=5.168! [2023-02-23 20:14:35,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3415.6). Total num frames: 1376256. Throughput: 0: 864.7. Samples: 343722. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:14:35,202][00631] Avg episode reward: [(0, '5.217')] [2023-02-23 20:14:35,225][10884] Saving new best policy, reward=5.217! [2023-02-23 20:14:40,200][00631] Fps is (10 sec: 2456.8, 60 sec: 3413.2, 300 sec: 3401.7). Total num frames: 1388544. Throughput: 0: 860.5. Samples: 347748. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:14:40,202][00631] Avg episode reward: [(0, '5.291')] [2023-02-23 20:14:40,252][10884] Saving new best policy, reward=5.291! [2023-02-23 20:14:40,273][10898] Updated weights for policy 0, policy_version 340 (0.0023) [2023-02-23 20:14:45,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 1409024. Throughput: 0: 878.7. Samples: 353152. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:14:45,200][00631] Avg episode reward: [(0, '5.197')] [2023-02-23 20:14:50,197][00631] Fps is (10 sec: 4097.3, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 1429504. Throughput: 0: 876.9. Samples: 356348. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:14:50,200][00631] Avg episode reward: [(0, '5.056')] [2023-02-23 20:14:50,357][10898] Updated weights for policy 0, policy_version 350 (0.0016) [2023-02-23 20:14:55,198][00631] Fps is (10 sec: 3686.1, 60 sec: 3481.9, 300 sec: 3401.8). Total num frames: 1445888. Throughput: 0: 855.1. Samples: 361836. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:14:55,207][00631] Avg episode reward: [(0, '5.167')] [2023-02-23 20:15:00,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3415.7). Total num frames: 1462272. Throughput: 0: 856.5. Samples: 365960. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:15:00,200][00631] Avg episode reward: [(0, '4.956')] [2023-02-23 20:15:03,900][10898] Updated weights for policy 0, policy_version 360 (0.0024) [2023-02-23 20:15:05,197][00631] Fps is (10 sec: 3277.0, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 1478656. Throughput: 0: 862.0. Samples: 368240. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:15:05,205][00631] Avg episode reward: [(0, '5.097')] [2023-02-23 20:15:05,225][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000361_1478656.pth... [2023-02-23 20:15:05,364][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000158_647168.pth [2023-02-23 20:15:10,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 1499136. Throughput: 0: 878.5. Samples: 374656. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:15:10,200][00631] Avg episode reward: [(0, '5.143')] [2023-02-23 20:15:14,035][10898] Updated weights for policy 0, policy_version 370 (0.0014) [2023-02-23 20:15:15,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.7, 300 sec: 3415.6). Total num frames: 1515520. Throughput: 0: 858.7. Samples: 380184. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:15:15,202][00631] Avg episode reward: [(0, '5.081')] [2023-02-23 20:15:20,197][00631] Fps is (10 sec: 3276.7, 60 sec: 3549.9, 300 sec: 3429.5). Total num frames: 1531904. Throughput: 0: 854.8. Samples: 382186. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:15:20,204][00631] Avg episode reward: [(0, '5.154')] [2023-02-23 20:15:25,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 1548288. Throughput: 0: 861.1. Samples: 386494. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:15:25,199][00631] Avg episode reward: [(0, '5.350')] [2023-02-23 20:15:25,215][10884] Saving new best policy, reward=5.350! [2023-02-23 20:15:27,003][10898] Updated weights for policy 0, policy_version 380 (0.0035) [2023-02-23 20:15:30,197][00631] Fps is (10 sec: 3686.5, 60 sec: 3413.3, 300 sec: 3443.5). Total num frames: 1568768. Throughput: 0: 881.5. Samples: 392820. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:15:30,204][00631] Avg episode reward: [(0, '5.653')] [2023-02-23 20:15:30,206][10884] Saving new best policy, reward=5.653! [2023-02-23 20:15:35,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 1589248. Throughput: 0: 879.4. Samples: 395920. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:15:35,200][00631] Avg episode reward: [(0, '5.533')] [2023-02-23 20:15:38,106][10898] Updated weights for policy 0, policy_version 390 (0.0017) [2023-02-23 20:15:40,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3550.1, 300 sec: 3471.2). Total num frames: 1601536. Throughput: 0: 854.3. Samples: 400280. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:15:40,200][00631] Avg episode reward: [(0, '5.266')] [2023-02-23 20:15:45,197][00631] Fps is (10 sec: 2457.6, 60 sec: 3413.3, 300 sec: 3471.3). Total num frames: 1613824. Throughput: 0: 854.9. Samples: 404432. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0) [2023-02-23 20:15:45,205][00631] Avg episode reward: [(0, '5.129')] [2023-02-23 20:15:50,151][10898] Updated weights for policy 0, policy_version 400 (0.0023) [2023-02-23 20:15:50,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 1638400. Throughput: 0: 874.9. Samples: 407612. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:15:50,202][00631] Avg episode reward: [(0, '5.390')] [2023-02-23 20:15:55,202][00631] Fps is (10 sec: 4503.6, 60 sec: 3549.6, 300 sec: 3471.1). Total num frames: 1658880. Throughput: 0: 879.6. Samples: 414244. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:15:55,204][00631] Avg episode reward: [(0, '5.415')] [2023-02-23 20:16:00,200][00631] Fps is (10 sec: 3275.7, 60 sec: 3481.4, 300 sec: 3471.2). Total num frames: 1671168. Throughput: 0: 854.4. Samples: 418634. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:16:00,203][00631] Avg episode reward: [(0, '5.618')] [2023-02-23 20:16:02,511][10898] Updated weights for policy 0, policy_version 410 (0.0023) [2023-02-23 20:16:05,198][00631] Fps is (10 sec: 2458.4, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 1683456. Throughput: 0: 853.9. Samples: 420614. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:16:05,201][00631] Avg episode reward: [(0, '5.386')] [2023-02-23 20:16:10,199][00631] Fps is (10 sec: 2458.0, 60 sec: 3276.7, 300 sec: 3443.4). Total num frames: 1695744. Throughput: 0: 833.8. Samples: 424018. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:16:10,202][00631] Avg episode reward: [(0, '5.548')] [2023-02-23 20:16:15,197][00631] Fps is (10 sec: 2457.9, 60 sec: 3208.5, 300 sec: 3401.8). Total num frames: 1708032. Throughput: 0: 785.2. Samples: 428156. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:16:15,200][00631] Avg episode reward: [(0, '5.754')] [2023-02-23 20:16:15,213][10884] Saving new best policy, reward=5.754! [2023-02-23 20:16:17,357][10898] Updated weights for policy 0, policy_version 420 (0.0038) [2023-02-23 20:16:20,198][00631] Fps is (10 sec: 2867.3, 60 sec: 3208.5, 300 sec: 3415.6). Total num frames: 1724416. Throughput: 0: 783.9. Samples: 431198. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:16:20,203][00631] Avg episode reward: [(0, '5.921')] [2023-02-23 20:16:20,260][10884] Saving new best policy, reward=5.921! [2023-02-23 20:16:25,203][00631] Fps is (10 sec: 3275.1, 60 sec: 3208.2, 300 sec: 3429.5). Total num frames: 1740800. Throughput: 0: 777.7. Samples: 435280. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:16:25,205][00631] Avg episode reward: [(0, '5.646')] [2023-02-23 20:16:30,197][00631] Fps is (10 sec: 3277.2, 60 sec: 3140.3, 300 sec: 3415.6). Total num frames: 1757184. Throughput: 0: 786.1. Samples: 439808. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) [2023-02-23 20:16:30,200][00631] Avg episode reward: [(0, '5.704')] [2023-02-23 20:16:31,005][10898] Updated weights for policy 0, policy_version 430 (0.0039) [2023-02-23 20:16:35,197][00631] Fps is (10 sec: 3688.3, 60 sec: 3140.3, 300 sec: 3415.6). Total num frames: 1777664. Throughput: 0: 788.0. Samples: 443074. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:16:35,203][00631] Avg episode reward: [(0, '5.820')] [2023-02-23 20:16:40,199][00631] Fps is (10 sec: 4095.0, 60 sec: 3276.7, 300 sec: 3429.5). Total num frames: 1798144. Throughput: 0: 784.9. Samples: 449562. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:16:40,202][00631] Avg episode reward: [(0, '6.686')] [2023-02-23 20:16:40,204][10884] Saving new best policy, reward=6.686! [2023-02-23 20:16:41,533][10898] Updated weights for policy 0, policy_version 440 (0.0023) [2023-02-23 20:16:45,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3276.8, 300 sec: 3415.6). Total num frames: 1810432. Throughput: 0: 773.6. Samples: 453444. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) [2023-02-23 20:16:45,200][00631] Avg episode reward: [(0, '6.589')] [2023-02-23 20:16:50,197][00631] Fps is (10 sec: 2867.9, 60 sec: 3140.3, 300 sec: 3415.6). Total num frames: 1826816. Throughput: 0: 776.1. Samples: 455538. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:16:50,199][00631] Avg episode reward: [(0, '7.056')] [2023-02-23 20:16:50,207][10884] Saving new best policy, reward=7.056! [2023-02-23 20:16:54,063][10898] Updated weights for policy 0, policy_version 450 (0.0031) [2023-02-23 20:16:55,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3140.5, 300 sec: 3415.6). Total num frames: 1847296. Throughput: 0: 828.6. Samples: 461304. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:16:55,200][00631] Avg episode reward: [(0, '6.928')] [2023-02-23 20:17:00,197][00631] Fps is (10 sec: 4095.9, 60 sec: 3277.0, 300 sec: 3429.6). Total num frames: 1867776. Throughput: 0: 877.6. Samples: 467646. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:17:00,203][00631] Avg episode reward: [(0, '6.895')] [2023-02-23 20:17:05,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3276.9, 300 sec: 3415.6). Total num frames: 1880064. Throughput: 0: 854.9. Samples: 469668. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:17:05,203][00631] Avg episode reward: [(0, '6.679')] [2023-02-23 20:17:05,223][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000459_1880064.pth... [2023-02-23 20:17:05,380][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000260_1064960.pth [2023-02-23 20:17:05,613][10898] Updated weights for policy 0, policy_version 460 (0.0025) [2023-02-23 20:17:10,197][00631] Fps is (10 sec: 2867.3, 60 sec: 3345.1, 300 sec: 3429.5). Total num frames: 1896448. Throughput: 0: 854.7. Samples: 473738. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:17:10,209][00631] Avg episode reward: [(0, '6.361')] [2023-02-23 20:17:15,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 1916928. Throughput: 0: 880.8. Samples: 479446. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:17:15,200][00631] Avg episode reward: [(0, '6.224')] [2023-02-23 20:17:17,031][10898] Updated weights for policy 0, policy_version 470 (0.0036) [2023-02-23 20:17:20,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3429.5). Total num frames: 1937408. Throughput: 0: 880.4. Samples: 482692. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:17:20,200][00631] Avg episode reward: [(0, '6.567')] [2023-02-23 20:17:25,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.9, 300 sec: 3415.6). Total num frames: 1949696. Throughput: 0: 852.9. Samples: 487940. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:17:25,206][00631] Avg episode reward: [(0, '6.631')] [2023-02-23 20:17:30,107][10898] Updated weights for policy 0, policy_version 480 (0.0026) [2023-02-23 20:17:30,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3429.5). Total num frames: 1966080. Throughput: 0: 858.1. Samples: 492058. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:17:30,201][00631] Avg episode reward: [(0, '6.598')] [2023-02-23 20:17:35,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 1982464. Throughput: 0: 864.1. Samples: 494424. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:17:35,201][00631] Avg episode reward: [(0, '7.240')] [2023-02-23 20:17:35,218][10884] Saving new best policy, reward=7.240! [2023-02-23 20:17:40,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.5, 300 sec: 3415.7). Total num frames: 2002944. Throughput: 0: 875.8. Samples: 500716. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:17:40,204][00631] Avg episode reward: [(0, '7.084')] [2023-02-23 20:17:40,498][10898] Updated weights for policy 0, policy_version 490 (0.0024) [2023-02-23 20:17:45,204][00631] Fps is (10 sec: 3683.7, 60 sec: 3481.2, 300 sec: 3415.6). Total num frames: 2019328. Throughput: 0: 851.6. Samples: 505974. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:17:45,210][00631] Avg episode reward: [(0, '7.505')] [2023-02-23 20:17:45,219][10884] Saving new best policy, reward=7.505! [2023-02-23 20:17:50,198][00631] Fps is (10 sec: 2866.9, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 2031616. Throughput: 0: 850.2. Samples: 507926. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:17:50,201][00631] Avg episode reward: [(0, '7.473')] [2023-02-23 20:17:53,994][10898] Updated weights for policy 0, policy_version 500 (0.0017) [2023-02-23 20:17:55,197][00631] Fps is (10 sec: 3279.2, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 2052096. Throughput: 0: 857.4. Samples: 512322. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:17:55,200][00631] Avg episode reward: [(0, '7.523')] [2023-02-23 20:17:55,207][10884] Saving new best policy, reward=7.523! [2023-02-23 20:18:00,197][00631] Fps is (10 sec: 4096.5, 60 sec: 3413.4, 300 sec: 3415.6). Total num frames: 2072576. Throughput: 0: 871.5. Samples: 518664. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:18:00,200][00631] Avg episode reward: [(0, '6.969')] [2023-02-23 20:18:04,006][10898] Updated weights for policy 0, policy_version 510 (0.0019) [2023-02-23 20:18:05,203][00631] Fps is (10 sec: 3684.1, 60 sec: 3481.2, 300 sec: 3415.6). Total num frames: 2088960. Throughput: 0: 868.7. Samples: 521790. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:18:05,206][00631] Avg episode reward: [(0, '7.577')] [2023-02-23 20:18:05,219][10884] Saving new best policy, reward=7.577! [2023-02-23 20:18:10,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 2101248. Throughput: 0: 842.7. Samples: 525862. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:18:10,199][00631] Avg episode reward: [(0, '7.828')] [2023-02-23 20:18:10,225][10884] Saving new best policy, reward=7.828! [2023-02-23 20:18:15,197][00631] Fps is (10 sec: 2869.0, 60 sec: 3345.1, 300 sec: 3401.8). Total num frames: 2117632. Throughput: 0: 844.0. Samples: 530036. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:18:15,203][00631] Avg episode reward: [(0, '7.907')] [2023-02-23 20:18:15,221][10884] Saving new best policy, reward=7.907! [2023-02-23 20:18:17,647][10898] Updated weights for policy 0, policy_version 520 (0.0013) [2023-02-23 20:18:20,201][00631] Fps is (10 sec: 3685.0, 60 sec: 3344.9, 300 sec: 3401.7). Total num frames: 2138112. Throughput: 0: 862.2. Samples: 533224. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:18:20,204][00631] Avg episode reward: [(0, '7.665')] [2023-02-23 20:18:25,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 2158592. Throughput: 0: 866.1. Samples: 539690. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:18:25,202][00631] Avg episode reward: [(0, '7.608')] [2023-02-23 20:18:28,881][10898] Updated weights for policy 0, policy_version 530 (0.0016) [2023-02-23 20:18:30,197][00631] Fps is (10 sec: 3278.0, 60 sec: 3413.3, 300 sec: 3415.7). Total num frames: 2170880. Throughput: 0: 843.2. Samples: 543912. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:18:30,200][00631] Avg episode reward: [(0, '8.311')] [2023-02-23 20:18:30,206][10884] Saving new best policy, reward=8.311! [2023-02-23 20:18:35,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 2187264. Throughput: 0: 843.1. Samples: 545866. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:18:35,205][00631] Avg episode reward: [(0, '8.714')] [2023-02-23 20:18:35,216][10884] Saving new best policy, reward=8.714! [2023-02-23 20:18:40,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 2207744. Throughput: 0: 868.2. Samples: 551392. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:18:40,203][00631] Avg episode reward: [(0, '8.961')] [2023-02-23 20:18:40,207][10884] Saving new best policy, reward=8.961! [2023-02-23 20:18:40,895][10898] Updated weights for policy 0, policy_version 540 (0.0035) [2023-02-23 20:18:45,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3482.0, 300 sec: 3415.6). Total num frames: 2228224. Throughput: 0: 867.2. Samples: 557688. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:18:45,201][00631] Avg episode reward: [(0, '8.587')] [2023-02-23 20:18:50,199][00631] Fps is (10 sec: 3276.1, 60 sec: 3481.5, 300 sec: 3401.8). Total num frames: 2240512. Throughput: 0: 847.1. Samples: 559906. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:18:50,206][00631] Avg episode reward: [(0, '8.543')] [2023-02-23 20:18:53,554][10898] Updated weights for policy 0, policy_version 550 (0.0015) [2023-02-23 20:18:55,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 2256896. Throughput: 0: 847.9. Samples: 564018. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:18:55,204][00631] Avg episode reward: [(0, '8.362')] [2023-02-23 20:19:00,197][00631] Fps is (10 sec: 3277.5, 60 sec: 3345.1, 300 sec: 3387.9). Total num frames: 2273280. Throughput: 0: 876.4. Samples: 569474. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:19:00,206][00631] Avg episode reward: [(0, '8.083')] [2023-02-23 20:19:04,094][10898] Updated weights for policy 0, policy_version 560 (0.0013) [2023-02-23 20:19:05,197][00631] Fps is (10 sec: 4096.1, 60 sec: 3482.0, 300 sec: 3401.8). Total num frames: 2297856. Throughput: 0: 878.2. Samples: 572738. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:19:05,204][00631] Avg episode reward: [(0, '8.450')] [2023-02-23 20:19:05,215][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000561_2297856.pth... [2023-02-23 20:19:05,358][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000361_1478656.pth [2023-02-23 20:19:10,197][00631] Fps is (10 sec: 3686.3, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 2310144. Throughput: 0: 854.0. Samples: 578120. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:19:10,204][00631] Avg episode reward: [(0, '8.656')] [2023-02-23 20:19:15,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 2326528. Throughput: 0: 850.0. Samples: 582160. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:19:15,201][00631] Avg episode reward: [(0, '9.083')] [2023-02-23 20:19:15,211][10884] Saving new best policy, reward=9.083! [2023-02-23 20:19:17,827][10898] Updated weights for policy 0, policy_version 570 (0.0049) [2023-02-23 20:19:20,197][00631] Fps is (10 sec: 3276.9, 60 sec: 3413.6, 300 sec: 3401.8). Total num frames: 2342912. Throughput: 0: 856.6. Samples: 584412. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:19:20,204][00631] Avg episode reward: [(0, '8.578')] [2023-02-23 20:19:25,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 2363392. Throughput: 0: 878.8. Samples: 590940. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:19:25,205][00631] Avg episode reward: [(0, '9.034')] [2023-02-23 20:19:27,237][10898] Updated weights for policy 0, policy_version 580 (0.0014) [2023-02-23 20:19:30,203][00631] Fps is (10 sec: 3684.2, 60 sec: 3481.3, 300 sec: 3401.7). Total num frames: 2379776. Throughput: 0: 856.6. Samples: 596238. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:19:30,207][00631] Avg episode reward: [(0, '8.816')] [2023-02-23 20:19:35,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3415.7). Total num frames: 2396160. Throughput: 0: 853.0. Samples: 598290. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:19:35,202][00631] Avg episode reward: [(0, '8.581')] [2023-02-23 20:19:40,198][00631] Fps is (10 sec: 3278.6, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 2412544. Throughput: 0: 858.7. Samples: 602660. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:19:40,201][00631] Avg episode reward: [(0, '9.021')] [2023-02-23 20:19:40,998][10898] Updated weights for policy 0, policy_version 590 (0.0013) [2023-02-23 20:19:45,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 2433024. Throughput: 0: 874.3. Samples: 608816. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:19:45,200][00631] Avg episode reward: [(0, '9.892')] [2023-02-23 20:19:45,212][10884] Saving new best policy, reward=9.892! [2023-02-23 20:19:50,198][00631] Fps is (10 sec: 3686.3, 60 sec: 3481.7, 300 sec: 3401.8). Total num frames: 2449408. Throughput: 0: 869.1. Samples: 611850. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:19:50,203][00631] Avg episode reward: [(0, '9.855')] [2023-02-23 20:19:52,216][10898] Updated weights for policy 0, policy_version 600 (0.0021) [2023-02-23 20:19:55,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 2461696. Throughput: 0: 844.8. Samples: 616136. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:19:55,199][00631] Avg episode reward: [(0, '10.865')] [2023-02-23 20:19:55,217][10884] Saving new best policy, reward=10.865! [2023-02-23 20:20:00,197][00631] Fps is (10 sec: 2867.4, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 2478080. Throughput: 0: 847.5. Samples: 620296. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:20:00,204][00631] Avg episode reward: [(0, '9.850')] [2023-02-23 20:20:04,430][10898] Updated weights for policy 0, policy_version 610 (0.0015) [2023-02-23 20:20:05,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3345.1, 300 sec: 3387.9). Total num frames: 2498560. Throughput: 0: 870.4. Samples: 623580. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:20:05,200][00631] Avg episode reward: [(0, '10.555')] [2023-02-23 20:20:10,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 2519040. Throughput: 0: 868.5. Samples: 630024. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:20:10,200][00631] Avg episode reward: [(0, '10.528')] [2023-02-23 20:20:15,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 2531328. Throughput: 0: 839.2. Samples: 633996. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:20:15,199][00631] Avg episode reward: [(0, '10.914')] [2023-02-23 20:20:15,228][10884] Saving new best policy, reward=10.914! [2023-02-23 20:20:17,326][10898] Updated weights for policy 0, policy_version 620 (0.0026) [2023-02-23 20:20:20,197][00631] Fps is (10 sec: 2457.5, 60 sec: 3345.0, 300 sec: 3374.0). Total num frames: 2543616. Throughput: 0: 836.2. Samples: 635920. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:20:20,204][00631] Avg episode reward: [(0, '10.304')] [2023-02-23 20:20:25,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 2568192. Throughput: 0: 862.1. Samples: 641454. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:20:25,205][00631] Avg episode reward: [(0, '10.527')] [2023-02-23 20:20:27,898][10898] Updated weights for policy 0, policy_version 630 (0.0018) [2023-02-23 20:20:30,197][00631] Fps is (10 sec: 4505.6, 60 sec: 3481.9, 300 sec: 3387.9). Total num frames: 2588672. Throughput: 0: 863.9. Samples: 647690. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:20:30,204][00631] Avg episode reward: [(0, '11.505')] [2023-02-23 20:20:30,208][10884] Saving new best policy, reward=11.505! [2023-02-23 20:20:35,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 2600960. Throughput: 0: 844.1. Samples: 649836. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:20:35,204][00631] Avg episode reward: [(0, '11.784')] [2023-02-23 20:20:35,216][10884] Saving new best policy, reward=11.784! [2023-02-23 20:20:40,198][00631] Fps is (10 sec: 2457.6, 60 sec: 3345.1, 300 sec: 3387.9). Total num frames: 2613248. Throughput: 0: 837.7. Samples: 653832. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:20:40,210][00631] Avg episode reward: [(0, '12.264')] [2023-02-23 20:20:40,213][10884] Saving new best policy, reward=12.264! [2023-02-23 20:20:41,805][10898] Updated weights for policy 0, policy_version 640 (0.0032) [2023-02-23 20:20:45,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3345.1, 300 sec: 3374.0). Total num frames: 2633728. Throughput: 0: 866.8. Samples: 659302. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:20:45,205][00631] Avg episode reward: [(0, '11.640')] [2023-02-23 20:20:50,197][00631] Fps is (10 sec: 4096.2, 60 sec: 3413.4, 300 sec: 3374.0). Total num frames: 2654208. Throughput: 0: 865.6. Samples: 662530. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:20:50,204][00631] Avg episode reward: [(0, '11.628')] [2023-02-23 20:20:51,374][10898] Updated weights for policy 0, policy_version 650 (0.0015) [2023-02-23 20:20:55,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3387.9). Total num frames: 2670592. Throughput: 0: 842.7. Samples: 667944. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:20:55,202][00631] Avg episode reward: [(0, '11.410')] [2023-02-23 20:21:00,197][00631] Fps is (10 sec: 2867.1, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 2682880. Throughput: 0: 845.6. Samples: 672046. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:21:00,201][00631] Avg episode reward: [(0, '11.291')] [2023-02-23 20:21:04,799][10898] Updated weights for policy 0, policy_version 660 (0.0030) [2023-02-23 20:21:05,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3415.7). Total num frames: 2703360. Throughput: 0: 854.4. Samples: 674370. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:21:05,205][00631] Avg episode reward: [(0, '11.255')] [2023-02-23 20:21:05,220][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000660_2703360.pth... [2023-02-23 20:21:05,342][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000459_1880064.pth [2023-02-23 20:21:10,197][00631] Fps is (10 sec: 4096.1, 60 sec: 3413.3, 300 sec: 3443.4). Total num frames: 2723840. Throughput: 0: 873.2. Samples: 680750. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:21:10,204][00631] Avg episode reward: [(0, '11.247')] [2023-02-23 20:21:15,202][00631] Fps is (10 sec: 3684.7, 60 sec: 3481.3, 300 sec: 3443.4). Total num frames: 2740224. Throughput: 0: 850.8. Samples: 685978. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:21:15,205][00631] Avg episode reward: [(0, '11.546')] [2023-02-23 20:21:15,967][10898] Updated weights for policy 0, policy_version 670 (0.0026) [2023-02-23 20:21:20,197][00631] Fps is (10 sec: 2867.1, 60 sec: 3481.6, 300 sec: 3429.6). Total num frames: 2752512. Throughput: 0: 848.4. Samples: 688016. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:21:20,202][00631] Avg episode reward: [(0, '12.145')] [2023-02-23 20:21:25,197][00631] Fps is (10 sec: 2868.5, 60 sec: 3345.1, 300 sec: 3429.5). Total num frames: 2768896. Throughput: 0: 855.5. Samples: 692330. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:21:25,200][00631] Avg episode reward: [(0, '12.932')] [2023-02-23 20:21:25,208][10884] Saving new best policy, reward=12.932! [2023-02-23 20:21:28,273][10898] Updated weights for policy 0, policy_version 680 (0.0039) [2023-02-23 20:21:30,205][00631] Fps is (10 sec: 3683.7, 60 sec: 3344.7, 300 sec: 3429.4). Total num frames: 2789376. Throughput: 0: 866.7. Samples: 698312. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:21:30,207][00631] Avg episode reward: [(0, '12.863')] [2023-02-23 20:21:35,200][00631] Fps is (10 sec: 3275.8, 60 sec: 3344.9, 300 sec: 3401.8). Total num frames: 2801664. Throughput: 0: 838.9. Samples: 700282. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:21:35,202][00631] Avg episode reward: [(0, '12.977')] [2023-02-23 20:21:35,222][10884] Saving new best policy, reward=12.977! [2023-02-23 20:21:40,201][00631] Fps is (10 sec: 2458.5, 60 sec: 3344.9, 300 sec: 3401.7). Total num frames: 2813952. Throughput: 0: 790.6. Samples: 703522. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:21:40,208][00631] Avg episode reward: [(0, '12.004')] [2023-02-23 20:21:45,085][10898] Updated weights for policy 0, policy_version 690 (0.0015) [2023-02-23 20:21:45,197][00631] Fps is (10 sec: 2458.4, 60 sec: 3208.5, 300 sec: 3387.9). Total num frames: 2826240. Throughput: 0: 778.9. Samples: 707094. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:21:45,203][00631] Avg episode reward: [(0, '11.558')] [2023-02-23 20:21:50,197][00631] Fps is (10 sec: 2868.3, 60 sec: 3140.3, 300 sec: 3374.0). Total num frames: 2842624. Throughput: 0: 777.7. Samples: 709366. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:21:50,202][00631] Avg episode reward: [(0, '11.112')] [2023-02-23 20:21:55,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3208.5, 300 sec: 3374.0). Total num frames: 2863104. Throughput: 0: 780.9. Samples: 715890. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:21:55,200][00631] Avg episode reward: [(0, '12.171')] [2023-02-23 20:21:55,303][10898] Updated weights for policy 0, policy_version 700 (0.0018) [2023-02-23 20:22:00,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3345.1, 300 sec: 3401.8). Total num frames: 2883584. Throughput: 0: 788.0. Samples: 721432. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:22:00,205][00631] Avg episode reward: [(0, '12.791')] [2023-02-23 20:22:05,200][00631] Fps is (10 sec: 3275.8, 60 sec: 3208.4, 300 sec: 3387.8). Total num frames: 2895872. Throughput: 0: 787.2. Samples: 723442. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:22:05,204][00631] Avg episode reward: [(0, '13.207')] [2023-02-23 20:22:05,225][10884] Saving new best policy, reward=13.207! [2023-02-23 20:22:08,745][10898] Updated weights for policy 0, policy_version 710 (0.0015) [2023-02-23 20:22:10,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3140.3, 300 sec: 3374.0). Total num frames: 2912256. Throughput: 0: 787.7. Samples: 727778. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:22:10,200][00631] Avg episode reward: [(0, '13.409')] [2023-02-23 20:22:10,203][10884] Saving new best policy, reward=13.409! [2023-02-23 20:22:15,197][00631] Fps is (10 sec: 3687.5, 60 sec: 3208.8, 300 sec: 3374.0). Total num frames: 2932736. Throughput: 0: 797.6. Samples: 734196. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:22:15,204][00631] Avg episode reward: [(0, '13.174')] [2023-02-23 20:22:18,311][10898] Updated weights for policy 0, policy_version 720 (0.0031) [2023-02-23 20:22:20,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3345.1, 300 sec: 3401.8). Total num frames: 2953216. Throughput: 0: 825.6. Samples: 737432. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:22:20,199][00631] Avg episode reward: [(0, '13.895')] [2023-02-23 20:22:20,202][10884] Saving new best policy, reward=13.895! [2023-02-23 20:22:25,198][00631] Fps is (10 sec: 3276.5, 60 sec: 3276.7, 300 sec: 3387.9). Total num frames: 2965504. Throughput: 0: 844.9. Samples: 741540. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:22:25,204][00631] Avg episode reward: [(0, '13.690')] [2023-02-23 20:22:30,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3208.9, 300 sec: 3387.9). Total num frames: 2981888. Throughput: 0: 861.5. Samples: 745862. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:22:30,205][00631] Avg episode reward: [(0, '14.377')] [2023-02-23 20:22:30,208][10884] Saving new best policy, reward=14.377! [2023-02-23 20:22:32,140][10898] Updated weights for policy 0, policy_version 730 (0.0022) [2023-02-23 20:22:35,197][00631] Fps is (10 sec: 3686.7, 60 sec: 3345.2, 300 sec: 3387.9). Total num frames: 3002368. Throughput: 0: 879.9. Samples: 748964. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:22:35,205][00631] Avg episode reward: [(0, '13.019')] [2023-02-23 20:22:40,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.8, 300 sec: 3401.8). Total num frames: 3022848. Throughput: 0: 881.2. Samples: 755546. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:22:40,201][00631] Avg episode reward: [(0, '12.255')] [2023-02-23 20:22:42,687][10898] Updated weights for policy 0, policy_version 740 (0.0013) [2023-02-23 20:22:45,197][00631] Fps is (10 sec: 3276.9, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 3035136. Throughput: 0: 851.1. Samples: 759730. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:22:45,204][00631] Avg episode reward: [(0, '12.477')] [2023-02-23 20:22:50,197][00631] Fps is (10 sec: 2457.6, 60 sec: 3413.3, 300 sec: 3374.0). Total num frames: 3047424. Throughput: 0: 850.7. Samples: 761722. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:22:50,200][00631] Avg episode reward: [(0, '12.962')] [2023-02-23 20:22:55,134][10898] Updated weights for policy 0, policy_version 750 (0.0018) [2023-02-23 20:22:55,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3387.9). Total num frames: 3072000. Throughput: 0: 877.5. Samples: 767264. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:22:55,199][00631] Avg episode reward: [(0, '14.248')] [2023-02-23 20:23:00,197][00631] Fps is (10 sec: 4505.6, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 3092480. Throughput: 0: 878.4. Samples: 773726. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) [2023-02-23 20:23:00,205][00631] Avg episode reward: [(0, '15.095')] [2023-02-23 20:23:00,209][10884] Saving new best policy, reward=15.095! [2023-02-23 20:23:05,197][00631] Fps is (10 sec: 3276.7, 60 sec: 3481.8, 300 sec: 3401.8). Total num frames: 3104768. Throughput: 0: 853.1. Samples: 775820. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:23:05,202][00631] Avg episode reward: [(0, '14.526')] [2023-02-23 20:23:05,217][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000758_3104768.pth... [2023-02-23 20:23:05,427][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000561_2297856.pth [2023-02-23 20:23:07,533][10898] Updated weights for policy 0, policy_version 760 (0.0019) [2023-02-23 20:23:10,197][00631] Fps is (10 sec: 2457.6, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 3117056. Throughput: 0: 849.4. Samples: 779762. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:23:10,204][00631] Avg episode reward: [(0, '15.004')] [2023-02-23 20:23:15,198][00631] Fps is (10 sec: 3276.7, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 3137536. Throughput: 0: 874.8. Samples: 785228. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:23:15,201][00631] Avg episode reward: [(0, '15.152')] [2023-02-23 20:23:15,217][10884] Saving new best policy, reward=15.152! [2023-02-23 20:23:18,398][10898] Updated weights for policy 0, policy_version 770 (0.0033) [2023-02-23 20:23:20,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 3158016. Throughput: 0: 876.7. Samples: 788416. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:23:20,200][00631] Avg episode reward: [(0, '14.772')] [2023-02-23 20:23:25,197][00631] Fps is (10 sec: 3686.6, 60 sec: 3481.7, 300 sec: 3401.8). Total num frames: 3174400. Throughput: 0: 854.1. Samples: 793980. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:23:25,203][00631] Avg episode reward: [(0, '14.043')] [2023-02-23 20:23:30,199][00631] Fps is (10 sec: 2866.7, 60 sec: 3413.2, 300 sec: 3387.9). Total num frames: 3186688. Throughput: 0: 851.5. Samples: 798048. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:23:30,209][00631] Avg episode reward: [(0, '14.067')] [2023-02-23 20:23:31,778][10898] Updated weights for policy 0, policy_version 780 (0.0013) [2023-02-23 20:23:35,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 3207168. Throughput: 0: 858.6. Samples: 800360. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:23:35,203][00631] Avg episode reward: [(0, '14.713')] [2023-02-23 20:23:40,197][00631] Fps is (10 sec: 4096.7, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 3227648. Throughput: 0: 881.8. Samples: 806944. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:23:40,200][00631] Avg episode reward: [(0, '16.030')] [2023-02-23 20:23:40,207][10884] Saving new best policy, reward=16.030! [2023-02-23 20:23:41,511][10898] Updated weights for policy 0, policy_version 790 (0.0014) [2023-02-23 20:23:45,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 3244032. Throughput: 0: 857.7. Samples: 812322. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:23:45,201][00631] Avg episode reward: [(0, '15.609')] [2023-02-23 20:23:50,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3401.8). Total num frames: 3260416. Throughput: 0: 857.3. Samples: 814398. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:23:50,200][00631] Avg episode reward: [(0, '16.033')] [2023-02-23 20:23:50,202][10884] Saving new best policy, reward=16.033! [2023-02-23 20:23:54,949][10898] Updated weights for policy 0, policy_version 800 (0.0026) [2023-02-23 20:23:55,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 3276800. Throughput: 0: 863.8. Samples: 818632. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:23:55,200][00631] Avg episode reward: [(0, '16.357')] [2023-02-23 20:23:55,208][10884] Saving new best policy, reward=16.357! [2023-02-23 20:24:00,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 3297280. Throughput: 0: 882.1. Samples: 824924. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:24:00,200][00631] Avg episode reward: [(0, '15.760')] [2023-02-23 20:24:05,144][10898] Updated weights for policy 0, policy_version 810 (0.0032) [2023-02-23 20:24:05,200][00631] Fps is (10 sec: 4094.7, 60 sec: 3549.7, 300 sec: 3415.6). Total num frames: 3317760. Throughput: 0: 885.4. Samples: 828260. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:24:05,203][00631] Avg episode reward: [(0, '16.946')] [2023-02-23 20:24:05,222][10884] Saving new best policy, reward=16.946! [2023-02-23 20:24:10,199][00631] Fps is (10 sec: 3276.3, 60 sec: 3549.8, 300 sec: 3401.7). Total num frames: 3330048. Throughput: 0: 859.5. Samples: 832658. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:24:10,213][00631] Avg episode reward: [(0, '17.842')] [2023-02-23 20:24:10,223][10884] Saving new best policy, reward=17.842! [2023-02-23 20:24:15,197][00631] Fps is (10 sec: 2458.4, 60 sec: 3413.4, 300 sec: 3387.9). Total num frames: 3342336. Throughput: 0: 861.2. Samples: 836800. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:24:15,199][00631] Avg episode reward: [(0, '17.808')] [2023-02-23 20:24:18,119][10898] Updated weights for policy 0, policy_version 820 (0.0032) [2023-02-23 20:24:20,197][00631] Fps is (10 sec: 3686.9, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 3366912. Throughput: 0: 884.0. Samples: 840138. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:24:20,203][00631] Avg episode reward: [(0, '16.501')] [2023-02-23 20:24:25,197][00631] Fps is (10 sec: 4505.5, 60 sec: 3549.9, 300 sec: 3415.7). Total num frames: 3387392. Throughput: 0: 879.2. Samples: 846510. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) [2023-02-23 20:24:25,200][00631] Avg episode reward: [(0, '15.105')] [2023-02-23 20:24:29,173][10898] Updated weights for policy 0, policy_version 830 (0.0012) [2023-02-23 20:24:30,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3401.8). Total num frames: 3399680. Throughput: 0: 856.3. Samples: 850854. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:24:30,205][00631] Avg episode reward: [(0, '14.501')] [2023-02-23 20:24:35,197][00631] Fps is (10 sec: 2457.6, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 3411968. Throughput: 0: 856.1. Samples: 852922. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:24:35,202][00631] Avg episode reward: [(0, '14.072')] [2023-02-23 20:24:40,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3401.8). Total num frames: 3436544. Throughput: 0: 886.3. Samples: 858514. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:24:40,204][00631] Avg episode reward: [(0, '14.796')] [2023-02-23 20:24:41,030][10898] Updated weights for policy 0, policy_version 840 (0.0016) [2023-02-23 20:24:45,197][00631] Fps is (10 sec: 4505.6, 60 sec: 3549.9, 300 sec: 3415.7). Total num frames: 3457024. Throughput: 0: 890.0. Samples: 864976. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:24:45,207][00631] Avg episode reward: [(0, '15.032')] [2023-02-23 20:24:50,203][00631] Fps is (10 sec: 3274.8, 60 sec: 3481.2, 300 sec: 3415.6). Total num frames: 3469312. Throughput: 0: 866.1. Samples: 867236. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:24:50,212][00631] Avg episode reward: [(0, '14.688')] [2023-02-23 20:24:53,575][10898] Updated weights for policy 0, policy_version 850 (0.0027) [2023-02-23 20:24:55,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 3485696. Throughput: 0: 857.5. Samples: 871244. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:24:55,203][00631] Avg episode reward: [(0, '16.377')] [2023-02-23 20:25:00,197][00631] Fps is (10 sec: 3688.7, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 3506176. Throughput: 0: 889.9. Samples: 876846. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:25:00,200][00631] Avg episode reward: [(0, '18.595')] [2023-02-23 20:25:00,205][10884] Saving new best policy, reward=18.595! [2023-02-23 20:25:03,944][10898] Updated weights for policy 0, policy_version 860 (0.0027) [2023-02-23 20:25:05,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.8, 300 sec: 3415.6). Total num frames: 3526656. Throughput: 0: 885.9. Samples: 880004. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:25:05,199][00631] Avg episode reward: [(0, '18.896')] [2023-02-23 20:25:05,214][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000861_3526656.pth... [2023-02-23 20:25:05,366][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000660_2703360.pth [2023-02-23 20:25:05,394][10884] Saving new best policy, reward=18.896! [2023-02-23 20:25:10,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.7, 300 sec: 3415.6). Total num frames: 3538944. Throughput: 0: 860.0. Samples: 885210. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0) [2023-02-23 20:25:10,204][00631] Avg episode reward: [(0, '19.572')] [2023-02-23 20:25:10,226][10884] Saving new best policy, reward=19.572! [2023-02-23 20:25:15,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3429.5). Total num frames: 3555328. Throughput: 0: 852.2. Samples: 889202. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:25:15,204][00631] Avg episode reward: [(0, '20.910')] [2023-02-23 20:25:15,222][10884] Saving new best policy, reward=20.910! [2023-02-23 20:25:17,752][10898] Updated weights for policy 0, policy_version 870 (0.0017) [2023-02-23 20:25:20,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 3571712. Throughput: 0: 858.7. Samples: 891562. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:25:20,200][00631] Avg episode reward: [(0, '21.470')] [2023-02-23 20:25:20,205][10884] Saving new best policy, reward=21.470! [2023-02-23 20:25:25,197][00631] Fps is (10 sec: 3686.3, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 3592192. Throughput: 0: 876.0. Samples: 897934. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:25:25,200][00631] Avg episode reward: [(0, '21.191')] [2023-02-23 20:25:27,606][10898] Updated weights for policy 0, policy_version 880 (0.0024) [2023-02-23 20:25:30,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 3608576. Throughput: 0: 851.2. Samples: 903282. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:25:30,201][00631] Avg episode reward: [(0, '21.903')] [2023-02-23 20:25:30,206][10884] Saving new best policy, reward=21.903! [2023-02-23 20:25:35,197][00631] Fps is (10 sec: 3276.9, 60 sec: 3549.9, 300 sec: 3429.5). Total num frames: 3624960. Throughput: 0: 845.0. Samples: 905256. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:25:35,206][00631] Avg episode reward: [(0, '23.333')] [2023-02-23 20:25:35,218][10884] Saving new best policy, reward=23.333! [2023-02-23 20:25:40,198][00631] Fps is (10 sec: 3276.6, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 3641344. Throughput: 0: 854.0. Samples: 909674. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:25:40,208][00631] Avg episode reward: [(0, '23.403')] [2023-02-23 20:25:40,211][10884] Saving new best policy, reward=23.403! [2023-02-23 20:25:41,099][10898] Updated weights for policy 0, policy_version 890 (0.0013) [2023-02-23 20:25:45,197][00631] Fps is (10 sec: 3686.3, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 3661824. Throughput: 0: 869.1. Samples: 915954. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:25:45,200][00631] Avg episode reward: [(0, '23.378')] [2023-02-23 20:25:50,201][00631] Fps is (10 sec: 3685.1, 60 sec: 3481.7, 300 sec: 3415.6). Total num frames: 3678208. Throughput: 0: 871.2. Samples: 919212. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:25:50,205][00631] Avg episode reward: [(0, '24.062')] [2023-02-23 20:25:50,207][10884] Saving new best policy, reward=24.062! [2023-02-23 20:25:52,341][10898] Updated weights for policy 0, policy_version 900 (0.0016) [2023-02-23 20:25:55,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3429.5). Total num frames: 3694592. Throughput: 0: 847.6. Samples: 923350. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0) [2023-02-23 20:25:55,202][00631] Avg episode reward: [(0, '23.451')] [2023-02-23 20:26:00,197][00631] Fps is (10 sec: 2868.3, 60 sec: 3345.1, 300 sec: 3401.8). Total num frames: 3706880. Throughput: 0: 859.9. Samples: 927898. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:26:00,200][00631] Avg episode reward: [(0, '23.280')] [2023-02-23 20:26:03,952][10898] Updated weights for policy 0, policy_version 910 (0.0031) [2023-02-23 20:26:05,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 3731456. Throughput: 0: 881.3. Samples: 931220. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:26:05,203][00631] Avg episode reward: [(0, '22.549')] [2023-02-23 20:26:10,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3415.7). Total num frames: 3747840. Throughput: 0: 880.3. Samples: 937546. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:26:10,199][00631] Avg episode reward: [(0, '23.821')] [2023-02-23 20:26:15,198][00631] Fps is (10 sec: 3276.5, 60 sec: 3481.5, 300 sec: 3429.5). Total num frames: 3764224. Throughput: 0: 852.3. Samples: 941638. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:26:15,201][00631] Avg episode reward: [(0, '23.852')] [2023-02-23 20:26:16,581][10898] Updated weights for policy 0, policy_version 920 (0.0021) [2023-02-23 20:26:20,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 3776512. Throughput: 0: 852.7. Samples: 943628. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0) [2023-02-23 20:26:20,200][00631] Avg episode reward: [(0, '25.148')] [2023-02-23 20:26:20,205][10884] Saving new best policy, reward=25.148! [2023-02-23 20:26:25,197][00631] Fps is (10 sec: 3277.1, 60 sec: 3413.3, 300 sec: 3415.7). Total num frames: 3796992. Throughput: 0: 879.0. Samples: 949230. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0) [2023-02-23 20:26:25,202][00631] Avg episode reward: [(0, '24.122')] [2023-02-23 20:26:27,505][10898] Updated weights for policy 0, policy_version 930 (0.0015) [2023-02-23 20:26:30,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3443.5). Total num frames: 3817472. Throughput: 0: 880.2. Samples: 955562. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:26:30,202][00631] Avg episode reward: [(0, '23.277')] [2023-02-23 20:26:35,199][00631] Fps is (10 sec: 3685.9, 60 sec: 3481.5, 300 sec: 3457.3). Total num frames: 3833856. Throughput: 0: 854.0. Samples: 957642. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:26:35,203][00631] Avg episode reward: [(0, '22.759')] [2023-02-23 20:26:40,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3457.3). Total num frames: 3846144. Throughput: 0: 851.7. Samples: 961676. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:26:40,202][00631] Avg episode reward: [(0, '22.627')] [2023-02-23 20:26:41,056][10898] Updated weights for policy 0, policy_version 940 (0.0024) [2023-02-23 20:26:45,197][00631] Fps is (10 sec: 3277.3, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 3866624. Throughput: 0: 875.6. Samples: 967302. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0) [2023-02-23 20:26:45,204][00631] Avg episode reward: [(0, '21.283')] [2023-02-23 20:26:50,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3413.6, 300 sec: 3457.3). Total num frames: 3883008. Throughput: 0: 874.4. Samples: 970568. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:26:50,200][00631] Avg episode reward: [(0, '19.885')] [2023-02-23 20:26:52,110][10898] Updated weights for policy 0, policy_version 950 (0.0032) [2023-02-23 20:26:55,197][00631] Fps is (10 sec: 2867.2, 60 sec: 3345.1, 300 sec: 3429.5). Total num frames: 3895296. Throughput: 0: 818.3. Samples: 974370. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:26:55,200][00631] Avg episode reward: [(0, '19.712')] [2023-02-23 20:27:00,197][00631] Fps is (10 sec: 2457.6, 60 sec: 3345.1, 300 sec: 3429.6). Total num frames: 3907584. Throughput: 0: 798.8. Samples: 977582. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:27:00,202][00631] Avg episode reward: [(0, '20.625')] [2023-02-23 20:27:05,197][00631] Fps is (10 sec: 2457.6, 60 sec: 3140.3, 300 sec: 3415.6). Total num frames: 3919872. Throughput: 0: 794.0. Samples: 979356. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:27:05,206][00631] Avg episode reward: [(0, '21.015')] [2023-02-23 20:27:05,222][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000957_3919872.pth... [2023-02-23 20:27:05,398][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000758_3104768.pth [2023-02-23 20:27:07,807][10898] Updated weights for policy 0, policy_version 960 (0.0017) [2023-02-23 20:27:10,197][00631] Fps is (10 sec: 3276.8, 60 sec: 3208.5, 300 sec: 3415.6). Total num frames: 3940352. Throughput: 0: 789.1. Samples: 984738. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:27:10,205][00631] Avg episode reward: [(0, '20.055')] [2023-02-23 20:27:15,197][00631] Fps is (10 sec: 4096.0, 60 sec: 3276.9, 300 sec: 3415.6). Total num frames: 3960832. Throughput: 0: 790.4. Samples: 991132. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0) [2023-02-23 20:27:15,200][00631] Avg episode reward: [(0, '20.939')] [2023-02-23 20:27:18,274][10898] Updated weights for policy 0, policy_version 970 (0.0019) [2023-02-23 20:27:20,197][00631] Fps is (10 sec: 3686.4, 60 sec: 3345.1, 300 sec: 3429.5). Total num frames: 3977216. Throughput: 0: 795.6. Samples: 993442. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0) [2023-02-23 20:27:20,201][00631] Avg episode reward: [(0, '21.019')] [2023-02-23 20:27:25,197][00631] Fps is (10 sec: 2867.1, 60 sec: 3208.5, 300 sec: 3415.6). Total num frames: 3989504. Throughput: 0: 796.6. Samples: 997524. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0) [2023-02-23 20:27:25,210][00631] Avg episode reward: [(0, '21.804')] [2023-02-23 20:27:28,918][10884] Stopping Batcher_0... [2023-02-23 20:27:28,919][10884] Loop batcher_evt_loop terminating... [2023-02-23 20:27:28,920][00631] Component Batcher_0 stopped! [2023-02-23 20:27:28,925][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... [2023-02-23 20:27:28,967][10904] Stopping RolloutWorker_w5... [2023-02-23 20:27:28,968][00631] Component RolloutWorker_w5 stopped! [2023-02-23 20:27:28,979][10900] Stopping RolloutWorker_w1... [2023-02-23 20:27:28,969][10904] Loop rollout_proc5_evt_loop terminating... [2023-02-23 20:27:28,979][00631] Component RolloutWorker_w1 stopped! [2023-02-23 20:27:28,987][10906] Stopping RolloutWorker_w7... [2023-02-23 20:27:28,990][10902] Stopping RolloutWorker_w3... [2023-02-23 20:27:28,988][00631] Component RolloutWorker_w7 stopped! [2023-02-23 20:27:28,992][00631] Component RolloutWorker_w3 stopped! [2023-02-23 20:27:28,980][10900] Loop rollout_proc1_evt_loop terminating... [2023-02-23 20:27:28,988][10906] Loop rollout_proc7_evt_loop terminating... [2023-02-23 20:27:29,001][10902] Loop rollout_proc3_evt_loop terminating... [2023-02-23 20:27:29,015][10898] Weights refcount: 2 0 [2023-02-23 20:27:29,022][00631] Component RolloutWorker_w6 stopped! [2023-02-23 20:27:29,026][10905] Stopping RolloutWorker_w6... [2023-02-23 20:27:29,027][10905] Loop rollout_proc6_evt_loop terminating... [2023-02-23 20:27:29,034][00631] Component InferenceWorker_p0-w0 stopped! [2023-02-23 20:27:29,034][10898] Stopping InferenceWorker_p0-w0... [2023-02-23 20:27:29,040][10898] Loop inference_proc0-0_evt_loop terminating... [2023-02-23 20:27:29,046][00631] Component RolloutWorker_w4 stopped! [2023-02-23 20:27:29,046][10903] Stopping RolloutWorker_w4... [2023-02-23 20:27:29,062][10903] Loop rollout_proc4_evt_loop terminating... [2023-02-23 20:27:29,076][10899] Stopping RolloutWorker_w0... [2023-02-23 20:27:29,077][10899] Loop rollout_proc0_evt_loop terminating... [2023-02-23 20:27:29,082][00631] Component RolloutWorker_w0 stopped! [2023-02-23 20:27:29,087][10901] Stopping RolloutWorker_w2... [2023-02-23 20:27:29,089][00631] Component RolloutWorker_w2 stopped! [2023-02-23 20:27:29,088][10901] Loop rollout_proc2_evt_loop terminating... [2023-02-23 20:27:29,140][10884] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000861_3526656.pth [2023-02-23 20:27:29,149][10884] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... [2023-02-23 20:27:29,310][00631] Component LearnerWorker_p0 stopped! [2023-02-23 20:27:29,310][10884] Stopping LearnerWorker_p0... [2023-02-23 20:27:29,312][00631] Waiting for process learner_proc0 to stop... [2023-02-23 20:27:29,312][10884] Loop learner_proc0_evt_loop terminating... [2023-02-23 20:27:31,206][00631] Waiting for process inference_proc0-0 to join... [2023-02-23 20:27:31,589][00631] Waiting for process rollout_proc0 to join... [2023-02-23 20:27:32,015][00631] Waiting for process rollout_proc1 to join... [2023-02-23 20:27:32,016][00631] Waiting for process rollout_proc2 to join... [2023-02-23 20:27:32,028][00631] Waiting for process rollout_proc3 to join... [2023-02-23 20:27:32,029][00631] Waiting for process rollout_proc4 to join... [2023-02-23 20:27:32,032][00631] Waiting for process rollout_proc5 to join... [2023-02-23 20:27:32,035][00631] Waiting for process rollout_proc6 to join... [2023-02-23 20:27:32,038][00631] Waiting for process rollout_proc7 to join... [2023-02-23 20:27:32,045][00631] Batcher 0 profile tree view: batching: 27.7991, releasing_batches: 0.0274 [2023-02-23 20:27:32,052][00631] InferenceWorker_p0-w0 profile tree view: wait_policy: 0.0001 wait_policy_total: 571.8816 update_model: 8.3421 weight_update: 0.0026 one_step: 0.0110 handle_policy_step: 566.0898 deserialize: 15.8038, stack: 3.1940, obs_to_device_normalize: 121.8924, forward: 277.7904, send_messages: 27.5475 prepare_outputs: 90.8741 to_cpu: 56.2697 [2023-02-23 20:27:32,054][00631] Learner 0 profile tree view: misc: 0.0064, prepare_batch: 17.4821 train: 77.7810 epoch_init: 0.0106, minibatch_init: 0.0064, losses_postprocess: 0.6149, kl_divergence: 0.6251, after_optimizer: 32.6310 calculate_losses: 27.8452 losses_init: 0.0039, forward_head: 1.8086, bptt_initial: 18.1649, tail: 1.3877, advantages_returns: 0.2862, losses: 3.4075 bptt: 2.4140 bptt_forward_core: 2.3457 update: 15.4625 clip: 1.5144 [2023-02-23 20:27:32,055][00631] RolloutWorker_w0 profile tree view: wait_for_trajectories: 0.4067, enqueue_policy_requests: 161.8164, env_step: 890.7249, overhead: 24.0875, complete_rollouts: 7.8281 save_policy_outputs: 22.5890 split_output_tensors: 11.2162 [2023-02-23 20:27:32,057][00631] RolloutWorker_w7 profile tree view: wait_for_trajectories: 0.3422, enqueue_policy_requests: 165.6100, env_step: 886.8571, overhead: 23.7131, complete_rollouts: 7.5647 save_policy_outputs: 22.4796 split_output_tensors: 10.8264 [2023-02-23 20:27:32,058][00631] Loop Runner_EvtLoop terminating... [2023-02-23 20:27:32,060][00631] Runner profile tree view: main_loop: 1221.9194 [2023-02-23 20:27:32,062][00631] Collected {0: 4005888}, FPS: 3278.4 [2023-02-23 20:27:32,214][00631] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json [2023-02-23 20:27:32,217][00631] Overriding arg 'num_workers' with value 1 passed from command line [2023-02-23 20:27:32,221][00631] Adding new argument 'no_render'=True that is not in the saved config file! [2023-02-23 20:27:32,224][00631] Adding new argument 'save_video'=True that is not in the saved config file! [2023-02-23 20:27:32,227][00631] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! [2023-02-23 20:27:32,230][00631] Adding new argument 'video_name'=None that is not in the saved config file! [2023-02-23 20:27:32,231][00631] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file! [2023-02-23 20:27:32,236][00631] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! [2023-02-23 20:27:32,238][00631] Adding new argument 'push_to_hub'=False that is not in the saved config file! [2023-02-23 20:27:32,240][00631] Adding new argument 'hf_repository'=None that is not in the saved config file! [2023-02-23 20:27:32,244][00631] Adding new argument 'policy_index'=0 that is not in the saved config file! [2023-02-23 20:27:32,248][00631] Adding new argument 'eval_deterministic'=False that is not in the saved config file! [2023-02-23 20:27:32,249][00631] Adding new argument 'train_script'=None that is not in the saved config file! [2023-02-23 20:27:32,252][00631] Adding new argument 'enjoy_script'=None that is not in the saved config file! [2023-02-23 20:27:32,253][00631] Using frameskip 1 and render_action_repeat=4 for evaluation [2023-02-23 20:27:32,274][00631] Doom resolution: 160x120, resize resolution: (128, 72) [2023-02-23 20:27:32,278][00631] RunningMeanStd input shape: (3, 72, 128) [2023-02-23 20:27:32,282][00631] RunningMeanStd input shape: (1,) [2023-02-23 20:27:32,300][00631] ConvEncoder: input_channels=3 [2023-02-23 20:27:32,999][00631] Conv encoder output size: 512 [2023-02-23 20:27:33,001][00631] Policy head output size: 512 [2023-02-23 20:27:35,369][00631] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... [2023-02-23 20:27:36,809][00631] Num frames 100... [2023-02-23 20:27:36,967][00631] Num frames 200... [2023-02-23 20:27:37,127][00631] Num frames 300... [2023-02-23 20:27:37,297][00631] Num frames 400... [2023-02-23 20:27:37,462][00631] Num frames 500... [2023-02-23 20:27:37,627][00631] Num frames 600... [2023-02-23 20:27:37,797][00631] Num frames 700... [2023-02-23 20:27:37,953][00631] Num frames 800... [2023-02-23 20:27:38,119][00631] Num frames 900... [2023-02-23 20:27:38,289][00631] Num frames 1000... [2023-02-23 20:27:38,387][00631] Avg episode rewards: #0: 20.240, true rewards: #0: 10.240 [2023-02-23 20:27:38,390][00631] Avg episode reward: 20.240, avg true_objective: 10.240 [2023-02-23 20:27:38,518][00631] Num frames 1100... [2023-02-23 20:27:38,680][00631] Num frames 1200... [2023-02-23 20:27:38,842][00631] Num frames 1300... [2023-02-23 20:27:38,999][00631] Num frames 1400... [2023-02-23 20:27:39,158][00631] Num frames 1500... [2023-02-23 20:27:39,235][00631] Avg episode rewards: #0: 13.560, true rewards: #0: 7.560 [2023-02-23 20:27:39,238][00631] Avg episode reward: 13.560, avg true_objective: 7.560 [2023-02-23 20:27:39,410][00631] Num frames 1600... [2023-02-23 20:27:39,573][00631] Num frames 1700... [2023-02-23 20:27:39,742][00631] Num frames 1800... [2023-02-23 20:27:39,904][00631] Num frames 1900... [2023-02-23 20:27:40,054][00631] Num frames 2000... [2023-02-23 20:27:40,179][00631] Num frames 2100... [2023-02-23 20:27:40,339][00631] Avg episode rewards: #0: 12.947, true rewards: #0: 7.280 [2023-02-23 20:27:40,341][00631] Avg episode reward: 12.947, avg true_objective: 7.280 [2023-02-23 20:27:40,368][00631] Num frames 2200... [2023-02-23 20:27:40,491][00631] Num frames 2300... [2023-02-23 20:27:40,620][00631] Num frames 2400... [2023-02-23 20:27:40,744][00631] Num frames 2500... [2023-02-23 20:27:40,870][00631] Num frames 2600... [2023-02-23 20:27:40,983][00631] Num frames 2700... [2023-02-23 20:27:41,093][00631] Num frames 2800... [2023-02-23 20:27:41,217][00631] Num frames 2900... [2023-02-23 20:27:41,332][00631] Num frames 3000... [2023-02-23 20:27:41,426][00631] Avg episode rewards: #0: 14.330, true rewards: #0: 7.580 [2023-02-23 20:27:41,428][00631] Avg episode reward: 14.330, avg true_objective: 7.580 [2023-02-23 20:27:41,517][00631] Num frames 3100... [2023-02-23 20:27:41,633][00631] Num frames 3200... [2023-02-23 20:27:41,750][00631] Num frames 3300... [2023-02-23 20:27:41,887][00631] Avg episode rewards: #0: 12.930, true rewards: #0: 6.730 [2023-02-23 20:27:41,888][00631] Avg episode reward: 12.930, avg true_objective: 6.730 [2023-02-23 20:27:41,937][00631] Num frames 3400... [2023-02-23 20:27:42,050][00631] Num frames 3500... [2023-02-23 20:27:42,167][00631] Num frames 3600... [2023-02-23 20:27:42,290][00631] Num frames 3700... [2023-02-23 20:27:42,405][00631] Num frames 3800... [2023-02-23 20:27:42,519][00631] Num frames 3900... [2023-02-23 20:27:42,633][00631] Num frames 4000... [2023-02-23 20:27:42,696][00631] Avg episode rewards: #0: 12.842, true rewards: #0: 6.675 [2023-02-23 20:27:42,698][00631] Avg episode reward: 12.842, avg true_objective: 6.675 [2023-02-23 20:27:42,813][00631] Num frames 4100... [2023-02-23 20:27:42,941][00631] Num frames 4200... [2023-02-23 20:27:43,051][00631] Num frames 4300... [2023-02-23 20:27:43,160][00631] Num frames 4400... [2023-02-23 20:27:43,278][00631] Num frames 4500... [2023-02-23 20:27:43,393][00631] Num frames 4600... [2023-02-23 20:27:43,509][00631] Num frames 4700... [2023-02-23 20:27:43,634][00631] Num frames 4800... [2023-02-23 20:27:43,703][00631] Avg episode rewards: #0: 13.872, true rewards: #0: 6.871 [2023-02-23 20:27:43,708][00631] Avg episode reward: 13.872, avg true_objective: 6.871 [2023-02-23 20:27:43,817][00631] Num frames 4900... [2023-02-23 20:27:43,946][00631] Num frames 5000... [2023-02-23 20:27:44,058][00631] Num frames 5100... [2023-02-23 20:27:44,172][00631] Num frames 5200... [2023-02-23 20:27:44,297][00631] Num frames 5300... [2023-02-23 20:27:44,417][00631] Num frames 5400... [2023-02-23 20:27:44,535][00631] Num frames 5500... [2023-02-23 20:27:44,668][00631] Num frames 5600... [2023-02-23 20:27:44,794][00631] Num frames 5700... [2023-02-23 20:27:44,921][00631] Num frames 5800... [2023-02-23 20:27:45,044][00631] Num frames 5900... [2023-02-23 20:27:45,160][00631] Num frames 6000... [2023-02-23 20:27:45,275][00631] Num frames 6100... [2023-02-23 20:27:45,398][00631] Num frames 6200... [2023-02-23 20:27:45,515][00631] Num frames 6300... [2023-02-23 20:27:45,632][00631] Num frames 6400... [2023-02-23 20:27:45,746][00631] Num frames 6500... [2023-02-23 20:27:45,864][00631] Num frames 6600... [2023-02-23 20:27:45,984][00631] Num frames 6700... [2023-02-23 20:27:46,104][00631] Num frames 6800... [2023-02-23 20:27:46,228][00631] Avg episode rewards: #0: 19.072, true rewards: #0: 8.572 [2023-02-23 20:27:46,230][00631] Avg episode reward: 19.072, avg true_objective: 8.572 [2023-02-23 20:27:46,285][00631] Num frames 6900... [2023-02-23 20:27:46,414][00631] Num frames 7000... [2023-02-23 20:27:46,540][00631] Num frames 7100... [2023-02-23 20:27:46,653][00631] Num frames 7200... [2023-02-23 20:27:46,765][00631] Num frames 7300... [2023-02-23 20:27:46,880][00631] Num frames 7400... [2023-02-23 20:27:47,000][00631] Num frames 7500... [2023-02-23 20:27:47,116][00631] Num frames 7600... [2023-02-23 20:27:47,233][00631] Num frames 7700... [2023-02-23 20:27:47,356][00631] Num frames 7800... [2023-02-23 20:27:47,471][00631] Num frames 7900... [2023-02-23 20:27:47,587][00631] Num frames 8000... [2023-02-23 20:27:47,657][00631] Avg episode rewards: #0: 20.011, true rewards: #0: 8.900 [2023-02-23 20:27:47,658][00631] Avg episode reward: 20.011, avg true_objective: 8.900 [2023-02-23 20:27:47,771][00631] Num frames 8100... [2023-02-23 20:27:47,889][00631] Num frames 8200... [2023-02-23 20:27:48,005][00631] Num frames 8300... [2023-02-23 20:27:48,120][00631] Num frames 8400... [2023-02-23 20:27:48,240][00631] Num frames 8500... [2023-02-23 20:27:48,356][00631] Num frames 8600... [2023-02-23 20:27:48,474][00631] Num frames 8700... [2023-02-23 20:27:48,589][00631] Num frames 8800... [2023-02-23 20:27:48,707][00631] Num frames 8900... [2023-02-23 20:27:48,819][00631] Num frames 9000... [2023-02-23 20:27:48,933][00631] Num frames 9100... [2023-02-23 20:27:49,103][00631] Avg episode rewards: #0: 20.794, true rewards: #0: 9.194 [2023-02-23 20:27:49,105][00631] Avg episode reward: 20.794, avg true_objective: 9.194 [2023-02-23 20:28:50,274][00631] Replay video saved to /content/train_dir/default_experiment/replay.mp4! [2023-02-23 20:39:39,759][00631] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json [2023-02-23 20:39:39,763][00631] Overriding arg 'num_workers' with value 1 passed from command line [2023-02-23 20:39:39,766][00631] Adding new argument 'no_render'=True that is not in the saved config file! [2023-02-23 20:39:39,767][00631] Adding new argument 'save_video'=True that is not in the saved config file! [2023-02-23 20:39:39,768][00631] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file! [2023-02-23 20:39:39,770][00631] Adding new argument 'video_name'=None that is not in the saved config file! [2023-02-23 20:39:39,772][00631] Adding new argument 'max_num_frames'=100000 that is not in the saved config file! [2023-02-23 20:39:39,778][00631] Adding new argument 'max_num_episodes'=10 that is not in the saved config file! [2023-02-23 20:39:39,783][00631] Adding new argument 'push_to_hub'=True that is not in the saved config file! [2023-02-23 20:39:39,784][00631] Adding new argument 'hf_repository'='albertqueralto/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file! [2023-02-23 20:39:39,786][00631] Adding new argument 'policy_index'=0 that is not in the saved config file! [2023-02-23 20:39:39,787][00631] Adding new argument 'eval_deterministic'=False that is not in the saved config file! [2023-02-23 20:39:39,788][00631] Adding new argument 'train_script'=None that is not in the saved config file! [2023-02-23 20:39:39,789][00631] Adding new argument 'enjoy_script'=None that is not in the saved config file! [2023-02-23 20:39:39,790][00631] Using frameskip 1 and render_action_repeat=4 for evaluation [2023-02-23 20:39:39,815][00631] RunningMeanStd input shape: (3, 72, 128) [2023-02-23 20:39:39,820][00631] RunningMeanStd input shape: (1,) [2023-02-23 20:39:39,833][00631] ConvEncoder: input_channels=3 [2023-02-23 20:39:39,873][00631] Conv encoder output size: 512 [2023-02-23 20:39:39,874][00631] Policy head output size: 512 [2023-02-23 20:39:39,897][00631] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth... [2023-02-23 20:39:40,340][00631] Num frames 100... [2023-02-23 20:39:40,472][00631] Num frames 200... [2023-02-23 20:39:40,596][00631] Num frames 300... [2023-02-23 20:39:40,713][00631] Num frames 400... [2023-02-23 20:39:40,836][00631] Num frames 500... [2023-02-23 20:39:40,953][00631] Num frames 600... [2023-02-23 20:39:41,066][00631] Num frames 700... [2023-02-23 20:39:41,186][00631] Num frames 800... [2023-02-23 20:39:41,308][00631] Num frames 900... [2023-02-23 20:39:41,434][00631] Num frames 1000... [2023-02-23 20:39:41,566][00631] Num frames 1100... [2023-02-23 20:39:41,720][00631] Avg episode rewards: #0: 28.840, true rewards: #0: 11.840 [2023-02-23 20:39:41,722][00631] Avg episode reward: 28.840, avg true_objective: 11.840 [2023-02-23 20:39:41,744][00631] Num frames 1200... [2023-02-23 20:39:41,856][00631] Num frames 1300... [2023-02-23 20:39:41,975][00631] Num frames 1400... [2023-02-23 20:39:42,097][00631] Num frames 1500... [2023-02-23 20:39:42,212][00631] Num frames 1600... [2023-02-23 20:39:42,327][00631] Num frames 1700... [2023-02-23 20:39:42,441][00631] Num frames 1800... [2023-02-23 20:39:42,563][00631] Num frames 1900... [2023-02-23 20:39:42,693][00631] Num frames 2000... [2023-02-23 20:39:42,812][00631] Num frames 2100... [2023-02-23 20:39:42,930][00631] Num frames 2200... [2023-02-23 20:39:43,049][00631] Num frames 2300... [2023-02-23 20:39:43,162][00631] Num frames 2400... [2023-02-23 20:39:43,277][00631] Num frames 2500... [2023-02-23 20:39:43,387][00631] Num frames 2600... [2023-02-23 20:39:43,505][00631] Num frames 2700... [2023-02-23 20:39:43,629][00631] Num frames 2800... [2023-02-23 20:39:43,754][00631] Num frames 2900... [2023-02-23 20:39:43,877][00631] Num frames 3000... [2023-02-23 20:39:44,003][00631] Num frames 3100... [2023-02-23 20:39:44,122][00631] Num frames 3200... [2023-02-23 20:39:44,278][00631] Avg episode rewards: #0: 42.885, true rewards: #0: 16.385 [2023-02-23 20:39:44,280][00631] Avg episode reward: 42.885, avg true_objective: 16.385 [2023-02-23 20:39:44,312][00631] Num frames 3300... [2023-02-23 20:39:44,443][00631] Num frames 3400... [2023-02-23 20:39:44,587][00631] Num frames 3500... [2023-02-23 20:39:44,713][00631] Num frames 3600... [2023-02-23 20:39:44,838][00631] Num frames 3700... [2023-02-23 20:39:44,962][00631] Num frames 3800... [2023-02-23 20:39:45,084][00631] Num frames 3900... [2023-02-23 20:39:45,204][00631] Num frames 4000... [2023-02-23 20:39:45,319][00631] Num frames 4100... [2023-02-23 20:39:45,434][00631] Num frames 4200... [2023-02-23 20:39:45,551][00631] Num frames 4300... [2023-02-23 20:39:45,676][00631] Num frames 4400... [2023-02-23 20:39:45,803][00631] Num frames 4500... [2023-02-23 20:39:45,855][00631] Avg episode rewards: #0: 37.666, true rewards: #0: 15.000 [2023-02-23 20:39:45,857][00631] Avg episode reward: 37.666, avg true_objective: 15.000 [2023-02-23 20:39:45,980][00631] Num frames 4600... [2023-02-23 20:39:46,099][00631] Num frames 4700... [2023-02-23 20:39:46,214][00631] Num frames 4800... [2023-02-23 20:39:46,331][00631] Num frames 4900... [2023-02-23 20:39:46,463][00631] Num frames 5000... [2023-02-23 20:39:46,584][00631] Num frames 5100... [2023-02-23 20:39:46,709][00631] Num frames 5200... [2023-02-23 20:39:46,827][00631] Num frames 5300... [2023-02-23 20:39:46,946][00631] Num frames 5400... [2023-02-23 20:39:47,042][00631] Avg episode rewards: #0: 34.340, true rewards: #0: 13.590 [2023-02-23 20:39:47,044][00631] Avg episode reward: 34.340, avg true_objective: 13.590 [2023-02-23 20:39:47,128][00631] Num frames 5500... [2023-02-23 20:39:47,267][00631] Num frames 5600... [2023-02-23 20:39:47,399][00631] Num frames 5700... [2023-02-23 20:39:47,527][00631] Num frames 5800... [2023-02-23 20:39:47,662][00631] Num frames 5900... [2023-02-23 20:39:47,787][00631] Num frames 6000... [2023-02-23 20:39:47,913][00631] Num frames 6100... [2023-02-23 20:39:48,028][00631] Num frames 6200... [2023-02-23 20:39:48,145][00631] Num frames 6300... [2023-02-23 20:39:48,263][00631] Num frames 6400... [2023-02-23 20:39:48,382][00631] Num frames 6500... [2023-02-23 20:39:48,501][00631] Avg episode rewards: #0: 32.912, true rewards: #0: 13.112 [2023-02-23 20:39:48,503][00631] Avg episode reward: 32.912, avg true_objective: 13.112 [2023-02-23 20:39:48,559][00631] Num frames 6600... [2023-02-23 20:39:48,693][00631] Num frames 6700... [2023-02-23 20:39:48,812][00631] Num frames 6800... [2023-02-23 20:39:48,932][00631] Num frames 6900... [2023-02-23 20:39:49,075][00631] Num frames 7000... [2023-02-23 20:39:49,239][00631] Num frames 7100... [2023-02-23 20:39:49,397][00631] Num frames 7200... [2023-02-23 20:39:49,560][00631] Num frames 7300... [2023-02-23 20:39:49,786][00631] Avg episode rewards: #0: 30.825, true rewards: #0: 12.325 [2023-02-23 20:39:49,788][00631] Avg episode reward: 30.825, avg true_objective: 12.325 [2023-02-23 20:39:49,803][00631] Num frames 7400... [2023-02-23 20:39:49,965][00631] Num frames 7500... [2023-02-23 20:39:50,141][00631] Num frames 7600... [2023-02-23 20:39:50,299][00631] Num frames 7700... [2023-02-23 20:39:50,467][00631] Num frames 7800... [2023-02-23 20:39:50,635][00631] Num frames 7900... [2023-02-23 20:39:50,810][00631] Num frames 8000... [2023-02-23 20:39:50,979][00631] Num frames 8100... [2023-02-23 20:39:51,143][00631] Num frames 8200... [2023-02-23 20:39:51,307][00631] Num frames 8300... [2023-02-23 20:39:51,472][00631] Num frames 8400... [2023-02-23 20:39:51,641][00631] Num frames 8500... [2023-02-23 20:39:51,812][00631] Num frames 8600... [2023-02-23 20:39:51,981][00631] Num frames 8700... [2023-02-23 20:39:52,147][00631] Num frames 8800... [2023-02-23 20:39:52,318][00631] Num frames 8900... [2023-02-23 20:39:52,487][00631] Num frames 9000... [2023-02-23 20:39:52,653][00631] Num frames 9100... [2023-02-23 20:39:52,770][00631] Num frames 9200... [2023-02-23 20:39:52,903][00631] Num frames 9300... [2023-02-23 20:39:53,032][00631] Num frames 9400... [2023-02-23 20:39:53,199][00631] Avg episode rewards: #0: 34.707, true rewards: #0: 13.564 [2023-02-23 20:39:53,202][00631] Avg episode reward: 34.707, avg true_objective: 13.564 [2023-02-23 20:39:53,217][00631] Num frames 9500... [2023-02-23 20:39:53,346][00631] Num frames 9600... [2023-02-23 20:39:53,473][00631] Num frames 9700... [2023-02-23 20:39:53,611][00631] Num frames 9800... [2023-02-23 20:39:53,737][00631] Num frames 9900... [2023-02-23 20:39:53,861][00631] Num frames 10000... [2023-02-23 20:39:54,001][00631] Avg episode rewards: #0: 31.839, true rewards: #0: 12.589 [2023-02-23 20:39:54,003][00631] Avg episode reward: 31.839, avg true_objective: 12.589 [2023-02-23 20:39:54,041][00631] Num frames 10100... [2023-02-23 20:39:54,159][00631] Num frames 10200... [2023-02-23 20:39:54,274][00631] Num frames 10300... [2023-02-23 20:39:54,387][00631] Num frames 10400... [2023-02-23 20:39:54,512][00631] Num frames 10500... [2023-02-23 20:39:54,626][00631] Num frames 10600... [2023-02-23 20:39:54,739][00631] Num frames 10700... [2023-02-23 20:39:54,861][00631] Num frames 10800... [2023-02-23 20:39:54,984][00631] Num frames 10900... [2023-02-23 20:39:55,100][00631] Num frames 11000... [2023-02-23 20:39:55,224][00631] Num frames 11100... [2023-02-23 20:39:55,290][00631] Avg episode rewards: #0: 31.007, true rewards: #0: 12.340 [2023-02-23 20:39:55,292][00631] Avg episode reward: 31.007, avg true_objective: 12.340 [2023-02-23 20:39:55,412][00631] Num frames 11200... [2023-02-23 20:39:55,531][00631] Num frames 11300... [2023-02-23 20:39:55,653][00631] Num frames 11400... [2023-02-23 20:39:55,776][00631] Num frames 11500... [2023-02-23 20:39:55,907][00631] Num frames 11600... [2023-02-23 20:39:56,020][00631] Num frames 11700... [2023-02-23 20:39:56,131][00631] Num frames 11800... [2023-02-23 20:39:56,245][00631] Num frames 11900... [2023-02-23 20:39:56,362][00631] Num frames 12000... [2023-02-23 20:39:56,485][00631] Avg episode rewards: #0: 29.957, true rewards: #0: 12.057 [2023-02-23 20:39:56,487][00631] Avg episode reward: 29.957, avg true_objective: 12.057 [2023-02-23 20:41:14,867][00631] Replay video saved to /content/train_dir/default_experiment/replay.mp4!