[2023-02-22 19:57:11,336][01716] Saving configuration to /content/train_dir/default_experiment/config.json...
[2023-02-22 19:57:11,340][01716] Rollout worker 0 uses device cpu
[2023-02-22 19:57:11,342][01716] Rollout worker 1 uses device cpu
[2023-02-22 19:57:11,345][01716] Rollout worker 2 uses device cpu
[2023-02-22 19:57:11,347][01716] Rollout worker 3 uses device cpu
[2023-02-22 19:57:11,350][01716] Rollout worker 4 uses device cpu
[2023-02-22 19:57:11,351][01716] Rollout worker 5 uses device cpu
[2023-02-22 19:57:11,352][01716] Rollout worker 6 uses device cpu
[2023-02-22 19:57:11,353][01716] Rollout worker 7 uses device cpu
[2023-02-22 19:57:11,526][01716] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 19:57:11,529][01716] InferenceWorker_p0-w0: min num requests: 2
[2023-02-22 19:57:11,560][01716] Starting all processes...
[2023-02-22 19:57:11,561][01716] Starting process learner_proc0
[2023-02-22 19:57:11,614][01716] Starting all processes...
[2023-02-22 19:57:11,622][01716] Starting process inference_proc0-0
[2023-02-22 19:57:11,622][01716] Starting process rollout_proc0
[2023-02-22 19:57:11,624][01716] Starting process rollout_proc1
[2023-02-22 19:57:11,624][01716] Starting process rollout_proc2
[2023-02-22 19:57:11,624][01716] Starting process rollout_proc3
[2023-02-22 19:57:11,624][01716] Starting process rollout_proc4
[2023-02-22 19:57:11,624][01716] Starting process rollout_proc5
[2023-02-22 19:57:11,625][01716] Starting process rollout_proc6
[2023-02-22 19:57:11,625][01716] Starting process rollout_proc7
[2023-02-22 19:57:22,769][12913] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 19:57:22,769][12913] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0
[2023-02-22 19:57:23,030][12927] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 19:57:23,033][12927] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0
[2023-02-22 19:57:23,052][12930] Worker 2 uses CPU cores [0]
[2023-02-22 19:57:23,082][12934] Worker 6 uses CPU cores [0]
[2023-02-22 19:57:23,085][12933] Worker 5 uses CPU cores [1]
[2023-02-22 19:57:23,097][12931] Worker 3 uses CPU cores [1]
[2023-02-22 19:57:23,106][12928] Worker 0 uses CPU cores [0]
[2023-02-22 19:57:23,126][12929] Worker 1 uses CPU cores [1]
[2023-02-22 19:57:23,236][12932] Worker 4 uses CPU cores [0]
[2023-02-22 19:57:23,277][12935] Worker 7 uses CPU cores [1]
[2023-02-22 19:57:23,587][12913] Num visible devices: 1
[2023-02-22 19:57:23,587][12927] Num visible devices: 1
[2023-02-22 19:57:23,598][12913] Starting seed is not provided
[2023-02-22 19:57:23,599][12913] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 19:57:23,599][12913] Initializing actor-critic model on device cuda:0
[2023-02-22 19:57:23,599][12913] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 19:57:23,601][12913] RunningMeanStd input shape: (1,)
[2023-02-22 19:57:23,614][12913] ConvEncoder: input_channels=3
[2023-02-22 19:57:23,856][12913] Conv encoder output size: 512
[2023-02-22 19:57:23,856][12913] Policy head output size: 512
[2023-02-22 19:57:23,896][12913] Created Actor Critic model with architecture:
[2023-02-22 19:57:23,896][12913] 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)
  )
)
[2023-02-22 19:57:30,005][12913] Using optimizer <class 'torch.optim.adam.Adam'>
[2023-02-22 19:57:30,007][12913] No checkpoints found
[2023-02-22 19:57:30,007][12913] Did not load from checkpoint, starting from scratch!
[2023-02-22 19:57:30,008][12913] Initialized policy 0 weights for model version 0
[2023-02-22 19:57:30,012][12913] LearnerWorker_p0 finished initialization!
[2023-02-22 19:57:30,014][12913] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 19:57:30,215][12927] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 19:57:30,216][12927] RunningMeanStd input shape: (1,)
[2023-02-22 19:57:30,228][12927] ConvEncoder: input_channels=3
[2023-02-22 19:57:30,322][12927] Conv encoder output size: 512
[2023-02-22 19:57:30,323][12927] Policy head output size: 512
[2023-02-22 19:57:31,518][01716] Heartbeat connected on Batcher_0
[2023-02-22 19:57:31,521][01716] Heartbeat connected on LearnerWorker_p0
[2023-02-22 19:57:31,537][01716] Heartbeat connected on RolloutWorker_w0
[2023-02-22 19:57:31,547][01716] Heartbeat connected on RolloutWorker_w2
[2023-02-22 19:57:31,549][01716] Heartbeat connected on RolloutWorker_w3
[2023-02-22 19:57:31,557][01716] Heartbeat connected on RolloutWorker_w1
[2023-02-22 19:57:31,559][01716] Heartbeat connected on RolloutWorker_w6
[2023-02-22 19:57:31,560][01716] Heartbeat connected on RolloutWorker_w4
[2023-02-22 19:57:31,566][01716] Heartbeat connected on RolloutWorker_w7
[2023-02-22 19:57:31,567][01716] Heartbeat connected on RolloutWorker_w5
[2023-02-22 19:57:31,857][01716] 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)
[2023-02-22 19:57:33,433][01716] Inference worker 0-0 is ready!
[2023-02-22 19:57:33,438][01716] All inference workers are ready! Signal rollout workers to start!
[2023-02-22 19:57:33,442][01716] Heartbeat connected on InferenceWorker_p0-w0
[2023-02-22 19:57:33,574][12932] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:33,584][12930] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:33,589][12935] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:33,591][12933] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:33,621][12929] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:33,708][12931] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:33,780][12928] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:33,770][12934] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 19:57:35,132][12932] Decorrelating experience for 0 frames...
[2023-02-22 19:57:35,153][12934] Decorrelating experience for 0 frames...
[2023-02-22 19:57:35,206][12933] Decorrelating experience for 0 frames...
[2023-02-22 19:57:35,211][12935] Decorrelating experience for 0 frames...
[2023-02-22 19:57:35,221][12929] Decorrelating experience for 0 frames...
[2023-02-22 19:57:35,280][12931] Decorrelating experience for 0 frames...
[2023-02-22 19:57:36,015][12929] Decorrelating experience for 32 frames...
[2023-02-22 19:57:36,071][12935] Decorrelating experience for 32 frames...
[2023-02-22 19:57:36,248][12934] Decorrelating experience for 32 frames...
[2023-02-22 19:57:36,290][12932] Decorrelating experience for 32 frames...
[2023-02-22 19:57:36,341][12928] Decorrelating experience for 0 frames...
[2023-02-22 19:57:36,857][01716] 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)
[2023-02-22 19:57:37,008][12931] Decorrelating experience for 32 frames...
[2023-02-22 19:57:37,098][12930] Decorrelating experience for 0 frames...
[2023-02-22 19:57:37,129][12934] Decorrelating experience for 64 frames...
[2023-02-22 19:57:37,288][12935] Decorrelating experience for 64 frames...
[2023-02-22 19:57:37,414][12933] Decorrelating experience for 32 frames...
[2023-02-22 19:57:37,846][12930] Decorrelating experience for 32 frames...
[2023-02-22 19:57:37,892][12932] Decorrelating experience for 64 frames...
[2023-02-22 19:57:37,902][12929] Decorrelating experience for 64 frames...
[2023-02-22 19:57:38,125][12933] Decorrelating experience for 64 frames...
[2023-02-22 19:57:38,681][12934] Decorrelating experience for 96 frames...
[2023-02-22 19:57:38,687][12928] Decorrelating experience for 32 frames...
[2023-02-22 19:57:38,996][12932] Decorrelating experience for 96 frames...
[2023-02-22 19:57:39,453][12933] Decorrelating experience for 96 frames...
[2023-02-22 19:57:39,477][12929] Decorrelating experience for 96 frames...
[2023-02-22 19:57:39,743][12928] Decorrelating experience for 64 frames...
[2023-02-22 19:57:40,006][12931] Decorrelating experience for 64 frames...
[2023-02-22 19:57:40,640][12930] Decorrelating experience for 64 frames...
[2023-02-22 19:57:40,780][12935] Decorrelating experience for 96 frames...
[2023-02-22 19:57:40,813][12931] Decorrelating experience for 96 frames...
[2023-02-22 19:57:40,958][12928] Decorrelating experience for 96 frames...
[2023-02-22 19:57:41,327][12930] Decorrelating experience for 96 frames...
[2023-02-22 19:57:41,857][01716] 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)
[2023-02-22 19:57:45,150][12913] Signal inference workers to stop experience collection...
[2023-02-22 19:57:45,167][12927] InferenceWorker_p0-w0: stopping experience collection
[2023-02-22 19:57:46,857][01716] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 166.4. Samples: 2496. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-22 19:57:46,863][01716] Avg episode reward: [(0, '2.010')]
[2023-02-22 19:57:47,606][12913] Signal inference workers to resume experience collection...
[2023-02-22 19:57:47,607][12927] InferenceWorker_p0-w0: resuming experience collection
[2023-02-22 19:57:51,857][01716] Fps is (10 sec: 1228.8, 60 sec: 614.4, 300 sec: 614.4). Total num frames: 12288. Throughput: 0: 221.2. Samples: 4424. Policy #0 lag: (min: 1.0, avg: 1.0, max: 1.0)
[2023-02-22 19:57:51,864][01716] Avg episode reward: [(0, '3.018')]
[2023-02-22 19:57:56,857][01716] Fps is (10 sec: 3277.0, 60 sec: 1310.7, 300 sec: 1310.7). Total num frames: 32768. Throughput: 0: 278.3. Samples: 6958. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 19:57:56,864][01716] Avg episode reward: [(0, '4.035')]
[2023-02-22 19:57:57,816][12927] Updated weights for policy 0, policy_version 10 (0.0019)
[2023-02-22 19:58:01,857][01716] Fps is (10 sec: 4505.6, 60 sec: 1911.5, 300 sec: 1911.5). Total num frames: 57344. Throughput: 0: 463.4. Samples: 13902. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:58:01,865][01716] Avg episode reward: [(0, '4.592')]
[2023-02-22 19:58:06,859][01716] Fps is (10 sec: 4095.0, 60 sec: 2106.4, 300 sec: 2106.4). Total num frames: 73728. Throughput: 0: 562.0. Samples: 19670. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 19:58:06,862][01716] Avg episode reward: [(0, '4.382')]
[2023-02-22 19:58:08,396][12927] Updated weights for policy 0, policy_version 20 (0.0019)
[2023-02-22 19:58:11,857][01716] Fps is (10 sec: 3276.7, 60 sec: 2252.8, 300 sec: 2252.8). Total num frames: 90112. Throughput: 0: 546.2. Samples: 21848. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:58:11,861][01716] Avg episode reward: [(0, '4.256')]
[2023-02-22 19:58:16,857][01716] Fps is (10 sec: 3687.3, 60 sec: 2457.6, 300 sec: 2457.6). Total num frames: 110592. Throughput: 0: 602.0. Samples: 27088. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 19:58:16,863][01716] Avg episode reward: [(0, '4.239')]
[2023-02-22 19:58:16,874][12913] Saving new best policy, reward=4.239!
[2023-02-22 19:58:19,374][12927] Updated weights for policy 0, policy_version 30 (0.0026)
[2023-02-22 19:58:21,857][01716] Fps is (10 sec: 4096.2, 60 sec: 2621.4, 300 sec: 2621.4). Total num frames: 131072. Throughput: 0: 742.4. Samples: 33406. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 19:58:21,863][01716] Avg episode reward: [(0, '4.366')]
[2023-02-22 19:58:21,866][12913] Saving new best policy, reward=4.366!
[2023-02-22 19:58:26,861][01716] Fps is (10 sec: 3684.8, 60 sec: 2680.8, 300 sec: 2680.8). Total num frames: 147456. Throughput: 0: 807.0. Samples: 36318. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 19:58:26,864][01716] Avg episode reward: [(0, '4.363')]
[2023-02-22 19:58:31,850][12927] Updated weights for policy 0, policy_version 40 (0.0017)
[2023-02-22 19:58:31,857][01716] Fps is (10 sec: 3276.8, 60 sec: 2730.7, 300 sec: 2730.7). Total num frames: 163840. Throughput: 0: 846.6. Samples: 40594. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 19:58:31,859][01716] Avg episode reward: [(0, '4.370')]
[2023-02-22 19:58:31,870][12913] Saving new best policy, reward=4.370!
[2023-02-22 19:58:36,857][01716] Fps is (10 sec: 3278.2, 60 sec: 3003.7, 300 sec: 2772.7). Total num frames: 180224. Throughput: 0: 926.3. Samples: 46106. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 19:58:36,860][01716] Avg episode reward: [(0, '4.387')]
[2023-02-22 19:58:36,921][12913] Saving new best policy, reward=4.387!
[2023-02-22 19:58:41,314][12927] Updated weights for policy 0, policy_version 50 (0.0028)
[2023-02-22 19:58:41,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3413.3, 300 sec: 2925.7). Total num frames: 204800. Throughput: 0: 947.1. Samples: 49576. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 19:58:41,862][01716] Avg episode reward: [(0, '4.614')]
[2023-02-22 19:58:41,864][12913] Saving new best policy, reward=4.614!
[2023-02-22 19:58:46,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3754.7, 300 sec: 3003.7). Total num frames: 225280. Throughput: 0: 930.1. Samples: 55758. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 19:58:46,862][01716] Avg episode reward: [(0, '4.585')]
[2023-02-22 19:58:51,857][01716] Fps is (10 sec: 3276.6, 60 sec: 3754.6, 300 sec: 2969.6). Total num frames: 237568. Throughput: 0: 904.8. Samples: 60382. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 19:58:51,860][01716] Avg episode reward: [(0, '4.465')]
[2023-02-22 19:58:53,356][12927] Updated weights for policy 0, policy_version 60 (0.0033)
[2023-02-22 19:58:56,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3084.1). Total num frames: 262144. Throughput: 0: 918.6. Samples: 63186. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 19:58:56,864][01716] Avg episode reward: [(0, '4.355')]
[2023-02-22 19:59:01,857][01716] Fps is (10 sec: 4505.8, 60 sec: 3754.7, 300 sec: 3140.3). Total num frames: 282624. Throughput: 0: 962.3. Samples: 70392. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 19:59:01,862][01716] Avg episode reward: [(0, '4.362')]
[2023-02-22 19:59:01,907][12927] Updated weights for policy 0, policy_version 70 (0.0023)
[2023-02-22 19:59:06,862][01716] Fps is (10 sec: 4093.7, 60 sec: 3822.7, 300 sec: 3190.4). Total num frames: 303104. Throughput: 0: 952.9. Samples: 76290. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 19:59:06,864][01716] Avg episode reward: [(0, '4.541')]
[2023-02-22 19:59:06,879][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000074_303104.pth...
[2023-02-22 19:59:11,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3153.9). Total num frames: 315392. Throughput: 0: 937.3. Samples: 78492. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:59:11,864][01716] Avg episode reward: [(0, '4.520')]
[2023-02-22 19:59:14,092][12927] Updated weights for policy 0, policy_version 80 (0.0019)
[2023-02-22 19:59:16,857][01716] Fps is (10 sec: 3688.4, 60 sec: 3822.9, 300 sec: 3237.8). Total num frames: 339968. Throughput: 0: 969.3. Samples: 84212. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:59:16,859][01716] Avg episode reward: [(0, '4.570')]
[2023-02-22 19:59:21,857][01716] Fps is (10 sec: 4915.2, 60 sec: 3891.2, 300 sec: 3314.0). Total num frames: 364544. Throughput: 0: 1005.3. Samples: 91344. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:59:21,859][01716] Avg episode reward: [(0, '4.451')]
[2023-02-22 19:59:22,640][12927] Updated weights for policy 0, policy_version 90 (0.0016)
[2023-02-22 19:59:26,864][01716] Fps is (10 sec: 4092.9, 60 sec: 3891.0, 300 sec: 3312.2). Total num frames: 380928. Throughput: 0: 992.3. Samples: 94236. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:59:26,869][01716] Avg episode reward: [(0, '4.354')]
[2023-02-22 19:59:31,857][01716] Fps is (10 sec: 2867.0, 60 sec: 3822.9, 300 sec: 3276.8). Total num frames: 393216. Throughput: 0: 954.7. Samples: 98722. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 19:59:31,865][01716] Avg episode reward: [(0, '4.455')]
[2023-02-22 19:59:34,857][12927] Updated weights for policy 0, policy_version 100 (0.0016)
[2023-02-22 19:59:36,857][01716] Fps is (10 sec: 3689.2, 60 sec: 3959.5, 300 sec: 3342.3). Total num frames: 417792. Throughput: 0: 991.9. Samples: 105016. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:59:36,862][01716] Avg episode reward: [(0, '4.453')]
[2023-02-22 19:59:41,857][01716] Fps is (10 sec: 4915.5, 60 sec: 3959.5, 300 sec: 3402.8). Total num frames: 442368. Throughput: 0: 1009.1. Samples: 108594. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 19:59:41,864][01716] Avg episode reward: [(0, '4.477')]
[2023-02-22 19:59:43,499][12927] Updated weights for policy 0, policy_version 110 (0.0014)
[2023-02-22 19:59:46,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3398.2). Total num frames: 458752. Throughput: 0: 979.2. Samples: 114458. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 19:59:46,865][01716] Avg episode reward: [(0, '4.637')]
[2023-02-22 19:59:46,873][12913] Saving new best policy, reward=4.637!
[2023-02-22 19:59:51,858][01716] Fps is (10 sec: 2866.8, 60 sec: 3891.1, 300 sec: 3364.5). Total num frames: 471040. Throughput: 0: 946.9. Samples: 118896. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:59:51,862][01716] Avg episode reward: [(0, '4.641')]
[2023-02-22 19:59:51,870][12913] Saving new best policy, reward=4.641!
[2023-02-22 19:59:55,645][12927] Updated weights for policy 0, policy_version 120 (0.0020)
[2023-02-22 19:59:56,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3418.0). Total num frames: 495616. Throughput: 0: 968.3. Samples: 122064. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 19:59:56,864][01716] Avg episode reward: [(0, '4.445')]
[2023-02-22 20:00:01,859][01716] Fps is (10 sec: 4505.1, 60 sec: 3891.0, 300 sec: 3440.6). Total num frames: 516096. Throughput: 0: 990.1. Samples: 128768. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:00:01,862][01716] Avg episode reward: [(0, '4.583')]
[2023-02-22 20:00:06,866][01716] Fps is (10 sec: 3273.7, 60 sec: 3754.4, 300 sec: 3408.7). Total num frames: 528384. Throughput: 0: 916.6. Samples: 132602. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:00:06,874][01716] Avg episode reward: [(0, '4.801')]
[2023-02-22 20:00:06,889][12913] Saving new best policy, reward=4.801!
[2023-02-22 20:00:08,472][12927] Updated weights for policy 0, policy_version 130 (0.0031)
[2023-02-22 20:00:11,857][01716] Fps is (10 sec: 2048.5, 60 sec: 3686.4, 300 sec: 3353.6). Total num frames: 536576. Throughput: 0: 890.9. Samples: 134322. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:00:11,862][01716] Avg episode reward: [(0, '4.727')]
[2023-02-22 20:00:16,857][01716] Fps is (10 sec: 2869.9, 60 sec: 3618.1, 300 sec: 3376.1). Total num frames: 557056. Throughput: 0: 886.4. Samples: 138608. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:00:16,858][01716] Avg episode reward: [(0, '4.607')]
[2023-02-22 20:00:19,995][12927] Updated weights for policy 0, policy_version 140 (0.0016)
[2023-02-22 20:00:21,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3618.1, 300 sec: 3421.4). Total num frames: 581632. Throughput: 0: 904.8. Samples: 145730. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:00:21,863][01716] Avg episode reward: [(0, '4.593')]
[2023-02-22 20:00:26,857][01716] Fps is (10 sec: 4505.5, 60 sec: 3686.9, 300 sec: 3440.6). Total num frames: 602112. Throughput: 0: 903.7. Samples: 149262. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:00:26,861][01716] Avg episode reward: [(0, '4.474')]
[2023-02-22 20:00:30,788][12927] Updated weights for policy 0, policy_version 150 (0.0039)
[2023-02-22 20:00:31,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3413.3). Total num frames: 614400. Throughput: 0: 879.6. Samples: 154038. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:00:31,863][01716] Avg episode reward: [(0, '4.326')]
[2023-02-22 20:00:36,857][01716] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3431.8). Total num frames: 634880. Throughput: 0: 898.6. Samples: 159330. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:00:36,860][01716] Avg episode reward: [(0, '4.386')]
[2023-02-22 20:00:40,849][12927] Updated weights for policy 0, policy_version 160 (0.0027)
[2023-02-22 20:00:41,857][01716] Fps is (10 sec: 4505.5, 60 sec: 3618.1, 300 sec: 3470.8). Total num frames: 659456. Throughput: 0: 907.2. Samples: 162886. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:00:41,860][01716] Avg episode reward: [(0, '4.530')]
[2023-02-22 20:00:46,857][01716] Fps is (10 sec: 4505.4, 60 sec: 3686.4, 300 sec: 3486.8). Total num frames: 679936. Throughput: 0: 910.2. Samples: 169726. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:00:46,862][01716] Avg episode reward: [(0, '4.447')]
[2023-02-22 20:00:51,857][01716] Fps is (10 sec: 3276.9, 60 sec: 3686.5, 300 sec: 3461.1). Total num frames: 692224. Throughput: 0: 925.6. Samples: 174244. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:00:51,860][01716] Avg episode reward: [(0, '4.346')]
[2023-02-22 20:00:52,111][12927] Updated weights for policy 0, policy_version 170 (0.0020)
[2023-02-22 20:00:56,857][01716] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3476.6). Total num frames: 712704. Throughput: 0: 938.3. Samples: 176544. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:00:56,865][01716] Avg episode reward: [(0, '4.457')]
[2023-02-22 20:01:01,677][12927] Updated weights for policy 0, policy_version 180 (0.0026)
[2023-02-22 20:01:01,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3686.6, 300 sec: 3510.9). Total num frames: 737280. Throughput: 0: 997.3. Samples: 183488. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:01:01,864][01716] Avg episode reward: [(0, '4.524')]
[2023-02-22 20:01:06,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3823.5, 300 sec: 3524.5). Total num frames: 757760. Throughput: 0: 982.3. Samples: 189934. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:01:06,861][01716] Avg episode reward: [(0, '4.565')]
[2023-02-22 20:01:06,870][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000185_757760.pth...
[2023-02-22 20:01:11,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3500.2). Total num frames: 770048. Throughput: 0: 953.6. Samples: 192172. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:01:11,863][01716] Avg episode reward: [(0, '4.733')]
[2023-02-22 20:01:13,134][12927] Updated weights for policy 0, policy_version 190 (0.0018)
[2023-02-22 20:01:16,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3513.5). Total num frames: 790528. Throughput: 0: 960.7. Samples: 197268. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:01:16,860][01716] Avg episode reward: [(0, '4.708')]
[2023-02-22 20:01:21,857][01716] Fps is (10 sec: 4505.5, 60 sec: 3891.2, 300 sec: 3543.9). Total num frames: 815104. Throughput: 0: 1001.7. Samples: 204408. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:01:21,859][01716] Avg episode reward: [(0, '4.692')]
[2023-02-22 20:01:22,104][12927] Updated weights for policy 0, policy_version 200 (0.0014)
[2023-02-22 20:01:26,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3555.7). Total num frames: 835584. Throughput: 0: 1002.7. Samples: 208006. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:01:26,865][01716] Avg episode reward: [(0, '4.625')]
[2023-02-22 20:01:31,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3549.9). Total num frames: 851968. Throughput: 0: 950.6. Samples: 212502. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:01:31,860][01716] Avg episode reward: [(0, '4.568')]
[2023-02-22 20:01:34,159][12927] Updated weights for policy 0, policy_version 210 (0.0011)
[2023-02-22 20:01:36,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3561.0). Total num frames: 872448. Throughput: 0: 974.4. Samples: 218092. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:01:36,864][01716] Avg episode reward: [(0, '4.633')]
[2023-02-22 20:01:41,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3571.7). Total num frames: 892928. Throughput: 0: 1003.3. Samples: 221694. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:01:41,859][01716] Avg episode reward: [(0, '4.538')]
[2023-02-22 20:01:42,804][12927] Updated weights for policy 0, policy_version 220 (0.0015)
[2023-02-22 20:01:46,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3582.0). Total num frames: 913408. Throughput: 0: 994.7. Samples: 228250. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:01:46,862][01716] Avg episode reward: [(0, '4.548')]
[2023-02-22 20:01:51,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3576.1). Total num frames: 929792. Throughput: 0: 952.9. Samples: 232814. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:01:51,863][01716] Avg episode reward: [(0, '4.538')]
[2023-02-22 20:01:55,043][12927] Updated weights for policy 0, policy_version 230 (0.0028)
[2023-02-22 20:01:56,858][01716] Fps is (10 sec: 3686.1, 60 sec: 3959.4, 300 sec: 3585.9). Total num frames: 950272. Throughput: 0: 957.6. Samples: 235264. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:01:56,863][01716] Avg episode reward: [(0, '4.667')]
[2023-02-22 20:02:01,857][01716] Fps is (10 sec: 4505.7, 60 sec: 3959.5, 300 sec: 3610.5). Total num frames: 974848. Throughput: 0: 1004.2. Samples: 242456. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:02:01,860][01716] Avg episode reward: [(0, '4.498')]
[2023-02-22 20:02:03,507][12927] Updated weights for policy 0, policy_version 240 (0.0019)
[2023-02-22 20:02:06,857][01716] Fps is (10 sec: 4096.3, 60 sec: 3891.2, 300 sec: 3604.5). Total num frames: 991232. Throughput: 0: 981.6. Samples: 248578. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:02:06,860][01716] Avg episode reward: [(0, '4.598')]
[2023-02-22 20:02:11,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3598.6). Total num frames: 1007616. Throughput: 0: 952.5. Samples: 250870. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:02:11,865][01716] Avg episode reward: [(0, '4.599')]
[2023-02-22 20:02:15,814][12927] Updated weights for policy 0, policy_version 250 (0.0031)
[2023-02-22 20:02:16,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3607.4). Total num frames: 1028096. Throughput: 0: 968.6. Samples: 256090. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:02:16,863][01716] Avg episode reward: [(0, '4.742')]
[2023-02-22 20:02:21,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3629.9). Total num frames: 1052672. Throughput: 0: 1004.7. Samples: 263304. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:02:21,859][01716] Avg episode reward: [(0, '4.589')]
[2023-02-22 20:02:24,790][12927] Updated weights for policy 0, policy_version 260 (0.0023)
[2023-02-22 20:02:26,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3623.9). Total num frames: 1069056. Throughput: 0: 997.0. Samples: 266558. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:02:26,863][01716] Avg episode reward: [(0, '4.588')]
[2023-02-22 20:02:31,858][01716] Fps is (10 sec: 3276.4, 60 sec: 3891.1, 300 sec: 3679.4). Total num frames: 1085440. Throughput: 0: 952.7. Samples: 271124. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:02:31,862][01716] Avg episode reward: [(0, '4.768')]
[2023-02-22 20:02:36,569][12927] Updated weights for policy 0, policy_version 270 (0.0027)
[2023-02-22 20:02:36,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3748.9). Total num frames: 1105920. Throughput: 0: 983.0. Samples: 277050. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:02:36,865][01716] Avg episode reward: [(0, '4.678')]
[2023-02-22 20:02:41,857][01716] Fps is (10 sec: 4506.2, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 1130496. Throughput: 0: 1007.8. Samples: 280616. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:02:41,864][01716] Avg episode reward: [(0, '4.758')]
[2023-02-22 20:02:46,042][12927] Updated weights for policy 0, policy_version 280 (0.0011)
[2023-02-22 20:02:46,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 1146880. Throughput: 0: 986.8. Samples: 286864. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:02:46,861][01716] Avg episode reward: [(0, '4.813')]
[2023-02-22 20:02:46,883][12913] Saving new best policy, reward=4.813!
[2023-02-22 20:02:51,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1163264. Throughput: 0: 949.2. Samples: 291290. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:02:51,867][01716] Avg episode reward: [(0, '5.042')]
[2023-02-22 20:02:51,870][12913] Saving new best policy, reward=5.042!
[2023-02-22 20:02:56,859][01716] Fps is (10 sec: 3685.4, 60 sec: 3891.1, 300 sec: 3818.3). Total num frames: 1183744. Throughput: 0: 958.3. Samples: 293998. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:02:56,863][01716] Avg episode reward: [(0, '5.062')]
[2023-02-22 20:02:56,878][12913] Saving new best policy, reward=5.062!
[2023-02-22 20:02:57,631][12927] Updated weights for policy 0, policy_version 290 (0.0017)
[2023-02-22 20:03:01,857][01716] Fps is (10 sec: 4096.1, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 1204224. Throughput: 0: 999.5. Samples: 301068. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:03:01,859][01716] Avg episode reward: [(0, '5.075')]
[2023-02-22 20:03:01,869][12913] Saving new best policy, reward=5.075!
[2023-02-22 20:03:06,857][01716] Fps is (10 sec: 4097.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 1224704. Throughput: 0: 964.4. Samples: 306700. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:03:06,864][01716] Avg episode reward: [(0, '5.278')]
[2023-02-22 20:03:06,879][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000299_1224704.pth...
[2023-02-22 20:03:07,102][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000074_303104.pth
[2023-02-22 20:03:07,121][12913] Saving new best policy, reward=5.278!
[2023-02-22 20:03:07,992][12927] Updated weights for policy 0, policy_version 300 (0.0022)
[2023-02-22 20:03:11,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3818.3). Total num frames: 1236992. Throughput: 0: 939.1. Samples: 308816. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:03:11,860][01716] Avg episode reward: [(0, '5.288')]
[2023-02-22 20:03:11,867][12913] Saving new best policy, reward=5.288!
[2023-02-22 20:03:16,857][01716] Fps is (10 sec: 3276.9, 60 sec: 3822.9, 300 sec: 3818.3). Total num frames: 1257472. Throughput: 0: 958.2. Samples: 314240. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:03:16,860][01716] Avg episode reward: [(0, '5.151')]
[2023-02-22 20:03:18,551][12927] Updated weights for policy 0, policy_version 310 (0.0016)
[2023-02-22 20:03:21,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 1282048. Throughput: 0: 984.5. Samples: 321354. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:03:21,859][01716] Avg episode reward: [(0, '5.144')]
[2023-02-22 20:03:26,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 1298432. Throughput: 0: 970.7. Samples: 324296. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:03:26,867][01716] Avg episode reward: [(0, '5.168')]
[2023-02-22 20:03:29,896][12927] Updated weights for policy 0, policy_version 320 (0.0020)
[2023-02-22 20:03:31,858][01716] Fps is (10 sec: 3276.3, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 1314816. Throughput: 0: 930.2. Samples: 328724. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:03:31,860][01716] Avg episode reward: [(0, '5.225')]
[2023-02-22 20:03:36,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 1335296. Throughput: 0: 966.4. Samples: 334780. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:03:36,865][01716] Avg episode reward: [(0, '5.570')]
[2023-02-22 20:03:36,874][12913] Saving new best policy, reward=5.570!
[2023-02-22 20:03:39,805][12927] Updated weights for policy 0, policy_version 330 (0.0015)
[2023-02-22 20:03:41,857][01716] Fps is (10 sec: 4506.2, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 1359872. Throughput: 0: 981.4. Samples: 338158. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:03:41,860][01716] Avg episode reward: [(0, '5.346')]
[2023-02-22 20:03:46,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3860.0). Total num frames: 1376256. Throughput: 0: 959.5. Samples: 344246. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:03:46,859][01716] Avg episode reward: [(0, '5.277')]
[2023-02-22 20:03:51,349][12927] Updated weights for policy 0, policy_version 340 (0.0032)
[2023-02-22 20:03:51,858][01716] Fps is (10 sec: 3276.6, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 1392640. Throughput: 0: 935.1. Samples: 348782. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:03:51,866][01716] Avg episode reward: [(0, '5.451')]
[2023-02-22 20:03:56,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3823.1, 300 sec: 3832.2). Total num frames: 1413120. Throughput: 0: 953.3. Samples: 351714. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:03:56,859][01716] Avg episode reward: [(0, '5.321')]
[2023-02-22 20:04:00,346][12927] Updated weights for policy 0, policy_version 350 (0.0035)
[2023-02-22 20:04:01,857][01716] Fps is (10 sec: 4506.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 1437696. Throughput: 0: 994.0. Samples: 358968. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:04:01,859][01716] Avg episode reward: [(0, '4.903')]
[2023-02-22 20:04:06,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3860.0). Total num frames: 1454080. Throughput: 0: 962.8. Samples: 364680. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:04:06,861][01716] Avg episode reward: [(0, '5.301')]
[2023-02-22 20:04:11,858][01716] Fps is (10 sec: 3276.7, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1470464. Throughput: 0: 948.2. Samples: 366966. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:04:11,867][01716] Avg episode reward: [(0, '5.430')]
[2023-02-22 20:04:12,554][12927] Updated weights for policy 0, policy_version 360 (0.0021)
[2023-02-22 20:04:16,857][01716] Fps is (10 sec: 4095.9, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 1495040. Throughput: 0: 978.2. Samples: 372740. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:04:16,860][01716] Avg episode reward: [(0, '5.536')]
[2023-02-22 20:04:21,862][01716] Fps is (10 sec: 3684.5, 60 sec: 3754.3, 300 sec: 3818.3). Total num frames: 1507328. Throughput: 0: 958.3. Samples: 377908. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:04:21,865][01716] Avg episode reward: [(0, '5.483')]
[2023-02-22 20:04:23,445][12927] Updated weights for policy 0, policy_version 370 (0.0030)
[2023-02-22 20:04:26,857][01716] Fps is (10 sec: 2457.7, 60 sec: 3686.4, 300 sec: 3818.3). Total num frames: 1519616. Throughput: 0: 929.2. Samples: 379974. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:04:26,863][01716] Avg episode reward: [(0, '5.464')]
[2023-02-22 20:04:31,857][01716] Fps is (10 sec: 2868.7, 60 sec: 3686.5, 300 sec: 3790.5). Total num frames: 1536000. Throughput: 0: 881.3. Samples: 383904. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:04:31,859][01716] Avg episode reward: [(0, '5.284')]
[2023-02-22 20:04:36,688][12927] Updated weights for policy 0, policy_version 380 (0.0018)
[2023-02-22 20:04:36,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3776.7). Total num frames: 1556480. Throughput: 0: 905.8. Samples: 389542. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:04:36,860][01716] Avg episode reward: [(0, '5.261')]
[2023-02-22 20:04:41,857][01716] Fps is (10 sec: 4505.7, 60 sec: 3686.4, 300 sec: 3804.4). Total num frames: 1581056. Throughput: 0: 918.8. Samples: 393060. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:04:41,859][01716] Avg episode reward: [(0, '5.057')]
[2023-02-22 20:04:45,517][12927] Updated weights for policy 0, policy_version 390 (0.0027)
[2023-02-22 20:04:46,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3818.3). Total num frames: 1597440. Throughput: 0: 907.7. Samples: 399814. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:04:46,864][01716] Avg episode reward: [(0, '5.405')]
[2023-02-22 20:04:51,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3686.5, 300 sec: 3790.5). Total num frames: 1613824. Throughput: 0: 878.4. Samples: 404206. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:04:51,862][01716] Avg episode reward: [(0, '5.819')]
[2023-02-22 20:04:51,867][12913] Saving new best policy, reward=5.819!
[2023-02-22 20:04:56,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3790.6). Total num frames: 1634304. Throughput: 0: 879.9. Samples: 406562. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:04:56,859][01716] Avg episode reward: [(0, '5.804')]
[2023-02-22 20:04:57,561][12927] Updated weights for policy 0, policy_version 400 (0.0016)
[2023-02-22 20:05:01,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3818.4). Total num frames: 1654784. Throughput: 0: 909.2. Samples: 413652. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:05:01,866][01716] Avg episode reward: [(0, '5.480')]
[2023-02-22 20:05:06,860][01716] Fps is (10 sec: 4094.5, 60 sec: 3686.2, 300 sec: 3859.9). Total num frames: 1675264. Throughput: 0: 930.7. Samples: 419790. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:05:06,863][01716] Avg episode reward: [(0, '5.590')]
[2023-02-22 20:05:06,873][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000409_1675264.pth...
[2023-02-22 20:05:07,011][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000185_757760.pth
[2023-02-22 20:05:07,299][12927] Updated weights for policy 0, policy_version 410 (0.0017)
[2023-02-22 20:05:11,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3846.1). Total num frames: 1691648. Throughput: 0: 932.8. Samples: 421952. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:05:11,862][01716] Avg episode reward: [(0, '5.758')]
[2023-02-22 20:05:16,857][01716] Fps is (10 sec: 3687.7, 60 sec: 3618.1, 300 sec: 3832.2). Total num frames: 1712128. Throughput: 0: 962.0. Samples: 427196. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:05:16,859][01716] Avg episode reward: [(0, '5.687')]
[2023-02-22 20:05:18,353][12927] Updated weights for policy 0, policy_version 420 (0.0036)
[2023-02-22 20:05:21,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3823.3, 300 sec: 3846.1). Total num frames: 1736704. Throughput: 0: 996.4. Samples: 434380. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:05:21,863][01716] Avg episode reward: [(0, '6.088')]
[2023-02-22 20:05:21,868][12913] Saving new best policy, reward=6.088!
[2023-02-22 20:05:26,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3860.0). Total num frames: 1753088. Throughput: 0: 987.8. Samples: 437510. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:05:26,861][01716] Avg episode reward: [(0, '6.170')]
[2023-02-22 20:05:26,875][12913] Saving new best policy, reward=6.170!
[2023-02-22 20:05:28,974][12927] Updated weights for policy 0, policy_version 430 (0.0038)
[2023-02-22 20:05:31,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 1769472. Throughput: 0: 935.8. Samples: 441926. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:05:31,861][01716] Avg episode reward: [(0, '6.218')]
[2023-02-22 20:05:31,865][12913] Saving new best policy, reward=6.218!
[2023-02-22 20:05:36,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1789952. Throughput: 0: 968.9. Samples: 447806. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:05:36,863][01716] Avg episode reward: [(0, '6.528')]
[2023-02-22 20:05:36,875][12913] Saving new best policy, reward=6.528!
[2023-02-22 20:05:39,165][12927] Updated weights for policy 0, policy_version 440 (0.0014)
[2023-02-22 20:05:41,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 1814528. Throughput: 0: 994.7. Samples: 451324. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:05:41,860][01716] Avg episode reward: [(0, '6.626')]
[2023-02-22 20:05:41,862][12913] Saving new best policy, reward=6.626!
[2023-02-22 20:05:46,861][01716] Fps is (10 sec: 4094.1, 60 sec: 3890.9, 300 sec: 3859.9). Total num frames: 1830912. Throughput: 0: 973.1. Samples: 457446. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:05:46,865][01716] Avg episode reward: [(0, '7.005')]
[2023-02-22 20:05:46,885][12913] Saving new best policy, reward=7.005!
[2023-02-22 20:05:50,776][12927] Updated weights for policy 0, policy_version 450 (0.0018)
[2023-02-22 20:05:51,858][01716] Fps is (10 sec: 2866.9, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 1843200. Throughput: 0: 935.1. Samples: 461868. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:05:51,864][01716] Avg episode reward: [(0, '6.837')]
[2023-02-22 20:05:56,857][01716] Fps is (10 sec: 3688.1, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1867776. Throughput: 0: 954.6. Samples: 464908. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:05:56,864][01716] Avg episode reward: [(0, '7.549')]
[2023-02-22 20:05:56,872][12913] Saving new best policy, reward=7.549!
[2023-02-22 20:06:00,042][12927] Updated weights for policy 0, policy_version 460 (0.0018)
[2023-02-22 20:06:01,857][01716] Fps is (10 sec: 4915.7, 60 sec: 3959.5, 300 sec: 3846.1). Total num frames: 1892352. Throughput: 0: 998.3. Samples: 472120. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:06:01,859][01716] Avg episode reward: [(0, '7.868')]
[2023-02-22 20:06:01,866][12913] Saving new best policy, reward=7.868!
[2023-02-22 20:06:06,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.4, 300 sec: 3860.0). Total num frames: 1908736. Throughput: 0: 961.3. Samples: 477638. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:06:06,859][01716] Avg episode reward: [(0, '8.629')]
[2023-02-22 20:06:06,871][12913] Saving new best policy, reward=8.629!
[2023-02-22 20:06:11,857][01716] Fps is (10 sec: 2867.1, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 1921024. Throughput: 0: 939.9. Samples: 479804. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:06:11,863][01716] Avg episode reward: [(0, '8.430')]
[2023-02-22 20:06:12,071][12927] Updated weights for policy 0, policy_version 470 (0.0015)
[2023-02-22 20:06:16,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 1945600. Throughput: 0: 975.8. Samples: 485836. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:06:16,862][01716] Avg episode reward: [(0, '8.901')]
[2023-02-22 20:06:16,874][12913] Saving new best policy, reward=8.901!
[2023-02-22 20:06:20,771][12927] Updated weights for policy 0, policy_version 480 (0.0014)
[2023-02-22 20:06:21,857][01716] Fps is (10 sec: 4915.3, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 1970176. Throughput: 0: 1002.2. Samples: 492906. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:06:21,859][01716] Avg episode reward: [(0, '8.161')]
[2023-02-22 20:06:26,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 1986560. Throughput: 0: 985.8. Samples: 495684. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:06:26,861][01716] Avg episode reward: [(0, '7.846')]
[2023-02-22 20:06:31,857][01716] Fps is (10 sec: 2867.2, 60 sec: 3822.9, 300 sec: 3818.3). Total num frames: 1998848. Throughput: 0: 949.8. Samples: 500184. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:06:31,863][01716] Avg episode reward: [(0, '7.436')]
[2023-02-22 20:06:32,985][12927] Updated weights for policy 0, policy_version 490 (0.0028)
[2023-02-22 20:06:36,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 2023424. Throughput: 0: 993.9. Samples: 506592. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:06:36,859][01716] Avg episode reward: [(0, '7.982')]
[2023-02-22 20:06:41,420][12927] Updated weights for policy 0, policy_version 500 (0.0023)
[2023-02-22 20:06:41,857][01716] Fps is (10 sec: 4915.2, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2048000. Throughput: 0: 1008.0. Samples: 510266. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:06:41,859][01716] Avg episode reward: [(0, '8.198')]
[2023-02-22 20:06:46,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.5, 300 sec: 3846.1). Total num frames: 2064384. Throughput: 0: 978.0. Samples: 516132. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:06:46,861][01716] Avg episode reward: [(0, '7.632')]
[2023-02-22 20:06:51,857][01716] Fps is (10 sec: 3276.7, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2080768. Throughput: 0: 958.3. Samples: 520760. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:06:51,860][01716] Avg episode reward: [(0, '7.729')]
[2023-02-22 20:06:53,427][12927] Updated weights for policy 0, policy_version 510 (0.0029)
[2023-02-22 20:06:56,857][01716] Fps is (10 sec: 4096.1, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2105344. Throughput: 0: 984.8. Samples: 524118. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:06:56,866][01716] Avg episode reward: [(0, '8.144')]
[2023-02-22 20:07:01,857][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2125824. Throughput: 0: 1010.8. Samples: 531320. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:07:01,859][01716] Avg episode reward: [(0, '9.519')]
[2023-02-22 20:07:01,889][12913] Saving new best policy, reward=9.519!
[2023-02-22 20:07:01,898][12927] Updated weights for policy 0, policy_version 520 (0.0011)
[2023-02-22 20:07:06,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2142208. Throughput: 0: 969.5. Samples: 536532. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:07:06,862][01716] Avg episode reward: [(0, '9.511')]
[2023-02-22 20:07:06,878][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000523_2142208.pth...
[2023-02-22 20:07:07,012][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000299_1224704.pth
[2023-02-22 20:07:11,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2158592. Throughput: 0: 956.5. Samples: 538726. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:07:11,863][01716] Avg episode reward: [(0, '9.215')]
[2023-02-22 20:07:14,101][12927] Updated weights for policy 0, policy_version 530 (0.0019)
[2023-02-22 20:07:16,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2183168. Throughput: 0: 997.0. Samples: 545050. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:07:16,858][01716] Avg episode reward: [(0, '9.989')]
[2023-02-22 20:07:16,873][12913] Saving new best policy, reward=9.989!
[2023-02-22 20:07:21,857][01716] Fps is (10 sec: 4915.2, 60 sec: 3959.5, 300 sec: 3860.0). Total num frames: 2207744. Throughput: 0: 1010.9. Samples: 552082. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:07:21,863][01716] Avg episode reward: [(0, '10.382')]
[2023-02-22 20:07:21,865][12913] Saving new best policy, reward=10.382!
[2023-02-22 20:07:23,172][12927] Updated weights for policy 0, policy_version 540 (0.0026)
[2023-02-22 20:07:26,858][01716] Fps is (10 sec: 3686.0, 60 sec: 3891.1, 300 sec: 3846.1). Total num frames: 2220032. Throughput: 0: 981.5. Samples: 554436. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:07:26,866][01716] Avg episode reward: [(0, '11.182')]
[2023-02-22 20:07:26,878][12913] Saving new best policy, reward=11.182!
[2023-02-22 20:07:31,857][01716] Fps is (10 sec: 2867.2, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2236416. Throughput: 0: 950.0. Samples: 558880. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:07:31,860][01716] Avg episode reward: [(0, '11.597')]
[2023-02-22 20:07:31,864][12913] Saving new best policy, reward=11.597!
[2023-02-22 20:07:34,847][12927] Updated weights for policy 0, policy_version 550 (0.0042)
[2023-02-22 20:07:36,857][01716] Fps is (10 sec: 4096.4, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2260992. Throughput: 0: 997.3. Samples: 565636. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:07:36,864][01716] Avg episode reward: [(0, '12.141')]
[2023-02-22 20:07:36,876][12913] Saving new best policy, reward=12.141!
[2023-02-22 20:07:41,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2281472. Throughput: 0: 997.0. Samples: 568982. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:07:41,865][01716] Avg episode reward: [(0, '11.898')]
[2023-02-22 20:07:45,096][12927] Updated weights for policy 0, policy_version 560 (0.0017)
[2023-02-22 20:07:46,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2297856. Throughput: 0: 955.4. Samples: 574314. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:07:46,861][01716] Avg episode reward: [(0, '11.506')]
[2023-02-22 20:07:51,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 2314240. Throughput: 0: 941.1. Samples: 578882. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:07:51,865][01716] Avg episode reward: [(0, '10.992')]
[2023-02-22 20:07:56,027][12927] Updated weights for policy 0, policy_version 570 (0.0018)
[2023-02-22 20:07:56,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2338816. Throughput: 0: 971.1. Samples: 582426. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:07:56,859][01716] Avg episode reward: [(0, '10.319')]
[2023-02-22 20:08:01,857][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2359296. Throughput: 0: 989.6. Samples: 589582. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:08:01,868][01716] Avg episode reward: [(0, '11.403')]
[2023-02-22 20:08:06,644][12927] Updated weights for policy 0, policy_version 580 (0.0027)
[2023-02-22 20:08:06,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3860.0). Total num frames: 2375680. Throughput: 0: 940.4. Samples: 594402. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:08:06,861][01716] Avg episode reward: [(0, '11.734')]
[2023-02-22 20:08:11,857][01716] Fps is (10 sec: 3276.7, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2392064. Throughput: 0: 937.1. Samples: 596606. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:08:11,867][01716] Avg episode reward: [(0, '13.304')]
[2023-02-22 20:08:11,869][12913] Saving new best policy, reward=13.304!
[2023-02-22 20:08:16,770][12927] Updated weights for policy 0, policy_version 590 (0.0025)
[2023-02-22 20:08:16,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2416640. Throughput: 0: 984.3. Samples: 603174. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:08:16,859][01716] Avg episode reward: [(0, '14.807')]
[2023-02-22 20:08:16,871][12913] Saving new best policy, reward=14.807!
[2023-02-22 20:08:21,857][01716] Fps is (10 sec: 4096.1, 60 sec: 3754.7, 300 sec: 3846.1). Total num frames: 2433024. Throughput: 0: 972.9. Samples: 609418. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:08:21,861][01716] Avg episode reward: [(0, '15.720')]
[2023-02-22 20:08:21,867][12913] Saving new best policy, reward=15.720!
[2023-02-22 20:08:26,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3823.0, 300 sec: 3846.1). Total num frames: 2449408. Throughput: 0: 945.6. Samples: 611536. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:08:26,862][01716] Avg episode reward: [(0, '15.600')]
[2023-02-22 20:08:28,876][12927] Updated weights for policy 0, policy_version 600 (0.0011)
[2023-02-22 20:08:31,857][01716] Fps is (10 sec: 2867.2, 60 sec: 3754.7, 300 sec: 3818.3). Total num frames: 2461696. Throughput: 0: 926.4. Samples: 616004. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:08:31,864][01716] Avg episode reward: [(0, '15.524')]
[2023-02-22 20:08:36,857][01716] Fps is (10 sec: 2867.2, 60 sec: 3618.1, 300 sec: 3790.5). Total num frames: 2478080. Throughput: 0: 923.0. Samples: 620416. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:08:36,860][01716] Avg episode reward: [(0, '14.881')]
[2023-02-22 20:08:41,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3790.5). Total num frames: 2494464. Throughput: 0: 894.0. Samples: 622654. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:08:41,862][01716] Avg episode reward: [(0, '14.256')]
[2023-02-22 20:08:41,974][12927] Updated weights for policy 0, policy_version 610 (0.0029)
[2023-02-22 20:08:46,858][01716] Fps is (10 sec: 3276.4, 60 sec: 3549.8, 300 sec: 3790.5). Total num frames: 2510848. Throughput: 0: 847.2. Samples: 627706. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:08:46,863][01716] Avg episode reward: [(0, '14.240')]
[2023-02-22 20:08:51,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3776.7). Total num frames: 2527232. Throughput: 0: 845.4. Samples: 632446. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:08:51,860][01716] Avg episode reward: [(0, '14.835')]
[2023-02-22 20:08:54,085][12927] Updated weights for policy 0, policy_version 620 (0.0031)
[2023-02-22 20:08:56,857][01716] Fps is (10 sec: 4096.5, 60 sec: 3549.9, 300 sec: 3776.6). Total num frames: 2551808. Throughput: 0: 875.6. Samples: 636010. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 20:08:56,859][01716] Avg episode reward: [(0, '15.516')]
[2023-02-22 20:09:01,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3549.9, 300 sec: 3790.5). Total num frames: 2572288. Throughput: 0: 889.8. Samples: 643214. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:09:01,863][01716] Avg episode reward: [(0, '16.221')]
[2023-02-22 20:09:01,869][12913] Saving new best policy, reward=16.221!
[2023-02-22 20:09:03,605][12927] Updated weights for policy 0, policy_version 630 (0.0022)
[2023-02-22 20:09:06,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3790.5). Total num frames: 2588672. Throughput: 0: 853.9. Samples: 647844. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:06,864][01716] Avg episode reward: [(0, '16.688')]
[2023-02-22 20:09:06,877][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000632_2588672.pth...
[2023-02-22 20:09:07,020][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000409_1675264.pth
[2023-02-22 20:09:07,065][12913] Saving new best policy, reward=16.688!
[2023-02-22 20:09:11,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3762.8). Total num frames: 2605056. Throughput: 0: 854.8. Samples: 650000. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:11,858][01716] Avg episode reward: [(0, '16.753')]
[2023-02-22 20:09:11,864][12913] Saving new best policy, reward=16.753!
[2023-02-22 20:09:14,775][12927] Updated weights for policy 0, policy_version 640 (0.0025)
[2023-02-22 20:09:16,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3804.5). Total num frames: 2629632. Throughput: 0: 905.1. Samples: 656734. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:09:16,866][01716] Avg episode reward: [(0, '17.336')]
[2023-02-22 20:09:16,877][12913] Saving new best policy, reward=17.336!
[2023-02-22 20:09:21,857][01716] Fps is (10 sec: 4505.5, 60 sec: 3618.1, 300 sec: 3832.2). Total num frames: 2650112. Throughput: 0: 956.8. Samples: 663474. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:21,865][01716] Avg episode reward: [(0, '16.831')]
[2023-02-22 20:09:24,970][12927] Updated weights for policy 0, policy_version 650 (0.0019)
[2023-02-22 20:09:26,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3832.2). Total num frames: 2666496. Throughput: 0: 958.2. Samples: 665772. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:26,866][01716] Avg episode reward: [(0, '16.557')]
[2023-02-22 20:09:31,857][01716] Fps is (10 sec: 3276.9, 60 sec: 3686.4, 300 sec: 3818.3). Total num frames: 2682880. Throughput: 0: 950.9. Samples: 670494. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:31,859][01716] Avg episode reward: [(0, '16.353')]
[2023-02-22 20:09:35,321][12927] Updated weights for policy 0, policy_version 660 (0.0012)
[2023-02-22 20:09:36,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3818.3). Total num frames: 2707456. Throughput: 0: 1004.9. Samples: 677668. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:36,860][01716] Avg episode reward: [(0, '16.769')]
[2023-02-22 20:09:41,857][01716] Fps is (10 sec: 4505.2, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 2727936. Throughput: 0: 1005.3. Samples: 681248. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:41,865][01716] Avg episode reward: [(0, '17.437')]
[2023-02-22 20:09:41,870][12913] Saving new best policy, reward=17.437!
[2023-02-22 20:09:46,415][12927] Updated weights for policy 0, policy_version 670 (0.0039)
[2023-02-22 20:09:46,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.3, 300 sec: 3832.2). Total num frames: 2744320. Throughput: 0: 948.5. Samples: 685896. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:09:46,862][01716] Avg episode reward: [(0, '18.076')]
[2023-02-22 20:09:46,874][12913] Saving new best policy, reward=18.076!
[2023-02-22 20:09:51,857][01716] Fps is (10 sec: 3277.0, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 2760704. Throughput: 0: 962.6. Samples: 691162. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:09:51,862][01716] Avg episode reward: [(0, '18.744')]
[2023-02-22 20:09:51,925][12913] Saving new best policy, reward=18.744!
[2023-02-22 20:09:56,383][12927] Updated weights for policy 0, policy_version 680 (0.0033)
[2023-02-22 20:09:56,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 2785280. Throughput: 0: 991.9. Samples: 694636. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:09:56,859][01716] Avg episode reward: [(0, '18.962')]
[2023-02-22 20:09:56,871][12913] Saving new best policy, reward=18.962!
[2023-02-22 20:10:01,858][01716] Fps is (10 sec: 4504.9, 60 sec: 3891.1, 300 sec: 3832.2). Total num frames: 2805760. Throughput: 0: 992.6. Samples: 701402. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:10:01,861][01716] Avg episode reward: [(0, '18.161')]
[2023-02-22 20:10:06,859][01716] Fps is (10 sec: 3685.5, 60 sec: 3891.0, 300 sec: 3832.2). Total num frames: 2822144. Throughput: 0: 943.1. Samples: 705914. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:10:06,864][01716] Avg episode reward: [(0, '18.035')]
[2023-02-22 20:10:08,222][12927] Updated weights for policy 0, policy_version 690 (0.0027)
[2023-02-22 20:10:11,861][01716] Fps is (10 sec: 3275.8, 60 sec: 3890.9, 300 sec: 3818.2). Total num frames: 2838528. Throughput: 0: 941.7. Samples: 708154. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:10:11,868][01716] Avg episode reward: [(0, '17.014')]
[2023-02-22 20:10:16,857][01716] Fps is (10 sec: 4097.0, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 2863104. Throughput: 0: 995.9. Samples: 715310. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:10:16,865][01716] Avg episode reward: [(0, '16.914')]
[2023-02-22 20:10:17,098][12927] Updated weights for policy 0, policy_version 700 (0.0021)
[2023-02-22 20:10:21,857][01716] Fps is (10 sec: 4507.4, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 2883584. Throughput: 0: 977.7. Samples: 721666. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:10:21,865][01716] Avg episode reward: [(0, '16.700')]
[2023-02-22 20:10:26,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 2899968. Throughput: 0: 949.2. Samples: 723960. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:10:26,860][01716] Avg episode reward: [(0, '15.498')]
[2023-02-22 20:10:29,310][12927] Updated weights for policy 0, policy_version 710 (0.0057)
[2023-02-22 20:10:31,857][01716] Fps is (10 sec: 3686.5, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2920448. Throughput: 0: 957.9. Samples: 729002. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:10:31,859][01716] Avg episode reward: [(0, '16.470')]
[2023-02-22 20:10:36,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2945024. Throughput: 0: 1002.2. Samples: 736260. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:10:36,863][01716] Avg episode reward: [(0, '16.476')]
[2023-02-22 20:10:37,685][12927] Updated weights for policy 0, policy_version 720 (0.0012)
[2023-02-22 20:10:41,857][01716] Fps is (10 sec: 4096.1, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 2961408. Throughput: 0: 1004.1. Samples: 739820. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:10:41,859][01716] Avg episode reward: [(0, '17.254')]
[2023-02-22 20:10:46,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 2977792. Throughput: 0: 955.5. Samples: 744396. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:10:46,869][01716] Avg episode reward: [(0, '17.732')]
[2023-02-22 20:10:49,723][12927] Updated weights for policy 0, policy_version 730 (0.0021)
[2023-02-22 20:10:51,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 2998272. Throughput: 0: 983.3. Samples: 750158. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:10:51,859][01716] Avg episode reward: [(0, '17.798')]
[2023-02-22 20:10:56,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 3022848. Throughput: 0: 1015.4. Samples: 753844. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:10:56,859][01716] Avg episode reward: [(0, '18.659')]
[2023-02-22 20:10:58,130][12927] Updated weights for policy 0, policy_version 740 (0.0013)
[2023-02-22 20:11:01,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.6, 300 sec: 3846.1). Total num frames: 3043328. Throughput: 0: 1002.6. Samples: 760428. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:11:01,859][01716] Avg episode reward: [(0, '19.253')]
[2023-02-22 20:11:01,865][12913] Saving new best policy, reward=19.253!
[2023-02-22 20:11:06,857][01716] Fps is (10 sec: 3276.7, 60 sec: 3891.3, 300 sec: 3846.1). Total num frames: 3055616. Throughput: 0: 961.5. Samples: 764932. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:11:06,864][01716] Avg episode reward: [(0, '19.389')]
[2023-02-22 20:11:06,916][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000747_3059712.pth...
[2023-02-22 20:11:07,079][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000523_2142208.pth
[2023-02-22 20:11:07,095][12913] Saving new best policy, reward=19.389!
[2023-02-22 20:11:10,178][12927] Updated weights for policy 0, policy_version 750 (0.0017)
[2023-02-22 20:11:11,857][01716] Fps is (10 sec: 3686.2, 60 sec: 4028.0, 300 sec: 3846.1). Total num frames: 3080192. Throughput: 0: 966.8. Samples: 767466. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:11:11,860][01716] Avg episode reward: [(0, '20.659')]
[2023-02-22 20:11:11,866][12913] Saving new best policy, reward=20.659!
[2023-02-22 20:11:16,857][01716] Fps is (10 sec: 4505.7, 60 sec: 3959.5, 300 sec: 3832.2). Total num frames: 3100672. Throughput: 0: 1015.7. Samples: 774708. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:11:16,864][01716] Avg episode reward: [(0, '21.728')]
[2023-02-22 20:11:16,876][12913] Saving new best policy, reward=21.728!
[2023-02-22 20:11:18,971][12927] Updated weights for policy 0, policy_version 760 (0.0022)
[2023-02-22 20:11:21,857][01716] Fps is (10 sec: 4096.2, 60 sec: 3959.5, 300 sec: 3846.1). Total num frames: 3121152. Throughput: 0: 987.4. Samples: 780692. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:11:21,866][01716] Avg episode reward: [(0, '20.377')]
[2023-02-22 20:11:26,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3846.1). Total num frames: 3133440. Throughput: 0: 954.4. Samples: 782766. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:11:26,861][01716] Avg episode reward: [(0, '20.165')]
[2023-02-22 20:11:31,024][12927] Updated weights for policy 0, policy_version 770 (0.0020)
[2023-02-22 20:11:31,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3153920. Throughput: 0: 972.8. Samples: 788174. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:11:31,859][01716] Avg episode reward: [(0, '19.948')]
[2023-02-22 20:11:36,857][01716] Fps is (10 sec: 4505.5, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3178496. Throughput: 0: 1006.4. Samples: 795448. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:11:36,860][01716] Avg episode reward: [(0, '19.996')]
[2023-02-22 20:11:40,458][12927] Updated weights for policy 0, policy_version 780 (0.0013)
[2023-02-22 20:11:41,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3194880. Throughput: 0: 994.3. Samples: 798586. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:11:41,862][01716] Avg episode reward: [(0, '20.948')]
[2023-02-22 20:11:46,857][01716] Fps is (10 sec: 3276.7, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3211264. Throughput: 0: 944.7. Samples: 802940. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:11:46,865][01716] Avg episode reward: [(0, '21.494')]
[2023-02-22 20:11:51,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 3231744. Throughput: 0: 976.0. Samples: 808852. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:11:51,859][01716] Avg episode reward: [(0, '21.399')]
[2023-02-22 20:11:51,986][12927] Updated weights for policy 0, policy_version 790 (0.0018)
[2023-02-22 20:11:56,857][01716] Fps is (10 sec: 4505.9, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3256320. Throughput: 0: 999.1. Samples: 812424. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:11:56,864][01716] Avg episode reward: [(0, '19.957')]
[2023-02-22 20:12:01,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 3272704. Throughput: 0: 978.2. Samples: 818728. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:12:01,864][01716] Avg episode reward: [(0, '20.374')]
[2023-02-22 20:12:01,893][12927] Updated weights for policy 0, policy_version 800 (0.0016)
[2023-02-22 20:12:06,858][01716] Fps is (10 sec: 3276.4, 60 sec: 3891.1, 300 sec: 3832.2). Total num frames: 3289088. Throughput: 0: 941.1. Samples: 823042. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:12:06,862][01716] Avg episode reward: [(0, '19.927')]
[2023-02-22 20:12:11,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3823.0, 300 sec: 3818.3). Total num frames: 3309568. Throughput: 0: 955.3. Samples: 825754. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:12:11,863][01716] Avg episode reward: [(0, '20.023')]
[2023-02-22 20:12:13,163][12927] Updated weights for policy 0, policy_version 810 (0.0023)
[2023-02-22 20:12:16,857][01716] Fps is (10 sec: 4506.1, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 3334144. Throughput: 0: 993.1. Samples: 832864. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:12:16,865][01716] Avg episode reward: [(0, '20.168')]
[2023-02-22 20:12:21,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3832.2). Total num frames: 3350528. Throughput: 0: 957.3. Samples: 838526. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:12:21,867][01716] Avg episode reward: [(0, '20.196')]
[2023-02-22 20:12:24,001][12927] Updated weights for policy 0, policy_version 820 (0.0018)
[2023-02-22 20:12:26,857][01716] Fps is (10 sec: 3276.7, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3366912. Throughput: 0: 936.0. Samples: 840704. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 20:12:26,863][01716] Avg episode reward: [(0, '19.176')]
[2023-02-22 20:12:31,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3818.3). Total num frames: 3387392. Throughput: 0: 971.1. Samples: 846640. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:12:31,866][01716] Avg episode reward: [(0, '19.074')]
[2023-02-22 20:12:33,646][12927] Updated weights for policy 0, policy_version 830 (0.0030)
[2023-02-22 20:12:36,857][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3411968. Throughput: 0: 1001.6. Samples: 853922. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:12:36,865][01716] Avg episode reward: [(0, '19.068')]
[2023-02-22 20:12:41,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3832.2). Total num frames: 3428352. Throughput: 0: 985.0. Samples: 856750. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:12:41,859][01716] Avg episode reward: [(0, '19.297')]
[2023-02-22 20:12:45,557][12927] Updated weights for policy 0, policy_version 840 (0.0042)
[2023-02-22 20:12:46,857][01716] Fps is (10 sec: 2867.2, 60 sec: 3823.0, 300 sec: 3818.3). Total num frames: 3440640. Throughput: 0: 930.2. Samples: 860586. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:12:46,860][01716] Avg episode reward: [(0, '18.783')]
[2023-02-22 20:12:51,857][01716] Fps is (10 sec: 2457.6, 60 sec: 3686.4, 300 sec: 3776.7). Total num frames: 3452928. Throughput: 0: 917.6. Samples: 864332. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:12:51,865][01716] Avg episode reward: [(0, '19.141')]
[2023-02-22 20:12:56,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3790.5). Total num frames: 3477504. Throughput: 0: 917.3. Samples: 867032. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:12:56,864][01716] Avg episode reward: [(0, '19.310')]
[2023-02-22 20:12:57,738][12927] Updated weights for policy 0, policy_version 850 (0.0016)
[2023-02-22 20:13:01,863][01716] Fps is (10 sec: 4502.7, 60 sec: 3754.3, 300 sec: 3804.3). Total num frames: 3497984. Throughput: 0: 917.7. Samples: 874168. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:13:01,870][01716] Avg episode reward: [(0, '19.233')]
[2023-02-22 20:13:06,857][01716] Fps is (10 sec: 3686.2, 60 sec: 3754.7, 300 sec: 3804.4). Total num frames: 3514368. Throughput: 0: 897.8. Samples: 878926. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:13:06,861][01716] Avg episode reward: [(0, '18.773')]
[2023-02-22 20:13:06,879][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000858_3514368.pth...
[2023-02-22 20:13:07,054][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000632_2588672.pth
[2023-02-22 20:13:09,421][12927] Updated weights for policy 0, policy_version 860 (0.0020)
[2023-02-22 20:13:11,857][01716] Fps is (10 sec: 3278.9, 60 sec: 3686.4, 300 sec: 3776.7). Total num frames: 3530752. Throughput: 0: 899.0. Samples: 881158. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:13:11,859][01716] Avg episode reward: [(0, '19.333')]
[2023-02-22 20:13:16,857][01716] Fps is (10 sec: 4096.2, 60 sec: 3686.4, 300 sec: 3804.4). Total num frames: 3555328. Throughput: 0: 916.9. Samples: 887900. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:13:16,859][01716] Avg episode reward: [(0, '17.825')]
[2023-02-22 20:13:18,477][12927] Updated weights for policy 0, policy_version 870 (0.0012)
[2023-02-22 20:13:21,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3754.7, 300 sec: 3818.3). Total num frames: 3575808. Throughput: 0: 910.8. Samples: 894906. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:13:21,861][01716] Avg episode reward: [(0, '18.711')]
[2023-02-22 20:13:26,861][01716] Fps is (10 sec: 3684.7, 60 sec: 3754.4, 300 sec: 3832.1). Total num frames: 3592192. Throughput: 0: 898.5. Samples: 897186. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:13:26,867][01716] Avg episode reward: [(0, '19.718')]
[2023-02-22 20:13:30,319][12927] Updated weights for policy 0, policy_version 880 (0.0027)
[2023-02-22 20:13:31,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3832.2). Total num frames: 3608576. Throughput: 0: 916.8. Samples: 901842. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:13:31,859][01716] Avg episode reward: [(0, '19.592')]
[2023-02-22 20:13:36,857][01716] Fps is (10 sec: 4097.9, 60 sec: 3686.4, 300 sec: 3860.0). Total num frames: 3633152. Throughput: 0: 996.6. Samples: 909178. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:13:36,868][01716] Avg episode reward: [(0, '20.419')]
[2023-02-22 20:13:38,719][12927] Updated weights for policy 0, policy_version 890 (0.0020)
[2023-02-22 20:13:41,857][01716] Fps is (10 sec: 4915.2, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 3657728. Throughput: 0: 1018.5. Samples: 912864. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:13:41,861][01716] Avg episode reward: [(0, '20.015')]
[2023-02-22 20:13:46,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 3670016. Throughput: 0: 974.2. Samples: 918000. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:13:46,859][01716] Avg episode reward: [(0, '19.929')]
[2023-02-22 20:13:50,578][12927] Updated weights for policy 0, policy_version 900 (0.0014)
[2023-02-22 20:13:51,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3860.0). Total num frames: 3690496. Throughput: 0: 984.2. Samples: 923216. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:13:51,863][01716] Avg episode reward: [(0, '20.091')]
[2023-02-22 20:13:56,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3873.8). Total num frames: 3715072. Throughput: 0: 1015.8. Samples: 926870. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:13:56,862][01716] Avg episode reward: [(0, '20.254')]
[2023-02-22 20:13:59,092][12927] Updated weights for policy 0, policy_version 910 (0.0019)
[2023-02-22 20:14:01,859][01716] Fps is (10 sec: 4504.4, 60 sec: 3959.7, 300 sec: 3887.7). Total num frames: 3735552. Throughput: 0: 1022.9. Samples: 933932. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:14:01,863][01716] Avg episode reward: [(0, '20.251')]
[2023-02-22 20:14:06,859][01716] Fps is (10 sec: 3685.7, 60 sec: 3959.4, 300 sec: 3887.7). Total num frames: 3751936. Throughput: 0: 964.2. Samples: 938298. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:14:06,861][01716] Avg episode reward: [(0, '20.457')]
[2023-02-22 20:14:11,414][12927] Updated weights for policy 0, policy_version 920 (0.0027)
[2023-02-22 20:14:11,857][01716] Fps is (10 sec: 3277.7, 60 sec: 3959.5, 300 sec: 3860.0). Total num frames: 3768320. Throughput: 0: 961.7. Samples: 940456. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:14:11,859][01716] Avg episode reward: [(0, '20.969')]
[2023-02-22 20:14:16,857][01716] Fps is (10 sec: 4096.8, 60 sec: 3959.5, 300 sec: 3873.8). Total num frames: 3792896. Throughput: 0: 1014.0. Samples: 947474. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:14:16,863][01716] Avg episode reward: [(0, '20.675')]
[2023-02-22 20:14:20,415][12927] Updated weights for policy 0, policy_version 930 (0.0018)
[2023-02-22 20:14:21,863][01716] Fps is (10 sec: 4093.3, 60 sec: 3890.8, 300 sec: 3873.8). Total num frames: 3809280. Throughput: 0: 988.7. Samples: 953674. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:14:21,866][01716] Avg episode reward: [(0, '20.193')]
[2023-02-22 20:14:26,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.5, 300 sec: 3873.8). Total num frames: 3825664. Throughput: 0: 955.2. Samples: 955848. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:14:26,860][01716] Avg episode reward: [(0, '21.470')]
[2023-02-22 20:14:31,857][01716] Fps is (10 sec: 3688.8, 60 sec: 3959.5, 300 sec: 3860.0). Total num frames: 3846144. Throughput: 0: 947.3. Samples: 960628. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:14:31,864][01716] Avg episode reward: [(0, '21.168')]
[2023-02-22 20:14:32,662][12927] Updated weights for policy 0, policy_version 940 (0.0036)
[2023-02-22 20:14:36,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3860.0). Total num frames: 3866624. Throughput: 0: 980.8. Samples: 967352. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:14:36,862][01716] Avg episode reward: [(0, '20.642')]
[2023-02-22 20:14:41,858][01716] Fps is (10 sec: 4095.3, 60 sec: 3822.8, 300 sec: 3873.8). Total num frames: 3887104. Throughput: 0: 975.7. Samples: 970776. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:14:41,860][01716] Avg episode reward: [(0, '20.629')]
[2023-02-22 20:14:43,124][12927] Updated weights for policy 0, policy_version 950 (0.0017)
[2023-02-22 20:14:46,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3860.0). Total num frames: 3899392. Throughput: 0: 915.7. Samples: 975134. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:14:46,868][01716] Avg episode reward: [(0, '21.409')]
[2023-02-22 20:14:51,857][01716] Fps is (10 sec: 3277.3, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 3919872. Throughput: 0: 940.1. Samples: 980600. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:14:51,864][01716] Avg episode reward: [(0, '20.421')]
[2023-02-22 20:14:53,975][12927] Updated weights for policy 0, policy_version 960 (0.0015)
[2023-02-22 20:14:56,857][01716] Fps is (10 sec: 4505.6, 60 sec: 3822.9, 300 sec: 3860.0). Total num frames: 3944448. Throughput: 0: 969.5. Samples: 984082. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:14:56,859][01716] Avg episode reward: [(0, '20.327')]
[2023-02-22 20:15:01,857][01716] Fps is (10 sec: 4096.0, 60 sec: 3754.8, 300 sec: 3860.0). Total num frames: 3960832. Throughput: 0: 959.2. Samples: 990636. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:15:01,860][01716] Avg episode reward: [(0, '20.431')]
[2023-02-22 20:15:04,671][12927] Updated weights for policy 0, policy_version 970 (0.0015)
[2023-02-22 20:15:06,857][01716] Fps is (10 sec: 3276.8, 60 sec: 3754.8, 300 sec: 3860.0). Total num frames: 3977216. Throughput: 0: 919.7. Samples: 995054. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:15:06,863][01716] Avg episode reward: [(0, '21.731')]
[2023-02-22 20:15:06,873][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000971_3977216.pth...
[2023-02-22 20:15:07,006][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000747_3059712.pth
[2023-02-22 20:15:07,021][12913] Saving new best policy, reward=21.731!
[2023-02-22 20:15:11,857][01716] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3846.1). Total num frames: 3997696. Throughput: 0: 924.8. Samples: 997462. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:15:11,864][01716] Avg episode reward: [(0, '21.715')]
[2023-02-22 20:15:13,321][12913] Stopping Batcher_0...
[2023-02-22 20:15:13,321][12913] Loop batcher_evt_loop terminating...
[2023-02-22 20:15:13,322][01716] Component Batcher_0 stopped!
[2023-02-22 20:15:13,326][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2023-02-22 20:15:13,370][12927] Weights refcount: 2 0
[2023-02-22 20:15:13,378][12927] Stopping InferenceWorker_p0-w0...
[2023-02-22 20:15:13,379][01716] Component InferenceWorker_p0-w0 stopped!
[2023-02-22 20:15:13,385][12927] Loop inference_proc0-0_evt_loop terminating...
[2023-02-22 20:15:13,392][12934] Stopping RolloutWorker_w6...
[2023-02-22 20:15:13,392][01716] Component RolloutWorker_w6 stopped!
[2023-02-22 20:15:13,401][12932] Stopping RolloutWorker_w4...
[2023-02-22 20:15:13,401][01716] Component RolloutWorker_w7 stopped!
[2023-02-22 20:15:13,405][01716] Component RolloutWorker_w4 stopped!
[2023-02-22 20:15:13,393][12934] Loop rollout_proc6_evt_loop terminating...
[2023-02-22 20:15:13,413][12933] Stopping RolloutWorker_w5...
[2023-02-22 20:15:13,414][12933] Loop rollout_proc5_evt_loop terminating...
[2023-02-22 20:15:13,402][12932] Loop rollout_proc4_evt_loop terminating...
[2023-02-22 20:15:13,412][01716] Component RolloutWorker_w5 stopped!
[2023-02-22 20:15:13,427][01716] Component RolloutWorker_w0 stopped!
[2023-02-22 20:15:13,418][12935] Stopping RolloutWorker_w7...
[2023-02-22 20:15:13,433][12935] Loop rollout_proc7_evt_loop terminating...
[2023-02-22 20:15:13,427][12928] Stopping RolloutWorker_w0...
[2023-02-22 20:15:13,436][12928] Loop rollout_proc0_evt_loop terminating...
[2023-02-22 20:15:13,439][01716] Component RolloutWorker_w3 stopped!
[2023-02-22 20:15:13,442][12931] Stopping RolloutWorker_w3...
[2023-02-22 20:15:13,443][12931] Loop rollout_proc3_evt_loop terminating...
[2023-02-22 20:15:13,450][12930] Stopping RolloutWorker_w2...
[2023-02-22 20:15:13,450][01716] Component RolloutWorker_w2 stopped!
[2023-02-22 20:15:13,451][12930] Loop rollout_proc2_evt_loop terminating...
[2023-02-22 20:15:13,460][01716] Component RolloutWorker_w1 stopped!
[2023-02-22 20:15:13,464][12929] Stopping RolloutWorker_w1...
[2023-02-22 20:15:13,464][12929] Loop rollout_proc1_evt_loop terminating...
[2023-02-22 20:15:13,508][12913] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000858_3514368.pth
[2023-02-22 20:15:13,535][12913] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2023-02-22 20:15:13,784][01716] Component LearnerWorker_p0 stopped!
[2023-02-22 20:15:13,787][01716] Waiting for process learner_proc0 to stop...
[2023-02-22 20:15:13,793][12913] Stopping LearnerWorker_p0...
[2023-02-22 20:15:13,796][12913] Loop learner_proc0_evt_loop terminating...
[2023-02-22 20:15:15,566][01716] Waiting for process inference_proc0-0 to join...
[2023-02-22 20:15:15,921][01716] Waiting for process rollout_proc0 to join...
[2023-02-22 20:15:15,923][01716] Waiting for process rollout_proc1 to join...
[2023-02-22 20:15:16,284][01716] Waiting for process rollout_proc2 to join...
[2023-02-22 20:15:16,287][01716] Waiting for process rollout_proc3 to join...
[2023-02-22 20:15:16,288][01716] Waiting for process rollout_proc4 to join...
[2023-02-22 20:15:16,289][01716] Waiting for process rollout_proc5 to join...
[2023-02-22 20:15:16,294][01716] Waiting for process rollout_proc6 to join...
[2023-02-22 20:15:16,297][01716] Waiting for process rollout_proc7 to join...
[2023-02-22 20:15:16,299][01716] Batcher 0 profile tree view:
batching: 25.4083, releasing_batches: 0.0234
[2023-02-22 20:15:16,300][01716] InferenceWorker_p0-w0 profile tree view:
wait_policy: 0.0023
  wait_policy_total: 518.0777
update_model: 7.4290
  weight_update: 0.0040
one_step: 0.0088
  handle_policy_step: 493.7652
    deserialize: 14.5493, stack: 2.7287, obs_to_device_normalize: 111.6272, forward: 234.4924, send_messages: 25.8665
    prepare_outputs: 79.9748
      to_cpu: 50.5944
[2023-02-22 20:15:16,301][01716] Learner 0 profile tree view:
misc: 0.0059, prepare_batch: 16.5361
train: 74.9717
  epoch_init: 0.0054, minibatch_init: 0.0063, losses_postprocess: 0.6532, kl_divergence: 0.5577, after_optimizer: 32.8695
  calculate_losses: 26.6181
    losses_init: 0.0033, forward_head: 1.8122, bptt_initial: 17.6187, tail: 1.0513, advantages_returns: 0.2655, losses: 3.4581
    bptt: 2.0981
      bptt_forward_core: 2.0337
  update: 13.6653
    clip: 1.3475
[2023-02-22 20:15:16,302][01716] RolloutWorker_w0 profile tree view:
wait_for_trajectories: 0.3625, enqueue_policy_requests: 135.9894, env_step: 801.8848, overhead: 19.2748, complete_rollouts: 6.8519
save_policy_outputs: 18.9574
  split_output_tensors: 9.1797
[2023-02-22 20:15:16,304][01716] RolloutWorker_w7 profile tree view:
wait_for_trajectories: 0.3424, enqueue_policy_requests: 139.1966, env_step: 797.9545, overhead: 19.7604, complete_rollouts: 6.7238
save_policy_outputs: 18.8366
  split_output_tensors: 9.2421
[2023-02-22 20:15:16,305][01716] Loop Runner_EvtLoop terminating...
[2023-02-22 20:15:16,307][01716] Runner profile tree view:
main_loop: 1084.7474
[2023-02-22 20:15:16,308][01716] Collected {0: 4005888}, FPS: 3692.9
[2023-02-22 20:15:40,996][01716] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2023-02-22 20:15:41,004][01716] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-22 20:15:41,006][01716] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-22 20:15:41,008][01716] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-22 20:15:41,010][01716] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:15:41,014][01716] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-22 20:15:41,016][01716] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:15:41,019][01716] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-22 20:15:41,020][01716] Adding new argument 'push_to_hub'=False that is not in the saved config file!
[2023-02-22 20:15:41,021][01716] Adding new argument 'hf_repository'=None that is not in the saved config file!
[2023-02-22 20:15:41,022][01716] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-22 20:15:41,023][01716] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-22 20:15:41,038][01716] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-22 20:15:41,039][01716] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-22 20:15:41,041][01716] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-22 20:15:41,073][01716] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:15:41,077][01716] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:15:41,081][01716] RunningMeanStd input shape: (1,)
[2023-02-22 20:15:41,102][01716] ConvEncoder: input_channels=3
[2023-02-22 20:15:41,711][01716] Conv encoder output size: 512
[2023-02-22 20:15:41,713][01716] Policy head output size: 512
[2023-02-22 20:15:44,207][01716] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2023-02-22 20:15:45,997][01716] Num frames 100...
[2023-02-22 20:15:46,174][01716] Num frames 200...
[2023-02-22 20:15:46,337][01716] Num frames 300...
[2023-02-22 20:15:46,504][01716] Num frames 400...
[2023-02-22 20:15:46,664][01716] Num frames 500...
[2023-02-22 20:15:46,827][01716] Num frames 600...
[2023-02-22 20:15:46,986][01716] Num frames 700...
[2023-02-22 20:15:47,105][01716] Avg episode rewards: #0: 16.360, true rewards: #0: 7.360
[2023-02-22 20:15:47,107][01716] Avg episode reward: 16.360, avg true_objective: 7.360
[2023-02-22 20:15:47,210][01716] Num frames 800...
[2023-02-22 20:15:47,368][01716] Num frames 900...
[2023-02-22 20:15:47,482][01716] Num frames 1000...
[2023-02-22 20:15:47,591][01716] Num frames 1100...
[2023-02-22 20:15:47,700][01716] Num frames 1200...
[2023-02-22 20:15:47,824][01716] Num frames 1300...
[2023-02-22 20:15:47,936][01716] Num frames 1400...
[2023-02-22 20:15:48,036][01716] Avg episode rewards: #0: 13.700, true rewards: #0: 7.200
[2023-02-22 20:15:48,038][01716] Avg episode reward: 13.700, avg true_objective: 7.200
[2023-02-22 20:15:48,106][01716] Num frames 1500...
[2023-02-22 20:15:48,217][01716] Num frames 1600...
[2023-02-22 20:15:48,326][01716] Num frames 1700...
[2023-02-22 20:15:48,441][01716] Num frames 1800...
[2023-02-22 20:15:48,563][01716] Avg episode rewards: #0: 11.533, true rewards: #0: 6.200
[2023-02-22 20:15:48,566][01716] Avg episode reward: 11.533, avg true_objective: 6.200
[2023-02-22 20:15:48,614][01716] Num frames 1900...
[2023-02-22 20:15:48,726][01716] Num frames 2000...
[2023-02-22 20:15:48,846][01716] Num frames 2100...
[2023-02-22 20:15:48,957][01716] Num frames 2200...
[2023-02-22 20:15:49,070][01716] Num frames 2300...
[2023-02-22 20:15:49,183][01716] Num frames 2400...
[2023-02-22 20:15:49,297][01716] Num frames 2500...
[2023-02-22 20:15:49,417][01716] Num frames 2600...
[2023-02-22 20:15:49,530][01716] Num frames 2700...
[2023-02-22 20:15:49,682][01716] Avg episode rewards: #0: 13.720, true rewards: #0: 6.970
[2023-02-22 20:15:49,684][01716] Avg episode reward: 13.720, avg true_objective: 6.970
[2023-02-22 20:15:49,703][01716] Num frames 2800...
[2023-02-22 20:15:49,821][01716] Num frames 2900...
[2023-02-22 20:15:49,931][01716] Num frames 3000...
[2023-02-22 20:15:50,044][01716] Num frames 3100...
[2023-02-22 20:15:50,162][01716] Num frames 3200...
[2023-02-22 20:15:50,270][01716] Num frames 3300...
[2023-02-22 20:15:50,378][01716] Num frames 3400...
[2023-02-22 20:15:50,489][01716] Num frames 3500...
[2023-02-22 20:15:50,603][01716] Num frames 3600...
[2023-02-22 20:15:50,723][01716] Num frames 3700...
[2023-02-22 20:15:50,775][01716] Avg episode rewards: #0: 14.800, true rewards: #0: 7.400
[2023-02-22 20:15:50,778][01716] Avg episode reward: 14.800, avg true_objective: 7.400
[2023-02-22 20:15:50,890][01716] Num frames 3800...
[2023-02-22 20:15:51,003][01716] Num frames 3900...
[2023-02-22 20:15:51,111][01716] Num frames 4000...
[2023-02-22 20:15:51,256][01716] Avg episode rewards: #0: 12.973, true rewards: #0: 6.807
[2023-02-22 20:15:51,258][01716] Avg episode reward: 12.973, avg true_objective: 6.807
[2023-02-22 20:15:51,282][01716] Num frames 4100...
[2023-02-22 20:15:51,404][01716] Num frames 4200...
[2023-02-22 20:15:51,517][01716] Num frames 4300...
[2023-02-22 20:15:51,626][01716] Num frames 4400...
[2023-02-22 20:15:51,738][01716] Num frames 4500...
[2023-02-22 20:15:51,905][01716] Avg episode rewards: #0: 12.280, true rewards: #0: 6.566
[2023-02-22 20:15:51,908][01716] Avg episode reward: 12.280, avg true_objective: 6.566
[2023-02-22 20:15:51,917][01716] Num frames 4600...
[2023-02-22 20:15:52,028][01716] Num frames 4700...
[2023-02-22 20:15:52,154][01716] Num frames 4800...
[2023-02-22 20:15:52,268][01716] Num frames 4900...
[2023-02-22 20:15:52,378][01716] Num frames 5000...
[2023-02-22 20:15:52,489][01716] Num frames 5100...
[2023-02-22 20:15:52,599][01716] Num frames 5200...
[2023-02-22 20:15:52,660][01716] Avg episode rewards: #0: 12.005, true rewards: #0: 6.505
[2023-02-22 20:15:52,662][01716] Avg episode reward: 12.005, avg true_objective: 6.505
[2023-02-22 20:15:52,771][01716] Num frames 5300...
[2023-02-22 20:15:52,887][01716] Num frames 5400...
[2023-02-22 20:15:52,993][01716] Num frames 5500...
[2023-02-22 20:15:53,106][01716] Num frames 5600...
[2023-02-22 20:15:53,218][01716] Num frames 5700...
[2023-02-22 20:15:53,330][01716] Num frames 5800...
[2023-02-22 20:15:53,469][01716] Avg episode rewards: #0: 12.085, true rewards: #0: 6.529
[2023-02-22 20:15:53,472][01716] Avg episode reward: 12.085, avg true_objective: 6.529
[2023-02-22 20:15:53,501][01716] Num frames 5900...
[2023-02-22 20:15:53,612][01716] Num frames 6000...
[2023-02-22 20:15:53,722][01716] Num frames 6100...
[2023-02-22 20:15:53,846][01716] Num frames 6200...
[2023-02-22 20:15:53,964][01716] Num frames 6300...
[2023-02-22 20:15:54,075][01716] Num frames 6400...
[2023-02-22 20:15:54,185][01716] Num frames 6500...
[2023-02-22 20:15:54,300][01716] Num frames 6600...
[2023-02-22 20:15:54,429][01716] Avg episode rewards: #0: 12.468, true rewards: #0: 6.668
[2023-02-22 20:15:54,430][01716] Avg episode reward: 12.468, avg true_objective: 6.668
[2023-02-22 20:16:33,419][01716] Replay video saved to /content/train_dir/default_experiment/replay.mp4!
[2023-02-22 20:22:41,835][01716] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2023-02-22 20:22:41,837][01716] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-22 20:22:41,839][01716] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-22 20:22:41,841][01716] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-22 20:22:41,843][01716] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:22:41,845][01716] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-22 20:22:41,846][01716] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
[2023-02-22 20:22:41,847][01716] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-22 20:22:41,849][01716] Adding new argument 'push_to_hub'=True that is not in the saved config file!
[2023-02-22 20:22:41,850][01716] Adding new argument 'hf_repository'='RamonAnkersmit/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file!
[2023-02-22 20:22:41,851][01716] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-22 20:22:41,852][01716] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-22 20:22:41,853][01716] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-22 20:22:41,854][01716] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-22 20:22:41,856][01716] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-22 20:22:41,884][01716] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:22:41,887][01716] RunningMeanStd input shape: (1,)
[2023-02-22 20:22:41,902][01716] ConvEncoder: input_channels=3
[2023-02-22 20:22:41,938][01716] Conv encoder output size: 512
[2023-02-22 20:22:41,940][01716] Policy head output size: 512
[2023-02-22 20:22:41,961][01716] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2023-02-22 20:22:42,393][01716] Num frames 100...
[2023-02-22 20:22:42,518][01716] Num frames 200...
[2023-02-22 20:22:42,639][01716] Num frames 300...
[2023-02-22 20:22:42,771][01716] Num frames 400...
[2023-02-22 20:22:42,886][01716] Num frames 500...
[2023-02-22 20:22:43,008][01716] Num frames 600...
[2023-02-22 20:22:43,126][01716] Num frames 700...
[2023-02-22 20:22:43,247][01716] Num frames 800...
[2023-02-22 20:22:43,374][01716] Avg episode rewards: #0: 14.640, true rewards: #0: 8.640
[2023-02-22 20:22:43,376][01716] Avg episode reward: 14.640, avg true_objective: 8.640
[2023-02-22 20:22:43,429][01716] Num frames 900...
[2023-02-22 20:22:43,540][01716] Num frames 1000...
[2023-02-22 20:22:43,658][01716] Num frames 1100...
[2023-02-22 20:22:43,780][01716] Num frames 1200...
[2023-02-22 20:22:43,890][01716] Avg episode rewards: #0: 9.240, true rewards: #0: 6.240
[2023-02-22 20:22:43,892][01716] Avg episode reward: 9.240, avg true_objective: 6.240
[2023-02-22 20:22:43,953][01716] Num frames 1300...
[2023-02-22 20:22:44,064][01716] Num frames 1400...
[2023-02-22 20:22:44,183][01716] Num frames 1500...
[2023-02-22 20:22:44,294][01716] Num frames 1600...
[2023-02-22 20:22:44,423][01716] Num frames 1700...
[2023-02-22 20:22:44,544][01716] Num frames 1800...
[2023-02-22 20:22:44,663][01716] Num frames 1900...
[2023-02-22 20:22:44,788][01716] Num frames 2000...
[2023-02-22 20:22:44,920][01716] Num frames 2100...
[2023-02-22 20:22:45,039][01716] Num frames 2200...
[2023-02-22 20:22:45,154][01716] Num frames 2300...
[2023-02-22 20:22:45,266][01716] Num frames 2400...
[2023-02-22 20:22:45,381][01716] Num frames 2500...
[2023-02-22 20:22:45,501][01716] Num frames 2600...
[2023-02-22 20:22:45,617][01716] Num frames 2700...
[2023-02-22 20:22:45,741][01716] Num frames 2800...
[2023-02-22 20:22:45,896][01716] Avg episode rewards: #0: 20.267, true rewards: #0: 9.600
[2023-02-22 20:22:45,898][01716] Avg episode reward: 20.267, avg true_objective: 9.600
[2023-02-22 20:22:45,926][01716] Num frames 2900...
[2023-02-22 20:22:46,043][01716] Num frames 3000...
[2023-02-22 20:22:46,156][01716] Num frames 3100...
[2023-02-22 20:22:46,277][01716] Num frames 3200...
[2023-02-22 20:22:46,388][01716] Num frames 3300...
[2023-02-22 20:22:46,505][01716] Num frames 3400...
[2023-02-22 20:22:46,619][01716] Num frames 3500...
[2023-02-22 20:22:46,741][01716] Num frames 3600...
[2023-02-22 20:22:46,818][01716] Avg episode rewards: #0: 19.040, true rewards: #0: 9.040
[2023-02-22 20:22:46,821][01716] Avg episode reward: 19.040, avg true_objective: 9.040
[2023-02-22 20:22:46,923][01716] Num frames 3700...
[2023-02-22 20:22:47,036][01716] Num frames 3800...
[2023-02-22 20:22:47,161][01716] Num frames 3900...
[2023-02-22 20:22:47,274][01716] Num frames 4000...
[2023-02-22 20:22:47,366][01716] Avg episode rewards: #0: 16.264, true rewards: #0: 8.064
[2023-02-22 20:22:47,368][01716] Avg episode reward: 16.264, avg true_objective: 8.064
[2023-02-22 20:22:47,452][01716] Num frames 4100...
[2023-02-22 20:22:47,566][01716] Num frames 4200...
[2023-02-22 20:22:47,685][01716] Num frames 4300...
[2023-02-22 20:22:47,800][01716] Num frames 4400...
[2023-02-22 20:22:47,915][01716] Num frames 4500...
[2023-02-22 20:22:48,025][01716] Num frames 4600...
[2023-02-22 20:22:48,143][01716] Num frames 4700...
[2023-02-22 20:22:48,256][01716] Num frames 4800...
[2023-02-22 20:22:48,380][01716] Num frames 4900...
[2023-02-22 20:22:48,505][01716] Avg episode rewards: #0: 17.100, true rewards: #0: 8.267
[2023-02-22 20:22:48,507][01716] Avg episode reward: 17.100, avg true_objective: 8.267
[2023-02-22 20:22:48,556][01716] Num frames 5000...
[2023-02-22 20:22:48,701][01716] Num frames 5100...
[2023-02-22 20:22:48,860][01716] Num frames 5200...
[2023-02-22 20:22:49,023][01716] Num frames 5300...
[2023-02-22 20:22:49,179][01716] Num frames 5400...
[2023-02-22 20:22:49,343][01716] Num frames 5500...
[2023-02-22 20:22:49,413][01716] Avg episode rewards: #0: 15.720, true rewards: #0: 7.863
[2023-02-22 20:22:49,417][01716] Avg episode reward: 15.720, avg true_objective: 7.863
[2023-02-22 20:22:49,572][01716] Num frames 5600...
[2023-02-22 20:22:49,730][01716] Num frames 5700...
[2023-02-22 20:22:49,889][01716] Num frames 5800...
[2023-02-22 20:22:50,049][01716] Num frames 5900...
[2023-02-22 20:22:50,222][01716] Num frames 6000...
[2023-02-22 20:22:50,386][01716] Num frames 6100...
[2023-02-22 20:22:50,554][01716] Num frames 6200...
[2023-02-22 20:22:50,716][01716] Num frames 6300...
[2023-02-22 20:22:50,880][01716] Num frames 6400...
[2023-02-22 20:22:51,054][01716] Num frames 6500...
[2023-02-22 20:22:51,222][01716] Num frames 6600...
[2023-02-22 20:22:51,369][01716] Avg episode rewards: #0: 16.570, true rewards: #0: 8.320
[2023-02-22 20:22:51,371][01716] Avg episode reward: 16.570, avg true_objective: 8.320
[2023-02-22 20:22:51,445][01716] Num frames 6700...
[2023-02-22 20:22:51,605][01716] Num frames 6800...
[2023-02-22 20:22:51,773][01716] Num frames 6900...
[2023-02-22 20:22:51,934][01716] Num frames 7000...
[2023-02-22 20:22:52,102][01716] Num frames 7100...
[2023-02-22 20:22:52,274][01716] Avg episode rewards: #0: 15.631, true rewards: #0: 7.964
[2023-02-22 20:22:52,276][01716] Avg episode reward: 15.631, avg true_objective: 7.964
[2023-02-22 20:22:52,316][01716] Num frames 7200...
[2023-02-22 20:22:52,437][01716] Num frames 7300...
[2023-02-22 20:22:52,550][01716] Num frames 7400...
[2023-02-22 20:22:52,663][01716] Num frames 7500...
[2023-02-22 20:22:52,776][01716] Num frames 7600...
[2023-02-22 20:22:52,900][01716] Num frames 7700...
[2023-02-22 20:22:53,041][01716] Avg episode rewards: #0: 14.976, true rewards: #0: 7.776
[2023-02-22 20:22:53,043][01716] Avg episode reward: 14.976, avg true_objective: 7.776
[2023-02-22 20:23:40,237][01716] Replay video saved to /content/train_dir/default_experiment/replay.mp4!
[2023-02-22 20:23:52,578][01716] The model has been pushed to https://huggingface.co/RamonAnkersmit/rl_course_vizdoom_health_gathering_supreme
[2023-02-22 20:25:32,697][01716] Loading legacy config file train_dir/doom_health_gathering_supreme_2222/cfg.json instead of train_dir/doom_health_gathering_supreme_2222/config.json
[2023-02-22 20:25:32,699][01716] Loading existing experiment configuration from train_dir/doom_health_gathering_supreme_2222/config.json
[2023-02-22 20:25:32,701][01716] Overriding arg 'experiment' with value 'doom_health_gathering_supreme_2222' passed from command line
[2023-02-22 20:25:32,703][01716] Overriding arg 'train_dir' with value 'train_dir' passed from command line
[2023-02-22 20:25:32,705][01716] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-22 20:25:32,707][01716] Adding new argument 'lr_adaptive_min'=1e-06 that is not in the saved config file!
[2023-02-22 20:25:32,709][01716] Adding new argument 'lr_adaptive_max'=0.01 that is not in the saved config file!
[2023-02-22 20:25:32,710][01716] Adding new argument 'env_gpu_observations'=True that is not in the saved config file!
[2023-02-22 20:25:32,711][01716] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-22 20:25:32,712][01716] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-22 20:25:32,713][01716] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:25:32,714][01716] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-22 20:25:32,716][01716] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:25:32,717][01716] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-22 20:25:32,718][01716] Adding new argument 'push_to_hub'=False that is not in the saved config file!
[2023-02-22 20:25:32,719][01716] Adding new argument 'hf_repository'=None that is not in the saved config file!
[2023-02-22 20:25:32,720][01716] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-22 20:25:32,721][01716] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-22 20:25:32,722][01716] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-22 20:25:32,724][01716] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-22 20:25:32,725][01716] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-22 20:25:32,752][01716] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:25:32,760][01716] RunningMeanStd input shape: (1,)
[2023-02-22 20:25:32,775][01716] ConvEncoder: input_channels=3
[2023-02-22 20:25:32,819][01716] Conv encoder output size: 512
[2023-02-22 20:25:32,821][01716] Policy head output size: 512
[2023-02-22 20:25:32,845][01716] Loading state from checkpoint train_dir/doom_health_gathering_supreme_2222/checkpoint_p0/checkpoint_000539850_4422451200.pth...
[2023-02-22 20:25:33,297][01716] Num frames 100...
[2023-02-22 20:25:33,418][01716] Num frames 200...
[2023-02-22 20:25:33,532][01716] Num frames 300...
[2023-02-22 20:25:33,658][01716] Num frames 400...
[2023-02-22 20:25:33,775][01716] Num frames 500...
[2023-02-22 20:25:33,896][01716] Num frames 600...
[2023-02-22 20:25:34,028][01716] Num frames 700...
[2023-02-22 20:25:34,141][01716] Num frames 800...
[2023-02-22 20:25:34,254][01716] Num frames 900...
[2023-02-22 20:25:34,368][01716] Num frames 1000...
[2023-02-22 20:25:34,481][01716] Num frames 1100...
[2023-02-22 20:25:34,595][01716] Num frames 1200...
[2023-02-22 20:25:34,709][01716] Num frames 1300...
[2023-02-22 20:25:34,831][01716] Num frames 1400...
[2023-02-22 20:25:34,950][01716] Num frames 1500...
[2023-02-22 20:25:35,073][01716] Num frames 1600...
[2023-02-22 20:25:35,189][01716] Num frames 1700...
[2023-02-22 20:25:35,312][01716] Num frames 1800...
[2023-02-22 20:25:35,426][01716] Num frames 1900...
[2023-02-22 20:25:35,536][01716] Num frames 2000...
[2023-02-22 20:25:35,655][01716] Num frames 2100...
[2023-02-22 20:25:35,708][01716] Avg episode rewards: #0: 66.999, true rewards: #0: 21.000
[2023-02-22 20:25:35,710][01716] Avg episode reward: 66.999, avg true_objective: 21.000
[2023-02-22 20:25:35,828][01716] Num frames 2200...
[2023-02-22 20:25:35,951][01716] Num frames 2300...
[2023-02-22 20:25:36,082][01716] Num frames 2400...
[2023-02-22 20:25:36,212][01716] Num frames 2500...
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[2023-02-22 20:25:37,387][01716] Num frames 3500...
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[2023-02-22 20:25:37,983][01716] Num frames 4000...
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[2023-02-22 20:25:38,226][01716] Num frames 4200...
[2023-02-22 20:25:38,281][01716] Avg episode rewards: #0: 65.499, true rewards: #0: 21.000
[2023-02-22 20:25:38,283][01716] Avg episode reward: 65.499, avg true_objective: 21.000
[2023-02-22 20:25:38,403][01716] Num frames 4300...
[2023-02-22 20:25:38,516][01716] Num frames 4400...
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[2023-02-22 20:25:39,396][01716] Num frames 5000...
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[2023-02-22 20:25:39,738][01716] Num frames 5200...
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[2023-02-22 20:25:40,088][01716] Num frames 5400...
[2023-02-22 20:25:40,243][01716] Num frames 5500...
[2023-02-22 20:25:40,399][01716] Num frames 5600...
[2023-02-22 20:25:40,557][01716] Num frames 5700...
[2023-02-22 20:25:40,716][01716] Num frames 5800...
[2023-02-22 20:25:40,879][01716] Num frames 5900...
[2023-02-22 20:25:41,037][01716] Num frames 6000...
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[2023-02-22 20:25:41,377][01716] Num frames 6200...
[2023-02-22 20:25:41,551][01716] Num frames 6300...
[2023-02-22 20:25:41,604][01716] Avg episode rewards: #0: 65.999, true rewards: #0: 21.000
[2023-02-22 20:25:41,606][01716] Avg episode reward: 65.999, avg true_objective: 21.000
[2023-02-22 20:25:41,770][01716] Num frames 6400...
[2023-02-22 20:25:41,934][01716] Num frames 6500...
[2023-02-22 20:25:42,099][01716] Num frames 6600...
[2023-02-22 20:25:42,271][01716] Num frames 6700...
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[2023-02-22 20:25:42,663][01716] Num frames 7000...
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[2023-02-22 20:25:42,897][01716] Num frames 7200...
[2023-02-22 20:25:43,013][01716] Num frames 7300...
[2023-02-22 20:25:43,134][01716] Num frames 7400...
[2023-02-22 20:25:43,261][01716] Num frames 7500...
[2023-02-22 20:25:43,378][01716] Num frames 7600...
[2023-02-22 20:25:43,496][01716] Num frames 7700...
[2023-02-22 20:25:43,621][01716] Num frames 7800...
[2023-02-22 20:25:43,740][01716] Num frames 7900...
[2023-02-22 20:25:43,859][01716] Num frames 8000...
[2023-02-22 20:25:43,974][01716] Num frames 8100...
[2023-02-22 20:25:44,100][01716] Avg episode rewards: #0: 64.389, true rewards: #0: 20.390
[2023-02-22 20:25:44,101][01716] Avg episode reward: 64.389, avg true_objective: 20.390
[2023-02-22 20:25:44,157][01716] Num frames 8200...
[2023-02-22 20:25:44,278][01716] Num frames 8300...
[2023-02-22 20:25:44,397][01716] Num frames 8400...
[2023-02-22 20:25:44,524][01716] Num frames 8500...
[2023-02-22 20:25:44,646][01716] Num frames 8600...
[2023-02-22 20:25:44,769][01716] Num frames 8700...
[2023-02-22 20:25:44,883][01716] Num frames 8800...
[2023-02-22 20:25:44,997][01716] Num frames 8900...
[2023-02-22 20:25:45,112][01716] Num frames 9000...
[2023-02-22 20:25:45,236][01716] Num frames 9100...
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[2023-02-22 20:25:45,591][01716] Num frames 9400...
[2023-02-22 20:25:45,705][01716] Num frames 9500...
[2023-02-22 20:25:45,825][01716] Num frames 9600...
[2023-02-22 20:25:45,939][01716] Num frames 9700...
[2023-02-22 20:25:46,058][01716] Num frames 9800...
[2023-02-22 20:25:46,175][01716] Num frames 9900...
[2023-02-22 20:25:46,303][01716] Num frames 10000...
[2023-02-22 20:25:46,429][01716] Num frames 10100...
[2023-02-22 20:25:46,547][01716] Num frames 10200...
[2023-02-22 20:25:46,667][01716] Avg episode rewards: #0: 63.711, true rewards: #0: 20.512
[2023-02-22 20:25:46,669][01716] Avg episode reward: 63.711, avg true_objective: 20.512
[2023-02-22 20:25:46,728][01716] Num frames 10300...
[2023-02-22 20:25:46,853][01716] Num frames 10400...
[2023-02-22 20:25:46,967][01716] Num frames 10500...
[2023-02-22 20:25:47,086][01716] Num frames 10600...
[2023-02-22 20:25:47,211][01716] Num frames 10700...
[2023-02-22 20:25:47,339][01716] Num frames 10800...
[2023-02-22 20:25:47,455][01716] Num frames 10900...
[2023-02-22 20:25:47,567][01716] Num frames 11000...
[2023-02-22 20:25:47,678][01716] Num frames 11100...
[2023-02-22 20:25:47,800][01716] Num frames 11200...
[2023-02-22 20:25:47,914][01716] Num frames 11300...
[2023-02-22 20:25:48,031][01716] Num frames 11400...
[2023-02-22 20:25:48,147][01716] Num frames 11500...
[2023-02-22 20:25:48,265][01716] Num frames 11600...
[2023-02-22 20:25:48,387][01716] Num frames 11700...
[2023-02-22 20:25:48,503][01716] Num frames 11800...
[2023-02-22 20:25:48,623][01716] Num frames 11900...
[2023-02-22 20:25:48,741][01716] Num frames 12000...
[2023-02-22 20:25:48,865][01716] Num frames 12100...
[2023-02-22 20:25:48,981][01716] Num frames 12200...
[2023-02-22 20:25:49,097][01716] Num frames 12300...
[2023-02-22 20:25:49,217][01716] Avg episode rewards: #0: 63.425, true rewards: #0: 20.593
[2023-02-22 20:25:49,220][01716] Avg episode reward: 63.425, avg true_objective: 20.593
[2023-02-22 20:25:49,275][01716] Num frames 12400...
[2023-02-22 20:25:49,397][01716] Num frames 12500...
[2023-02-22 20:25:49,517][01716] Num frames 12600...
[2023-02-22 20:25:49,631][01716] Num frames 12700...
[2023-02-22 20:25:49,746][01716] Num frames 12800...
[2023-02-22 20:25:49,861][01716] Num frames 12900...
[2023-02-22 20:25:49,989][01716] Num frames 13000...
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[2023-02-22 20:25:50,344][01716] Num frames 13300...
[2023-02-22 20:25:50,461][01716] Num frames 13400...
[2023-02-22 20:25:50,577][01716] Num frames 13500...
[2023-02-22 20:25:50,690][01716] Num frames 13600...
[2023-02-22 20:25:50,803][01716] Num frames 13700...
[2023-02-22 20:25:50,919][01716] Num frames 13800...
[2023-02-22 20:25:51,038][01716] Num frames 13900...
[2023-02-22 20:25:51,155][01716] Num frames 14000...
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[2023-02-22 20:25:51,397][01716] Num frames 14200...
[2023-02-22 20:25:51,513][01716] Num frames 14300...
[2023-02-22 20:25:51,624][01716] Num frames 14400...
[2023-02-22 20:25:51,743][01716] Avg episode rewards: #0: 63.364, true rewards: #0: 20.651
[2023-02-22 20:25:51,744][01716] Avg episode reward: 63.364, avg true_objective: 20.651
[2023-02-22 20:25:51,807][01716] Num frames 14500...
[2023-02-22 20:25:51,921][01716] Num frames 14600...
[2023-02-22 20:25:52,035][01716] Num frames 14700...
[2023-02-22 20:25:52,150][01716] Num frames 14800...
[2023-02-22 20:25:52,270][01716] Num frames 14900...
[2023-02-22 20:25:52,389][01716] Num frames 15000...
[2023-02-22 20:25:52,545][01716] Num frames 15100...
[2023-02-22 20:25:52,704][01716] Num frames 15200...
[2023-02-22 20:25:52,866][01716] Num frames 15300...
[2023-02-22 20:25:53,021][01716] Num frames 15400...
[2023-02-22 20:25:53,177][01716] Num frames 15500...
[2023-02-22 20:25:53,336][01716] Num frames 15600...
[2023-02-22 20:25:53,510][01716] Num frames 15700...
[2023-02-22 20:25:53,670][01716] Num frames 15800...
[2023-02-22 20:25:53,833][01716] Num frames 15900...
[2023-02-22 20:25:53,990][01716] Num frames 16000...
[2023-02-22 20:25:54,151][01716] Num frames 16100...
[2023-02-22 20:25:54,313][01716] Num frames 16200...
[2023-02-22 20:25:54,489][01716] Num frames 16300...
[2023-02-22 20:25:54,655][01716] Num frames 16400...
[2023-02-22 20:25:54,816][01716] Num frames 16500...
[2023-02-22 20:25:54,965][01716] Avg episode rewards: #0: 63.569, true rewards: #0: 20.695
[2023-02-22 20:25:54,967][01716] Avg episode reward: 63.569, avg true_objective: 20.695
[2023-02-22 20:25:55,039][01716] Num frames 16600...
[2023-02-22 20:25:55,196][01716] Num frames 16700...
[2023-02-22 20:25:55,352][01716] Num frames 16800...
[2023-02-22 20:25:55,515][01716] Num frames 16900...
[2023-02-22 20:25:55,679][01716] Num frames 17000...
[2023-02-22 20:25:55,841][01716] Num frames 17100...
[2023-02-22 20:25:56,008][01716] Num frames 17200...
[2023-02-22 20:25:56,126][01716] Num frames 17300...
[2023-02-22 20:25:56,239][01716] Num frames 17400...
[2023-02-22 20:25:56,351][01716] Num frames 17500...
[2023-02-22 20:25:56,470][01716] Num frames 17600...
[2023-02-22 20:25:56,594][01716] Num frames 17700...
[2023-02-22 20:25:56,709][01716] Num frames 17800...
[2023-02-22 20:25:56,826][01716] Num frames 17900...
[2023-02-22 20:25:56,940][01716] Num frames 18000...
[2023-02-22 20:25:57,062][01716] Num frames 18100...
[2023-02-22 20:25:57,180][01716] Num frames 18200...
[2023-02-22 20:25:57,291][01716] Num frames 18300...
[2023-02-22 20:25:57,405][01716] Num frames 18400...
[2023-02-22 20:25:57,522][01716] Num frames 18500...
[2023-02-22 20:25:57,644][01716] Num frames 18600...
[2023-02-22 20:25:57,764][01716] Avg episode rewards: #0: 63.728, true rewards: #0: 20.729
[2023-02-22 20:25:57,766][01716] Avg episode reward: 63.728, avg true_objective: 20.729
[2023-02-22 20:25:57,819][01716] Num frames 18700...
[2023-02-22 20:25:57,938][01716] Num frames 18800...
[2023-02-22 20:25:58,051][01716] Num frames 18900...
[2023-02-22 20:25:58,164][01716] Num frames 19000...
[2023-02-22 20:25:58,275][01716] Num frames 19100...
[2023-02-22 20:25:58,395][01716] Num frames 19200...
[2023-02-22 20:25:58,515][01716] Num frames 19300...
[2023-02-22 20:25:58,637][01716] Num frames 19400...
[2023-02-22 20:25:58,752][01716] Num frames 19500...
[2023-02-22 20:25:58,875][01716] Num frames 19600...
[2023-02-22 20:25:58,991][01716] Num frames 19700...
[2023-02-22 20:25:59,104][01716] Num frames 19800...
[2023-02-22 20:25:59,215][01716] Num frames 19900...
[2023-02-22 20:25:59,330][01716] Num frames 20000...
[2023-02-22 20:25:59,451][01716] Num frames 20100...
[2023-02-22 20:25:59,563][01716] Num frames 20200...
[2023-02-22 20:25:59,686][01716] Num frames 20300...
[2023-02-22 20:25:59,802][01716] Num frames 20400...
[2023-02-22 20:25:59,916][01716] Num frames 20500...
[2023-02-22 20:26:00,031][01716] Num frames 20600...
[2023-02-22 20:26:00,148][01716] Num frames 20700...
[2023-02-22 20:26:00,268][01716] Avg episode rewards: #0: 63.555, true rewards: #0: 20.756
[2023-02-22 20:26:00,269][01716] Avg episode reward: 63.555, avg true_objective: 20.756
[2023-02-22 20:28:02,145][01716] Replay video saved to train_dir/doom_health_gathering_supreme_2222/replay.mp4!
[2023-02-22 20:50:38,844][01716] Loading existing experiment configuration from /content/train_dir/doom_health_gathering_supreme_2222/config.json
[2023-02-22 20:50:38,847][01716] Overriding arg 'experiment' with value 'doom_health_gathering_supreme_2222' passed from command line
[2023-02-22 20:50:38,849][01716] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-22 20:50:38,851][01716] Adding new argument 'lr_adaptive_min'=1e-06 that is not in the saved config file!
[2023-02-22 20:50:38,852][01716] Adding new argument 'lr_adaptive_max'=0.01 that is not in the saved config file!
[2023-02-22 20:50:38,854][01716] Adding new argument 'env_gpu_observations'=True that is not in the saved config file!
[2023-02-22 20:50:38,855][01716] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-22 20:50:38,857][01716] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-22 20:50:38,858][01716] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:50:38,859][01716] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-22 20:50:38,860][01716] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
[2023-02-22 20:50:38,862][01716] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-22 20:50:38,863][01716] Adding new argument 'push_to_hub'=True that is not in the saved config file!
[2023-02-22 20:50:38,864][01716] Adding new argument 'hf_repository'='RamonAnkersmit/rl_course_vizdoom_health_gathering_supreme_v2' that is not in the saved config file!
[2023-02-22 20:50:38,865][01716] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-22 20:50:38,867][01716] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-22 20:50:38,868][01716] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-22 20:50:38,870][01716] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-22 20:50:38,871][01716] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-22 20:50:38,905][01716] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:50:38,907][01716] RunningMeanStd input shape: (1,)
[2023-02-22 20:50:38,921][01716] ConvEncoder: input_channels=3
[2023-02-22 20:50:38,959][01716] Conv encoder output size: 512
[2023-02-22 20:50:38,961][01716] Policy head output size: 512
[2023-02-22 20:50:38,984][01716] No checkpoints found
[2023-02-22 20:51:04,955][01716] Loading existing experiment configuration from /content/train_dir/doom_health_gathering_supreme_2222/config.json
[2023-02-22 20:51:04,961][01716] Overriding arg 'experiment' with value 'doom_health_gathering_supreme_2222' passed from command line
[2023-02-22 20:51:04,963][01716] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-22 20:51:04,966][01716] Adding new argument 'lr_adaptive_min'=1e-06 that is not in the saved config file!
[2023-02-22 20:51:04,970][01716] Adding new argument 'lr_adaptive_max'=0.01 that is not in the saved config file!
[2023-02-22 20:51:04,971][01716] Adding new argument 'env_gpu_observations'=True that is not in the saved config file!
[2023-02-22 20:51:04,974][01716] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-22 20:51:04,976][01716] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-22 20:51:04,977][01716] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:51:04,979][01716] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-22 20:51:04,980][01716] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
[2023-02-22 20:51:04,984][01716] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-22 20:51:04,986][01716] Adding new argument 'push_to_hub'=True that is not in the saved config file!
[2023-02-22 20:51:04,987][01716] Adding new argument 'hf_repository'='RamonAnkersmit/rl_course_vizdoom_health_gathering_supreme_v2' that is not in the saved config file!
[2023-02-22 20:51:04,988][01716] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-22 20:51:04,989][01716] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-22 20:51:04,991][01716] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-22 20:51:04,993][01716] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-22 20:51:04,994][01716] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-22 20:51:05,028][01716] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:51:05,031][01716] RunningMeanStd input shape: (1,)
[2023-02-22 20:51:05,056][01716] ConvEncoder: input_channels=3
[2023-02-22 20:51:05,119][01716] Conv encoder output size: 512
[2023-02-22 20:51:05,121][01716] Policy head output size: 512
[2023-02-22 20:51:05,155][01716] No checkpoints found
[2023-02-22 20:53:37,758][01716] Loading existing experiment configuration from /content/train_dir/doom_health_gathering_supreme_2222/config.json
[2023-02-22 20:53:37,760][01716] Overriding arg 'experiment' with value 'doom_health_gathering_supreme_2222' passed from command line
[2023-02-22 20:53:37,763][01716] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-22 20:53:37,765][01716] Adding new argument 'lr_adaptive_min'=1e-06 that is not in the saved config file!
[2023-02-22 20:53:37,768][01716] Adding new argument 'lr_adaptive_max'=0.01 that is not in the saved config file!
[2023-02-22 20:53:37,770][01716] Adding new argument 'env_gpu_observations'=True that is not in the saved config file!
[2023-02-22 20:53:37,772][01716] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-22 20:53:37,773][01716] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-22 20:53:37,774][01716] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 20:53:37,776][01716] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-22 20:53:37,777][01716] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
[2023-02-22 20:53:37,778][01716] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-22 20:53:37,779][01716] Adding new argument 'push_to_hub'=True that is not in the saved config file!
[2023-02-22 20:53:37,781][01716] Adding new argument 'hf_repository'='RamonAnkersmit/rl_course_vizdoom_health_gathering_supreme_v2' that is not in the saved config file!
[2023-02-22 20:53:37,782][01716] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-22 20:53:37,783][01716] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-22 20:53:37,785][01716] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-22 20:53:37,786][01716] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-22 20:53:37,787][01716] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-22 20:53:37,810][01716] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:53:37,814][01716] RunningMeanStd input shape: (1,)
[2023-02-22 20:53:37,826][01716] ConvEncoder: input_channels=3
[2023-02-22 20:53:37,862][01716] Conv encoder output size: 512
[2023-02-22 20:53:37,863][01716] Policy head output size: 512
[2023-02-22 20:53:37,885][01716] No checkpoints found
[2023-02-22 20:56:04,688][01716] Environment doom_basic already registered, overwriting...
[2023-02-22 20:56:04,691][01716] Environment doom_two_colors_easy already registered, overwriting...
[2023-02-22 20:56:04,693][01716] Environment doom_two_colors_hard already registered, overwriting...
[2023-02-22 20:56:04,695][01716] Environment doom_dm already registered, overwriting...
[2023-02-22 20:56:04,696][01716] Environment doom_dwango5 already registered, overwriting...
[2023-02-22 20:56:04,700][01716] Environment doom_my_way_home_flat_actions already registered, overwriting...
[2023-02-22 20:56:04,701][01716] Environment doom_defend_the_center_flat_actions already registered, overwriting...
[2023-02-22 20:56:04,703][01716] Environment doom_my_way_home already registered, overwriting...
[2023-02-22 20:56:04,705][01716] Environment doom_deadly_corridor already registered, overwriting...
[2023-02-22 20:56:04,707][01716] Environment doom_defend_the_center already registered, overwriting...
[2023-02-22 20:56:04,709][01716] Environment doom_defend_the_line already registered, overwriting...
[2023-02-22 20:56:04,710][01716] Environment doom_health_gathering already registered, overwriting...
[2023-02-22 20:56:04,711][01716] Environment doom_health_gathering_supreme already registered, overwriting...
[2023-02-22 20:56:04,712][01716] Environment doom_battle already registered, overwriting...
[2023-02-22 20:56:04,713][01716] Environment doom_battle2 already registered, overwriting...
[2023-02-22 20:56:04,714][01716] Environment doom_duel_bots already registered, overwriting...
[2023-02-22 20:56:04,716][01716] Environment doom_deathmatch_bots already registered, overwriting...
[2023-02-22 20:56:04,718][01716] Environment doom_duel already registered, overwriting...
[2023-02-22 20:56:04,719][01716] Environment doom_deathmatch_full already registered, overwriting...
[2023-02-22 20:56:04,721][01716] Environment doom_benchmark already registered, overwriting...
[2023-02-22 20:56:04,723][01716] register_encoder_factory: <function make_vizdoom_encoder at 0x7f74dfab4670>
[2023-02-22 20:56:04,754][01716] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2023-02-22 20:56:04,755][01716] Overriding arg 'train_for_env_steps' with value 10000000 passed from command line
[2023-02-22 20:56:04,764][01716] Experiment dir /content/train_dir/default_experiment already exists!
[2023-02-22 20:56:04,766][01716] Resuming existing experiment from /content/train_dir/default_experiment...
[2023-02-22 20:56:04,768][01716] Weights and Biases integration disabled
[2023-02-22 20:56:04,773][01716] Environment var CUDA_VISIBLE_DEVICES is 0

[2023-02-22 20:56:06,170][01716] Starting experiment with the following configuration:
help=False
algo=APPO
env=doom_health_gathering_supreme
experiment=default_experiment
train_dir=/content/train_dir
restart_behavior=resume
device=gpu
seed=None
num_policies=1
async_rl=True
serial_mode=False
batched_sampling=False
num_batches_to_accumulate=2
worker_num_splits=2
policy_workers_per_policy=1
max_policy_lag=1000
num_workers=8
num_envs_per_worker=4
batch_size=1024
num_batches_per_epoch=1
num_epochs=1
rollout=32
recurrence=32
shuffle_minibatches=False
gamma=0.99
reward_scale=1.0
reward_clip=1000.0
value_bootstrap=False
normalize_returns=True
exploration_loss_coeff=0.001
value_loss_coeff=0.5
kl_loss_coeff=0.0
exploration_loss=symmetric_kl
gae_lambda=0.95
ppo_clip_ratio=0.1
ppo_clip_value=0.2
with_vtrace=False
vtrace_rho=1.0
vtrace_c=1.0
optimizer=adam
adam_eps=1e-06
adam_beta1=0.9
adam_beta2=0.999
max_grad_norm=4.0
learning_rate=0.0001
lr_schedule=constant
lr_schedule_kl_threshold=0.008
lr_adaptive_min=1e-06
lr_adaptive_max=0.01
obs_subtract_mean=0.0
obs_scale=255.0
normalize_input=True
normalize_input_keys=None
decorrelate_experience_max_seconds=0
decorrelate_envs_on_one_worker=True
actor_worker_gpus=[]
set_workers_cpu_affinity=True
force_envs_single_thread=False
default_niceness=0
log_to_file=True
experiment_summaries_interval=10
flush_summaries_interval=30
stats_avg=100
summaries_use_frameskip=True
heartbeat_interval=20
heartbeat_reporting_interval=600
train_for_env_steps=10000000
train_for_seconds=10000000000
save_every_sec=120
keep_checkpoints=2
load_checkpoint_kind=latest
save_milestones_sec=-1
save_best_every_sec=5
save_best_metric=reward
save_best_after=100000
benchmark=False
encoder_mlp_layers=[512, 512]
encoder_conv_architecture=convnet_simple
encoder_conv_mlp_layers=[512]
use_rnn=True
rnn_size=512
rnn_type=gru
rnn_num_layers=1
decoder_mlp_layers=[]
nonlinearity=elu
policy_initialization=orthogonal
policy_init_gain=1.0
actor_critic_share_weights=True
adaptive_stddev=True
continuous_tanh_scale=0.0
initial_stddev=1.0
use_env_info_cache=False
env_gpu_actions=False
env_gpu_observations=True
env_frameskip=4
env_framestack=1
pixel_format=CHW
use_record_episode_statistics=False
with_wandb=False
wandb_user=None
wandb_project=sample_factory
wandb_group=None
wandb_job_type=SF
wandb_tags=[]
with_pbt=False
pbt_mix_policies_in_one_env=True
pbt_period_env_steps=5000000
pbt_start_mutation=20000000
pbt_replace_fraction=0.3
pbt_mutation_rate=0.15
pbt_replace_reward_gap=0.1
pbt_replace_reward_gap_absolute=1e-06
pbt_optimize_gamma=False
pbt_target_objective=true_objective
pbt_perturb_min=1.1
pbt_perturb_max=1.5
num_agents=-1
num_humans=0
num_bots=-1
start_bot_difficulty=None
timelimit=None
res_w=128
res_h=72
wide_aspect_ratio=False
eval_env_frameskip=1
fps=35
command_line=--env=doom_health_gathering_supreme --num_workers=8 --num_envs_per_worker=4 --train_for_env_steps=4000000
cli_args={'env': 'doom_health_gathering_supreme', 'num_workers': 8, 'num_envs_per_worker': 4, 'train_for_env_steps': 4000000}
git_hash=unknown
git_repo_name=not a git repository
[2023-02-22 20:56:06,175][01716] Saving configuration to /content/train_dir/default_experiment/config.json...
[2023-02-22 20:56:06,179][01716] Rollout worker 0 uses device cpu
[2023-02-22 20:56:06,184][01716] Rollout worker 1 uses device cpu
[2023-02-22 20:56:06,186][01716] Rollout worker 2 uses device cpu
[2023-02-22 20:56:06,189][01716] Rollout worker 3 uses device cpu
[2023-02-22 20:56:06,191][01716] Rollout worker 4 uses device cpu
[2023-02-22 20:56:06,196][01716] Rollout worker 5 uses device cpu
[2023-02-22 20:56:06,197][01716] Rollout worker 6 uses device cpu
[2023-02-22 20:56:06,200][01716] Rollout worker 7 uses device cpu
[2023-02-22 20:56:06,319][01716] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 20:56:06,320][01716] InferenceWorker_p0-w0: min num requests: 2
[2023-02-22 20:56:06,351][01716] Starting all processes...
[2023-02-22 20:56:06,353][01716] Starting process learner_proc0
[2023-02-22 20:56:06,496][01716] Starting all processes...
[2023-02-22 20:56:06,510][01716] Starting process inference_proc0-0
[2023-02-22 20:56:06,511][01716] Starting process rollout_proc0
[2023-02-22 20:56:06,516][01716] Starting process rollout_proc1
[2023-02-22 20:56:06,516][01716] Starting process rollout_proc2
[2023-02-22 20:56:06,516][01716] Starting process rollout_proc3
[2023-02-22 20:56:06,516][01716] Starting process rollout_proc4
[2023-02-22 20:56:06,516][01716] Starting process rollout_proc5
[2023-02-22 20:56:06,516][01716] Starting process rollout_proc6
[2023-02-22 20:56:06,516][01716] Starting process rollout_proc7
[2023-02-22 20:56:14,309][30129] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 20:56:14,314][30129] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0
[2023-02-22 20:56:14,373][30129] Num visible devices: 1
[2023-02-22 20:56:14,409][30129] Starting seed is not provided
[2023-02-22 20:56:14,416][30129] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 20:56:14,416][30129] Initializing actor-critic model on device cuda:0
[2023-02-22 20:56:14,417][30129] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:56:14,417][30129] RunningMeanStd input shape: (1,)
[2023-02-22 20:56:14,591][30129] ConvEncoder: input_channels=3
[2023-02-22 20:56:16,296][30129] Conv encoder output size: 512
[2023-02-22 20:56:16,308][30129] Policy head output size: 512
[2023-02-22 20:56:16,492][30129] Created Actor Critic model with architecture:
[2023-02-22 20:56:16,505][30129] 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)
  )
)
[2023-02-22 20:56:16,939][30144] Worker 1 uses CPU cores [1]
[2023-02-22 20:56:16,999][30143] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 20:56:17,000][30143] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0
[2023-02-22 20:56:17,079][30143] Num visible devices: 1
[2023-02-22 20:56:18,153][30151] Worker 0 uses CPU cores [0]
[2023-02-22 20:56:18,418][30152] Worker 2 uses CPU cores [0]
[2023-02-22 20:56:18,688][30158] Worker 4 uses CPU cores [0]
[2023-02-22 20:56:18,733][30154] Worker 3 uses CPU cores [1]
[2023-02-22 20:56:18,787][30156] Worker 5 uses CPU cores [1]
[2023-02-22 20:56:18,811][30166] Worker 6 uses CPU cores [0]
[2023-02-22 20:56:18,920][30164] Worker 7 uses CPU cores [1]
[2023-02-22 20:56:20,939][30129] Using optimizer <class 'torch.optim.adam.Adam'>
[2023-02-22 20:56:20,940][30129] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2023-02-22 20:56:20,975][30129] Loading model from checkpoint
[2023-02-22 20:56:20,979][30129] Loaded experiment state at self.train_step=978, self.env_steps=4005888
[2023-02-22 20:56:20,979][30129] Initialized policy 0 weights for model version 978
[2023-02-22 20:56:20,982][30129] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-22 20:56:20,989][30129] LearnerWorker_p0 finished initialization!
[2023-02-22 20:56:21,202][30143] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 20:56:21,203][30143] RunningMeanStd input shape: (1,)
[2023-02-22 20:56:21,216][30143] ConvEncoder: input_channels=3
[2023-02-22 20:56:21,311][30143] Conv encoder output size: 512
[2023-02-22 20:56:21,312][30143] Policy head output size: 512
[2023-02-22 20:56:23,625][01716] Inference worker 0-0 is ready!
[2023-02-22 20:56:23,626][01716] All inference workers are ready! Signal rollout workers to start!
[2023-02-22 20:56:23,761][30151] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:23,771][30158] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:23,784][30166] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:23,787][30154] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:23,781][30152] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:23,796][30156] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:23,800][30164] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:23,815][30144] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-22 20:56:24,612][30154] Decorrelating experience for 0 frames...
[2023-02-22 20:56:24,626][30144] Decorrelating experience for 0 frames...
[2023-02-22 20:56:24,773][01716] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 4005888. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-22 20:56:24,921][30151] Decorrelating experience for 0 frames...
[2023-02-22 20:56:24,925][30158] Decorrelating experience for 0 frames...
[2023-02-22 20:56:24,923][30166] Decorrelating experience for 0 frames...
[2023-02-22 20:56:25,308][30154] Decorrelating experience for 32 frames...
[2023-02-22 20:56:25,322][30144] Decorrelating experience for 32 frames...
[2023-02-22 20:56:25,918][30166] Decorrelating experience for 32 frames...
[2023-02-22 20:56:25,922][30151] Decorrelating experience for 32 frames...
[2023-02-22 20:56:25,927][30158] Decorrelating experience for 32 frames...
[2023-02-22 20:56:26,187][30164] Decorrelating experience for 0 frames...
[2023-02-22 20:56:26,311][01716] Heartbeat connected on Batcher_0
[2023-02-22 20:56:26,317][01716] Heartbeat connected on LearnerWorker_p0
[2023-02-22 20:56:26,361][01716] Heartbeat connected on InferenceWorker_p0-w0
[2023-02-22 20:56:26,377][30144] Decorrelating experience for 64 frames...
[2023-02-22 20:56:26,847][30166] Decorrelating experience for 64 frames...
[2023-02-22 20:56:26,862][30156] Decorrelating experience for 0 frames...
[2023-02-22 20:56:26,940][30158] Decorrelating experience for 64 frames...
[2023-02-22 20:56:27,066][30164] Decorrelating experience for 32 frames...
[2023-02-22 20:56:27,342][30152] Decorrelating experience for 0 frames...
[2023-02-22 20:56:27,685][30156] Decorrelating experience for 32 frames...
[2023-02-22 20:56:27,773][30154] Decorrelating experience for 64 frames...
[2023-02-22 20:56:28,230][30152] Decorrelating experience for 32 frames...
[2023-02-22 20:56:28,379][30151] Decorrelating experience for 64 frames...
[2023-02-22 20:56:29,011][30158] Decorrelating experience for 96 frames...
[2023-02-22 20:56:29,079][30164] Decorrelating experience for 64 frames...
[2023-02-22 20:56:29,197][30154] Decorrelating experience for 96 frames...
[2023-02-22 20:56:29,284][01716] Heartbeat connected on RolloutWorker_w4
[2023-02-22 20:56:29,596][01716] Heartbeat connected on RolloutWorker_w3
[2023-02-22 20:56:29,773][01716] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 4005888. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-22 20:56:30,490][30144] Decorrelating experience for 96 frames...
[2023-02-22 20:56:30,786][30151] Decorrelating experience for 96 frames...
[2023-02-22 20:56:31,069][01716] Heartbeat connected on RolloutWorker_w1
[2023-02-22 20:56:31,271][01716] Heartbeat connected on RolloutWorker_w0
[2023-02-22 20:56:32,083][30152] Decorrelating experience for 64 frames...
[2023-02-22 20:56:32,297][30166] Decorrelating experience for 96 frames...
[2023-02-22 20:56:32,431][30164] Decorrelating experience for 96 frames...
[2023-02-22 20:56:32,723][01716] Heartbeat connected on RolloutWorker_w6
[2023-02-22 20:56:33,030][01716] Heartbeat connected on RolloutWorker_w7
[2023-02-22 20:56:34,033][30156] Decorrelating experience for 64 frames...
[2023-02-22 20:56:34,780][01716] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 4005888. Throughput: 0: 51.8. Samples: 518. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-22 20:56:34,783][01716] Avg episode reward: [(0, '2.088')]
[2023-02-22 20:56:36,503][30156] Decorrelating experience for 96 frames...
[2023-02-22 20:56:36,753][01716] Heartbeat connected on RolloutWorker_w5
[2023-02-22 20:56:37,398][30129] Signal inference workers to stop experience collection...
[2023-02-22 20:56:37,441][30143] InferenceWorker_p0-w0: stopping experience collection
[2023-02-22 20:56:37,507][30152] Decorrelating experience for 96 frames...
[2023-02-22 20:56:37,612][01716] Heartbeat connected on RolloutWorker_w2
[2023-02-22 20:56:39,774][01716] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 4005888. Throughput: 0: 170.3. Samples: 2554. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-22 20:56:39,780][01716] Avg episode reward: [(0, '3.052')]
[2023-02-22 20:56:40,128][30129] Signal inference workers to resume experience collection...
[2023-02-22 20:56:40,130][30143] InferenceWorker_p0-w0: resuming experience collection
[2023-02-22 20:56:44,773][01716] Fps is (10 sec: 2459.3, 60 sec: 1228.8, 300 sec: 1228.8). Total num frames: 4030464. Throughput: 0: 340.5. Samples: 6810. Policy #0 lag: (min: 0.0, avg: 1.0, max: 3.0)
[2023-02-22 20:56:44,781][01716] Avg episode reward: [(0, '8.043')]
[2023-02-22 20:56:47,908][30143] Updated weights for policy 0, policy_version 988 (0.0012)
[2023-02-22 20:56:49,773][01716] Fps is (10 sec: 4915.3, 60 sec: 1966.1, 300 sec: 1966.1). Total num frames: 4055040. Throughput: 0: 415.9. Samples: 10398. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:56:49,780][01716] Avg episode reward: [(0, '12.550')]
[2023-02-22 20:56:54,775][01716] Fps is (10 sec: 3685.7, 60 sec: 2047.9, 300 sec: 2047.9). Total num frames: 4067328. Throughput: 0: 524.8. Samples: 15746. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:56:54,782][01716] Avg episode reward: [(0, '15.775')]
[2023-02-22 20:56:59,774][01716] Fps is (10 sec: 2867.1, 60 sec: 2223.5, 300 sec: 2223.5). Total num frames: 4083712. Throughput: 0: 572.9. Samples: 20050. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:56:59,783][01716] Avg episode reward: [(0, '16.874')]
[2023-02-22 20:57:00,602][30143] Updated weights for policy 0, policy_version 998 (0.0022)
[2023-02-22 20:57:04,773][01716] Fps is (10 sec: 3687.1, 60 sec: 2457.6, 300 sec: 2457.6). Total num frames: 4104192. Throughput: 0: 585.7. Samples: 23428. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:57:04,781][01716] Avg episode reward: [(0, '17.312')]
[2023-02-22 20:57:09,017][30143] Updated weights for policy 0, policy_version 1008 (0.0016)
[2023-02-22 20:57:09,773][01716] Fps is (10 sec: 4505.7, 60 sec: 2730.7, 300 sec: 2730.7). Total num frames: 4128768. Throughput: 0: 684.3. Samples: 30792. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:57:09,779][01716] Avg episode reward: [(0, '20.443')]
[2023-02-22 20:57:14,773][01716] Fps is (10 sec: 4096.0, 60 sec: 2785.3, 300 sec: 2785.3). Total num frames: 4145152. Throughput: 0: 795.2. Samples: 35782. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:57:14,783][01716] Avg episode reward: [(0, '20.017')]
[2023-02-22 20:57:19,773][01716] Fps is (10 sec: 3276.8, 60 sec: 2830.0, 300 sec: 2830.0). Total num frames: 4161536. Throughput: 0: 831.9. Samples: 37948. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:57:19,776][01716] Avg episode reward: [(0, '19.271')]
[2023-02-22 20:57:21,500][30143] Updated weights for policy 0, policy_version 1018 (0.0023)
[2023-02-22 20:57:24,773][01716] Fps is (10 sec: 3686.4, 60 sec: 2935.5, 300 sec: 2935.5). Total num frames: 4182016. Throughput: 0: 924.9. Samples: 44174. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:57:24,776][01716] Avg episode reward: [(0, '19.421')]
[2023-02-22 20:57:29,779][01716] Fps is (10 sec: 4503.3, 60 sec: 3344.8, 300 sec: 3087.5). Total num frames: 4206592. Throughput: 0: 990.2. Samples: 51376. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:57:29,782][01716] Avg episode reward: [(0, '19.425')]
[2023-02-22 20:57:30,152][30143] Updated weights for policy 0, policy_version 1028 (0.0013)
[2023-02-22 20:57:34,775][01716] Fps is (10 sec: 4095.5, 60 sec: 3618.5, 300 sec: 3101.2). Total num frames: 4222976. Throughput: 0: 959.9. Samples: 53596. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:57:34,779][01716] Avg episode reward: [(0, '19.348')]
[2023-02-22 20:57:39,777][01716] Fps is (10 sec: 2867.6, 60 sec: 3822.7, 300 sec: 3058.2). Total num frames: 4235264. Throughput: 0: 936.9. Samples: 57908. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:57:39,780][01716] Avg episode reward: [(0, '19.459')]
[2023-02-22 20:57:42,371][30143] Updated weights for policy 0, policy_version 1038 (0.0013)
[2023-02-22 20:57:44,773][01716] Fps is (10 sec: 3686.8, 60 sec: 3822.9, 300 sec: 3174.4). Total num frames: 4259840. Throughput: 0: 991.1. Samples: 64648. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:57:44,776][01716] Avg episode reward: [(0, '20.158')]
[2023-02-22 20:57:49,773][01716] Fps is (10 sec: 4917.0, 60 sec: 3822.9, 300 sec: 3276.8). Total num frames: 4284416. Throughput: 0: 994.4. Samples: 68174. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:57:49,779][01716] Avg episode reward: [(0, '19.573')]
[2023-02-22 20:57:51,856][30143] Updated weights for policy 0, policy_version 1048 (0.0019)
[2023-02-22 20:57:54,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.3, 300 sec: 3276.8). Total num frames: 4300800. Throughput: 0: 949.4. Samples: 73516. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:57:54,782][01716] Avg episode reward: [(0, '19.375')]
[2023-02-22 20:57:59,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3276.8). Total num frames: 4317184. Throughput: 0: 942.9. Samples: 78214. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:57:59,776][01716] Avg episode reward: [(0, '19.182')]
[2023-02-22 20:58:03,139][30143] Updated weights for policy 0, policy_version 1058 (0.0024)
[2023-02-22 20:58:04,774][01716] Fps is (10 sec: 3686.3, 60 sec: 3891.2, 300 sec: 3317.8). Total num frames: 4337664. Throughput: 0: 975.6. Samples: 81850. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 20:58:04,781][01716] Avg episode reward: [(0, '19.684')]
[2023-02-22 20:58:04,792][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001059_4337664.pth...
[2023-02-22 20:58:05,007][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000971_3977216.pth
[2023-02-22 20:58:09,774][01716] Fps is (10 sec: 4505.5, 60 sec: 3891.2, 300 sec: 3393.8). Total num frames: 4362240. Throughput: 0: 993.6. Samples: 88888. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:58:09,776][01716] Avg episode reward: [(0, '20.165')]
[2023-02-22 20:58:13,396][30143] Updated weights for policy 0, policy_version 1068 (0.0012)
[2023-02-22 20:58:14,773][01716] Fps is (10 sec: 4096.1, 60 sec: 3891.2, 300 sec: 3388.5). Total num frames: 4378624. Throughput: 0: 942.2. Samples: 93768. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 20:58:14,778][01716] Avg episode reward: [(0, '20.740')]
[2023-02-22 20:58:19,775][01716] Fps is (10 sec: 2866.7, 60 sec: 3822.8, 300 sec: 3348.0). Total num frames: 4390912. Throughput: 0: 942.9. Samples: 96026. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:58:19,781][01716] Avg episode reward: [(0, '20.443')]
[2023-02-22 20:58:24,026][30143] Updated weights for policy 0, policy_version 1078 (0.0016)
[2023-02-22 20:58:24,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3413.3). Total num frames: 4415488. Throughput: 0: 992.3. Samples: 102560. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:58:24,778][01716] Avg episode reward: [(0, '21.369')]
[2023-02-22 20:58:29,773][01716] Fps is (10 sec: 4916.1, 60 sec: 3891.5, 300 sec: 3473.4). Total num frames: 4440064. Throughput: 0: 999.9. Samples: 109642. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:58:29,780][01716] Avg episode reward: [(0, '21.297')]
[2023-02-22 20:58:34,432][30143] Updated weights for policy 0, policy_version 1088 (0.0012)
[2023-02-22 20:58:34,774][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.3, 300 sec: 3465.8). Total num frames: 4456448. Throughput: 0: 971.5. Samples: 111890. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:58:34,780][01716] Avg episode reward: [(0, '21.099')]
[2023-02-22 20:58:39,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.7, 300 sec: 3458.8). Total num frames: 4472832. Throughput: 0: 951.6. Samples: 116336. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:58:39,776][01716] Avg episode reward: [(0, '21.691')]
[2023-02-22 20:58:44,632][30143] Updated weights for policy 0, policy_version 1098 (0.0016)
[2023-02-22 20:58:44,773][01716] Fps is (10 sec: 4096.1, 60 sec: 3959.5, 300 sec: 3510.9). Total num frames: 4497408. Throughput: 0: 1005.6. Samples: 123466. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:58:44,782][01716] Avg episode reward: [(0, '21.404')]
[2023-02-22 20:58:49,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3531.0). Total num frames: 4517888. Throughput: 0: 1003.5. Samples: 127008. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:58:49,776][01716] Avg episode reward: [(0, '20.927')]
[2023-02-22 20:58:54,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3522.6). Total num frames: 4534272. Throughput: 0: 959.8. Samples: 132078. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 20:58:54,781][01716] Avg episode reward: [(0, '22.404')]
[2023-02-22 20:58:54,797][30129] Saving new best policy, reward=22.404!
[2023-02-22 20:58:55,764][30143] Updated weights for policy 0, policy_version 1108 (0.0022)
[2023-02-22 20:58:59,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3514.6). Total num frames: 4550656. Throughput: 0: 962.0. Samples: 137056. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:58:59,775][01716] Avg episode reward: [(0, '23.799')]
[2023-02-22 20:58:59,782][30129] Saving new best policy, reward=23.799!
[2023-02-22 20:59:04,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3558.4). Total num frames: 4575232. Throughput: 0: 989.0. Samples: 140528. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:59:04,776][01716] Avg episode reward: [(0, '21.984')]
[2023-02-22 20:59:05,486][30143] Updated weights for policy 0, policy_version 1118 (0.0022)
[2023-02-22 20:59:09,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3574.7). Total num frames: 4595712. Throughput: 0: 1002.2. Samples: 147660. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:59:09,777][01716] Avg episode reward: [(0, '21.844')]
[2023-02-22 20:59:14,778][01716] Fps is (10 sec: 3684.7, 60 sec: 3890.9, 300 sec: 3565.8). Total num frames: 4612096. Throughput: 0: 944.9. Samples: 152166. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:59:14,789][01716] Avg episode reward: [(0, '21.964')]
[2023-02-22 20:59:17,114][30143] Updated weights for policy 0, policy_version 1128 (0.0020)
[2023-02-22 20:59:19,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.6, 300 sec: 3557.7). Total num frames: 4628480. Throughput: 0: 947.1. Samples: 154510. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 20:59:19,776][01716] Avg episode reward: [(0, '20.456')]
[2023-02-22 20:59:24,773][01716] Fps is (10 sec: 4097.9, 60 sec: 3959.5, 300 sec: 3595.4). Total num frames: 4653056. Throughput: 0: 1002.0. Samples: 161428. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:59:24,776][01716] Avg episode reward: [(0, '20.783')]
[2023-02-22 20:59:26,149][30143] Updated weights for policy 0, policy_version 1138 (0.0013)
[2023-02-22 20:59:29,775][01716] Fps is (10 sec: 4505.0, 60 sec: 3891.1, 300 sec: 3608.9). Total num frames: 4673536. Throughput: 0: 988.7. Samples: 167958. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:59:29,777][01716] Avg episode reward: [(0, '22.849')]
[2023-02-22 20:59:34,775][01716] Fps is (10 sec: 3686.0, 60 sec: 3891.1, 300 sec: 3600.1). Total num frames: 4689920. Throughput: 0: 960.2. Samples: 170216. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:59:34,779][01716] Avg episode reward: [(0, '23.730')]
[2023-02-22 20:59:38,286][30143] Updated weights for policy 0, policy_version 1148 (0.0018)
[2023-02-22 20:59:39,775][01716] Fps is (10 sec: 3276.6, 60 sec: 3891.1, 300 sec: 3591.8). Total num frames: 4706304. Throughput: 0: 952.4. Samples: 174940. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 20:59:39,783][01716] Avg episode reward: [(0, '24.309')]
[2023-02-22 20:59:39,789][30129] Saving new best policy, reward=24.309!
[2023-02-22 20:59:44,773][01716] Fps is (10 sec: 4096.5, 60 sec: 3891.2, 300 sec: 3625.0). Total num frames: 4730880. Throughput: 0: 996.7. Samples: 181908. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 20:59:44,776][01716] Avg episode reward: [(0, '24.812')]
[2023-02-22 20:59:44,794][30129] Saving new best policy, reward=24.812!
[2023-02-22 20:59:47,277][30143] Updated weights for policy 0, policy_version 1158 (0.0012)
[2023-02-22 20:59:49,773][01716] Fps is (10 sec: 4506.5, 60 sec: 3891.2, 300 sec: 3636.4). Total num frames: 4751360. Throughput: 0: 997.3. Samples: 185408. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:59:49,776][01716] Avg episode reward: [(0, '26.716')]
[2023-02-22 20:59:49,787][30129] Saving new best policy, reward=26.716!
[2023-02-22 20:59:54,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3608.4). Total num frames: 4763648. Throughput: 0: 939.5. Samples: 189938. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 20:59:54,781][01716] Avg episode reward: [(0, '25.633')]
[2023-02-22 20:59:59,424][30143] Updated weights for policy 0, policy_version 1168 (0.0039)
[2023-02-22 20:59:59,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3619.7). Total num frames: 4784128. Throughput: 0: 960.0. Samples: 195362. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 20:59:59,781][01716] Avg episode reward: [(0, '24.169')]
[2023-02-22 21:00:04,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3649.2). Total num frames: 4808704. Throughput: 0: 988.7. Samples: 199000. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:00:04,777][01716] Avg episode reward: [(0, '23.167')]
[2023-02-22 21:00:04,786][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001174_4808704.pth...
[2023-02-22 21:00:04,945][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth
[2023-02-22 21:00:08,357][30143] Updated weights for policy 0, policy_version 1178 (0.0019)
[2023-02-22 21:00:09,774][01716] Fps is (10 sec: 4505.5, 60 sec: 3891.2, 300 sec: 3659.1). Total num frames: 4829184. Throughput: 0: 981.9. Samples: 205614. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:00:09,780][01716] Avg episode reward: [(0, '21.795')]
[2023-02-22 21:00:14,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3823.2, 300 sec: 3633.0). Total num frames: 4841472. Throughput: 0: 936.4. Samples: 210096. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:00:14,778][01716] Avg episode reward: [(0, '20.608')]
[2023-02-22 21:00:19,773][01716] Fps is (10 sec: 3276.9, 60 sec: 3891.2, 300 sec: 3642.8). Total num frames: 4861952. Throughput: 0: 937.3. Samples: 212394. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:00:19,781][01716] Avg episode reward: [(0, '19.318')]
[2023-02-22 21:00:20,320][30143] Updated weights for policy 0, policy_version 1188 (0.0014)
[2023-02-22 21:00:24,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3669.3). Total num frames: 4886528. Throughput: 0: 989.7. Samples: 219476. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:00:24,781][01716] Avg episode reward: [(0, '19.289')]
[2023-02-22 21:00:29,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3823.0, 300 sec: 3661.3). Total num frames: 4902912. Throughput: 0: 970.6. Samples: 225586. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:00:29,776][01716] Avg episode reward: [(0, '20.252')]
[2023-02-22 21:00:30,026][30143] Updated weights for policy 0, policy_version 1198 (0.0012)
[2023-02-22 21:00:34,781][01716] Fps is (10 sec: 3274.2, 60 sec: 3822.5, 300 sec: 3653.5). Total num frames: 4919296. Throughput: 0: 941.7. Samples: 227790. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:00:34,784][01716] Avg episode reward: [(0, '20.185')]
[2023-02-22 21:00:39,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.3, 300 sec: 3662.3). Total num frames: 4939776. Throughput: 0: 950.8. Samples: 232722. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:00:39,776][01716] Avg episode reward: [(0, '20.462')]
[2023-02-22 21:00:41,472][30143] Updated weights for policy 0, policy_version 1208 (0.0025)
[2023-02-22 21:00:44,773][01716] Fps is (10 sec: 4099.2, 60 sec: 3822.9, 300 sec: 3670.6). Total num frames: 4960256. Throughput: 0: 986.2. Samples: 239740. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:00:44,776][01716] Avg episode reward: [(0, '23.406')]
[2023-02-22 21:00:49,777][01716] Fps is (10 sec: 4094.7, 60 sec: 3822.7, 300 sec: 3678.6). Total num frames: 4980736. Throughput: 0: 980.6. Samples: 243132. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:00:49,786][01716] Avg episode reward: [(0, '22.908')]
[2023-02-22 21:00:51,971][30143] Updated weights for policy 0, policy_version 1218 (0.0020)
[2023-02-22 21:00:54,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3671.2). Total num frames: 4997120. Throughput: 0: 933.4. Samples: 247618. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:00:54,780][01716] Avg episode reward: [(0, '24.733')]
[2023-02-22 21:00:59,773][01716] Fps is (10 sec: 3277.8, 60 sec: 3822.9, 300 sec: 3664.1). Total num frames: 5013504. Throughput: 0: 960.8. Samples: 253332. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:00:59,786][01716] Avg episode reward: [(0, '24.953')]
[2023-02-22 21:01:02,445][30143] Updated weights for policy 0, policy_version 1228 (0.0016)
[2023-02-22 21:01:04,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3686.4). Total num frames: 5038080. Throughput: 0: 987.1. Samples: 256812. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:01:04,776][01716] Avg episode reward: [(0, '25.336')]
[2023-02-22 21:01:09,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3822.9, 300 sec: 3693.6). Total num frames: 5058560. Throughput: 0: 975.3. Samples: 263364. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:01:09,780][01716] Avg episode reward: [(0, '24.191')]
[2023-02-22 21:01:13,110][30143] Updated weights for policy 0, policy_version 1238 (0.0014)
[2023-02-22 21:01:14,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3686.4). Total num frames: 5074944. Throughput: 0: 939.8. Samples: 267876. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 21:01:14,776][01716] Avg episode reward: [(0, '23.930')]
[2023-02-22 21:01:19,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3693.3). Total num frames: 5095424. Throughput: 0: 948.9. Samples: 270484. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:01:19,779][01716] Avg episode reward: [(0, '23.857')]
[2023-02-22 21:01:23,300][30143] Updated weights for policy 0, policy_version 1248 (0.0029)
[2023-02-22 21:01:24,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3762.8). Total num frames: 5115904. Throughput: 0: 996.4. Samples: 277562. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:01:24,779][01716] Avg episode reward: [(0, '23.644')]
[2023-02-22 21:01:29,775][01716] Fps is (10 sec: 4095.4, 60 sec: 3891.1, 300 sec: 3832.3). Total num frames: 5136384. Throughput: 0: 974.7. Samples: 283602. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:01:29,779][01716] Avg episode reward: [(0, '23.234')]
[2023-02-22 21:01:34,294][30143] Updated weights for policy 0, policy_version 1258 (0.0021)
[2023-02-22 21:01:34,774][01716] Fps is (10 sec: 3686.2, 60 sec: 3891.7, 300 sec: 3887.7). Total num frames: 5152768. Throughput: 0: 948.6. Samples: 285816. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:01:34,784][01716] Avg episode reward: [(0, '22.997')]
[2023-02-22 21:01:39,774][01716] Fps is (10 sec: 3686.7, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5173248. Throughput: 0: 967.3. Samples: 291148. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:01:39,777][01716] Avg episode reward: [(0, '24.026')]
[2023-02-22 21:01:44,190][30143] Updated weights for policy 0, policy_version 1268 (0.0012)
[2023-02-22 21:01:44,773][01716] Fps is (10 sec: 4096.2, 60 sec: 3891.2, 300 sec: 3860.0). Total num frames: 5193728. Throughput: 0: 997.4. Samples: 298214. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:01:44,776][01716] Avg episode reward: [(0, '23.926')]
[2023-02-22 21:01:49,773][01716] Fps is (10 sec: 4096.3, 60 sec: 3891.4, 300 sec: 3887.8). Total num frames: 5214208. Throughput: 0: 991.5. Samples: 301430. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:01:49,780][01716] Avg episode reward: [(0, '23.300')]
[2023-02-22 21:01:54,774][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5230592. Throughput: 0: 945.5. Samples: 305912. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:01:54,780][01716] Avg episode reward: [(0, '22.752')]
[2023-02-22 21:01:55,910][30143] Updated weights for policy 0, policy_version 1278 (0.0024)
[2023-02-22 21:01:59,774][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5246976. Throughput: 0: 974.2. Samples: 311716. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:01:59,779][01716] Avg episode reward: [(0, '23.214')]
[2023-02-22 21:02:04,773][01716] Fps is (10 sec: 4096.1, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5271552. Throughput: 0: 994.8. Samples: 315252. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 21:02:04,778][01716] Avg episode reward: [(0, '22.244')]
[2023-02-22 21:02:04,807][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001288_5275648.pth...
[2023-02-22 21:02:04,818][30143] Updated weights for policy 0, policy_version 1288 (0.0014)
[2023-02-22 21:02:04,960][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001059_4337664.pth
[2023-02-22 21:02:09,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5292032. Throughput: 0: 977.5. Samples: 321550. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:02:09,778][01716] Avg episode reward: [(0, '21.831')]
[2023-02-22 21:02:14,774][01716] Fps is (10 sec: 3276.7, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 5304320. Throughput: 0: 940.9. Samples: 325942. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 21:02:14,779][01716] Avg episode reward: [(0, '22.511')]
[2023-02-22 21:02:17,299][30143] Updated weights for policy 0, policy_version 1298 (0.0018)
[2023-02-22 21:02:19,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 5324800. Throughput: 0: 950.7. Samples: 328596. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:02:19,779][01716] Avg episode reward: [(0, '24.035')]
[2023-02-22 21:02:24,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3873.9). Total num frames: 5349376. Throughput: 0: 992.3. Samples: 335802. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:02:24,776][01716] Avg episode reward: [(0, '23.587')]
[2023-02-22 21:02:25,987][30143] Updated weights for policy 0, policy_version 1308 (0.0014)
[2023-02-22 21:02:29,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.3, 300 sec: 3887.7). Total num frames: 5369856. Throughput: 0: 964.0. Samples: 341592. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:02:29,781][01716] Avg episode reward: [(0, '23.861')]
[2023-02-22 21:02:34,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3823.0, 300 sec: 3887.8). Total num frames: 5382144. Throughput: 0: 942.8. Samples: 343854. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:02:34,780][01716] Avg episode reward: [(0, '25.188')]
[2023-02-22 21:02:38,135][30143] Updated weights for policy 0, policy_version 1318 (0.0022)
[2023-02-22 21:02:39,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3823.0, 300 sec: 3873.8). Total num frames: 5402624. Throughput: 0: 966.7. Samples: 349414. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:02:39,775][01716] Avg episode reward: [(0, '23.601')]
[2023-02-22 21:02:44,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5427200. Throughput: 0: 1000.2. Samples: 356724. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:02:44,776][01716] Avg episode reward: [(0, '22.119')]
[2023-02-22 21:02:46,686][30143] Updated weights for policy 0, policy_version 1328 (0.0016)
[2023-02-22 21:02:49,775][01716] Fps is (10 sec: 4505.1, 60 sec: 3891.1, 300 sec: 3887.7). Total num frames: 5447680. Throughput: 0: 987.3. Samples: 359680. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:02:49,785][01716] Avg episode reward: [(0, '22.113')]
[2023-02-22 21:02:54,774][01716] Fps is (10 sec: 3276.7, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 5459968. Throughput: 0: 944.1. Samples: 364034. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:02:54,780][01716] Avg episode reward: [(0, '21.871')]
[2023-02-22 21:02:58,870][30143] Updated weights for policy 0, policy_version 1338 (0.0021)
[2023-02-22 21:02:59,773][01716] Fps is (10 sec: 3686.8, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 5484544. Throughput: 0: 983.4. Samples: 370196. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:02:59,775][01716] Avg episode reward: [(0, '20.104')]
[2023-02-22 21:03:04,773][01716] Fps is (10 sec: 4915.4, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 5509120. Throughput: 0: 1006.2. Samples: 373874. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:03:04,775][01716] Avg episode reward: [(0, '20.134')]
[2023-02-22 21:03:07,825][30143] Updated weights for policy 0, policy_version 1348 (0.0014)
[2023-02-22 21:03:09,774][01716] Fps is (10 sec: 4095.7, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5525504. Throughput: 0: 981.4. Samples: 379966. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:03:09,781][01716] Avg episode reward: [(0, '20.444')]
[2023-02-22 21:03:14,774][01716] Fps is (10 sec: 2867.0, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5537792. Throughput: 0: 950.8. Samples: 384380. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:03:14,781][01716] Avg episode reward: [(0, '20.342')]
[2023-02-22 21:03:19,519][30143] Updated weights for policy 0, policy_version 1358 (0.0018)
[2023-02-22 21:03:19,774][01716] Fps is (10 sec: 3686.6, 60 sec: 3959.4, 300 sec: 3887.7). Total num frames: 5562368. Throughput: 0: 966.9. Samples: 387366. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:03:19,776][01716] Avg episode reward: [(0, '19.341')]
[2023-02-22 21:03:24,773][01716] Fps is (10 sec: 4915.6, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 5586944. Throughput: 0: 1003.0. Samples: 394548. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:03:24,775][01716] Avg episode reward: [(0, '20.463')]
[2023-02-22 21:03:29,519][30143] Updated weights for policy 0, policy_version 1368 (0.0011)
[2023-02-22 21:03:29,773][01716] Fps is (10 sec: 4096.1, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5603328. Throughput: 0: 962.0. Samples: 400014. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:03:29,781][01716] Avg episode reward: [(0, '20.755')]
[2023-02-22 21:03:34,774][01716] Fps is (10 sec: 2867.1, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5615616. Throughput: 0: 947.8. Samples: 402330. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:03:34,777][01716] Avg episode reward: [(0, '19.936')]
[2023-02-22 21:03:39,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3873.8). Total num frames: 5640192. Throughput: 0: 979.6. Samples: 408116. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:03:39,779][01716] Avg episode reward: [(0, '20.130')]
[2023-02-22 21:03:40,430][30143] Updated weights for policy 0, policy_version 1378 (0.0017)
[2023-02-22 21:03:44,773][01716] Fps is (10 sec: 4505.8, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5660672. Throughput: 0: 1000.0. Samples: 415198. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:03:44,775][01716] Avg episode reward: [(0, '21.034')]
[2023-02-22 21:03:49,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.3, 300 sec: 3887.7). Total num frames: 5681152. Throughput: 0: 979.6. Samples: 417958. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:03:49,781][01716] Avg episode reward: [(0, '21.043')]
[2023-02-22 21:03:50,830][30143] Updated weights for policy 0, policy_version 1388 (0.0020)
[2023-02-22 21:03:54,775][01716] Fps is (10 sec: 3276.2, 60 sec: 3891.1, 300 sec: 3873.8). Total num frames: 5693440. Throughput: 0: 943.3. Samples: 422414. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:03:54,778][01716] Avg episode reward: [(0, '21.476')]
[2023-02-22 21:03:59,773][01716] Fps is (10 sec: 3686.3, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5718016. Throughput: 0: 983.7. Samples: 428644. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:03:59,779][01716] Avg episode reward: [(0, '21.118')]
[2023-02-22 21:04:01,324][30143] Updated weights for policy 0, policy_version 1398 (0.0018)
[2023-02-22 21:04:04,773][01716] Fps is (10 sec: 4916.1, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5742592. Throughput: 0: 997.0. Samples: 432232. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:04:04,775][01716] Avg episode reward: [(0, '21.876')]
[2023-02-22 21:04:04,789][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001402_5742592.pth...
[2023-02-22 21:04:04,949][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001174_4808704.pth
[2023-02-22 21:04:09,773][01716] Fps is (10 sec: 4096.1, 60 sec: 3891.3, 300 sec: 3887.8). Total num frames: 5758976. Throughput: 0: 965.9. Samples: 438012. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:04:09,782][01716] Avg episode reward: [(0, '22.801')]
[2023-02-22 21:04:12,669][30143] Updated weights for policy 0, policy_version 1408 (0.0012)
[2023-02-22 21:04:14,773][01716] Fps is (10 sec: 2867.2, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5771264. Throughput: 0: 943.2. Samples: 442460. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:04:14,775][01716] Avg episode reward: [(0, '23.716')]
[2023-02-22 21:04:19,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5795840. Throughput: 0: 963.2. Samples: 445674. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:04:19,776][01716] Avg episode reward: [(0, '25.777')]
[2023-02-22 21:04:22,230][30143] Updated weights for policy 0, policy_version 1418 (0.0018)
[2023-02-22 21:04:24,773][01716] Fps is (10 sec: 4915.2, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5820416. Throughput: 0: 997.8. Samples: 453018. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:04:24,776][01716] Avg episode reward: [(0, '27.561')]
[2023-02-22 21:04:24,784][30129] Saving new best policy, reward=27.561!
[2023-02-22 21:04:29,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5836800. Throughput: 0: 955.5. Samples: 458196. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:04:29,779][01716] Avg episode reward: [(0, '28.935')]
[2023-02-22 21:04:29,781][30129] Saving new best policy, reward=28.935!
[2023-02-22 21:04:34,093][30143] Updated weights for policy 0, policy_version 1428 (0.0028)
[2023-02-22 21:04:34,773][01716] Fps is (10 sec: 2867.2, 60 sec: 3891.2, 300 sec: 3873.9). Total num frames: 5849088. Throughput: 0: 943.1. Samples: 460398. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:04:34,778][01716] Avg episode reward: [(0, '28.694')]
[2023-02-22 21:04:39,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5873664. Throughput: 0: 979.0. Samples: 466466. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:04:39,776][01716] Avg episode reward: [(0, '28.845')]
[2023-02-22 21:04:42,969][30143] Updated weights for policy 0, policy_version 1438 (0.0013)
[2023-02-22 21:04:44,773][01716] Fps is (10 sec: 4915.2, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 5898240. Throughput: 0: 1002.0. Samples: 473732. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:04:44,776][01716] Avg episode reward: [(0, '25.736')]
[2023-02-22 21:04:49,775][01716] Fps is (10 sec: 3685.7, 60 sec: 3822.8, 300 sec: 3887.7). Total num frames: 5910528. Throughput: 0: 977.5. Samples: 476222. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:04:49,784][01716] Avg episode reward: [(0, '23.470')]
[2023-02-22 21:04:54,774][01716] Fps is (10 sec: 2867.1, 60 sec: 3891.3, 300 sec: 3873.8). Total num frames: 5926912. Throughput: 0: 950.9. Samples: 480802. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 21:04:54,782][01716] Avg episode reward: [(0, '22.173')]
[2023-02-22 21:04:55,192][30143] Updated weights for policy 0, policy_version 1448 (0.0015)
[2023-02-22 21:04:59,773][01716] Fps is (10 sec: 4096.8, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 5951488. Throughput: 0: 995.2. Samples: 487246. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:04:59,776][01716] Avg episode reward: [(0, '22.571')]
[2023-02-22 21:05:03,700][30143] Updated weights for policy 0, policy_version 1458 (0.0014)
[2023-02-22 21:05:04,774][01716] Fps is (10 sec: 4915.2, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 5976064. Throughput: 0: 1006.3. Samples: 490960. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:05:04,777][01716] Avg episode reward: [(0, '21.632')]
[2023-02-22 21:05:09,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 5992448. Throughput: 0: 970.5. Samples: 496690. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:05:09,778][01716] Avg episode reward: [(0, '21.409')]
[2023-02-22 21:05:14,774][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 6008832. Throughput: 0: 954.8. Samples: 501162. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:05:14,776][01716] Avg episode reward: [(0, '22.795')]
[2023-02-22 21:05:15,669][30143] Updated weights for policy 0, policy_version 1468 (0.0021)
[2023-02-22 21:05:19,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 6029312. Throughput: 0: 982.6. Samples: 504616. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:05:19,780][01716] Avg episode reward: [(0, '23.816')]
[2023-02-22 21:05:24,144][30143] Updated weights for policy 0, policy_version 1478 (0.0018)
[2023-02-22 21:05:24,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6053888. Throughput: 0: 1006.9. Samples: 511776. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:05:24,781][01716] Avg episode reward: [(0, '24.853')]
[2023-02-22 21:05:29,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.7). Total num frames: 6070272. Throughput: 0: 954.7. Samples: 516692. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:05:29,780][01716] Avg episode reward: [(0, '24.306')]
[2023-02-22 21:05:34,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 6086656. Throughput: 0: 948.5. Samples: 518902. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:05:34,782][01716] Avg episode reward: [(0, '25.231')]
[2023-02-22 21:05:36,487][30143] Updated weights for policy 0, policy_version 1488 (0.0038)
[2023-02-22 21:05:39,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6107136. Throughput: 0: 989.2. Samples: 525316. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:05:39,775][01716] Avg episode reward: [(0, '24.952')]
[2023-02-22 21:05:44,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.7). Total num frames: 6131712. Throughput: 0: 1001.2. Samples: 532300. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:05:44,776][01716] Avg episode reward: [(0, '25.356')]
[2023-02-22 21:05:45,823][30143] Updated weights for policy 0, policy_version 1498 (0.0013)
[2023-02-22 21:05:49,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.3, 300 sec: 3887.7). Total num frames: 6144000. Throughput: 0: 966.1. Samples: 534436. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:05:49,781][01716] Avg episode reward: [(0, '25.439')]
[2023-02-22 21:05:54,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 6164480. Throughput: 0: 940.9. Samples: 539030. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:05:54,779][01716] Avg episode reward: [(0, '25.420')]
[2023-02-22 21:05:57,350][30143] Updated weights for policy 0, policy_version 1508 (0.0035)
[2023-02-22 21:05:59,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6184960. Throughput: 0: 998.6. Samples: 546100. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:05:59,776][01716] Avg episode reward: [(0, '25.266')]
[2023-02-22 21:06:04,773][01716] Fps is (10 sec: 4505.5, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6209536. Throughput: 0: 1002.1. Samples: 549712. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:06:04,776][01716] Avg episode reward: [(0, '24.208')]
[2023-02-22 21:06:04,798][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001516_6209536.pth...
[2023-02-22 21:06:04,993][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001288_5275648.pth
[2023-02-22 21:06:07,054][30143] Updated weights for policy 0, policy_version 1518 (0.0016)
[2023-02-22 21:06:09,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6225920. Throughput: 0: 957.0. Samples: 554842. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:06:09,776][01716] Avg episode reward: [(0, '24.906')]
[2023-02-22 21:06:14,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6242304. Throughput: 0: 958.0. Samples: 559802. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:06:14,781][01716] Avg episode reward: [(0, '24.595')]
[2023-02-22 21:06:17,974][30143] Updated weights for policy 0, policy_version 1528 (0.0012)
[2023-02-22 21:06:19,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 6266880. Throughput: 0: 989.3. Samples: 563422. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:06:19,776][01716] Avg episode reward: [(0, '23.488')]
[2023-02-22 21:06:24,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6287360. Throughput: 0: 1008.0. Samples: 570678. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:06:24,779][01716] Avg episode reward: [(0, '25.519')]
[2023-02-22 21:06:28,518][30143] Updated weights for policy 0, policy_version 1538 (0.0011)
[2023-02-22 21:06:29,776][01716] Fps is (10 sec: 3275.9, 60 sec: 3822.8, 300 sec: 3887.7). Total num frames: 6299648. Throughput: 0: 948.8. Samples: 574998. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:06:29,782][01716] Avg episode reward: [(0, '24.349')]
[2023-02-22 21:06:34,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6320128. Throughput: 0: 949.9. Samples: 577182. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:06:34,776][01716] Avg episode reward: [(0, '25.185')]
[2023-02-22 21:06:38,934][30143] Updated weights for policy 0, policy_version 1548 (0.0013)
[2023-02-22 21:06:39,773][01716] Fps is (10 sec: 4097.2, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6340608. Throughput: 0: 995.7. Samples: 583836. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:06:39,776][01716] Avg episode reward: [(0, '24.334')]
[2023-02-22 21:06:44,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6365184. Throughput: 0: 990.6. Samples: 590676. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:06:44,781][01716] Avg episode reward: [(0, '24.854')]
[2023-02-22 21:06:49,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6377472. Throughput: 0: 957.7. Samples: 592810. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:06:49,781][01716] Avg episode reward: [(0, '25.561')]
[2023-02-22 21:06:49,879][30143] Updated weights for policy 0, policy_version 1558 (0.0026)
[2023-02-22 21:06:54,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6397952. Throughput: 0: 943.4. Samples: 597296. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:06:54,782][01716] Avg episode reward: [(0, '22.374')]
[2023-02-22 21:06:59,774][01716] Fps is (10 sec: 4095.9, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6418432. Throughput: 0: 991.4. Samples: 604416. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:06:59,778][01716] Avg episode reward: [(0, '22.570')]
[2023-02-22 21:06:59,849][30143] Updated weights for policy 0, policy_version 1568 (0.0020)
[2023-02-22 21:07:04,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6443008. Throughput: 0: 986.1. Samples: 607798. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:07:04,780][01716] Avg episode reward: [(0, '23.061')]
[2023-02-22 21:07:09,773][01716] Fps is (10 sec: 3686.5, 60 sec: 3822.9, 300 sec: 3901.6). Total num frames: 6455296. Throughput: 0: 936.1. Samples: 612802. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:07:09,779][01716] Avg episode reward: [(0, '22.046')]
[2023-02-22 21:07:11,433][30143] Updated weights for policy 0, policy_version 1578 (0.0025)
[2023-02-22 21:07:14,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6475776. Throughput: 0: 952.9. Samples: 617874. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:07:14,784][01716] Avg episode reward: [(0, '22.633')]
[2023-02-22 21:07:19,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 6496256. Throughput: 0: 983.4. Samples: 621436. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:07:19,776][01716] Avg episode reward: [(0, '23.384')]
[2023-02-22 21:07:20,918][30143] Updated weights for policy 0, policy_version 1588 (0.0013)
[2023-02-22 21:07:24,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 6516736. Throughput: 0: 989.7. Samples: 628374. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:07:24,777][01716] Avg episode reward: [(0, '23.174')]
[2023-02-22 21:07:29,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.4, 300 sec: 3901.6). Total num frames: 6533120. Throughput: 0: 937.4. Samples: 632858. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:07:29,781][01716] Avg episode reward: [(0, '24.140')]
[2023-02-22 21:07:32,929][30143] Updated weights for policy 0, policy_version 1598 (0.0016)
[2023-02-22 21:07:34,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 6549504. Throughput: 0: 941.5. Samples: 635176. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:07:34,781][01716] Avg episode reward: [(0, '24.129')]
[2023-02-22 21:07:39,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6574080. Throughput: 0: 994.5. Samples: 642050. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:07:39,776][01716] Avg episode reward: [(0, '24.751')]
[2023-02-22 21:07:41,696][30143] Updated weights for policy 0, policy_version 1608 (0.0020)
[2023-02-22 21:07:44,779][01716] Fps is (10 sec: 4503.0, 60 sec: 3822.6, 300 sec: 3887.7). Total num frames: 6594560. Throughput: 0: 982.6. Samples: 648640. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:07:44,782][01716] Avg episode reward: [(0, '23.269')]
[2023-02-22 21:07:49,778][01716] Fps is (10 sec: 3684.6, 60 sec: 3890.9, 300 sec: 3901.6). Total num frames: 6610944. Throughput: 0: 955.9. Samples: 650818. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:07:49,783][01716] Avg episode reward: [(0, '23.501')]
[2023-02-22 21:07:54,105][30143] Updated weights for policy 0, policy_version 1618 (0.0040)
[2023-02-22 21:07:54,774][01716] Fps is (10 sec: 3278.6, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 6627328. Throughput: 0: 949.1. Samples: 655512. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:07:54,776][01716] Avg episode reward: [(0, '22.967')]
[2023-02-22 21:07:59,773][01716] Fps is (10 sec: 4098.0, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 6651904. Throughput: 0: 998.5. Samples: 662806. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:07:59,776][01716] Avg episode reward: [(0, '23.952')]
[2023-02-22 21:08:02,391][30143] Updated weights for policy 0, policy_version 1628 (0.0017)
[2023-02-22 21:08:04,773][01716] Fps is (10 sec: 4915.3, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6676480. Throughput: 0: 999.3. Samples: 666404. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:08:04,777][01716] Avg episode reward: [(0, '23.326')]
[2023-02-22 21:08:04,790][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001630_6676480.pth...
[2023-02-22 21:08:05,035][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001402_5742592.pth
[2023-02-22 21:08:09,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6688768. Throughput: 0: 952.2. Samples: 671222. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:08:09,778][01716] Avg episode reward: [(0, '23.675')]
[2023-02-22 21:08:14,608][30143] Updated weights for policy 0, policy_version 1638 (0.0025)
[2023-02-22 21:08:14,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6709248. Throughput: 0: 967.3. Samples: 676388. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:08:14,775][01716] Avg episode reward: [(0, '22.783')]
[2023-02-22 21:08:19,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 6733824. Throughput: 0: 997.6. Samples: 680068. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:08:19,776][01716] Avg episode reward: [(0, '22.386')]
[2023-02-22 21:08:23,170][30143] Updated weights for policy 0, policy_version 1648 (0.0012)
[2023-02-22 21:08:24,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 6754304. Throughput: 0: 997.6. Samples: 686940. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:08:24,775][01716] Avg episode reward: [(0, '21.892')]
[2023-02-22 21:08:29,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6766592. Throughput: 0: 952.2. Samples: 691484. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:08:29,781][01716] Avg episode reward: [(0, '23.216')]
[2023-02-22 21:08:34,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 6787072. Throughput: 0: 954.6. Samples: 693770. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:08:34,776][01716] Avg episode reward: [(0, '22.836')]
[2023-02-22 21:08:35,418][30143] Updated weights for policy 0, policy_version 1658 (0.0019)
[2023-02-22 21:08:39,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 6811648. Throughput: 0: 1007.3. Samples: 700842. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:08:39,781][01716] Avg episode reward: [(0, '23.507')]
[2023-02-22 21:08:44,322][30143] Updated weights for policy 0, policy_version 1668 (0.0019)
[2023-02-22 21:08:44,781][01716] Fps is (10 sec: 4502.0, 60 sec: 3959.3, 300 sec: 3901.5). Total num frames: 6832128. Throughput: 0: 988.5. Samples: 707296. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:08:44,787][01716] Avg episode reward: [(0, '24.849')]
[2023-02-22 21:08:49,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.5, 300 sec: 3901.6). Total num frames: 6844416. Throughput: 0: 960.1. Samples: 709610. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:08:49,780][01716] Avg episode reward: [(0, '24.862')]
[2023-02-22 21:08:54,773][01716] Fps is (10 sec: 3279.4, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 6864896. Throughput: 0: 960.1. Samples: 714426. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:08:54,781][01716] Avg episode reward: [(0, '23.618')]
[2023-02-22 21:08:56,365][30143] Updated weights for policy 0, policy_version 1678 (0.0046)
[2023-02-22 21:08:59,775][01716] Fps is (10 sec: 4095.4, 60 sec: 3891.1, 300 sec: 3873.8). Total num frames: 6885376. Throughput: 0: 1004.1. Samples: 721574. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:08:59,777][01716] Avg episode reward: [(0, '25.054')]
[2023-02-22 21:09:04,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6909952. Throughput: 0: 1000.8. Samples: 725106. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:09:04,779][01716] Avg episode reward: [(0, '25.677')]
[2023-02-22 21:09:05,747][30143] Updated weights for policy 0, policy_version 1688 (0.0011)
[2023-02-22 21:09:09,779][01716] Fps is (10 sec: 3684.8, 60 sec: 3890.8, 300 sec: 3901.5). Total num frames: 6922240. Throughput: 0: 953.6. Samples: 729858. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:09:09,784][01716] Avg episode reward: [(0, '23.738')]
[2023-02-22 21:09:14,774][01716] Fps is (10 sec: 3276.7, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6942720. Throughput: 0: 970.0. Samples: 735132. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:09:14,776][01716] Avg episode reward: [(0, '23.449')]
[2023-02-22 21:09:17,009][30143] Updated weights for policy 0, policy_version 1698 (0.0021)
[2023-02-22 21:09:19,773][01716] Fps is (10 sec: 4508.2, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 6967296. Throughput: 0: 999.9. Samples: 738764. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:09:19,776][01716] Avg episode reward: [(0, '24.748')]
[2023-02-22 21:09:24,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 6987776. Throughput: 0: 990.3. Samples: 745404. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:09:24,783][01716] Avg episode reward: [(0, '23.726')]
[2023-02-22 21:09:27,267][30143] Updated weights for policy 0, policy_version 1708 (0.0017)
[2023-02-22 21:09:29,774][01716] Fps is (10 sec: 3276.5, 60 sec: 3891.1, 300 sec: 3901.6). Total num frames: 7000064. Throughput: 0: 944.2. Samples: 749778. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:09:29,777][01716] Avg episode reward: [(0, '24.040')]
[2023-02-22 21:09:34,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7020544. Throughput: 0: 942.8. Samples: 752034. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:09:34,781][01716] Avg episode reward: [(0, '23.787')]
[2023-02-22 21:09:38,034][30143] Updated weights for policy 0, policy_version 1718 (0.0012)
[2023-02-22 21:09:39,773][01716] Fps is (10 sec: 4096.3, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 7041024. Throughput: 0: 993.2. Samples: 759122. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:09:39,775][01716] Avg episode reward: [(0, '25.691')]
[2023-02-22 21:09:44,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.7, 300 sec: 3915.5). Total num frames: 7065600. Throughput: 0: 973.5. Samples: 765382. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:09:44,780][01716] Avg episode reward: [(0, '24.987')]
[2023-02-22 21:09:48,894][30143] Updated weights for policy 0, policy_version 1728 (0.0038)
[2023-02-22 21:09:49,780][01716] Fps is (10 sec: 3683.9, 60 sec: 3890.8, 300 sec: 3901.5). Total num frames: 7077888. Throughput: 0: 943.5. Samples: 767568. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:09:49,783][01716] Avg episode reward: [(0, '24.949')]
[2023-02-22 21:09:54,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7098368. Throughput: 0: 948.6. Samples: 772540. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:09:54,781][01716] Avg episode reward: [(0, '26.207')]
[2023-02-22 21:09:58,850][30143] Updated weights for policy 0, policy_version 1738 (0.0020)
[2023-02-22 21:09:59,773][01716] Fps is (10 sec: 4508.7, 60 sec: 3959.6, 300 sec: 3887.7). Total num frames: 7122944. Throughput: 0: 992.6. Samples: 779798. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:09:59,776][01716] Avg episode reward: [(0, '26.617')]
[2023-02-22 21:10:04,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 7143424. Throughput: 0: 991.5. Samples: 783380. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:10:04,777][01716] Avg episode reward: [(0, '27.678')]
[2023-02-22 21:10:04,791][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001744_7143424.pth...
[2023-02-22 21:10:04,933][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001516_6209536.pth
[2023-02-22 21:10:09,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.6, 300 sec: 3887.7). Total num frames: 7155712. Throughput: 0: 943.4. Samples: 787858. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:10:09,778][01716] Avg episode reward: [(0, '27.080')]
[2023-02-22 21:10:10,302][30143] Updated weights for policy 0, policy_version 1748 (0.0020)
[2023-02-22 21:10:14,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7176192. Throughput: 0: 969.8. Samples: 793418. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:10:14,776][01716] Avg episode reward: [(0, '26.193')]
[2023-02-22 21:10:19,591][30143] Updated weights for policy 0, policy_version 1758 (0.0015)
[2023-02-22 21:10:19,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7200768. Throughput: 0: 999.8. Samples: 797024. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:10:19,776][01716] Avg episode reward: [(0, '25.591')]
[2023-02-22 21:10:24,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 7221248. Throughput: 0: 992.0. Samples: 803760. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:10:24,777][01716] Avg episode reward: [(0, '25.167')]
[2023-02-22 21:10:29,774][01716] Fps is (10 sec: 3276.6, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7233536. Throughput: 0: 951.9. Samples: 808216. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:10:29,783][01716] Avg episode reward: [(0, '24.805')]
[2023-02-22 21:10:31,298][30143] Updated weights for policy 0, policy_version 1768 (0.0014)
[2023-02-22 21:10:34,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7254016. Throughput: 0: 955.6. Samples: 810564. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:10:34,779][01716] Avg episode reward: [(0, '24.467')]
[2023-02-22 21:10:39,773][01716] Fps is (10 sec: 4505.9, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 7278592. Throughput: 0: 1006.1. Samples: 817816. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:10:39,776][01716] Avg episode reward: [(0, '25.097')]
[2023-02-22 21:10:40,329][30143] Updated weights for policy 0, policy_version 1778 (0.0011)
[2023-02-22 21:10:44,778][01716] Fps is (10 sec: 4503.5, 60 sec: 3890.9, 300 sec: 3915.4). Total num frames: 7299072. Throughput: 0: 981.8. Samples: 823984. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:10:44,791][01716] Avg episode reward: [(0, '25.759')]
[2023-02-22 21:10:49,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.6, 300 sec: 3887.7). Total num frames: 7311360. Throughput: 0: 951.8. Samples: 826210. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:10:49,779][01716] Avg episode reward: [(0, '23.760')]
[2023-02-22 21:10:52,673][30143] Updated weights for policy 0, policy_version 1788 (0.0014)
[2023-02-22 21:10:54,773][01716] Fps is (10 sec: 3278.3, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7331840. Throughput: 0: 964.1. Samples: 831242. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:10:54,782][01716] Avg episode reward: [(0, '22.623')]
[2023-02-22 21:10:59,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7356416. Throughput: 0: 997.7. Samples: 838316. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:10:59,781][01716] Avg episode reward: [(0, '21.446')]
[2023-02-22 21:11:01,322][30143] Updated weights for policy 0, policy_version 1798 (0.0011)
[2023-02-22 21:11:04,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 7376896. Throughput: 0: 991.8. Samples: 841656. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:04,778][01716] Avg episode reward: [(0, '21.258')]
[2023-02-22 21:11:09,776][01716] Fps is (10 sec: 3275.9, 60 sec: 3891.0, 300 sec: 3887.7). Total num frames: 7389184. Throughput: 0: 942.5. Samples: 846176. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:11:09,779][01716] Avg episode reward: [(0, '21.729')]
[2023-02-22 21:11:13,386][30143] Updated weights for policy 0, policy_version 1808 (0.0012)
[2023-02-22 21:11:14,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 7409664. Throughput: 0: 972.6. Samples: 851982. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:11:14,781][01716] Avg episode reward: [(0, '21.571')]
[2023-02-22 21:11:19,773][01716] Fps is (10 sec: 4506.9, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7434240. Throughput: 0: 1000.3. Samples: 855576. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:19,780][01716] Avg episode reward: [(0, '22.713')]
[2023-02-22 21:11:22,223][30143] Updated weights for policy 0, policy_version 1818 (0.0013)
[2023-02-22 21:11:24,781][01716] Fps is (10 sec: 4092.8, 60 sec: 3822.4, 300 sec: 3901.5). Total num frames: 7450624. Throughput: 0: 976.5. Samples: 861764. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:24,784][01716] Avg episode reward: [(0, '23.307')]
[2023-02-22 21:11:29,774][01716] Fps is (10 sec: 3276.7, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7467008. Throughput: 0: 938.4. Samples: 866206. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:11:29,779][01716] Avg episode reward: [(0, '24.166')]
[2023-02-22 21:11:34,450][30143] Updated weights for policy 0, policy_version 1828 (0.0013)
[2023-02-22 21:11:34,773][01716] Fps is (10 sec: 3689.3, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7487488. Throughput: 0: 948.8. Samples: 868904. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:11:34,782][01716] Avg episode reward: [(0, '24.424')]
[2023-02-22 21:11:39,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7512064. Throughput: 0: 995.9. Samples: 876058. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:39,781][01716] Avg episode reward: [(0, '23.502')]
[2023-02-22 21:11:43,845][30143] Updated weights for policy 0, policy_version 1838 (0.0012)
[2023-02-22 21:11:44,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3823.2, 300 sec: 3901.6). Total num frames: 7528448. Throughput: 0: 967.1. Samples: 881836. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:44,779][01716] Avg episode reward: [(0, '22.885')]
[2023-02-22 21:11:49,774][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7544832. Throughput: 0: 943.0. Samples: 884092. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:49,777][01716] Avg episode reward: [(0, '23.464')]
[2023-02-22 21:11:54,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7565312. Throughput: 0: 963.2. Samples: 889516. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:54,776][01716] Avg episode reward: [(0, '24.197')]
[2023-02-22 21:11:55,344][30143] Updated weights for policy 0, policy_version 1848 (0.0047)
[2023-02-22 21:11:59,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7589888. Throughput: 0: 993.3. Samples: 896680. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:11:59,776][01716] Avg episode reward: [(0, '24.309')]
[2023-02-22 21:12:04,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3822.9, 300 sec: 3901.6). Total num frames: 7606272. Throughput: 0: 979.2. Samples: 899640. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:12:04,776][01716] Avg episode reward: [(0, '24.012')]
[2023-02-22 21:12:04,795][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001857_7606272.pth...
[2023-02-22 21:12:04,988][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001630_6676480.pth
[2023-02-22 21:12:05,351][30143] Updated weights for policy 0, policy_version 1858 (0.0015)
[2023-02-22 21:12:09,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.4, 300 sec: 3887.7). Total num frames: 7622656. Throughput: 0: 939.4. Samples: 904028. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:12:09,776][01716] Avg episode reward: [(0, '24.010')]
[2023-02-22 21:12:14,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7643136. Throughput: 0: 977.6. Samples: 910196. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:12:14,778][01716] Avg episode reward: [(0, '25.358')]
[2023-02-22 21:12:15,933][30143] Updated weights for policy 0, policy_version 1868 (0.0034)
[2023-02-22 21:12:19,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 7667712. Throughput: 0: 997.1. Samples: 913774. Policy #0 lag: (min: 0.0, avg: 0.3, max: 2.0)
[2023-02-22 21:12:19,776][01716] Avg episode reward: [(0, '24.114')]
[2023-02-22 21:12:24,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.7, 300 sec: 3901.6). Total num frames: 7684096. Throughput: 0: 975.5. Samples: 919954. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:12:24,780][01716] Avg episode reward: [(0, '23.219')]
[2023-02-22 21:12:26,256][30143] Updated weights for policy 0, policy_version 1878 (0.0013)
[2023-02-22 21:12:29,775][01716] Fps is (10 sec: 3276.4, 60 sec: 3891.1, 300 sec: 3901.6). Total num frames: 7700480. Throughput: 0: 947.3. Samples: 924466. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-22 21:12:29,782][01716] Avg episode reward: [(0, '23.783')]
[2023-02-22 21:12:34,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7720960. Throughput: 0: 965.0. Samples: 927516. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:12:34,780][01716] Avg episode reward: [(0, '24.072')]
[2023-02-22 21:12:36,516][30143] Updated weights for policy 0, policy_version 1888 (0.0012)
[2023-02-22 21:12:39,774][01716] Fps is (10 sec: 4506.1, 60 sec: 3891.2, 300 sec: 3901.7). Total num frames: 7745536. Throughput: 0: 1007.2. Samples: 934842. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:12:39,776][01716] Avg episode reward: [(0, '24.365')]
[2023-02-22 21:12:44,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.7). Total num frames: 7761920. Throughput: 0: 972.2. Samples: 940428. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:12:44,775][01716] Avg episode reward: [(0, '23.948')]
[2023-02-22 21:12:47,764][30143] Updated weights for policy 0, policy_version 1898 (0.0020)
[2023-02-22 21:12:49,774][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 7778304. Throughput: 0: 955.9. Samples: 942654. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:12:49,779][01716] Avg episode reward: [(0, '25.235')]
[2023-02-22 21:12:54,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7798784. Throughput: 0: 985.7. Samples: 948386. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:12:54,781][01716] Avg episode reward: [(0, '24.590')]
[2023-02-22 21:12:57,386][30143] Updated weights for policy 0, policy_version 1908 (0.0016)
[2023-02-22 21:12:59,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7823360. Throughput: 0: 1011.9. Samples: 955732. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:12:59,780][01716] Avg episode reward: [(0, '25.114')]
[2023-02-22 21:13:04,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3959.5, 300 sec: 3915.5). Total num frames: 7843840. Throughput: 0: 992.7. Samples: 958444. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:13:04,779][01716] Avg episode reward: [(0, '25.475')]
[2023-02-22 21:13:09,006][30143] Updated weights for policy 0, policy_version 1918 (0.0012)
[2023-02-22 21:13:09,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 7856128. Throughput: 0: 955.8. Samples: 962966. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:13:09,776][01716] Avg episode reward: [(0, '24.795')]
[2023-02-22 21:13:14,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 7880704. Throughput: 0: 1000.9. Samples: 969506. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:13:14,780][01716] Avg episode reward: [(0, '24.059')]
[2023-02-22 21:13:17,783][30143] Updated weights for policy 0, policy_version 1928 (0.0023)
[2023-02-22 21:13:19,773][01716] Fps is (10 sec: 4915.2, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 7905280. Throughput: 0: 1014.6. Samples: 973174. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:13:19,780][01716] Avg episode reward: [(0, '24.955')]
[2023-02-22 21:13:24,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3915.5). Total num frames: 7921664. Throughput: 0: 978.8. Samples: 978888. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:13:24,782][01716] Avg episode reward: [(0, '23.892')]
[2023-02-22 21:13:29,774][01716] Fps is (10 sec: 2867.1, 60 sec: 3891.3, 300 sec: 3887.7). Total num frames: 7933952. Throughput: 0: 954.6. Samples: 983384. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:13:29,781][01716] Avg episode reward: [(0, '22.923')]
[2023-02-22 21:13:30,221][30143] Updated weights for policy 0, policy_version 1938 (0.0011)
[2023-02-22 21:13:34,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 7958528. Throughput: 0: 979.4. Samples: 986728. Policy #0 lag: (min: 0.0, avg: 0.8, max: 2.0)
[2023-02-22 21:13:34,776][01716] Avg episode reward: [(0, '22.927')]
[2023-02-22 21:13:38,619][30143] Updated weights for policy 0, policy_version 1948 (0.0012)
[2023-02-22 21:13:39,774][01716] Fps is (10 sec: 4915.3, 60 sec: 3959.5, 300 sec: 3901.7). Total num frames: 7983104. Throughput: 0: 1009.9. Samples: 993832. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:13:39,776][01716] Avg episode reward: [(0, '23.777')]
[2023-02-22 21:13:44,776][01716] Fps is (10 sec: 4095.0, 60 sec: 3959.3, 300 sec: 3915.5). Total num frames: 7999488. Throughput: 0: 961.3. Samples: 998994. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:13:44,783][01716] Avg episode reward: [(0, '24.205')]
[2023-02-22 21:13:49,776][01716] Fps is (10 sec: 2866.5, 60 sec: 3891.1, 300 sec: 3887.7). Total num frames: 8011776. Throughput: 0: 949.5. Samples: 1001176. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:13:49,778][01716] Avg episode reward: [(0, '24.026')]
[2023-02-22 21:13:50,822][30143] Updated weights for policy 0, policy_version 1958 (0.0038)
[2023-02-22 21:13:54,773][01716] Fps is (10 sec: 3687.4, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 8036352. Throughput: 0: 986.8. Samples: 1007370. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:13:54,781][01716] Avg episode reward: [(0, '25.416')]
[2023-02-22 21:13:59,409][30143] Updated weights for policy 0, policy_version 1968 (0.0012)
[2023-02-22 21:13:59,777][01716] Fps is (10 sec: 4914.4, 60 sec: 3959.2, 300 sec: 3901.6). Total num frames: 8060928. Throughput: 0: 1001.9. Samples: 1014596. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:13:59,780][01716] Avg episode reward: [(0, '27.070')]
[2023-02-22 21:14:04,774][01716] Fps is (10 sec: 4095.9, 60 sec: 3891.2, 300 sec: 3915.6). Total num frames: 8077312. Throughput: 0: 973.6. Samples: 1016988. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:14:04,776][01716] Avg episode reward: [(0, '27.779')]
[2023-02-22 21:14:04,791][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001972_8077312.pth...
[2023-02-22 21:14:04,959][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001744_7143424.pth
[2023-02-22 21:14:09,773][01716] Fps is (10 sec: 2868.3, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 8089600. Throughput: 0: 945.2. Samples: 1021422. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:14:09,780][01716] Avg episode reward: [(0, '27.172')]
[2023-02-22 21:14:11,683][30143] Updated weights for policy 0, policy_version 1978 (0.0019)
[2023-02-22 21:14:14,773][01716] Fps is (10 sec: 3686.5, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 8114176. Throughput: 0: 994.1. Samples: 1028120. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:14:14,781][01716] Avg episode reward: [(0, '27.659')]
[2023-02-22 21:14:19,773][01716] Fps is (10 sec: 4915.2, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8138752. Throughput: 0: 999.6. Samples: 1031710. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:14:19,779][01716] Avg episode reward: [(0, '27.195')]
[2023-02-22 21:14:20,331][30143] Updated weights for policy 0, policy_version 1988 (0.0013)
[2023-02-22 21:14:24,777][01716] Fps is (10 sec: 4094.4, 60 sec: 3890.9, 300 sec: 3915.5). Total num frames: 8155136. Throughput: 0: 964.3. Samples: 1037230. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:14:24,783][01716] Avg episode reward: [(0, '25.554')]
[2023-02-22 21:14:29,773][01716] Fps is (10 sec: 2867.2, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 8167424. Throughput: 0: 947.9. Samples: 1041646. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:14:29,780][01716] Avg episode reward: [(0, '25.162')]
[2023-02-22 21:14:32,540][30143] Updated weights for policy 0, policy_version 1998 (0.0014)
[2023-02-22 21:14:34,774][01716] Fps is (10 sec: 3687.7, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8192000. Throughput: 0: 978.0. Samples: 1045186. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:14:34,776][01716] Avg episode reward: [(0, '24.023')]
[2023-02-22 21:14:39,774][01716] Fps is (10 sec: 4914.9, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8216576. Throughput: 0: 1004.0. Samples: 1052550. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:14:39,777][01716] Avg episode reward: [(0, '23.659')]
[2023-02-22 21:14:41,696][30143] Updated weights for policy 0, policy_version 2008 (0.0012)
[2023-02-22 21:14:44,775][01716] Fps is (10 sec: 4095.3, 60 sec: 3891.2, 300 sec: 3915.6). Total num frames: 8232960. Throughput: 0: 951.7. Samples: 1057422. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:14:44,778][01716] Avg episode reward: [(0, '23.972')]
[2023-02-22 21:14:49,774][01716] Fps is (10 sec: 3276.9, 60 sec: 3959.6, 300 sec: 3901.6). Total num frames: 8249344. Throughput: 0: 948.4. Samples: 1059664. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:14:49,779][01716] Avg episode reward: [(0, '25.542')]
[2023-02-22 21:14:52,958][30143] Updated weights for policy 0, policy_version 2018 (0.0015)
[2023-02-22 21:14:54,773][01716] Fps is (10 sec: 4096.8, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 8273920. Throughput: 0: 999.2. Samples: 1066384. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:14:54,777][01716] Avg episode reward: [(0, '25.405')]
[2023-02-22 21:14:59,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.5, 300 sec: 3901.6). Total num frames: 8294400. Throughput: 0: 1007.0. Samples: 1073434. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:14:59,779][01716] Avg episode reward: [(0, '26.218')]
[2023-02-22 21:15:02,803][30143] Updated weights for policy 0, policy_version 2028 (0.0011)
[2023-02-22 21:15:04,774][01716] Fps is (10 sec: 3686.3, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 8310784. Throughput: 0: 977.4. Samples: 1075694. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:15:04,779][01716] Avg episode reward: [(0, '25.564')]
[2023-02-22 21:15:09,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 8327168. Throughput: 0: 954.7. Samples: 1080186. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:15:09,780][01716] Avg episode reward: [(0, '25.295')]
[2023-02-22 21:15:13,608][30143] Updated weights for policy 0, policy_version 2038 (0.0025)
[2023-02-22 21:15:14,774][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.4, 300 sec: 3901.6). Total num frames: 8351744. Throughput: 0: 1014.9. Samples: 1087316. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:15:14,781][01716] Avg episode reward: [(0, '24.805')]
[2023-02-22 21:15:19,780][01716] Fps is (10 sec: 4912.2, 60 sec: 3959.1, 300 sec: 3915.4). Total num frames: 8376320. Throughput: 0: 1016.5. Samples: 1090936. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:15:19,786][01716] Avg episode reward: [(0, '24.174')]
[2023-02-22 21:15:24,078][30143] Updated weights for policy 0, policy_version 2048 (0.0011)
[2023-02-22 21:15:24,773][01716] Fps is (10 sec: 3686.5, 60 sec: 3891.4, 300 sec: 3915.5). Total num frames: 8388608. Throughput: 0: 965.4. Samples: 1095992. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:15:24,780][01716] Avg episode reward: [(0, '24.809')]
[2023-02-22 21:15:29,773][01716] Fps is (10 sec: 2869.0, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 8404992. Throughput: 0: 967.6. Samples: 1100964. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:15:29,781][01716] Avg episode reward: [(0, '24.967')]
[2023-02-22 21:15:34,219][30143] Updated weights for policy 0, policy_version 2058 (0.0014)
[2023-02-22 21:15:34,774][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3901.6). Total num frames: 8429568. Throughput: 0: 995.8. Samples: 1104476. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:15:34,776][01716] Avg episode reward: [(0, '24.048')]
[2023-02-22 21:15:39,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.7). Total num frames: 8450048. Throughput: 0: 1004.8. Samples: 1111602. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:15:39,782][01716] Avg episode reward: [(0, '24.380')]
[2023-02-22 21:15:44,773][01716] Fps is (10 sec: 3686.5, 60 sec: 3891.3, 300 sec: 3915.5). Total num frames: 8466432. Throughput: 0: 947.9. Samples: 1116090. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:15:44,777][01716] Avg episode reward: [(0, '25.080')]
[2023-02-22 21:15:45,546][30143] Updated weights for policy 0, policy_version 2068 (0.0011)
[2023-02-22 21:15:49,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8482816. Throughput: 0: 949.0. Samples: 1118398. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:15:49,775][01716] Avg episode reward: [(0, '25.218')]
[2023-02-22 21:15:54,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8507392. Throughput: 0: 999.5. Samples: 1125164. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:15:54,776][01716] Avg episode reward: [(0, '23.778')]
[2023-02-22 21:15:55,215][30143] Updated weights for policy 0, policy_version 2078 (0.0019)
[2023-02-22 21:15:59,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8527872. Throughput: 0: 985.7. Samples: 1131670. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:15:59,781][01716] Avg episode reward: [(0, '23.161')]
[2023-02-22 21:16:04,775][01716] Fps is (10 sec: 3685.7, 60 sec: 3891.1, 300 sec: 3915.5). Total num frames: 8544256. Throughput: 0: 955.4. Samples: 1133924. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:16:04,779][01716] Avg episode reward: [(0, '24.395')]
[2023-02-22 21:16:04,801][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002086_8544256.pth...
[2023-02-22 21:16:04,990][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001857_7606272.pth
[2023-02-22 21:16:07,301][30143] Updated weights for policy 0, policy_version 2088 (0.0013)
[2023-02-22 21:16:09,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8560640. Throughput: 0: 938.7. Samples: 1138232. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:16:09,775][01716] Avg episode reward: [(0, '24.528')]
[2023-02-22 21:16:14,773][01716] Fps is (10 sec: 4096.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8585216. Throughput: 0: 989.4. Samples: 1145486. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:16:14,776][01716] Avg episode reward: [(0, '25.039')]
[2023-02-22 21:16:16,246][30143] Updated weights for policy 0, policy_version 2098 (0.0023)
[2023-02-22 21:16:19,773][01716] Fps is (10 sec: 4505.5, 60 sec: 3823.3, 300 sec: 3915.6). Total num frames: 8605696. Throughput: 0: 992.0. Samples: 1149118. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:16:19,781][01716] Avg episode reward: [(0, '23.825')]
[2023-02-22 21:16:24,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 8622080. Throughput: 0: 939.2. Samples: 1153866. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:16:24,779][01716] Avg episode reward: [(0, '24.268')]
[2023-02-22 21:16:28,515][30143] Updated weights for policy 0, policy_version 2108 (0.0023)
[2023-02-22 21:16:29,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8638464. Throughput: 0: 954.8. Samples: 1159058. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-22 21:16:29,779][01716] Avg episode reward: [(0, '23.129')]
[2023-02-22 21:16:34,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8663040. Throughput: 0: 982.9. Samples: 1162630. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:16:34,777][01716] Avg episode reward: [(0, '21.801')]
[2023-02-22 21:16:37,036][30143] Updated weights for policy 0, policy_version 2118 (0.0015)
[2023-02-22 21:16:39,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 8683520. Throughput: 0: 986.6. Samples: 1169560. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:16:39,782][01716] Avg episode reward: [(0, '21.615')]
[2023-02-22 21:16:44,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 8699904. Throughput: 0: 942.9. Samples: 1174100. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:16:44,776][01716] Avg episode reward: [(0, '22.704')]
[2023-02-22 21:16:49,149][30143] Updated weights for policy 0, policy_version 2128 (0.0014)
[2023-02-22 21:16:49,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8716288. Throughput: 0: 943.7. Samples: 1176390. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:16:49,782][01716] Avg episode reward: [(0, '23.645')]
[2023-02-22 21:16:54,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8740864. Throughput: 0: 1009.1. Samples: 1183640. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:16:54,776][01716] Avg episode reward: [(0, '24.857')]
[2023-02-22 21:16:57,736][30143] Updated weights for policy 0, policy_version 2138 (0.0020)
[2023-02-22 21:16:59,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 8761344. Throughput: 0: 985.6. Samples: 1189840. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:16:59,776][01716] Avg episode reward: [(0, '25.779')]
[2023-02-22 21:17:04,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.3, 300 sec: 3915.5). Total num frames: 8777728. Throughput: 0: 954.7. Samples: 1192080. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:17:04,779][01716] Avg episode reward: [(0, '25.913')]
[2023-02-22 21:17:09,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8794112. Throughput: 0: 960.5. Samples: 1197090. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:17:09,776][01716] Avg episode reward: [(0, '25.179')]
[2023-02-22 21:17:09,872][30143] Updated weights for policy 0, policy_version 2148 (0.0011)
[2023-02-22 21:17:14,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8818688. Throughput: 0: 1006.2. Samples: 1204336. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:17:14,778][01716] Avg episode reward: [(0, '23.812')]
[2023-02-22 21:17:19,269][30143] Updated weights for policy 0, policy_version 2158 (0.0016)
[2023-02-22 21:17:19,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 8839168. Throughput: 0: 1005.3. Samples: 1207868. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:17:19,779][01716] Avg episode reward: [(0, '23.453')]
[2023-02-22 21:17:24,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3915.5). Total num frames: 8855552. Throughput: 0: 945.7. Samples: 1212118. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:17:24,780][01716] Avg episode reward: [(0, '24.042')]
[2023-02-22 21:17:29,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3901.6). Total num frames: 8871936. Throughput: 0: 953.8. Samples: 1217020. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:17:29,779][01716] Avg episode reward: [(0, '24.121')]
[2023-02-22 21:17:31,666][30143] Updated weights for policy 0, policy_version 2168 (0.0014)
[2023-02-22 21:17:34,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 8892416. Throughput: 0: 972.4. Samples: 1220148. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:17:34,776][01716] Avg episode reward: [(0, '25.069')]
[2023-02-22 21:17:39,775][01716] Fps is (10 sec: 4095.4, 60 sec: 3822.8, 300 sec: 3901.6). Total num frames: 8912896. Throughput: 0: 955.3. Samples: 1226628. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:17:39,785][01716] Avg episode reward: [(0, '25.809')]
[2023-02-22 21:17:42,615][30143] Updated weights for policy 0, policy_version 2178 (0.0014)
[2023-02-22 21:17:44,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3887.7). Total num frames: 8925184. Throughput: 0: 915.4. Samples: 1231032. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:17:44,778][01716] Avg episode reward: [(0, '26.681')]
[2023-02-22 21:17:49,773][01716] Fps is (10 sec: 3277.3, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 8945664. Throughput: 0: 917.8. Samples: 1233380. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 21:17:49,776][01716] Avg episode reward: [(0, '26.386')]
[2023-02-22 21:17:52,884][30143] Updated weights for policy 0, policy_version 2188 (0.0017)
[2023-02-22 21:17:54,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3822.9, 300 sec: 3887.7). Total num frames: 8970240. Throughput: 0: 970.0. Samples: 1240738. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:17:54,776][01716] Avg episode reward: [(0, '25.730')]
[2023-02-22 21:17:59,774][01716] Fps is (10 sec: 4095.9, 60 sec: 3754.6, 300 sec: 3873.8). Total num frames: 8986624. Throughput: 0: 941.9. Samples: 1246720. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:17:59,778][01716] Avg episode reward: [(0, '24.378')]
[2023-02-22 21:18:03,729][30143] Updated weights for policy 0, policy_version 2198 (0.0012)
[2023-02-22 21:18:04,774][01716] Fps is (10 sec: 3276.8, 60 sec: 3754.7, 300 sec: 3887.7). Total num frames: 9003008. Throughput: 0: 911.5. Samples: 1248884. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:18:04,778][01716] Avg episode reward: [(0, '25.296')]
[2023-02-22 21:18:04,799][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002198_9003008.pth...
[2023-02-22 21:18:05,002][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001972_8077312.pth
[2023-02-22 21:18:09,773][01716] Fps is (10 sec: 3686.5, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 9023488. Throughput: 0: 934.2. Samples: 1254156. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:18:09,776][01716] Avg episode reward: [(0, '25.416')]
[2023-02-22 21:18:13,515][30143] Updated weights for policy 0, policy_version 2208 (0.0022)
[2023-02-22 21:18:14,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 9048064. Throughput: 0: 985.6. Samples: 1261370. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 21:18:14,779][01716] Avg episode reward: [(0, '26.202')]
[2023-02-22 21:18:19,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3873.8). Total num frames: 9064448. Throughput: 0: 988.0. Samples: 1264608. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:18:19,784][01716] Avg episode reward: [(0, '25.321')]
[2023-02-22 21:18:24,775][01716] Fps is (10 sec: 3276.1, 60 sec: 3754.5, 300 sec: 3887.7). Total num frames: 9080832. Throughput: 0: 941.3. Samples: 1268986. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:18:24,785][01716] Avg episode reward: [(0, '26.146')]
[2023-02-22 21:18:25,335][30143] Updated weights for policy 0, policy_version 2218 (0.0013)
[2023-02-22 21:18:29,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3822.9, 300 sec: 3873.8). Total num frames: 9101312. Throughput: 0: 973.7. Samples: 1274848. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:18:29,775][01716] Avg episode reward: [(0, '24.663')]
[2023-02-22 21:18:34,532][30143] Updated weights for policy 0, policy_version 2228 (0.0015)
[2023-02-22 21:18:34,774][01716] Fps is (10 sec: 4506.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9125888. Throughput: 0: 1001.9. Samples: 1278466. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:18:34,777][01716] Avg episode reward: [(0, '22.558')]
[2023-02-22 21:18:39,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3823.0, 300 sec: 3873.9). Total num frames: 9142272. Throughput: 0: 974.9. Samples: 1284608. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:18:39,785][01716] Avg episode reward: [(0, '22.539')]
[2023-02-22 21:18:44,773][01716] Fps is (10 sec: 3276.9, 60 sec: 3891.2, 300 sec: 3887.8). Total num frames: 9158656. Throughput: 0: 942.5. Samples: 1289132. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:18:44,781][01716] Avg episode reward: [(0, '21.623')]
[2023-02-22 21:18:46,728][30143] Updated weights for policy 0, policy_version 2238 (0.0027)
[2023-02-22 21:18:49,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9179136. Throughput: 0: 957.4. Samples: 1291968. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:18:49,779][01716] Avg episode reward: [(0, '21.435')]
[2023-02-22 21:18:54,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3873.9). Total num frames: 9203712. Throughput: 0: 998.7. Samples: 1299096. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:18:54,778][01716] Avg episode reward: [(0, '22.517')]
[2023-02-22 21:18:55,277][30143] Updated weights for policy 0, policy_version 2248 (0.0012)
[2023-02-22 21:18:59,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9220096. Throughput: 0: 965.5. Samples: 1304818. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:18:59,776][01716] Avg episode reward: [(0, '23.416')]
[2023-02-22 21:19:04,774][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 9236480. Throughput: 0: 943.3. Samples: 1307058. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:19:04,781][01716] Avg episode reward: [(0, '25.177')]
[2023-02-22 21:19:07,428][30143] Updated weights for policy 0, policy_version 2258 (0.0018)
[2023-02-22 21:19:09,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9256960. Throughput: 0: 972.6. Samples: 1312750. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:19:09,778][01716] Avg episode reward: [(0, '25.738')]
[2023-02-22 21:19:14,773][01716] Fps is (10 sec: 4505.7, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9281536. Throughput: 0: 1004.2. Samples: 1320036. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:19:14,778][01716] Avg episode reward: [(0, '25.569')]
[2023-02-22 21:19:15,865][30143] Updated weights for policy 0, policy_version 2268 (0.0021)
[2023-02-22 21:19:19,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3873.9). Total num frames: 9297920. Throughput: 0: 984.5. Samples: 1322766. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:19:19,778][01716] Avg episode reward: [(0, '26.209')]
[2023-02-22 21:19:24,776][01716] Fps is (10 sec: 3276.0, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 9314304. Throughput: 0: 947.9. Samples: 1327266. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:19:24,779][01716] Avg episode reward: [(0, '25.622')]
[2023-02-22 21:19:28,168][30143] Updated weights for policy 0, policy_version 2278 (0.0030)
[2023-02-22 21:19:29,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9334784. Throughput: 0: 986.6. Samples: 1333528. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:19:29,776][01716] Avg episode reward: [(0, '25.938')]
[2023-02-22 21:19:34,773][01716] Fps is (10 sec: 4506.7, 60 sec: 3891.2, 300 sec: 3873.9). Total num frames: 9359360. Throughput: 0: 1003.9. Samples: 1337142. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:19:34,785][01716] Avg episode reward: [(0, '26.451')]
[2023-02-22 21:19:37,518][30143] Updated weights for policy 0, policy_version 2288 (0.0013)
[2023-02-22 21:19:39,774][01716] Fps is (10 sec: 4095.9, 60 sec: 3891.2, 300 sec: 3873.9). Total num frames: 9375744. Throughput: 0: 975.5. Samples: 1342994. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:19:39,781][01716] Avg episode reward: [(0, '27.311')]
[2023-02-22 21:19:44,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9392128. Throughput: 0: 947.1. Samples: 1347438. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:19:44,776][01716] Avg episode reward: [(0, '26.909')]
[2023-02-22 21:19:48,945][30143] Updated weights for policy 0, policy_version 2298 (0.0011)
[2023-02-22 21:19:49,773][01716] Fps is (10 sec: 3686.5, 60 sec: 3891.2, 300 sec: 3860.0). Total num frames: 9412608. Throughput: 0: 970.9. Samples: 1350748. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:19:49,781][01716] Avg episode reward: [(0, '27.116')]
[2023-02-22 21:19:54,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9437184. Throughput: 0: 1005.5. Samples: 1357996. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:19:54,780][01716] Avg episode reward: [(0, '26.765')]
[2023-02-22 21:19:58,729][30143] Updated weights for policy 0, policy_version 2308 (0.0012)
[2023-02-22 21:19:59,776][01716] Fps is (10 sec: 4094.8, 60 sec: 3891.0, 300 sec: 3873.8). Total num frames: 9453568. Throughput: 0: 960.5. Samples: 1363262. Policy #0 lag: (min: 0.0, avg: 0.7, max: 1.0)
[2023-02-22 21:19:59,779][01716] Avg episode reward: [(0, '26.094')]
[2023-02-22 21:20:04,774][01716] Fps is (10 sec: 3276.5, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9469952. Throughput: 0: 949.4. Samples: 1365488. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:20:04,778][01716] Avg episode reward: [(0, '23.655')]
[2023-02-22 21:20:04,796][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002312_9469952.pth...
[2023-02-22 21:20:04,999][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002086_8544256.pth
[2023-02-22 21:20:09,524][30143] Updated weights for policy 0, policy_version 2318 (0.0011)
[2023-02-22 21:20:09,773][01716] Fps is (10 sec: 4097.2, 60 sec: 3959.5, 300 sec: 3873.8). Total num frames: 9494528. Throughput: 0: 986.4. Samples: 1371650. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:20:09,781][01716] Avg episode reward: [(0, '22.494')]
[2023-02-22 21:20:14,773][01716] Fps is (10 sec: 4915.6, 60 sec: 3959.5, 300 sec: 3873.9). Total num frames: 9519104. Throughput: 0: 1009.0. Samples: 1378934. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:20:14,781][01716] Avg episode reward: [(0, '22.458')]
[2023-02-22 21:20:19,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9531392. Throughput: 0: 982.5. Samples: 1381356. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:20:19,776][01716] Avg episode reward: [(0, '22.951')]
[2023-02-22 21:20:19,793][30143] Updated weights for policy 0, policy_version 2328 (0.0012)
[2023-02-22 21:20:24,773][01716] Fps is (10 sec: 2867.2, 60 sec: 3891.3, 300 sec: 3873.8). Total num frames: 9547776. Throughput: 0: 951.5. Samples: 1385810. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:20:24,778][01716] Avg episode reward: [(0, '23.472')]
[2023-02-22 21:20:29,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3873.8). Total num frames: 9572352. Throughput: 0: 1004.6. Samples: 1392644. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:20:29,781][01716] Avg episode reward: [(0, '23.836')]
[2023-02-22 21:20:30,104][30143] Updated weights for policy 0, policy_version 2338 (0.0017)
[2023-02-22 21:20:34,774][01716] Fps is (10 sec: 4915.1, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9596928. Throughput: 0: 1007.8. Samples: 1396100. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:20:34,776][01716] Avg episode reward: [(0, '24.676')]
[2023-02-22 21:20:39,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9609216. Throughput: 0: 965.0. Samples: 1401422. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:20:39,778][01716] Avg episode reward: [(0, '25.942')]
[2023-02-22 21:20:41,175][30143] Updated weights for policy 0, policy_version 2348 (0.0017)
[2023-02-22 21:20:44,774][01716] Fps is (10 sec: 2867.2, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9625600. Throughput: 0: 953.0. Samples: 1406144. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-22 21:20:44,791][01716] Avg episode reward: [(0, '25.902')]
[2023-02-22 21:20:49,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3873.8). Total num frames: 9650176. Throughput: 0: 983.5. Samples: 1409744. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:20:49,775][01716] Avg episode reward: [(0, '24.335')]
[2023-02-22 21:20:50,893][30143] Updated weights for policy 0, policy_version 2358 (0.0016)
[2023-02-22 21:20:54,773][01716] Fps is (10 sec: 4915.3, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9674752. Throughput: 0: 1008.5. Samples: 1417032. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:20:54,785][01716] Avg episode reward: [(0, '24.844')]
[2023-02-22 21:20:59,773][01716] Fps is (10 sec: 3686.4, 60 sec: 3891.4, 300 sec: 3873.9). Total num frames: 9687040. Throughput: 0: 953.6. Samples: 1421844. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:20:59,781][01716] Avg episode reward: [(0, '24.112')]
[2023-02-22 21:21:02,677][30143] Updated weights for policy 0, policy_version 2368 (0.0012)
[2023-02-22 21:21:04,773][01716] Fps is (10 sec: 2867.2, 60 sec: 3891.3, 300 sec: 3873.8). Total num frames: 9703424. Throughput: 0: 949.9. Samples: 1424100. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:21:04,779][01716] Avg episode reward: [(0, '24.372')]
[2023-02-22 21:21:09,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9728000. Throughput: 0: 996.8. Samples: 1430666. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:21:09,776][01716] Avg episode reward: [(0, '24.325')]
[2023-02-22 21:21:11,702][30143] Updated weights for policy 0, policy_version 2378 (0.0012)
[2023-02-22 21:21:14,773][01716] Fps is (10 sec: 4915.2, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 9752576. Throughput: 0: 996.9. Samples: 1437506. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:21:14,776][01716] Avg episode reward: [(0, '24.704')]
[2023-02-22 21:21:19,775][01716] Fps is (10 sec: 4095.2, 60 sec: 3959.3, 300 sec: 3887.7). Total num frames: 9768960. Throughput: 0: 971.3. Samples: 1439812. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:21:19,781][01716] Avg episode reward: [(0, '24.123')]
[2023-02-22 21:21:23,718][30143] Updated weights for policy 0, policy_version 2388 (0.0028)
[2023-02-22 21:21:24,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9785344. Throughput: 0: 954.7. Samples: 1444382. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:21:24,779][01716] Avg episode reward: [(0, '23.928')]
[2023-02-22 21:21:29,773][01716] Fps is (10 sec: 4096.8, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9809920. Throughput: 0: 1009.7. Samples: 1451580. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:21:29,776][01716] Avg episode reward: [(0, '25.169')]
[2023-02-22 21:21:32,364][30143] Updated weights for policy 0, policy_version 2398 (0.0016)
[2023-02-22 21:21:34,774][01716] Fps is (10 sec: 4505.5, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 9830400. Throughput: 0: 1006.5. Samples: 1455038. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:21:34,784][01716] Avg episode reward: [(0, '25.420')]
[2023-02-22 21:21:39,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9842688. Throughput: 0: 952.0. Samples: 1459874. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:21:39,783][01716] Avg episode reward: [(0, '24.772')]
[2023-02-22 21:21:44,574][30143] Updated weights for policy 0, policy_version 2408 (0.0025)
[2023-02-22 21:21:44,773][01716] Fps is (10 sec: 3276.9, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9863168. Throughput: 0: 956.8. Samples: 1464900. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:21:44,780][01716] Avg episode reward: [(0, '24.727')]
[2023-02-22 21:21:49,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3891.2, 300 sec: 3873.8). Total num frames: 9883648. Throughput: 0: 986.9. Samples: 1468512. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:21:49,781][01716] Avg episode reward: [(0, '26.153')]
[2023-02-22 21:21:53,279][30143] Updated weights for policy 0, policy_version 2418 (0.0014)
[2023-02-22 21:21:54,773][01716] Fps is (10 sec: 4505.6, 60 sec: 3891.2, 300 sec: 3887.7). Total num frames: 9908224. Throughput: 0: 998.6. Samples: 1475602. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2023-02-22 21:21:54,780][01716] Avg episode reward: [(0, '25.579')]
[2023-02-22 21:21:59,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9924608. Throughput: 0: 947.6. Samples: 1480150. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-22 21:21:59,775][01716] Avg episode reward: [(0, '25.572')]
[2023-02-22 21:22:04,773][01716] Fps is (10 sec: 3276.8, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9940992. Throughput: 0: 947.5. Samples: 1482450. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-22 21:22:04,776][01716] Avg episode reward: [(0, '25.779')]
[2023-02-22 21:22:04,783][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002427_9940992.pth...
[2023-02-22 21:22:04,950][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002198_9003008.pth
[2023-02-22 21:22:05,260][30143] Updated weights for policy 0, policy_version 2428 (0.0013)
[2023-02-22 21:22:09,773][01716] Fps is (10 sec: 4096.0, 60 sec: 3959.5, 300 sec: 3887.7). Total num frames: 9965568. Throughput: 0: 999.9. Samples: 1489376. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-22 21:22:09,782][01716] Avg episode reward: [(0, '25.236')]
[2023-02-22 21:22:14,351][30143] Updated weights for policy 0, policy_version 2438 (0.0012)
[2023-02-22 21:22:14,774][01716] Fps is (10 sec: 4505.1, 60 sec: 3891.1, 300 sec: 3887.7). Total num frames: 9986048. Throughput: 0: 987.2. Samples: 1496004. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:22:14,782][01716] Avg episode reward: [(0, '26.655')]
[2023-02-22 21:22:19,779][01716] Fps is (10 sec: 3684.2, 60 sec: 3890.9, 300 sec: 3887.7). Total num frames: 10002432. Throughput: 0: 960.2. Samples: 1498254. Policy #0 lag: (min: 0.0, avg: 0.7, max: 2.0)
[2023-02-22 21:22:19,786][01716] Avg episode reward: [(0, '26.202')]
[2023-02-22 21:22:20,987][30129] Stopping Batcher_0...
[2023-02-22 21:22:20,990][01716] Component Batcher_0 stopped!
[2023-02-22 21:22:20,987][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002443_10006528.pth...
[2023-02-22 21:22:20,990][30129] Loop batcher_evt_loop terminating...
[2023-02-22 21:22:21,089][30143] Weights refcount: 2 0
[2023-02-22 21:22:21,101][30143] Stopping InferenceWorker_p0-w0...
[2023-02-22 21:22:21,102][30143] Loop inference_proc0-0_evt_loop terminating...
[2023-02-22 21:22:21,101][01716] Component InferenceWorker_p0-w0 stopped!
[2023-02-22 21:22:21,178][30129] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002312_9469952.pth
[2023-02-22 21:22:21,191][30129] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002443_10006528.pth...
[2023-02-22 21:22:21,244][30154] Stopping RolloutWorker_w3...
[2023-02-22 21:22:21,244][01716] Component RolloutWorker_w3 stopped!
[2023-02-22 21:22:21,246][30154] Loop rollout_proc3_evt_loop terminating...
[2023-02-22 21:22:21,283][30156] Stopping RolloutWorker_w5...
[2023-02-22 21:22:21,283][01716] Component RolloutWorker_w5 stopped!
[2023-02-22 21:22:21,284][30156] Loop rollout_proc5_evt_loop terminating...
[2023-02-22 21:22:21,287][30144] Stopping RolloutWorker_w1...
[2023-02-22 21:22:21,288][01716] Component RolloutWorker_w1 stopped!
[2023-02-22 21:22:21,289][30144] Loop rollout_proc1_evt_loop terminating...
[2023-02-22 21:22:21,293][30164] Stopping RolloutWorker_w7...
[2023-02-22 21:22:21,296][01716] Component RolloutWorker_w7 stopped!
[2023-02-22 21:22:21,299][30164] Loop rollout_proc7_evt_loop terminating...
[2023-02-22 21:22:21,309][01716] Component RolloutWorker_w4 stopped!
[2023-02-22 21:22:21,309][30158] Stopping RolloutWorker_w4...
[2023-02-22 21:22:21,315][30158] Loop rollout_proc4_evt_loop terminating...
[2023-02-22 21:22:21,322][30166] Stopping RolloutWorker_w6...
[2023-02-22 21:22:21,327][01716] Component RolloutWorker_w6 stopped!
[2023-02-22 21:22:21,335][30166] Loop rollout_proc6_evt_loop terminating...
[2023-02-22 21:22:21,352][30151] Stopping RolloutWorker_w0...
[2023-02-22 21:22:21,353][01716] Component RolloutWorker_w0 stopped!
[2023-02-22 21:22:21,363][30152] Stopping RolloutWorker_w2...
[2023-02-22 21:22:21,364][30152] Loop rollout_proc2_evt_loop terminating...
[2023-02-22 21:22:21,363][01716] Component RolloutWorker_w2 stopped!
[2023-02-22 21:22:21,385][30151] Loop rollout_proc0_evt_loop terminating...
[2023-02-22 21:22:21,510][01716] Component LearnerWorker_p0 stopped!
[2023-02-22 21:22:21,515][01716] Waiting for process learner_proc0 to stop...
[2023-02-22 21:22:21,519][30129] Stopping LearnerWorker_p0...
[2023-02-22 21:22:21,520][30129] Loop learner_proc0_evt_loop terminating...
[2023-02-22 21:22:24,498][01716] Waiting for process inference_proc0-0 to join...
[2023-02-22 21:22:24,566][01716] Waiting for process rollout_proc0 to join...
[2023-02-22 21:22:24,600][01716] Waiting for process rollout_proc1 to join...
[2023-02-22 21:22:24,601][01716] Waiting for process rollout_proc2 to join...
[2023-02-22 21:22:24,607][01716] Waiting for process rollout_proc3 to join...
[2023-02-22 21:22:24,611][01716] Waiting for process rollout_proc4 to join...
[2023-02-22 21:22:24,614][01716] Waiting for process rollout_proc5 to join...
[2023-02-22 21:22:24,616][01716] Waiting for process rollout_proc6 to join...
[2023-02-22 21:22:24,618][01716] Waiting for process rollout_proc7 to join...
[2023-02-22 21:22:24,621][01716] Batcher 0 profile tree view:
batching: 36.7543, releasing_batches: 0.0330
[2023-02-22 21:22:24,622][01716] InferenceWorker_p0-w0 profile tree view:
wait_policy: 0.0000
  wait_policy_total: 738.9250
update_model: 10.4655
  weight_update: 0.0020
one_step: 0.0234
  handle_policy_step: 747.2770
    deserialize: 21.3510, stack: 4.1320, obs_to_device_normalize: 166.5630, forward: 358.9350, send_messages: 38.3094
    prepare_outputs: 120.6261
      to_cpu: 75.8902
[2023-02-22 21:22:24,626][01716] Learner 0 profile tree view:
misc: 0.0076, prepare_batch: 22.9233
train: 117.4736
  epoch_init: 0.0188, minibatch_init: 0.0207, losses_postprocess: 0.8619, kl_divergence: 0.7720, after_optimizer: 4.2342
  calculate_losses: 38.9349
    losses_init: 0.0168, forward_head: 2.3809, bptt_initial: 26.0329, tail: 1.4213, advantages_returns: 0.4061, losses: 5.1228
    bptt: 3.1087
      bptt_forward_core: 2.9924
  update: 71.5695
    clip: 2.0120
[2023-02-22 21:22:24,627][01716] RolloutWorker_w0 profile tree view:
wait_for_trajectories: 0.4836, enqueue_policy_requests: 194.9998, env_step: 1187.9953, overhead: 29.0663, complete_rollouts: 10.2064
save_policy_outputs: 28.2584
  split_output_tensors: 13.5573
[2023-02-22 21:22:24,628][01716] RolloutWorker_w7 profile tree view:
wait_for_trajectories: 0.5231, enqueue_policy_requests: 190.5061, env_step: 1188.8679, overhead: 28.9395, complete_rollouts: 9.5986
save_policy_outputs: 29.3909
  split_output_tensors: 14.3568
[2023-02-22 21:22:24,633][01716] Loop Runner_EvtLoop terminating...
[2023-02-22 21:22:24,635][01716] Runner profile tree view:
main_loop: 1578.2836
[2023-02-22 21:22:24,636][01716] Collected {0: 10006528}, FPS: 3802.0
[2023-02-22 21:24:52,432][01716] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2023-02-22 21:24:52,434][01716] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-22 21:24:52,435][01716] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-22 21:24:52,437][01716] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-22 21:24:52,439][01716] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-22 21:24:52,443][01716] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-22 21:24:52,445][01716] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
[2023-02-22 21:24:52,446][01716] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-22 21:24:52,448][01716] Adding new argument 'push_to_hub'=True that is not in the saved config file!
[2023-02-22 21:24:52,450][01716] Adding new argument 'hf_repository'='RamonAnkersmit/rl_course_vizdoom_health_gathering_supreme_v2' that is not in the saved config file!
[2023-02-22 21:24:52,455][01716] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-22 21:24:52,460][01716] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-22 21:24:52,461][01716] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-22 21:24:52,463][01716] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-22 21:24:52,465][01716] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-22 21:24:52,492][01716] RunningMeanStd input shape: (3, 72, 128)
[2023-02-22 21:24:52,497][01716] RunningMeanStd input shape: (1,)
[2023-02-22 21:24:52,520][01716] ConvEncoder: input_channels=3
[2023-02-22 21:24:52,648][01716] Conv encoder output size: 512
[2023-02-22 21:24:52,650][01716] Policy head output size: 512
[2023-02-22 21:24:52,740][01716] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002443_10006528.pth...
[2023-02-22 21:24:53,616][01716] Num frames 100...
[2023-02-22 21:24:53,744][01716] Num frames 200...
[2023-02-22 21:24:53,858][01716] Num frames 300...
[2023-02-22 21:24:53,963][01716] Avg episode rewards: #0: 8.410, true rewards: #0: 3.410
[2023-02-22 21:24:53,966][01716] Avg episode reward: 8.410, avg true_objective: 3.410
[2023-02-22 21:24:54,034][01716] Num frames 400...
[2023-02-22 21:24:54,146][01716] Num frames 500...
[2023-02-22 21:24:54,260][01716] Num frames 600...
[2023-02-22 21:24:54,371][01716] Num frames 700...
[2023-02-22 21:24:54,481][01716] Num frames 800...
[2023-02-22 21:24:54,600][01716] Num frames 900...
[2023-02-22 21:24:54,712][01716] Num frames 1000...
[2023-02-22 21:24:54,834][01716] Num frames 1100...
[2023-02-22 21:24:54,950][01716] Num frames 1200...
[2023-02-22 21:24:55,061][01716] Num frames 1300...
[2023-02-22 21:24:55,181][01716] Num frames 1400...
[2023-02-22 21:24:55,292][01716] Num frames 1500...
[2023-02-22 21:24:55,439][01716] Avg episode rewards: #0: 19.395, true rewards: #0: 7.895
[2023-02-22 21:24:55,441][01716] Avg episode reward: 19.395, avg true_objective: 7.895
[2023-02-22 21:24:55,467][01716] Num frames 1600...
[2023-02-22 21:24:55,578][01716] Num frames 1700...
[2023-02-22 21:24:55,690][01716] Num frames 1800...
[2023-02-22 21:24:55,811][01716] Num frames 1900...
[2023-02-22 21:24:55,930][01716] Num frames 2000...
[2023-02-22 21:24:56,056][01716] Num frames 2100...
[2023-02-22 21:24:56,170][01716] Num frames 2200...
[2023-02-22 21:24:56,285][01716] Num frames 2300...
[2023-02-22 21:24:56,409][01716] Num frames 2400...
[2023-02-22 21:24:56,549][01716] Avg episode rewards: #0: 18.917, true rewards: #0: 8.250
[2023-02-22 21:24:56,553][01716] Avg episode reward: 18.917, avg true_objective: 8.250
[2023-02-22 21:24:56,583][01716] Num frames 2500...
[2023-02-22 21:24:56,707][01716] Num frames 2600...
[2023-02-22 21:24:56,827][01716] Num frames 2700...
[2023-02-22 21:24:56,955][01716] Num frames 2800...
[2023-02-22 21:24:57,066][01716] Num frames 2900...
[2023-02-22 21:24:57,179][01716] Num frames 3000...
[2023-02-22 21:24:57,293][01716] Avg episode rewards: #0: 16.378, true rewards: #0: 7.627
[2023-02-22 21:24:57,295][01716] Avg episode reward: 16.378, avg true_objective: 7.627
[2023-02-22 21:24:57,352][01716] Num frames 3100...
[2023-02-22 21:24:57,462][01716] Num frames 3200...
[2023-02-22 21:24:57,578][01716] Num frames 3300...
[2023-02-22 21:24:57,697][01716] Num frames 3400...
[2023-02-22 21:24:57,816][01716] Num frames 3500...
[2023-02-22 21:24:57,934][01716] Num frames 3600...
[2023-02-22 21:24:58,043][01716] Num frames 3700...
[2023-02-22 21:24:58,164][01716] Num frames 3800...
[2023-02-22 21:24:58,274][01716] Num frames 3900...
[2023-02-22 21:24:58,395][01716] Num frames 4000...
[2023-02-22 21:24:58,510][01716] Num frames 4100...
[2023-02-22 21:24:58,666][01716] Avg episode rewards: #0: 17.984, true rewards: #0: 8.384
[2023-02-22 21:24:58,668][01716] Avg episode reward: 17.984, avg true_objective: 8.384
[2023-02-22 21:24:58,680][01716] Num frames 4200...
[2023-02-22 21:24:58,793][01716] Num frames 4300...
[2023-02-22 21:24:58,919][01716] Num frames 4400...
[2023-02-22 21:24:59,030][01716] Num frames 4500...
[2023-02-22 21:24:59,143][01716] Num frames 4600...
[2023-02-22 21:24:59,253][01716] Num frames 4700...
[2023-02-22 21:24:59,370][01716] Num frames 4800...
[2023-02-22 21:24:59,488][01716] Num frames 4900...
[2023-02-22 21:24:59,609][01716] Avg episode rewards: #0: 17.433, true rewards: #0: 8.267
[2023-02-22 21:24:59,611][01716] Avg episode reward: 17.433, avg true_objective: 8.267
[2023-02-22 21:24:59,661][01716] Num frames 5000...
[2023-02-22 21:24:59,772][01716] Num frames 5100...
[2023-02-22 21:24:59,894][01716] Num frames 5200...
[2023-02-22 21:25:00,014][01716] Num frames 5300...
[2023-02-22 21:25:00,124][01716] Num frames 5400...
[2023-02-22 21:25:00,240][01716] Num frames 5500...
[2023-02-22 21:25:00,349][01716] Num frames 5600...
[2023-02-22 21:25:00,469][01716] Num frames 5700...
[2023-02-22 21:25:00,579][01716] Num frames 5800...
[2023-02-22 21:25:00,690][01716] Num frames 5900...
[2023-02-22 21:25:00,802][01716] Num frames 6000...
[2023-02-22 21:25:00,951][01716] Num frames 6100...
[2023-02-22 21:25:01,107][01716] Num frames 6200...
[2023-02-22 21:25:01,281][01716] Avg episode rewards: #0: 19.389, true rewards: #0: 8.960
[2023-02-22 21:25:01,284][01716] Avg episode reward: 19.389, avg true_objective: 8.960
[2023-02-22 21:25:01,335][01716] Num frames 6300...
[2023-02-22 21:25:01,492][01716] Num frames 6400...
[2023-02-22 21:25:01,660][01716] Num frames 6500...
[2023-02-22 21:25:01,813][01716] Num frames 6600...
[2023-02-22 21:25:01,976][01716] Num frames 6700...
[2023-02-22 21:25:02,136][01716] Num frames 6800...
[2023-02-22 21:25:02,257][01716] Avg episode rewards: #0: 18.926, true rewards: #0: 8.551
[2023-02-22 21:25:02,259][01716] Avg episode reward: 18.926, avg true_objective: 8.551
[2023-02-22 21:25:02,348][01716] Num frames 6900...
[2023-02-22 21:25:02,503][01716] Num frames 7000...
[2023-02-22 21:25:02,655][01716] Num frames 7100...
[2023-02-22 21:25:02,813][01716] Num frames 7200...
[2023-02-22 21:25:02,981][01716] Num frames 7300...
[2023-02-22 21:25:03,144][01716] Num frames 7400...
[2023-02-22 21:25:03,309][01716] Num frames 7500...
[2023-02-22 21:25:03,470][01716] Num frames 7600...
[2023-02-22 21:25:03,626][01716] Num frames 7700...
[2023-02-22 21:25:03,785][01716] Num frames 7800...
[2023-02-22 21:25:03,951][01716] Num frames 7900...
[2023-02-22 21:25:04,112][01716] Num frames 8000...
[2023-02-22 21:25:04,273][01716] Num frames 8100...
[2023-02-22 21:25:04,413][01716] Num frames 8200...
[2023-02-22 21:25:04,525][01716] Num frames 8300...
[2023-02-22 21:25:04,635][01716] Num frames 8400...
[2023-02-22 21:25:04,756][01716] Num frames 8500...
[2023-02-22 21:25:04,870][01716] Num frames 8600...
[2023-02-22 21:25:05,043][01716] Avg episode rewards: #0: 22.330, true rewards: #0: 9.663
[2023-02-22 21:25:05,045][01716] Avg episode reward: 22.330, avg true_objective: 9.663
[2023-02-22 21:25:05,055][01716] Num frames 8700...
[2023-02-22 21:25:05,174][01716] Num frames 8800...
[2023-02-22 21:25:05,297][01716] Num frames 8900...
[2023-02-22 21:25:05,413][01716] Num frames 9000...
[2023-02-22 21:25:05,530][01716] Num frames 9100...
[2023-02-22 21:25:05,642][01716] Num frames 9200...
[2023-02-22 21:25:05,758][01716] Num frames 9300...
[2023-02-22 21:25:05,872][01716] Num frames 9400...
[2023-02-22 21:25:06,009][01716] Num frames 9500...
[2023-02-22 21:25:06,126][01716] Num frames 9600...
[2023-02-22 21:25:06,240][01716] Num frames 9700...
[2023-02-22 21:25:06,355][01716] Num frames 9800...
[2023-02-22 21:25:06,505][01716] Avg episode rewards: #0: 22.881, true rewards: #0: 9.881
[2023-02-22 21:25:06,508][01716] Avg episode reward: 22.881, avg true_objective: 9.881
[2023-02-22 21:26:05,022][01716] Replay video saved to /content/train_dir/default_experiment/replay.mp4!