sf_log.txt

[2024-08-01 07:58:11,807][00459] Saving configuration to /content/train_dir/default_experiment/config.json...
[2024-08-01 07:58:11,810][00459] Rollout worker 0 uses device cpu
[2024-08-01 07:58:11,812][00459] Rollout worker 1 uses device cpu
[2024-08-01 07:58:11,814][00459] Rollout worker 2 uses device cpu
[2024-08-01 07:58:11,815][00459] Rollout worker 3 uses device cpu
[2024-08-01 07:58:11,816][00459] Rollout worker 4 uses device cpu
[2024-08-01 07:58:11,817][00459] Rollout worker 5 uses device cpu
[2024-08-01 07:58:11,818][00459] Rollout worker 6 uses device cpu
[2024-08-01 07:58:11,819][00459] Rollout worker 7 uses device cpu
[2024-08-01 07:58:11,979][00459] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2024-08-01 07:58:11,980][00459] InferenceWorker_p0-w0: min num requests: 2
[2024-08-01 07:58:12,014][00459] Starting all processes...
[2024-08-01 07:58:12,015][00459] Starting process learner_proc0
[2024-08-01 07:58:13,334][00459] Starting all processes...
[2024-08-01 07:58:13,346][00459] Starting process inference_proc0-0
[2024-08-01 07:58:13,346][00459] Starting process rollout_proc0
[2024-08-01 07:58:13,347][00459] Starting process rollout_proc1
[2024-08-01 07:58:13,347][00459] Starting process rollout_proc2
[2024-08-01 07:58:13,347][00459] Starting process rollout_proc3
[2024-08-01 07:58:13,347][00459] Starting process rollout_proc4
[2024-08-01 07:58:13,347][00459] Starting process rollout_proc5
[2024-08-01 07:58:13,347][00459] Starting process rollout_proc6
[2024-08-01 07:58:13,347][00459] Starting process rollout_proc7
[2024-08-01 07:58:28,209][04176] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2024-08-01 07:58:28,210][04176] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0
[2024-08-01 07:58:28,283][04176] Num visible devices: 1
[2024-08-01 07:58:28,318][04192] Worker 2 uses CPU cores [0]
[2024-08-01 07:58:28,322][04176] Starting seed is not provided
[2024-08-01 07:58:28,323][04176] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2024-08-01 07:58:28,324][04176] Initializing actor-critic model on device cuda:0
[2024-08-01 07:58:28,325][04176] RunningMeanStd input shape: (3, 72, 128)
[2024-08-01 07:58:28,327][04176] RunningMeanStd input shape: (1,)
[2024-08-01 07:58:28,344][04193] Worker 3 uses CPU cores [1]
[2024-08-01 07:58:28,393][04190] Worker 1 uses CPU cores [1]
[2024-08-01 07:58:28,405][04196] Worker 6 uses CPU cores [0]
[2024-08-01 07:58:28,414][04176] ConvEncoder: input_channels=3
[2024-08-01 07:58:28,416][04197] Worker 7 uses CPU cores [1]
[2024-08-01 07:58:28,416][04191] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2024-08-01 07:58:28,417][04191] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0
[2024-08-01 07:58:28,461][04194] Worker 4 uses CPU cores [0]
[2024-08-01 07:58:28,470][04191] Num visible devices: 1
[2024-08-01 07:58:28,500][04195] Worker 5 uses CPU cores [1]
[2024-08-01 07:58:28,501][04189] Worker 0 uses CPU cores [0]
[2024-08-01 07:58:28,660][04176] Conv encoder output size: 512
[2024-08-01 07:58:28,661][04176] Policy head output size: 512
[2024-08-01 07:58:28,719][04176] Created Actor Critic model with architecture:
[2024-08-01 07:58:28,719][04176] 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)
  )
)
[2024-08-01 07:58:29,000][04176] Using optimizer <class 'torch.optim.adam.Adam'>
[2024-08-01 07:58:29,793][04176] No checkpoints found
[2024-08-01 07:58:29,794][04176] Did not load from checkpoint, starting from scratch!
[2024-08-01 07:58:29,794][04176] Initialized policy 0 weights for model version 0
[2024-08-01 07:58:29,797][04176] LearnerWorker_p0 finished initialization!
[2024-08-01 07:58:29,798][04176] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2024-08-01 07:58:29,940][04191] RunningMeanStd input shape: (3, 72, 128)
[2024-08-01 07:58:29,941][04191] RunningMeanStd input shape: (1,)
[2024-08-01 07:58:29,956][04191] ConvEncoder: input_channels=3
[2024-08-01 07:58:30,060][04191] Conv encoder output size: 512
[2024-08-01 07:58:30,060][04191] Policy head output size: 512
[2024-08-01 07:58:30,118][00459] Inference worker 0-0 is ready!
[2024-08-01 07:58:30,120][00459] All inference workers are ready! Signal rollout workers to start!
[2024-08-01 07:58:30,367][04197] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,374][04190] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,433][04196] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,429][04193] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,441][04194] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,477][04189] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,480][04195] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,502][04192] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 07:58:30,787][04193] VizDoom game.init() threw an exception ViZDoomUnexpectedExitException('Controlled ViZDoom instance exited unexpectedly.'). Terminate process...
[2024-08-01 07:58:30,791][04193] EvtLoop [rollout_proc3_evt_loop, process=rollout_proc3] unhandled exception in slot='init' connected to emitter=Emitter(object_id='Sampler', signal_name='_inference_workers_initialized'), args=()
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 228, in _game_init
    self.game.init()
vizdoom.vizdoom.ViZDoomUnexpectedExitException: Controlled ViZDoom instance exited unexpectedly.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/signal_slot/signal_slot.py", line 355, in _process_signal
    slot_callable(*args)
  File "/usr/local/lib/python3.10/dist-packages/sample_factory/algo/sampling/rollout_worker.py", line 150, in init
    env_runner.init(self.timing)
  File "/usr/local/lib/python3.10/dist-packages/sample_factory/algo/sampling/non_batched_sampling.py", line 418, in init
    self._reset()
  File "/usr/local/lib/python3.10/dist-packages/sample_factory/algo/sampling/non_batched_sampling.py", line 430, in _reset
    observations, info = e.reset(seed=seed)  # new way of doing seeding since Gym 0.26.0
  File "/usr/local/lib/python3.10/dist-packages/gymnasium/core.py", line 467, in reset
    return self.env.reset(seed=seed, options=options)
  File "/usr/local/lib/python3.10/dist-packages/sample_factory/algo/utils/make_env.py", line 125, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.10/dist-packages/sample_factory/algo/utils/make_env.py", line 110, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.10/dist-packages/sf_examples/vizdoom/doom/wrappers/scenario_wrappers/gathering_reward_shaping.py", line 30, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.10/dist-packages/gymnasium/core.py", line 515, in reset
    obs, info = self.env.reset(seed=seed, options=options)
  File "/usr/local/lib/python3.10/dist-packages/sample_factory/envs/env_wrappers.py", line 82, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.10/dist-packages/gymnasium/core.py", line 467, in reset
    return self.env.reset(seed=seed, options=options)
  File "/usr/local/lib/python3.10/dist-packages/sf_examples/vizdoom/doom/wrappers/multiplayer_stats.py", line 51, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.10/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 323, in reset
    self._ensure_initialized()
  File "/usr/local/lib/python3.10/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 274, in _ensure_initialized
    self.initialize()
  File "/usr/local/lib/python3.10/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 269, in initialize
    self._game_init()
  File "/usr/local/lib/python3.10/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 244, in _game_init
    raise EnvCriticalError()
sample_factory.envs.env_utils.EnvCriticalError
[2024-08-01 07:58:30,804][04193] Unhandled exception  in evt loop rollout_proc3_evt_loop
[2024-08-01 07:58:31,971][00459] Heartbeat connected on Batcher_0
[2024-08-01 07:58:31,977][00459] Heartbeat connected on LearnerWorker_p0
[2024-08-01 07:58:32,017][00459] Heartbeat connected on InferenceWorker_p0-w0
[2024-08-01 07:58:32,031][04196] Decorrelating experience for 0 frames...
[2024-08-01 07:58:32,032][04194] Decorrelating experience for 0 frames...
[2024-08-01 07:58:32,031][04192] Decorrelating experience for 0 frames...
[2024-08-01 07:58:32,034][04190] Decorrelating experience for 0 frames...
[2024-08-01 07:58:32,033][04197] Decorrelating experience for 0 frames...
[2024-08-01 07:58:33,023][04196] Decorrelating experience for 32 frames...
[2024-08-01 07:58:33,032][04194] Decorrelating experience for 32 frames...
[2024-08-01 07:58:33,037][04192] Decorrelating experience for 32 frames...
[2024-08-01 07:58:33,097][04189] Decorrelating experience for 0 frames...
[2024-08-01 07:58:33,801][04197] Decorrelating experience for 32 frames...
[2024-08-01 07:58:33,904][04195] Decorrelating experience for 0 frames...
[2024-08-01 07:58:34,022][00459] 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)
[2024-08-01 07:58:34,101][04189] Decorrelating experience for 32 frames...
[2024-08-01 07:58:34,451][04196] Decorrelating experience for 64 frames...
[2024-08-01 07:58:34,779][04190] Decorrelating experience for 32 frames...
[2024-08-01 07:58:35,133][04197] Decorrelating experience for 64 frames...
[2024-08-01 07:58:35,228][04192] Decorrelating experience for 64 frames...
[2024-08-01 07:58:35,416][04194] Decorrelating experience for 64 frames...
[2024-08-01 07:58:35,642][04195] Decorrelating experience for 32 frames...
[2024-08-01 07:58:35,869][04189] Decorrelating experience for 64 frames...
[2024-08-01 07:58:36,287][04197] Decorrelating experience for 96 frames...
[2024-08-01 07:58:36,431][00459] Heartbeat connected on RolloutWorker_w7
[2024-08-01 07:58:37,370][04196] Decorrelating experience for 96 frames...
[2024-08-01 07:58:37,526][04194] Decorrelating experience for 96 frames...
[2024-08-01 07:58:37,651][00459] Heartbeat connected on RolloutWorker_w6
[2024-08-01 07:58:37,679][04192] Decorrelating experience for 96 frames...
[2024-08-01 07:58:37,823][00459] Heartbeat connected on RolloutWorker_w4
[2024-08-01 07:58:37,938][00459] Heartbeat connected on RolloutWorker_w2
[2024-08-01 07:58:37,994][04189] Decorrelating experience for 96 frames...
[2024-08-01 07:58:38,284][00459] Heartbeat connected on RolloutWorker_w0
[2024-08-01 07:58:39,016][00459] 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)
[2024-08-01 07:58:39,021][00459] Avg episode reward: [(0, '0.320')]
[2024-08-01 07:58:39,038][04190] Decorrelating experience for 64 frames...
[2024-08-01 07:58:42,122][04195] Decorrelating experience for 64 frames...
[2024-08-01 07:58:42,485][04190] Decorrelating experience for 96 frames...
[2024-08-01 07:58:43,332][00459] Heartbeat connected on RolloutWorker_w1
[2024-08-01 07:58:43,767][04176] Signal inference workers to stop experience collection...
[2024-08-01 07:58:43,776][04191] InferenceWorker_p0-w0: stopping experience collection
[2024-08-01 07:58:44,016][00459] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 168.9. Samples: 1688. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2024-08-01 07:58:44,018][00459] Avg episode reward: [(0, '2.516')]
[2024-08-01 07:58:44,137][04195] Decorrelating experience for 96 frames...
[2024-08-01 07:58:44,222][00459] Heartbeat connected on RolloutWorker_w5
[2024-08-01 07:58:46,184][04176] Signal inference workers to resume experience collection...
[2024-08-01 07:58:46,186][04191] InferenceWorker_p0-w0: resuming experience collection
[2024-08-01 07:58:49,016][00459] Fps is (10 sec: 1638.4, 60 sec: 1092.7, 300 sec: 1092.7). Total num frames: 16384. Throughput: 0: 258.0. Samples: 3868. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 07:58:49,018][00459] Avg episode reward: [(0, '3.183')]
[2024-08-01 07:58:54,019][00459] Fps is (10 sec: 3275.9, 60 sec: 1638.7, 300 sec: 1638.7). Total num frames: 32768. Throughput: 0: 354.9. Samples: 7096. Policy #0 lag: (min: 0.0, avg: 0.3, max: 2.0)
[2024-08-01 07:58:54,025][00459] Avg episode reward: [(0, '3.715')]
[2024-08-01 07:58:55,692][04191] Updated weights for policy 0, policy_version 10 (0.0206)
[2024-08-01 07:58:59,016][00459] Fps is (10 sec: 3276.8, 60 sec: 1966.5, 300 sec: 1966.5). Total num frames: 49152. Throughput: 0: 464.9. Samples: 11620. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 07:58:59,024][00459] Avg episode reward: [(0, '4.198')]
[2024-08-01 07:59:04,016][00459] Fps is (10 sec: 3687.2, 60 sec: 2321.5, 300 sec: 2321.5). Total num frames: 69632. Throughput: 0: 570.2. Samples: 17102. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 07:59:04,021][00459] Avg episode reward: [(0, '4.339')]
[2024-08-01 07:59:06,846][04191] Updated weights for policy 0, policy_version 20 (0.0034)
[2024-08-01 07:59:09,016][00459] Fps is (10 sec: 4096.0, 60 sec: 2575.1, 300 sec: 2575.1). Total num frames: 90112. Throughput: 0: 581.2. Samples: 20340. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 07:59:09,020][00459] Avg episode reward: [(0, '4.327')]
[2024-08-01 07:59:14,016][00459] Fps is (10 sec: 3277.0, 60 sec: 2560.4, 300 sec: 2560.4). Total num frames: 102400. Throughput: 0: 642.3. Samples: 25690. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 07:59:14,025][00459] Avg episode reward: [(0, '4.333')]
[2024-08-01 07:59:14,033][04176] Saving new best policy, reward=4.333!
[2024-08-01 07:59:19,016][00459] Fps is (10 sec: 2867.0, 60 sec: 2639.9, 300 sec: 2639.9). Total num frames: 118784. Throughput: 0: 665.0. Samples: 29922. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 07:59:19,019][00459] Avg episode reward: [(0, '4.239')]
[2024-08-01 07:59:19,358][04191] Updated weights for policy 0, policy_version 30 (0.0020)
[2024-08-01 07:59:24,016][00459] Fps is (10 sec: 3686.4, 60 sec: 2785.6, 300 sec: 2785.6). Total num frames: 139264. Throughput: 0: 733.5. Samples: 33008. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 07:59:24,023][00459] Avg episode reward: [(0, '4.183')]
[2024-08-01 07:59:29,016][00459] Fps is (10 sec: 4096.3, 60 sec: 2904.7, 300 sec: 2904.7). Total num frames: 159744. Throughput: 0: 834.0. Samples: 39220. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 07:59:29,023][00459] Avg episode reward: [(0, '4.409')]
[2024-08-01 07:59:29,026][04176] Saving new best policy, reward=4.409!
[2024-08-01 07:59:30,588][04191] Updated weights for policy 0, policy_version 40 (0.0034)
[2024-08-01 07:59:34,016][00459] Fps is (10 sec: 3276.8, 60 sec: 2867.5, 300 sec: 2867.5). Total num frames: 172032. Throughput: 0: 873.3. Samples: 43168. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 07:59:34,023][00459] Avg episode reward: [(0, '4.514')]
[2024-08-01 07:59:34,032][04176] Saving new best policy, reward=4.514!
[2024-08-01 07:59:39,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3208.5, 300 sec: 2962.0). Total num frames: 192512. Throughput: 0: 869.7. Samples: 46228. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 07:59:39,020][00459] Avg episode reward: [(0, '4.534')]
[2024-08-01 07:59:39,028][04176] Saving new best policy, reward=4.534!
[2024-08-01 07:59:41,194][04191] Updated weights for policy 0, policy_version 50 (0.0023)
[2024-08-01 07:59:44,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3043.0). Total num frames: 212992. Throughput: 0: 913.2. Samples: 52716. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 07:59:44,020][00459] Avg episode reward: [(0, '4.341')]
[2024-08-01 07:59:49,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3004.0). Total num frames: 225280. Throughput: 0: 886.3. Samples: 56986. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 07:59:49,022][00459] Avg episode reward: [(0, '4.326')]
[2024-08-01 07:59:53,457][04191] Updated weights for policy 0, policy_version 60 (0.0032)
[2024-08-01 07:59:54,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3072.2). Total num frames: 245760. Throughput: 0: 866.1. Samples: 59314. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 07:59:54,021][00459] Avg episode reward: [(0, '4.397')]
[2024-08-01 07:59:59,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3132.4). Total num frames: 266240. Throughput: 0: 895.6. Samples: 65992. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 07:59:59,020][00459] Avg episode reward: [(0, '4.396')]
[2024-08-01 08:00:04,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3140.5). Total num frames: 282624. Throughput: 0: 919.0. Samples: 71278. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:00:04,021][00459] Avg episode reward: [(0, '4.288')]
[2024-08-01 08:00:04,031][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000069_282624.pth...
[2024-08-01 08:00:04,557][04191] Updated weights for policy 0, policy_version 70 (0.0020)
[2024-08-01 08:00:09,016][00459] Fps is (10 sec: 3276.7, 60 sec: 3481.6, 300 sec: 3147.6). Total num frames: 299008. Throughput: 0: 891.5. Samples: 73124. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:00:09,018][00459] Avg episode reward: [(0, '4.162')]
[2024-08-01 08:00:14,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3195.1). Total num frames: 319488. Throughput: 0: 885.9. Samples: 79086. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2024-08-01 08:00:14,019][00459] Avg episode reward: [(0, '4.052')]
[2024-08-01 08:00:15,291][04191] Updated weights for policy 0, policy_version 80 (0.0018)
[2024-08-01 08:00:19,018][00459] Fps is (10 sec: 4095.3, 60 sec: 3686.3, 300 sec: 3237.9). Total num frames: 339968. Throughput: 0: 931.2. Samples: 85072. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:00:19,020][00459] Avg episode reward: [(0, '4.248')]
[2024-08-01 08:00:24,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3202.5). Total num frames: 352256. Throughput: 0: 907.8. Samples: 87078. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:00:24,018][00459] Avg episode reward: [(0, '4.380')]
[2024-08-01 08:00:27,365][04191] Updated weights for policy 0, policy_version 90 (0.0018)
[2024-08-01 08:00:29,016][00459] Fps is (10 sec: 3277.4, 60 sec: 3549.9, 300 sec: 3241.3). Total num frames: 372736. Throughput: 0: 879.5. Samples: 92292. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:00:29,021][00459] Avg episode reward: [(0, '4.550')]
[2024-08-01 08:00:29,024][04176] Saving new best policy, reward=4.550!
[2024-08-01 08:00:34,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3277.0). Total num frames: 393216. Throughput: 0: 926.0. Samples: 98656. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:00:34,025][00459] Avg episode reward: [(0, '4.737')]
[2024-08-01 08:00:34,035][04176] Saving new best policy, reward=4.737!
[2024-08-01 08:00:39,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3244.2). Total num frames: 405504. Throughput: 0: 921.8. Samples: 100794. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:00:39,024][00459] Avg episode reward: [(0, '4.645')]
[2024-08-01 08:00:39,552][04191] Updated weights for policy 0, policy_version 100 (0.0025)
[2024-08-01 08:00:44,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3245.4). Total num frames: 421888. Throughput: 0: 866.3. Samples: 104974. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:00:44,027][00459] Avg episode reward: [(0, '4.697')]
[2024-08-01 08:00:49,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3276.9). Total num frames: 442368. Throughput: 0: 884.4. Samples: 111074. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:00:49,022][00459] Avg episode reward: [(0, '4.542')]
[2024-08-01 08:00:50,079][04191] Updated weights for policy 0, policy_version 110 (0.0025)
[2024-08-01 08:00:54,020][00459] Fps is (10 sec: 3685.0, 60 sec: 3549.6, 300 sec: 3276.8). Total num frames: 458752. Throughput: 0: 910.9. Samples: 114118. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:00:54,023][00459] Avg episode reward: [(0, '4.500')]
[2024-08-01 08:00:59,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3276.9). Total num frames: 475136. Throughput: 0: 862.9. Samples: 117918. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:00:59,018][00459] Avg episode reward: [(0, '4.317')]
[2024-08-01 08:01:02,724][04191] Updated weights for policy 0, policy_version 120 (0.0023)
[2024-08-01 08:01:04,016][00459] Fps is (10 sec: 3687.8, 60 sec: 3549.9, 300 sec: 3304.2). Total num frames: 495616. Throughput: 0: 861.9. Samples: 123858. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:01:04,018][00459] Avg episode reward: [(0, '4.274')]
[2024-08-01 08:01:09,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3618.2, 300 sec: 3329.8). Total num frames: 516096. Throughput: 0: 887.8. Samples: 127028. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:01:09,018][00459] Avg episode reward: [(0, '4.182')]
[2024-08-01 08:01:14,017][00459] Fps is (10 sec: 3276.2, 60 sec: 3481.5, 300 sec: 3302.5). Total num frames: 528384. Throughput: 0: 874.0. Samples: 131624. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:01:14,023][00459] Avg episode reward: [(0, '4.464')]
[2024-08-01 08:01:15,071][04191] Updated weights for policy 0, policy_version 130 (0.0018)
[2024-08-01 08:01:19,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3413.4, 300 sec: 3301.7). Total num frames: 544768. Throughput: 0: 847.9. Samples: 136810. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:01:19,022][00459] Avg episode reward: [(0, '4.518')]
[2024-08-01 08:01:24,016][00459] Fps is (10 sec: 4096.7, 60 sec: 3618.1, 300 sec: 3349.2). Total num frames: 569344. Throughput: 0: 871.9. Samples: 140028. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:01:24,018][00459] Avg episode reward: [(0, '4.621')]
[2024-08-01 08:01:24,695][04191] Updated weights for policy 0, policy_version 140 (0.0028)
[2024-08-01 08:01:29,016][00459] Fps is (10 sec: 4095.7, 60 sec: 3549.8, 300 sec: 3347.1). Total num frames: 585728. Throughput: 0: 902.0. Samples: 145566. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:01:29,020][00459] Avg episode reward: [(0, '4.790')]
[2024-08-01 08:01:29,022][04176] Saving new best policy, reward=4.790!
[2024-08-01 08:01:34,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3322.4). Total num frames: 598016. Throughput: 0: 864.3. Samples: 149968. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:01:34,018][00459] Avg episode reward: [(0, '4.630')]
[2024-08-01 08:01:36,765][04191] Updated weights for policy 0, policy_version 150 (0.0019)
[2024-08-01 08:01:39,016][00459] Fps is (10 sec: 3686.7, 60 sec: 3618.1, 300 sec: 3365.5). Total num frames: 622592. Throughput: 0: 867.5. Samples: 153152. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:01:39,018][00459] Avg episode reward: [(0, '4.397')]
[2024-08-01 08:01:44,017][00459] Fps is (10 sec: 4095.3, 60 sec: 3618.0, 300 sec: 3363.1). Total num frames: 638976. Throughput: 0: 923.0. Samples: 159456. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:01:44,020][00459] Avg episode reward: [(0, '4.361')]
[2024-08-01 08:01:49,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3339.9). Total num frames: 651264. Throughput: 0: 878.0. Samples: 163368. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:01:49,020][00459] Avg episode reward: [(0, '4.421')]
[2024-08-01 08:01:49,098][04191] Updated weights for policy 0, policy_version 160 (0.0031)
[2024-08-01 08:01:54,016][00459] Fps is (10 sec: 3687.0, 60 sec: 3618.4, 300 sec: 3379.3). Total num frames: 675840. Throughput: 0: 875.4. Samples: 166422. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:01:54,022][00459] Avg episode reward: [(0, '4.629')]
[2024-08-01 08:01:58,871][04191] Updated weights for policy 0, policy_version 170 (0.0029)
[2024-08-01 08:01:59,019][00459] Fps is (10 sec: 4504.3, 60 sec: 3686.2, 300 sec: 3396.7). Total num frames: 696320. Throughput: 0: 915.4. Samples: 172818. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:01:59,021][00459] Avg episode reward: [(0, '4.490')]
[2024-08-01 08:02:04,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3374.4). Total num frames: 708608. Throughput: 0: 901.9. Samples: 177394. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:02:04,022][00459] Avg episode reward: [(0, '4.435')]
[2024-08-01 08:02:04,032][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000173_708608.pth...
[2024-08-01 08:02:09,016][00459] Fps is (10 sec: 2868.0, 60 sec: 3481.6, 300 sec: 3372.1). Total num frames: 724992. Throughput: 0: 882.0. Samples: 179720. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:02:09,024][00459] Avg episode reward: [(0, '4.504')]
[2024-08-01 08:02:10,917][04191] Updated weights for policy 0, policy_version 180 (0.0014)
[2024-08-01 08:02:14,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.5, 300 sec: 3407.2). Total num frames: 749568. Throughput: 0: 901.2. Samples: 186118. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:02:14,022][00459] Avg episode reward: [(0, '4.402')]
[2024-08-01 08:02:19,020][00459] Fps is (10 sec: 3685.0, 60 sec: 3617.9, 300 sec: 3386.1). Total num frames: 761856. Throughput: 0: 920.3. Samples: 191384. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:02:19,023][00459] Avg episode reward: [(0, '4.380')]
[2024-08-01 08:02:23,124][04191] Updated weights for policy 0, policy_version 190 (0.0044)
[2024-08-01 08:02:24,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3383.7). Total num frames: 778240. Throughput: 0: 891.8. Samples: 193284. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:02:24,018][00459] Avg episode reward: [(0, '4.412')]
[2024-08-01 08:02:29,016][00459] Fps is (10 sec: 4097.6, 60 sec: 3618.2, 300 sec: 3416.3). Total num frames: 802816. Throughput: 0: 885.3. Samples: 199292. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:02:29,017][00459] Avg episode reward: [(0, '4.601')]
[2024-08-01 08:02:33,130][04191] Updated weights for policy 0, policy_version 200 (0.0022)
[2024-08-01 08:02:34,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3686.4, 300 sec: 3413.4). Total num frames: 819200. Throughput: 0: 933.1. Samples: 205360. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:02:34,020][00459] Avg episode reward: [(0, '4.562')]
[2024-08-01 08:02:39,019][00459] Fps is (10 sec: 2866.4, 60 sec: 3481.4, 300 sec: 3393.9). Total num frames: 831488. Throughput: 0: 907.1. Samples: 207246. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:02:39,021][00459] Avg episode reward: [(0, '4.592')]
[2024-08-01 08:02:44,016][00459] Fps is (10 sec: 3686.5, 60 sec: 3618.2, 300 sec: 3424.3). Total num frames: 856064. Throughput: 0: 882.1. Samples: 212508. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:02:44,018][00459] Avg episode reward: [(0, '4.480')]
[2024-08-01 08:02:45,003][04191] Updated weights for policy 0, policy_version 210 (0.0022)
[2024-08-01 08:02:49,016][00459] Fps is (10 sec: 4506.9, 60 sec: 3754.7, 300 sec: 3437.5). Total num frames: 876544. Throughput: 0: 918.0. Samples: 218704. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:02:49,021][00459] Avg episode reward: [(0, '4.716')]
[2024-08-01 08:02:54,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3418.7). Total num frames: 888832. Throughput: 0: 918.1. Samples: 221034. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:02:54,019][00459] Avg episode reward: [(0, '4.852')]
[2024-08-01 08:02:54,027][04176] Saving new best policy, reward=4.852!
[2024-08-01 08:02:57,467][04191] Updated weights for policy 0, policy_version 220 (0.0022)
[2024-08-01 08:02:59,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3481.8, 300 sec: 3416.0). Total num frames: 905216. Throughput: 0: 870.5. Samples: 225290. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:02:59,022][00459] Avg episode reward: [(0, '4.842')]
[2024-08-01 08:03:04,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3428.6). Total num frames: 925696. Throughput: 0: 886.6. Samples: 231276. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:03:04,018][00459] Avg episode reward: [(0, '4.945')]
[2024-08-01 08:03:04,030][04176] Saving new best policy, reward=4.945!
[2024-08-01 08:03:09,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3410.9). Total num frames: 937984. Throughput: 0: 905.9. Samples: 234048. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:03:09,021][00459] Avg episode reward: [(0, '4.811')]
[2024-08-01 08:03:09,280][04191] Updated weights for policy 0, policy_version 230 (0.0032)
[2024-08-01 08:03:14,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3408.5). Total num frames: 954368. Throughput: 0: 855.9. Samples: 237806. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:03:14,022][00459] Avg episode reward: [(0, '4.889')]
[2024-08-01 08:03:19,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3550.1, 300 sec: 3420.6). Total num frames: 974848. Throughput: 0: 847.2. Samples: 243482. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:03:19,018][00459] Avg episode reward: [(0, '4.773')]
[2024-08-01 08:03:20,721][04191] Updated weights for policy 0, policy_version 240 (0.0030)
[2024-08-01 08:03:24,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3418.1). Total num frames: 991232. Throughput: 0: 874.4. Samples: 246592. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:03:24,026][00459] Avg episode reward: [(0, '4.800')]
[2024-08-01 08:03:29,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3345.1, 300 sec: 3401.8). Total num frames: 1003520. Throughput: 0: 853.8. Samples: 250930. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:03:29,023][00459] Avg episode reward: [(0, '4.625')]
[2024-08-01 08:03:33,363][04191] Updated weights for policy 0, policy_version 250 (0.0026)
[2024-08-01 08:03:34,016][00459] Fps is (10 sec: 3276.7, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 1024000. Throughput: 0: 834.1. Samples: 256240. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:03:34,022][00459] Avg episode reward: [(0, '4.535')]
[2024-08-01 08:03:39,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3550.0, 300 sec: 3540.6). Total num frames: 1044480. Throughput: 0: 852.1. Samples: 259378. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:03:39,018][00459] Avg episode reward: [(0, '4.694')]
[2024-08-01 08:03:44,016][00459] Fps is (10 sec: 3686.5, 60 sec: 3413.3, 300 sec: 3540.6). Total num frames: 1060864. Throughput: 0: 874.9. Samples: 264660. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:03:44,019][00459] Avg episode reward: [(0, '4.799')]
[2024-08-01 08:03:45,259][04191] Updated weights for policy 0, policy_version 260 (0.0022)
[2024-08-01 08:03:49,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3345.1, 300 sec: 3540.6). Total num frames: 1077248. Throughput: 0: 841.2. Samples: 269132. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:03:49,018][00459] Avg episode reward: [(0, '4.876')]
[2024-08-01 08:03:54,018][00459] Fps is (10 sec: 3685.7, 60 sec: 3481.5, 300 sec: 3554.5). Total num frames: 1097728. Throughput: 0: 850.1. Samples: 272304. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:03:54,020][00459] Avg episode reward: [(0, '4.906')]
[2024-08-01 08:03:55,413][04191] Updated weights for policy 0, policy_version 270 (0.0025)
[2024-08-01 08:03:59,017][00459] Fps is (10 sec: 3686.1, 60 sec: 3481.6, 300 sec: 3540.6). Total num frames: 1114112. Throughput: 0: 908.9. Samples: 278706. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:03:59,019][00459] Avg episode reward: [(0, '5.143')]
[2024-08-01 08:03:59,025][04176] Saving new best policy, reward=5.143!
[2024-08-01 08:04:04,016][00459] Fps is (10 sec: 3277.4, 60 sec: 3413.3, 300 sec: 3526.7). Total num frames: 1130496. Throughput: 0: 869.2. Samples: 282598. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:04:04,020][00459] Avg episode reward: [(0, '5.008')]
[2024-08-01 08:04:04,029][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000276_1130496.pth...
[2024-08-01 08:04:04,137][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000069_282624.pth
[2024-08-01 08:04:07,802][04191] Updated weights for policy 0, policy_version 280 (0.0020)
[2024-08-01 08:04:09,016][00459] Fps is (10 sec: 3686.7, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 1150976. Throughput: 0: 863.9. Samples: 285466. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:04:09,021][00459] Avg episode reward: [(0, '5.023')]
[2024-08-01 08:04:14,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 1171456. Throughput: 0: 910.7. Samples: 291912. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:04:14,018][00459] Avg episode reward: [(0, '5.223')]
[2024-08-01 08:04:14,038][04176] Saving new best policy, reward=5.223!
[2024-08-01 08:04:19,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3540.6). Total num frames: 1183744. Throughput: 0: 889.1. Samples: 296250. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2024-08-01 08:04:19,018][00459] Avg episode reward: [(0, '5.324')]
[2024-08-01 08:04:19,020][04176] Saving new best policy, reward=5.324!
[2024-08-01 08:04:20,143][04191] Updated weights for policy 0, policy_version 290 (0.0020)
[2024-08-01 08:04:24,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3526.7). Total num frames: 1200128. Throughput: 0: 865.3. Samples: 298316. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:04:24,018][00459] Avg episode reward: [(0, '4.991')]
[2024-08-01 08:04:29,017][00459] Fps is (10 sec: 4095.6, 60 sec: 3686.4, 300 sec: 3568.4). Total num frames: 1224704. Throughput: 0: 892.0. Samples: 304802. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2024-08-01 08:04:29,020][00459] Avg episode reward: [(0, '4.825')]
[2024-08-01 08:04:29,655][04191] Updated weights for policy 0, policy_version 300 (0.0035)
[2024-08-01 08:04:34,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 1241088. Throughput: 0: 917.3. Samples: 310410. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2024-08-01 08:04:34,022][00459] Avg episode reward: [(0, '4.710')]
[2024-08-01 08:04:39,016][00459] Fps is (10 sec: 2867.4, 60 sec: 3481.6, 300 sec: 3526.7). Total num frames: 1253376. Throughput: 0: 891.4. Samples: 312414. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:04:39,020][00459] Avg episode reward: [(0, '4.869')]
[2024-08-01 08:04:41,664][04191] Updated weights for policy 0, policy_version 310 (0.0015)
[2024-08-01 08:04:44,016][00459] Fps is (10 sec: 3686.5, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 1277952. Throughput: 0: 878.6. Samples: 318244. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:04:44,018][00459] Avg episode reward: [(0, '4.779')]
[2024-08-01 08:04:49,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 1294336. Throughput: 0: 933.8. Samples: 324620. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:04:49,023][00459] Avg episode reward: [(0, '4.997')]
[2024-08-01 08:04:53,515][04191] Updated weights for policy 0, policy_version 320 (0.0021)
[2024-08-01 08:04:54,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3540.6). Total num frames: 1310720. Throughput: 0: 910.2. Samples: 326424. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:04:54,024][00459] Avg episode reward: [(0, '5.023')]
[2024-08-01 08:04:59,016][00459] Fps is (10 sec: 3686.5, 60 sec: 3618.2, 300 sec: 3554.5). Total num frames: 1331200. Throughput: 0: 879.5. Samples: 331490. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:04:59,022][00459] Avg episode reward: [(0, '4.877')]
[2024-08-01 08:05:03,609][04191] Updated weights for policy 0, policy_version 330 (0.0018)
[2024-08-01 08:05:04,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3568.4). Total num frames: 1351680. Throughput: 0: 926.8. Samples: 337954. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:05:04,021][00459] Avg episode reward: [(0, '4.738')]
[2024-08-01 08:05:09,017][00459] Fps is (10 sec: 3276.5, 60 sec: 3549.8, 300 sec: 3540.6). Total num frames: 1363968. Throughput: 0: 937.0. Samples: 340480. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:05:09,025][00459] Avg episode reward: [(0, '4.813')]
[2024-08-01 08:05:14,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3540.6). Total num frames: 1384448. Throughput: 0: 889.8. Samples: 344844. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:05:14,018][00459] Avg episode reward: [(0, '5.080')]
[2024-08-01 08:05:15,592][04191] Updated weights for policy 0, policy_version 340 (0.0024)
[2024-08-01 08:05:19,016][00459] Fps is (10 sec: 4096.4, 60 sec: 3686.4, 300 sec: 3568.4). Total num frames: 1404928. Throughput: 0: 911.2. Samples: 351412. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:05:19,019][00459] Avg episode reward: [(0, '5.289')]
[2024-08-01 08:05:24,017][00459] Fps is (10 sec: 3685.9, 60 sec: 3686.3, 300 sec: 3554.5). Total num frames: 1421312. Throughput: 0: 936.4. Samples: 354554. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:05:24,021][00459] Avg episode reward: [(0, '5.530')]
[2024-08-01 08:05:24,032][04176] Saving new best policy, reward=5.530!
[2024-08-01 08:05:27,772][04191] Updated weights for policy 0, policy_version 350 (0.0029)
[2024-08-01 08:05:29,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3540.6). Total num frames: 1437696. Throughput: 0: 893.8. Samples: 358466. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:05:29,018][00459] Avg episode reward: [(0, '5.450')]
[2024-08-01 08:05:34,016][00459] Fps is (10 sec: 3687.0, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 1458176. Throughput: 0: 889.7. Samples: 364654. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:05:34,020][00459] Avg episode reward: [(0, '5.401')]
[2024-08-01 08:05:37,290][04191] Updated weights for policy 0, policy_version 360 (0.0016)
[2024-08-01 08:05:39,021][00459] Fps is (10 sec: 4094.0, 60 sec: 3754.4, 300 sec: 3582.2). Total num frames: 1478656. Throughput: 0: 920.8. Samples: 367866. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:05:39,028][00459] Avg episode reward: [(0, '5.666')]
[2024-08-01 08:05:39,036][04176] Saving new best policy, reward=5.666!
[2024-08-01 08:05:44,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 1490944. Throughput: 0: 912.3. Samples: 372544. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:05:44,020][00459] Avg episode reward: [(0, '5.786')]
[2024-08-01 08:05:44,029][04176] Saving new best policy, reward=5.786!
[2024-08-01 08:05:49,016][00459] Fps is (10 sec: 3278.4, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 1511424. Throughput: 0: 887.6. Samples: 377896. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:05:49,023][00459] Avg episode reward: [(0, '6.202')]
[2024-08-01 08:05:49,028][04176] Saving new best policy, reward=6.202!
[2024-08-01 08:05:49,654][04191] Updated weights for policy 0, policy_version 370 (0.0024)
[2024-08-01 08:05:54,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3582.3). Total num frames: 1531904. Throughput: 0: 895.0. Samples: 380754. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:05:54,022][00459] Avg episode reward: [(0, '5.799')]
[2024-08-01 08:05:59,030][00459] Fps is (10 sec: 3272.2, 60 sec: 3549.0, 300 sec: 3554.3). Total num frames: 1544192. Throughput: 0: 918.2. Samples: 386174. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:05:59,038][00459] Avg episode reward: [(0, '5.557')]
[2024-08-01 08:06:02,107][04191] Updated weights for policy 0, policy_version 380 (0.0020)
[2024-08-01 08:06:04,016][00459] Fps is (10 sec: 2867.1, 60 sec: 3481.6, 300 sec: 3540.6). Total num frames: 1560576. Throughput: 0: 872.4. Samples: 390672. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:06:04,019][00459] Avg episode reward: [(0, '5.434')]
[2024-08-01 08:06:04,030][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000381_1560576.pth...
[2024-08-01 08:06:04,156][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000173_708608.pth
[2024-08-01 08:06:09,016][00459] Fps is (10 sec: 4101.7, 60 sec: 3686.5, 300 sec: 3582.3). Total num frames: 1585152. Throughput: 0: 876.3. Samples: 393986. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:06:09,019][00459] Avg episode reward: [(0, '5.939')]
[2024-08-01 08:06:11,528][04191] Updated weights for policy 0, policy_version 390 (0.0022)
[2024-08-01 08:06:14,016][00459] Fps is (10 sec: 4096.1, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 1601536. Throughput: 0: 931.3. Samples: 400374. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:06:14,018][00459] Avg episode reward: [(0, '6.391')]
[2024-08-01 08:06:14,028][04176] Saving new best policy, reward=6.391!
[2024-08-01 08:06:19,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 1617920. Throughput: 0: 880.2. Samples: 404264. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:06:19,019][00459] Avg episode reward: [(0, '6.110')]
[2024-08-01 08:06:23,616][04191] Updated weights for policy 0, policy_version 400 (0.0031)
[2024-08-01 08:06:24,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 1638400. Throughput: 0: 875.6. Samples: 407262. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:06:24,019][00459] Avg episode reward: [(0, '5.967')]
[2024-08-01 08:06:29,019][00459] Fps is (10 sec: 4094.9, 60 sec: 3686.2, 300 sec: 3596.1). Total num frames: 1658880. Throughput: 0: 914.8. Samples: 413712. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:06:29,020][00459] Avg episode reward: [(0, '5.779')]
[2024-08-01 08:06:34,020][00459] Fps is (10 sec: 3275.4, 60 sec: 3549.6, 300 sec: 3554.4). Total num frames: 1671168. Throughput: 0: 897.8. Samples: 418302. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:06:34,023][00459] Avg episode reward: [(0, '5.980')]
[2024-08-01 08:06:35,813][04191] Updated weights for policy 0, policy_version 410 (0.0019)
[2024-08-01 08:06:39,016][00459] Fps is (10 sec: 3277.7, 60 sec: 3550.2, 300 sec: 3568.4). Total num frames: 1691648. Throughput: 0: 888.7. Samples: 420746. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:06:39,019][00459] Avg episode reward: [(0, '6.045')]
[2024-08-01 08:06:44,016][00459] Fps is (10 sec: 4097.7, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 1712128. Throughput: 0: 914.3. Samples: 427304. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:06:44,020][00459] Avg episode reward: [(0, '5.633')]
[2024-08-01 08:06:45,074][04191] Updated weights for policy 0, policy_version 420 (0.0027)
[2024-08-01 08:06:49,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 1728512. Throughput: 0: 932.1. Samples: 432614. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:06:49,021][00459] Avg episode reward: [(0, '5.823')]
[2024-08-01 08:06:54,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 1744896. Throughput: 0: 901.2. Samples: 434542. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:06:54,022][00459] Avg episode reward: [(0, '6.130')]
[2024-08-01 08:06:57,454][04191] Updated weights for policy 0, policy_version 430 (0.0039)
[2024-08-01 08:06:59,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3687.3, 300 sec: 3582.3). Total num frames: 1765376. Throughput: 0: 894.5. Samples: 440626. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:06:59,019][00459] Avg episode reward: [(0, '6.566')]
[2024-08-01 08:06:59,026][04176] Saving new best policy, reward=6.566!
[2024-08-01 08:07:04,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3754.7, 300 sec: 3596.1). Total num frames: 1785856. Throughput: 0: 942.2. Samples: 446662. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:07:04,022][00459] Avg episode reward: [(0, '6.616')]
[2024-08-01 08:07:04,035][04176] Saving new best policy, reward=6.616!
[2024-08-01 08:07:09,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 1798144. Throughput: 0: 917.1. Samples: 448530. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:07:09,018][00459] Avg episode reward: [(0, '6.690')]
[2024-08-01 08:07:09,020][04176] Saving new best policy, reward=6.690!
[2024-08-01 08:07:09,478][04191] Updated weights for policy 0, policy_version 440 (0.0024)
[2024-08-01 08:07:14,016][00459] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 1818624. Throughput: 0: 891.8. Samples: 453840. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2024-08-01 08:07:14,018][00459] Avg episode reward: [(0, '7.230')]
[2024-08-01 08:07:14,030][04176] Saving new best policy, reward=7.230!
[2024-08-01 08:07:19,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 1839104. Throughput: 0: 932.9. Samples: 460278. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:07:19,019][00459] Avg episode reward: [(0, '7.593')]
[2024-08-01 08:07:19,021][04176] Saving new best policy, reward=7.593!
[2024-08-01 08:07:19,388][04191] Updated weights for policy 0, policy_version 450 (0.0025)
[2024-08-01 08:07:24,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 1855488. Throughput: 0: 929.9. Samples: 462592. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:07:24,018][00459] Avg episode reward: [(0, '7.827')]
[2024-08-01 08:07:24,028][04176] Saving new best policy, reward=7.827!
[2024-08-01 08:07:29,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3568.4). Total num frames: 1871872. Throughput: 0: 882.0. Samples: 466994. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:07:29,018][00459] Avg episode reward: [(0, '7.693')]
[2024-08-01 08:07:31,359][04191] Updated weights for policy 0, policy_version 460 (0.0018)
[2024-08-01 08:07:34,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3754.9, 300 sec: 3610.1). Total num frames: 1896448. Throughput: 0: 910.8. Samples: 473600. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:07:34,023][00459] Avg episode reward: [(0, '8.269')]
[2024-08-01 08:07:34,034][04176] Saving new best policy, reward=8.269!
[2024-08-01 08:07:39,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 1908736. Throughput: 0: 940.3. Samples: 476854. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:07:39,018][00459] Avg episode reward: [(0, '8.350')]
[2024-08-01 08:07:39,023][04176] Saving new best policy, reward=8.350!
[2024-08-01 08:07:43,296][04191] Updated weights for policy 0, policy_version 470 (0.0035)
[2024-08-01 08:07:44,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 1925120. Throughput: 0: 893.2. Samples: 480820. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:07:44,018][00459] Avg episode reward: [(0, '8.624')]
[2024-08-01 08:07:44,039][04176] Saving new best policy, reward=8.624!
[2024-08-01 08:07:49,016][00459] Fps is (10 sec: 4095.7, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 1949696. Throughput: 0: 894.0. Samples: 486892. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:07:49,018][00459] Avg episode reward: [(0, '8.541')]
[2024-08-01 08:07:52,885][04191] Updated weights for policy 0, policy_version 480 (0.0031)
[2024-08-01 08:07:54,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 1966080. Throughput: 0: 926.2. Samples: 490208. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2024-08-01 08:07:54,018][00459] Avg episode reward: [(0, '8.467')]
[2024-08-01 08:07:59,016][00459] Fps is (10 sec: 2867.4, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 1978368. Throughput: 0: 910.1. Samples: 494796. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:07:59,022][00459] Avg episode reward: [(0, '8.128')]
[2024-08-01 08:08:04,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3610.0). Total num frames: 2002944. Throughput: 0: 889.2. Samples: 500294. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:08:04,023][00459] Avg episode reward: [(0, '7.772')]
[2024-08-01 08:08:04,036][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000489_2002944.pth...
[2024-08-01 08:08:04,043][00459] Components not started: RolloutWorker_w3, wait_time=600.0 seconds
[2024-08-01 08:08:04,155][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000276_1130496.pth
[2024-08-01 08:08:04,940][04191] Updated weights for policy 0, policy_version 490 (0.0015)
[2024-08-01 08:08:09,016][00459] Fps is (10 sec: 4505.6, 60 sec: 3754.7, 300 sec: 3623.9). Total num frames: 2023424. Throughput: 0: 909.3. Samples: 503512. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:08:09,018][00459] Avg episode reward: [(0, '8.004')]
[2024-08-01 08:08:14,019][00459] Fps is (10 sec: 3275.9, 60 sec: 3618.0, 300 sec: 3596.1). Total num frames: 2035712. Throughput: 0: 932.6. Samples: 508964. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:08:14,021][00459] Avg episode reward: [(0, '8.771')]
[2024-08-01 08:08:14,036][04176] Saving new best policy, reward=8.771!
[2024-08-01 08:08:16,990][04191] Updated weights for policy 0, policy_version 500 (0.0028)
[2024-08-01 08:08:19,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3610.0). Total num frames: 2056192. Throughput: 0: 889.2. Samples: 513614. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:08:19,018][00459] Avg episode reward: [(0, '9.600')]
[2024-08-01 08:08:19,020][04176] Saving new best policy, reward=9.600!
[2024-08-01 08:08:24,016][00459] Fps is (10 sec: 4097.2, 60 sec: 3686.4, 300 sec: 3637.8). Total num frames: 2076672. Throughput: 0: 886.0. Samples: 516722. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2024-08-01 08:08:24,024][00459] Avg episode reward: [(0, '9.831')]
[2024-08-01 08:08:24,032][04176] Saving new best policy, reward=9.831!
[2024-08-01 08:08:26,934][04191] Updated weights for policy 0, policy_version 510 (0.0022)
[2024-08-01 08:08:29,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3623.9). Total num frames: 2093056. Throughput: 0: 934.4. Samples: 522868. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:08:29,018][00459] Avg episode reward: [(0, '10.413')]
[2024-08-01 08:08:29,020][04176] Saving new best policy, reward=10.413!
[2024-08-01 08:08:34,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3596.1). Total num frames: 2105344. Throughput: 0: 886.3. Samples: 526776. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:08:34,023][00459] Avg episode reward: [(0, '10.224')]
[2024-08-01 08:08:38,787][04191] Updated weights for policy 0, policy_version 520 (0.0033)
[2024-08-01 08:08:39,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3623.9). Total num frames: 2129920. Throughput: 0: 883.3. Samples: 529958. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:08:39,023][00459] Avg episode reward: [(0, '9.562')]
[2024-08-01 08:08:44,022][00459] Fps is (10 sec: 4503.0, 60 sec: 3754.3, 300 sec: 3637.7). Total num frames: 2150400. Throughput: 0: 927.6. Samples: 536542. Policy #0 lag: (min: 0.0, avg: 0.6, max: 2.0)
[2024-08-01 08:08:44,030][00459] Avg episode reward: [(0, '9.890')]
[2024-08-01 08:08:49,022][00459] Fps is (10 sec: 3274.9, 60 sec: 3549.6, 300 sec: 3610.0). Total num frames: 2162688. Throughput: 0: 907.5. Samples: 541138. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:08:49,028][00459] Avg episode reward: [(0, '10.754')]
[2024-08-01 08:08:49,029][04176] Saving new best policy, reward=10.754!
[2024-08-01 08:08:51,042][04191] Updated weights for policy 0, policy_version 530 (0.0021)
[2024-08-01 08:08:54,016][00459] Fps is (10 sec: 3278.7, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 2183168. Throughput: 0: 886.9. Samples: 543422. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:08:54,018][00459] Avg episode reward: [(0, '11.348')]
[2024-08-01 08:08:54,029][04176] Saving new best policy, reward=11.348!
[2024-08-01 08:08:59,016][00459] Fps is (10 sec: 4098.3, 60 sec: 3754.7, 300 sec: 3637.8). Total num frames: 2203648. Throughput: 0: 907.4. Samples: 549794. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:08:59,018][00459] Avg episode reward: [(0, '11.675')]
[2024-08-01 08:08:59,021][04176] Saving new best policy, reward=11.675!
[2024-08-01 08:09:00,838][04191] Updated weights for policy 0, policy_version 540 (0.0014)
[2024-08-01 08:09:04,019][00459] Fps is (10 sec: 3685.1, 60 sec: 3617.9, 300 sec: 3623.9). Total num frames: 2220032. Throughput: 0: 921.7. Samples: 555094. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:09:04,022][00459] Avg episode reward: [(0, '12.724')]
[2024-08-01 08:09:04,039][04176] Saving new best policy, reward=12.724!
[2024-08-01 08:09:09,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 2236416. Throughput: 0: 894.3. Samples: 556966. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:09:09,018][00459] Avg episode reward: [(0, '12.912')]
[2024-08-01 08:09:09,023][04176] Saving new best policy, reward=12.912!
[2024-08-01 08:09:12,567][04191] Updated weights for policy 0, policy_version 550 (0.0023)
[2024-08-01 08:09:14,016][00459] Fps is (10 sec: 3687.8, 60 sec: 3686.6, 300 sec: 3637.8). Total num frames: 2256896. Throughput: 0: 895.2. Samples: 563150. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:09:14,019][00459] Avg episode reward: [(0, '12.232')]
[2024-08-01 08:09:19,017][00459] Fps is (10 sec: 3686.1, 60 sec: 3618.1, 300 sec: 3637.8). Total num frames: 2273280. Throughput: 0: 944.2. Samples: 569264. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:09:19,023][00459] Avg episode reward: [(0, '11.512')]
[2024-08-01 08:09:24,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 2289664. Throughput: 0: 919.7. Samples: 571346. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:09:24,018][00459] Avg episode reward: [(0, '10.588')]
[2024-08-01 08:09:24,555][04191] Updated weights for policy 0, policy_version 560 (0.0035)
[2024-08-01 08:09:29,016][00459] Fps is (10 sec: 3686.7, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 2310144. Throughput: 0: 894.6. Samples: 576796. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:09:29,021][00459] Avg episode reward: [(0, '11.886')]
[2024-08-01 08:09:33,953][04191] Updated weights for policy 0, policy_version 570 (0.0028)
[2024-08-01 08:09:34,016][00459] Fps is (10 sec: 4505.6, 60 sec: 3822.9, 300 sec: 3665.6). Total num frames: 2334720. Throughput: 0: 938.2. Samples: 583352. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:09:34,021][00459] Avg episode reward: [(0, '12.131')]
[2024-08-01 08:09:39,022][00459] Fps is (10 sec: 3684.2, 60 sec: 3617.8, 300 sec: 3623.8). Total num frames: 2347008. Throughput: 0: 938.0. Samples: 585638. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:09:39,028][00459] Avg episode reward: [(0, '12.431')]
[2024-08-01 08:09:44,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3550.2, 300 sec: 3623.9). Total num frames: 2363392. Throughput: 0: 898.7. Samples: 590236. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:09:44,018][00459] Avg episode reward: [(0, '11.837')]
[2024-08-01 08:09:45,878][04191] Updated weights for policy 0, policy_version 580 (0.0014)
[2024-08-01 08:09:49,016][00459] Fps is (10 sec: 4098.4, 60 sec: 3755.0, 300 sec: 3651.7). Total num frames: 2387968. Throughput: 0: 928.7. Samples: 596882. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:09:49,022][00459] Avg episode reward: [(0, '12.317')]
[2024-08-01 08:09:54,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3686.4, 300 sec: 3637.8). Total num frames: 2404352. Throughput: 0: 952.8. Samples: 599840. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:09:54,019][00459] Avg episode reward: [(0, '12.645')]
[2024-08-01 08:09:57,989][04191] Updated weights for policy 0, policy_version 590 (0.0029)
[2024-08-01 08:09:59,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 2420736. Throughput: 0: 902.3. Samples: 603754. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:09:59,018][00459] Avg episode reward: [(0, '14.045')]
[2024-08-01 08:09:59,030][04176] Saving new best policy, reward=14.045!
[2024-08-01 08:10:04,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.6, 300 sec: 3651.7). Total num frames: 2441216. Throughput: 0: 907.5. Samples: 610100. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:10:04,020][00459] Avg episode reward: [(0, '15.456')]
[2024-08-01 08:10:04,030][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000596_2441216.pth...
[2024-08-01 08:10:04,158][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000381_1560576.pth
[2024-08-01 08:10:04,173][04176] Saving new best policy, reward=15.456!
[2024-08-01 08:10:08,045][04191] Updated weights for policy 0, policy_version 600 (0.0022)
[2024-08-01 08:10:09,017][00459] Fps is (10 sec: 3686.0, 60 sec: 3686.3, 300 sec: 3637.8). Total num frames: 2457600. Throughput: 0: 926.5. Samples: 613038. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:10:09,025][00459] Avg episode reward: [(0, '16.057')]
[2024-08-01 08:10:09,027][04176] Saving new best policy, reward=16.057!
[2024-08-01 08:10:14,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 2469888. Throughput: 0: 906.8. Samples: 617600. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:10:14,022][00459] Avg episode reward: [(0, '16.389')]
[2024-08-01 08:10:14,032][04176] Saving new best policy, reward=16.389!
[2024-08-01 08:10:19,016][00459] Fps is (10 sec: 3277.1, 60 sec: 3618.2, 300 sec: 3623.9). Total num frames: 2490368. Throughput: 0: 883.8. Samples: 623124. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:10:19,018][00459] Avg episode reward: [(0, '18.514')]
[2024-08-01 08:10:19,022][04176] Saving new best policy, reward=18.514!
[2024-08-01 08:10:20,091][04191] Updated weights for policy 0, policy_version 610 (0.0032)
[2024-08-01 08:10:24,016][00459] Fps is (10 sec: 4505.6, 60 sec: 3754.7, 300 sec: 3651.7). Total num frames: 2514944. Throughput: 0: 904.5. Samples: 626334. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:10:24,018][00459] Avg episode reward: [(0, '18.437')]
[2024-08-01 08:10:29,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 2527232. Throughput: 0: 916.8. Samples: 631494. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:10:29,018][00459] Avg episode reward: [(0, '17.698')]
[2024-08-01 08:10:32,369][04191] Updated weights for policy 0, policy_version 620 (0.0023)
[2024-08-01 08:10:34,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3610.1). Total num frames: 2543616. Throughput: 0: 877.2. Samples: 636358. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:10:34,020][00459] Avg episode reward: [(0, '17.482')]
[2024-08-01 08:10:39,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.8, 300 sec: 3651.7). Total num frames: 2568192. Throughput: 0: 884.5. Samples: 639644. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:10:39,018][00459] Avg episode reward: [(0, '14.587')]
[2024-08-01 08:10:41,648][04191] Updated weights for policy 0, policy_version 630 (0.0025)
[2024-08-01 08:10:44,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3637.8). Total num frames: 2584576. Throughput: 0: 936.3. Samples: 645886. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:10:44,018][00459] Avg episode reward: [(0, '13.543')]
[2024-08-01 08:10:49,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3623.9). Total num frames: 2600960. Throughput: 0: 887.0. Samples: 650014. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:10:49,017][00459] Avg episode reward: [(0, '13.450')]
[2024-08-01 08:10:53,421][04191] Updated weights for policy 0, policy_version 640 (0.0033)
[2024-08-01 08:10:54,017][00459] Fps is (10 sec: 3686.1, 60 sec: 3618.1, 300 sec: 3651.8). Total num frames: 2621440. Throughput: 0: 896.6. Samples: 653384. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:10:54,022][00459] Avg episode reward: [(0, '13.183')]
[2024-08-01 08:10:59,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 2641920. Throughput: 0: 936.2. Samples: 659728. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:10:59,018][00459] Avg episode reward: [(0, '14.462')]
[2024-08-01 08:11:04,021][00459] Fps is (10 sec: 3275.3, 60 sec: 3549.5, 300 sec: 3623.9). Total num frames: 2654208. Throughput: 0: 909.0. Samples: 664036. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:11:04,024][00459] Avg episode reward: [(0, '14.578')]
[2024-08-01 08:11:05,388][04191] Updated weights for policy 0, policy_version 650 (0.0021)
[2024-08-01 08:11:09,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.2, 300 sec: 3637.8). Total num frames: 2674688. Throughput: 0: 897.3. Samples: 666714. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:11:09,018][00459] Avg episode reward: [(0, '16.361')]
[2024-08-01 08:11:14,016][00459] Fps is (10 sec: 4098.3, 60 sec: 3754.7, 300 sec: 3651.7). Total num frames: 2695168. Throughput: 0: 925.4. Samples: 673138. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:11:14,018][00459] Avg episode reward: [(0, '16.814')]
[2024-08-01 08:11:15,293][04191] Updated weights for policy 0, policy_version 660 (0.0030)
[2024-08-01 08:11:19,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3637.8). Total num frames: 2711552. Throughput: 0: 929.4. Samples: 678182. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:11:19,019][00459] Avg episode reward: [(0, '17.569')]
[2024-08-01 08:11:24,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3624.0). Total num frames: 2727936. Throughput: 0: 900.9. Samples: 680186. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:11:24,018][00459] Avg episode reward: [(0, '18.386')]
[2024-08-01 08:11:27,151][04191] Updated weights for policy 0, policy_version 670 (0.0021)
[2024-08-01 08:11:29,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3651.7). Total num frames: 2748416. Throughput: 0: 900.9. Samples: 686426. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:11:29,019][00459] Avg episode reward: [(0, '17.657')]
[2024-08-01 08:11:34,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3651.7). Total num frames: 2768896. Throughput: 0: 940.1. Samples: 692320. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:11:34,019][00459] Avg episode reward: [(0, '18.062')]
[2024-08-01 08:11:39,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3623.9). Total num frames: 2781184. Throughput: 0: 908.6. Samples: 694272. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:11:39,018][00459] Avg episode reward: [(0, '18.069')]
[2024-08-01 08:11:39,223][04191] Updated weights for policy 0, policy_version 680 (0.0024)
[2024-08-01 08:11:44,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3637.8). Total num frames: 2801664. Throughput: 0: 893.9. Samples: 699954. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:11:44,017][00459] Avg episode reward: [(0, '18.341')]
[2024-08-01 08:11:49,021][00459] Fps is (10 sec: 4094.0, 60 sec: 3686.1, 300 sec: 3651.6). Total num frames: 2822144. Throughput: 0: 941.3. Samples: 706394. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:11:49,027][00459] Avg episode reward: [(0, '17.344')]
[2024-08-01 08:11:49,154][04191] Updated weights for policy 0, policy_version 690 (0.0021)
[2024-08-01 08:11:54,020][00459] Fps is (10 sec: 3685.0, 60 sec: 3618.0, 300 sec: 3637.8). Total num frames: 2838528. Throughput: 0: 926.9. Samples: 708428. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:11:54,024][00459] Avg episode reward: [(0, '18.350')]
[2024-08-01 08:11:59,021][00459] Fps is (10 sec: 3686.2, 60 sec: 3617.8, 300 sec: 3637.7). Total num frames: 2859008. Throughput: 0: 891.0. Samples: 713240. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:11:59,026][00459] Avg episode reward: [(0, '18.679')]
[2024-08-01 08:11:59,031][04176] Saving new best policy, reward=18.679!
[2024-08-01 08:12:01,120][04191] Updated weights for policy 0, policy_version 700 (0.0020)
[2024-08-01 08:12:04,016][00459] Fps is (10 sec: 4097.6, 60 sec: 3755.0, 300 sec: 3665.6). Total num frames: 2879488. Throughput: 0: 921.0. Samples: 719628. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:12:04,018][00459] Avg episode reward: [(0, '18.384')]
[2024-08-01 08:12:04,030][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000703_2879488.pth...
[2024-08-01 08:12:04,150][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000489_2002944.pth
[2024-08-01 08:12:09,020][00459] Fps is (10 sec: 3277.3, 60 sec: 3617.9, 300 sec: 3637.8). Total num frames: 2891776. Throughput: 0: 937.3. Samples: 722370. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:12:09,022][00459] Avg episode reward: [(0, '17.192')]
[2024-08-01 08:12:13,017][04191] Updated weights for policy 0, policy_version 710 (0.0032)
[2024-08-01 08:12:14,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3637.8). Total num frames: 2912256. Throughput: 0: 890.4. Samples: 726492. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:12:14,018][00459] Avg episode reward: [(0, '16.608')]
[2024-08-01 08:12:19,016][00459] Fps is (10 sec: 4097.6, 60 sec: 3686.4, 300 sec: 3651.7). Total num frames: 2932736. Throughput: 0: 910.2. Samples: 733278. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:12:19,022][00459] Avg episode reward: [(0, '15.720')]
[2024-08-01 08:12:22,400][04191] Updated weights for policy 0, policy_version 720 (0.0042)
[2024-08-01 08:12:24,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3665.6). Total num frames: 2953216. Throughput: 0: 940.7. Samples: 736604. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:12:24,019][00459] Avg episode reward: [(0, '14.986')]
[2024-08-01 08:12:29,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 2965504. Throughput: 0: 907.6. Samples: 740794. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:12:29,018][00459] Avg episode reward: [(0, '15.956')]
[2024-08-01 08:12:34,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 2985984. Throughput: 0: 898.3. Samples: 746814. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:12:34,027][00459] Avg episode reward: [(0, '16.880')]
[2024-08-01 08:12:34,109][04191] Updated weights for policy 0, policy_version 730 (0.0029)
[2024-08-01 08:12:39,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3754.6, 300 sec: 3665.6). Total num frames: 3006464. Throughput: 0: 924.7. Samples: 750038. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:12:39,018][00459] Avg episode reward: [(0, '19.115')]
[2024-08-01 08:12:39,024][04176] Saving new best policy, reward=19.115!
[2024-08-01 08:12:44,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3637.8). Total num frames: 3022848. Throughput: 0: 930.9. Samples: 755126. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:12:44,021][00459] Avg episode reward: [(0, '19.070')]
[2024-08-01 08:12:46,540][04191] Updated weights for policy 0, policy_version 740 (0.0018)
[2024-08-01 08:12:49,016][00459] Fps is (10 sec: 3276.9, 60 sec: 3618.4, 300 sec: 3637.8). Total num frames: 3039232. Throughput: 0: 901.2. Samples: 760184. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:12:49,018][00459] Avg episode reward: [(0, '19.110')]
[2024-08-01 08:12:54,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3754.9, 300 sec: 3679.5). Total num frames: 3063808. Throughput: 0: 911.4. Samples: 763380. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:12:54,018][00459] Avg episode reward: [(0, '16.800')]
[2024-08-01 08:12:55,764][04191] Updated weights for policy 0, policy_version 750 (0.0025)
[2024-08-01 08:12:59,019][00459] Fps is (10 sec: 4094.8, 60 sec: 3686.6, 300 sec: 3651.7). Total num frames: 3080192. Throughput: 0: 950.4. Samples: 769262. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:12:59,024][00459] Avg episode reward: [(0, '15.272')]
[2024-08-01 08:13:04,016][00459] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3623.9). Total num frames: 3092480. Throughput: 0: 891.2. Samples: 773380. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:13:04,018][00459] Avg episode reward: [(0, '15.248')]
[2024-08-01 08:13:07,913][04191] Updated weights for policy 0, policy_version 760 (0.0023)
[2024-08-01 08:13:09,016][00459] Fps is (10 sec: 3277.7, 60 sec: 3686.6, 300 sec: 3651.7). Total num frames: 3112960. Throughput: 0: 889.7. Samples: 776642. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:13:09,025][00459] Avg episode reward: [(0, '15.296')]
[2024-08-01 08:13:14,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3651.7). Total num frames: 3133440. Throughput: 0: 941.7. Samples: 783172. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:13:14,022][00459] Avg episode reward: [(0, '16.148')]
[2024-08-01 08:13:19,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3637.8). Total num frames: 3149824. Throughput: 0: 901.0. Samples: 787358. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:13:19,018][00459] Avg episode reward: [(0, '17.027')]
[2024-08-01 08:13:20,232][04191] Updated weights for policy 0, policy_version 770 (0.0023)
[2024-08-01 08:13:24,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3170304. Throughput: 0: 888.0. Samples: 789998. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:13:24,018][00459] Avg episode reward: [(0, '18.743')]
[2024-08-01 08:13:29,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 3190784. Throughput: 0: 920.0. Samples: 796524. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:13:29,023][00459] Avg episode reward: [(0, '19.414')]
[2024-08-01 08:13:29,027][04176] Saving new best policy, reward=19.414!
[2024-08-01 08:13:29,988][04191] Updated weights for policy 0, policy_version 780 (0.0018)
[2024-08-01 08:13:34,021][00459] Fps is (10 sec: 3275.2, 60 sec: 3617.8, 300 sec: 3637.7). Total num frames: 3203072. Throughput: 0: 913.5. Samples: 801296. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:13:34,025][00459] Avg episode reward: [(0, '18.988')]
[2024-08-01 08:13:39,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.2, 300 sec: 3637.9). Total num frames: 3223552. Throughput: 0: 887.3. Samples: 803310. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:13:39,017][00459] Avg episode reward: [(0, '19.297')]
[2024-08-01 08:13:41,760][04191] Updated weights for policy 0, policy_version 790 (0.0025)
[2024-08-01 08:13:44,016][00459] Fps is (10 sec: 4098.0, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3244032. Throughput: 0: 903.4. Samples: 809914. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:13:44,019][00459] Avg episode reward: [(0, '19.600')]
[2024-08-01 08:13:44,028][04176] Saving new best policy, reward=19.600!
[2024-08-01 08:13:49,016][00459] Fps is (10 sec: 3686.2, 60 sec: 3686.4, 300 sec: 3651.7). Total num frames: 3260416. Throughput: 0: 934.5. Samples: 815434. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:13:49,023][00459] Avg episode reward: [(0, '19.275')]
[2024-08-01 08:13:53,825][04191] Updated weights for policy 0, policy_version 800 (0.0025)
[2024-08-01 08:13:54,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3637.8). Total num frames: 3276800. Throughput: 0: 907.0. Samples: 817458. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:13:54,018][00459] Avg episode reward: [(0, '18.819')]
[2024-08-01 08:13:59,016][00459] Fps is (10 sec: 3686.5, 60 sec: 3618.3, 300 sec: 3651.7). Total num frames: 3297280. Throughput: 0: 888.4. Samples: 823152. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:13:59,018][00459] Avg episode reward: [(0, '19.489')]
[2024-08-01 08:14:03,399][04191] Updated weights for policy 0, policy_version 810 (0.0031)
[2024-08-01 08:14:04,022][00459] Fps is (10 sec: 4093.6, 60 sec: 3754.3, 300 sec: 3665.5). Total num frames: 3317760. Throughput: 0: 939.7. Samples: 829648. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:04,024][00459] Avg episode reward: [(0, '19.377')]
[2024-08-01 08:14:04,037][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000810_3317760.pth...
[2024-08-01 08:14:04,208][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000596_2441216.pth
[2024-08-01 08:14:09,016][00459] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3637.8). Total num frames: 3330048. Throughput: 0: 923.5. Samples: 831556. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:14:09,025][00459] Avg episode reward: [(0, '18.740')]
[2024-08-01 08:14:14,016][00459] Fps is (10 sec: 3278.7, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3350528. Throughput: 0: 890.7. Samples: 836604. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:14:14,023][00459] Avg episode reward: [(0, '19.895')]
[2024-08-01 08:14:14,035][04176] Saving new best policy, reward=19.895!
[2024-08-01 08:14:15,359][04191] Updated weights for policy 0, policy_version 820 (0.0029)
[2024-08-01 08:14:19,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3371008. Throughput: 0: 928.9. Samples: 843094. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:19,018][00459] Avg episode reward: [(0, '20.575')]
[2024-08-01 08:14:19,086][04176] Saving new best policy, reward=20.575!
[2024-08-01 08:14:24,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3387392. Throughput: 0: 940.9. Samples: 845650. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:24,023][00459] Avg episode reward: [(0, '21.299')]
[2024-08-01 08:14:24,034][04176] Saving new best policy, reward=21.299!
[2024-08-01 08:14:27,588][04191] Updated weights for policy 0, policy_version 830 (0.0028)
[2024-08-01 08:14:29,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3623.9). Total num frames: 3403776. Throughput: 0: 888.8. Samples: 849908. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:29,022][00459] Avg episode reward: [(0, '20.953')]
[2024-08-01 08:14:34,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.7, 300 sec: 3651.8). Total num frames: 3424256. Throughput: 0: 913.5. Samples: 856542. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:14:34,018][00459] Avg episode reward: [(0, '20.286')]
[2024-08-01 08:14:37,146][04191] Updated weights for policy 0, policy_version 840 (0.0024)
[2024-08-01 08:14:39,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3444736. Throughput: 0: 940.0. Samples: 859758. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:39,022][00459] Avg episode reward: [(0, '18.459')]
[2024-08-01 08:14:44,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3623.9). Total num frames: 3457024. Throughput: 0: 906.0. Samples: 863922. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:14:44,018][00459] Avg episode reward: [(0, '17.810')]
[2024-08-01 08:14:48,889][04191] Updated weights for policy 0, policy_version 850 (0.0022)
[2024-08-01 08:14:49,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3651.7). Total num frames: 3481600. Throughput: 0: 897.4. Samples: 870024. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:49,021][00459] Avg episode reward: [(0, '17.422')]
[2024-08-01 08:14:54,021][00459] Fps is (10 sec: 4503.5, 60 sec: 3754.4, 300 sec: 3665.5). Total num frames: 3502080. Throughput: 0: 928.5. Samples: 873344. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:54,023][00459] Avg episode reward: [(0, '18.009')]
[2024-08-01 08:14:59,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.2, 300 sec: 3637.8). Total num frames: 3514368. Throughput: 0: 924.1. Samples: 878188. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:14:59,018][00459] Avg episode reward: [(0, '18.714')]
[2024-08-01 08:15:00,992][04191] Updated weights for policy 0, policy_version 860 (0.0030)
[2024-08-01 08:15:04,016][00459] Fps is (10 sec: 3278.4, 60 sec: 3618.5, 300 sec: 3651.7). Total num frames: 3534848. Throughput: 0: 898.4. Samples: 883520. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:15:04,023][00459] Avg episode reward: [(0, '19.615')]
[2024-08-01 08:15:09,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 3555328. Throughput: 0: 913.3. Samples: 886750. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:15:09,018][00459] Avg episode reward: [(0, '20.205')]
[2024-08-01 08:15:10,304][04191] Updated weights for policy 0, policy_version 870 (0.0037)
[2024-08-01 08:15:14,016][00459] Fps is (10 sec: 3686.2, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3571712. Throughput: 0: 943.2. Samples: 892352. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:15:14,021][00459] Avg episode reward: [(0, '19.923')]
[2024-08-01 08:15:19,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3637.8). Total num frames: 3588096. Throughput: 0: 898.5. Samples: 896976. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:15:19,018][00459] Avg episode reward: [(0, '19.424')]
[2024-08-01 08:15:22,352][04191] Updated weights for policy 0, policy_version 880 (0.0025)
[2024-08-01 08:15:24,016][00459] Fps is (10 sec: 3686.6, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3608576. Throughput: 0: 901.8. Samples: 900340. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:15:24,018][00459] Avg episode reward: [(0, '18.706')]
[2024-08-01 08:15:29,016][00459] Fps is (10 sec: 4095.9, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 3629056. Throughput: 0: 949.7. Samples: 906660. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:15:29,020][00459] Avg episode reward: [(0, '17.616')]
[2024-08-01 08:15:34,016][00459] Fps is (10 sec: 3276.6, 60 sec: 3618.1, 300 sec: 3637.8). Total num frames: 3641344. Throughput: 0: 902.5. Samples: 910638. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:15:34,026][00459] Avg episode reward: [(0, '17.142')]
[2024-08-01 08:15:34,544][04191] Updated weights for policy 0, policy_version 890 (0.0020)
[2024-08-01 08:15:39,016][00459] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3661824. Throughput: 0: 895.9. Samples: 913656. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:15:39,019][00459] Avg episode reward: [(0, '17.444')]
[2024-08-01 08:15:43,735][04191] Updated weights for policy 0, policy_version 900 (0.0033)
[2024-08-01 08:15:44,016][00459] Fps is (10 sec: 4505.6, 60 sec: 3822.9, 300 sec: 3679.4). Total num frames: 3686400. Throughput: 0: 934.4. Samples: 920236. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:15:44,024][00459] Avg episode reward: [(0, '18.358')]
[2024-08-01 08:15:49,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3698688. Throughput: 0: 921.9. Samples: 925004. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:15:49,020][00459] Avg episode reward: [(0, '18.137')]
[2024-08-01 08:15:54,016][00459] Fps is (10 sec: 3277.0, 60 sec: 3618.4, 300 sec: 3651.7). Total num frames: 3719168. Throughput: 0: 898.8. Samples: 927198. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2024-08-01 08:15:54,022][00459] Avg episode reward: [(0, '18.934')]
[2024-08-01 08:15:55,760][04191] Updated weights for policy 0, policy_version 910 (0.0024)
[2024-08-01 08:15:59,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 3739648. Throughput: 0: 922.7. Samples: 933874. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:15:59,018][00459] Avg episode reward: [(0, '20.185')]
[2024-08-01 08:16:04,019][00459] Fps is (10 sec: 3685.3, 60 sec: 3686.2, 300 sec: 3665.5). Total num frames: 3756032. Throughput: 0: 937.3. Samples: 939156. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:16:04,021][00459] Avg episode reward: [(0, '21.009')]
[2024-08-01 08:16:04,036][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000917_3756032.pth...
[2024-08-01 08:16:04,210][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000703_2879488.pth
[2024-08-01 08:16:07,959][04191] Updated weights for policy 0, policy_version 920 (0.0024)
[2024-08-01 08:16:09,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3772416. Throughput: 0: 904.5. Samples: 941044. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:16:09,018][00459] Avg episode reward: [(0, '20.928')]
[2024-08-01 08:16:14,016][00459] Fps is (10 sec: 3687.4, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3792896. Throughput: 0: 896.8. Samples: 947014. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2024-08-01 08:16:14,021][00459] Avg episode reward: [(0, '21.414')]
[2024-08-01 08:16:14,036][04176] Saving new best policy, reward=21.414!
[2024-08-01 08:16:17,728][04191] Updated weights for policy 0, policy_version 930 (0.0028)
[2024-08-01 08:16:19,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3809280. Throughput: 0: 942.7. Samples: 953058. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:16:19,022][00459] Avg episode reward: [(0, '21.113')]
[2024-08-01 08:16:24,016][00459] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3825664. Throughput: 0: 920.9. Samples: 955096. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:16:24,019][00459] Avg episode reward: [(0, '20.606')]
[2024-08-01 08:16:29,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3846144. Throughput: 0: 892.1. Samples: 960382. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:16:29,022][00459] Avg episode reward: [(0, '21.595')]
[2024-08-01 08:16:29,025][04176] Saving new best policy, reward=21.595!
[2024-08-01 08:16:29,755][04191] Updated weights for policy 0, policy_version 940 (0.0031)
[2024-08-01 08:16:34,016][00459] Fps is (10 sec: 4096.0, 60 sec: 3754.7, 300 sec: 3679.5). Total num frames: 3866624. Throughput: 0: 926.0. Samples: 966676. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:16:34,019][00459] Avg episode reward: [(0, '21.247')]
[2024-08-01 08:16:39,016][00459] Fps is (10 sec: 3276.7, 60 sec: 3618.1, 300 sec: 3651.7). Total num frames: 3878912. Throughput: 0: 932.2. Samples: 969146. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:16:39,021][00459] Avg episode reward: [(0, '21.935')]
[2024-08-01 08:16:39,024][04176] Saving new best policy, reward=21.935!
[2024-08-01 08:16:41,908][04191] Updated weights for policy 0, policy_version 950 (0.0023)
[2024-08-01 08:16:44,016][00459] Fps is (10 sec: 3276.9, 60 sec: 3549.9, 300 sec: 3651.7). Total num frames: 3899392. Throughput: 0: 879.6. Samples: 973458. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:16:44,018][00459] Avg episode reward: [(0, '22.122')]
[2024-08-01 08:16:44,028][04176] Saving new best policy, reward=22.122!
[2024-08-01 08:16:49,016][00459] Fps is (10 sec: 4096.1, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3919872. Throughput: 0: 907.9. Samples: 980008. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:16:49,023][00459] Avg episode reward: [(0, '22.384')]
[2024-08-01 08:16:49,027][04176] Saving new best policy, reward=22.384!
[2024-08-01 08:16:51,635][04191] Updated weights for policy 0, policy_version 960 (0.0018)
[2024-08-01 08:16:54,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3651.8). Total num frames: 3936256. Throughput: 0: 936.0. Samples: 983162. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2024-08-01 08:16:54,020][00459] Avg episode reward: [(0, '21.016')]
[2024-08-01 08:16:59,017][00459] Fps is (10 sec: 3276.3, 60 sec: 3549.8, 300 sec: 3637.8). Total num frames: 3952640. Throughput: 0: 891.6. Samples: 987136. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2024-08-01 08:16:59,020][00459] Avg episode reward: [(0, '20.297')]
[2024-08-01 08:17:03,437][04191] Updated weights for policy 0, policy_version 970 (0.0035)
[2024-08-01 08:17:04,016][00459] Fps is (10 sec: 3686.4, 60 sec: 3618.3, 300 sec: 3665.6). Total num frames: 3973120. Throughput: 0: 895.5. Samples: 993354. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2024-08-01 08:17:04,020][00459] Avg episode reward: [(0, '19.585')]
[2024-08-01 08:17:09,016][00459] Fps is (10 sec: 4096.7, 60 sec: 3686.4, 300 sec: 3665.6). Total num frames: 3993600. Throughput: 0: 924.9. Samples: 996716. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2024-08-01 08:17:09,021][00459] Avg episode reward: [(0, '19.966')]
[2024-08-01 08:17:13,103][04176] Stopping Batcher_0...
[2024-08-01 08:17:13,104][04176] Loop batcher_evt_loop terminating...
[2024-08-01 08:17:13,106][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2024-08-01 08:17:13,105][00459] Component Batcher_0 stopped!
[2024-08-01 08:17:13,108][00459] Component RolloutWorker_w3 process died already! Don't wait for it.
[2024-08-01 08:17:13,233][04191] Weights refcount: 2 0
[2024-08-01 08:17:13,241][00459] Component InferenceWorker_p0-w0 stopped!
[2024-08-01 08:17:13,247][04191] Stopping InferenceWorker_p0-w0...
[2024-08-01 08:17:13,250][04191] Loop inference_proc0-0_evt_loop terminating...
[2024-08-01 08:17:13,273][00459] Component RolloutWorker_w5 stopped!
[2024-08-01 08:17:13,281][04197] Stopping RolloutWorker_w7...
[2024-08-01 08:17:13,282][04197] Loop rollout_proc7_evt_loop terminating...
[2024-08-01 08:17:13,279][04195] Stopping RolloutWorker_w5...
[2024-08-01 08:17:13,282][04195] Loop rollout_proc5_evt_loop terminating...
[2024-08-01 08:17:13,284][00459] Component RolloutWorker_w7 stopped!
[2024-08-01 08:17:13,312][04190] Stopping RolloutWorker_w1...
[2024-08-01 08:17:13,313][00459] Component RolloutWorker_w1 stopped!
[2024-08-01 08:17:13,313][04190] Loop rollout_proc1_evt_loop terminating...
[2024-08-01 08:17:13,331][00459] Component RolloutWorker_w2 stopped!
[2024-08-01 08:17:13,336][04192] Stopping RolloutWorker_w2...
[2024-08-01 08:17:13,346][04192] Loop rollout_proc2_evt_loop terminating...
[2024-08-01 08:17:13,355][04189] Stopping RolloutWorker_w0...
[2024-08-01 08:17:13,356][00459] Component RolloutWorker_w0 stopped!
[2024-08-01 08:17:13,365][04176] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000810_3317760.pth
[2024-08-01 08:17:13,373][04189] Loop rollout_proc0_evt_loop terminating...
[2024-08-01 08:17:13,392][04194] Stopping RolloutWorker_w4...
[2024-08-01 08:17:13,388][04176] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2024-08-01 08:17:13,414][04194] Loop rollout_proc4_evt_loop terminating...
[2024-08-01 08:17:13,392][00459] Component RolloutWorker_w4 stopped!
[2024-08-01 08:17:13,424][04196] Stopping RolloutWorker_w6...
[2024-08-01 08:17:13,425][00459] Component RolloutWorker_w6 stopped!
[2024-08-01 08:17:13,442][04196] Loop rollout_proc6_evt_loop terminating...
[2024-08-01 08:17:13,668][04176] Stopping LearnerWorker_p0...
[2024-08-01 08:17:13,670][00459] Component LearnerWorker_p0 stopped!
[2024-08-01 08:17:13,669][04176] Loop learner_proc0_evt_loop terminating...
[2024-08-01 08:17:13,679][00459] Waiting for process learner_proc0 to stop...
[2024-08-01 08:17:15,200][00459] Waiting for process inference_proc0-0 to join...
[2024-08-01 08:17:15,218][00459] Waiting for process rollout_proc0 to join...
[2024-08-01 08:17:16,827][00459] Waiting for process rollout_proc1 to join...
[2024-08-01 08:17:16,833][00459] Waiting for process rollout_proc2 to join...
[2024-08-01 08:17:16,837][00459] Waiting for process rollout_proc3 to join...
[2024-08-01 08:17:16,839][00459] Waiting for process rollout_proc4 to join...
[2024-08-01 08:17:16,843][00459] Waiting for process rollout_proc5 to join...
[2024-08-01 08:17:16,846][00459] Waiting for process rollout_proc6 to join...
[2024-08-01 08:17:16,849][00459] Waiting for process rollout_proc7 to join...
[2024-08-01 08:17:16,853][00459] Batcher 0 profile tree view:
batching: 25.7990, releasing_batches: 0.0354
[2024-08-01 08:17:16,855][00459] InferenceWorker_p0-w0 profile tree view:
wait_policy: 0.0001
  wait_policy_total: 438.5763
update_model: 9.7209
  weight_update: 0.0021
one_step: 0.0128
  handle_policy_step: 628.0504
    deserialize: 16.5745, stack: 3.4482, obs_to_device_normalize: 128.9487, forward: 339.5090, send_messages: 28.0933
    prepare_outputs: 80.9549
      to_cpu: 47.2104
[2024-08-01 08:17:16,857][00459] Learner 0 profile tree view:
misc: 0.0057, prepare_batch: 14.7157
train: 73.1379
  epoch_init: 0.0077, minibatch_init: 0.0158, losses_postprocess: 0.6246, kl_divergence: 0.6807, after_optimizer: 34.2073
  calculate_losses: 25.5974
    losses_init: 0.0108, forward_head: 1.2776, bptt_initial: 16.8364, tail: 1.2001, advantages_returns: 0.2679, losses: 3.7013
    bptt: 1.9693
      bptt_forward_core: 1.8608
  update: 11.2644
    clip: 0.9512
[2024-08-01 08:17:16,859][00459] RolloutWorker_w0 profile tree view:
wait_for_trajectories: 0.3385, enqueue_policy_requests: 102.1502, env_step: 880.4931, overhead: 15.4370, complete_rollouts: 8.1042
save_policy_outputs: 24.5524
  split_output_tensors: 9.6906
[2024-08-01 08:17:16,860][00459] RolloutWorker_w7 profile tree view:
wait_for_trajectories: 0.4012, enqueue_policy_requests: 137.4146, env_step: 841.7805, overhead: 15.8025, complete_rollouts: 6.5795
save_policy_outputs: 21.6830
  split_output_tensors: 8.8223
[2024-08-01 08:17:16,862][00459] Loop Runner_EvtLoop terminating...
[2024-08-01 08:17:16,863][00459] Runner profile tree view:
main_loop: 1144.8494
[2024-08-01 08:17:16,864][00459] Collected {0: 4005888}, FPS: 3499.1
[2024-08-01 08:19:56,929][00459] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2024-08-01 08:19:56,931][00459] Overriding arg 'num_workers' with value 1 passed from command line
[2024-08-01 08:19:56,934][00459] Adding new argument 'no_render'=True that is not in the saved config file!
[2024-08-01 08:19:56,937][00459] Adding new argument 'save_video'=True that is not in the saved config file!
[2024-08-01 08:19:56,939][00459] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2024-08-01 08:19:56,941][00459] Adding new argument 'video_name'=None that is not in the saved config file!
[2024-08-01 08:19:56,942][00459] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file!
[2024-08-01 08:19:56,944][00459] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2024-08-01 08:19:56,946][00459] Adding new argument 'push_to_hub'=False that is not in the saved config file!
[2024-08-01 08:19:56,947][00459] Adding new argument 'hf_repository'=None that is not in the saved config file!
[2024-08-01 08:19:56,948][00459] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2024-08-01 08:19:56,950][00459] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2024-08-01 08:19:56,951][00459] Adding new argument 'train_script'=None that is not in the saved config file!
[2024-08-01 08:19:56,953][00459] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2024-08-01 08:19:56,955][00459] Using frameskip 1 and render_action_repeat=4 for evaluation
[2024-08-01 08:19:56,992][00459] Doom resolution: 160x120, resize resolution: (128, 72)
[2024-08-01 08:19:56,995][00459] RunningMeanStd input shape: (3, 72, 128)
[2024-08-01 08:19:56,998][00459] RunningMeanStd input shape: (1,)
[2024-08-01 08:19:57,022][00459] ConvEncoder: input_channels=3
[2024-08-01 08:19:57,149][00459] Conv encoder output size: 512
[2024-08-01 08:19:57,152][00459] Policy head output size: 512
[2024-08-01 08:19:57,330][00459] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2024-08-01 08:19:58,101][00459] Num frames 100...
[2024-08-01 08:19:58,240][00459] Num frames 200...
[2024-08-01 08:19:58,435][00459] Num frames 300...
[2024-08-01 08:19:58,662][00459] Num frames 400...
[2024-08-01 08:19:58,999][00459] Num frames 500...
[2024-08-01 08:19:59,144][00459] Num frames 600...
[2024-08-01 08:19:59,277][00459] Num frames 700...
[2024-08-01 08:19:59,405][00459] Num frames 800...
[2024-08-01 08:19:59,459][00459] Avg episode rewards: #0: 15.000, true rewards: #0: 8.000
[2024-08-01 08:19:59,461][00459] Avg episode reward: 15.000, avg true_objective: 8.000
[2024-08-01 08:19:59,580][00459] Num frames 900...
[2024-08-01 08:19:59,707][00459] Num frames 1000...
[2024-08-01 08:19:59,835][00459] Num frames 1100...
[2024-08-01 08:19:59,961][00459] Num frames 1200...
[2024-08-01 08:20:00,100][00459] Num frames 1300...
[2024-08-01 08:20:00,268][00459] Num frames 1400...
[2024-08-01 08:20:00,413][00459] Avg episode rewards: #0: 14.360, true rewards: #0: 7.360
[2024-08-01 08:20:00,414][00459] Avg episode reward: 14.360, avg true_objective: 7.360
[2024-08-01 08:20:00,454][00459] Num frames 1500...
[2024-08-01 08:20:00,577][00459] Num frames 1600...
[2024-08-01 08:20:00,700][00459] Num frames 1700...
[2024-08-01 08:20:00,824][00459] Num frames 1800...
[2024-08-01 08:20:00,951][00459] Num frames 1900...
[2024-08-01 08:20:01,084][00459] Num frames 2000...
[2024-08-01 08:20:01,225][00459] Num frames 2100...
[2024-08-01 08:20:01,344][00459] Num frames 2200...
[2024-08-01 08:20:01,470][00459] Num frames 2300...
[2024-08-01 08:20:01,570][00459] Avg episode rewards: #0: 15.453, true rewards: #0: 7.787
[2024-08-01 08:20:01,572][00459] Avg episode reward: 15.453, avg true_objective: 7.787
[2024-08-01 08:20:01,654][00459] Num frames 2400...
[2024-08-01 08:20:01,771][00459] Num frames 2500...
[2024-08-01 08:20:01,891][00459] Num frames 2600...
[2024-08-01 08:20:02,053][00459] Avg episode rewards: #0: 13.220, true rewards: #0: 6.720
[2024-08-01 08:20:02,055][00459] Avg episode reward: 13.220, avg true_objective: 6.720
[2024-08-01 08:20:02,073][00459] Num frames 2700...
[2024-08-01 08:20:02,209][00459] Num frames 2800...
[2024-08-01 08:20:02,335][00459] Num frames 2900...
[2024-08-01 08:20:02,456][00459] Num frames 3000...
[2024-08-01 08:20:02,588][00459] Num frames 3100...
[2024-08-01 08:20:02,711][00459] Num frames 3200...
[2024-08-01 08:20:02,823][00459] Avg episode rewards: #0: 12.490, true rewards: #0: 6.490
[2024-08-01 08:20:02,825][00459] Avg episode reward: 12.490, avg true_objective: 6.490
[2024-08-01 08:20:02,895][00459] Num frames 3300...
[2024-08-01 08:20:03,022][00459] Num frames 3400...
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[2024-08-01 08:20:03,667][00459] Num frames 3900...
[2024-08-01 08:20:03,795][00459] Num frames 4000...
[2024-08-01 08:20:03,919][00459] Num frames 4100...
[2024-08-01 08:20:04,045][00459] Num frames 4200...
[2024-08-01 08:20:04,176][00459] Num frames 4300...
[2024-08-01 08:20:04,311][00459] Num frames 4400...
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[2024-08-01 08:20:05,171][00459] Num frames 4900...
[2024-08-01 08:20:05,343][00459] Num frames 5000...
[2024-08-01 08:20:05,510][00459] Num frames 5100...
[2024-08-01 08:20:05,682][00459] Num frames 5200...
[2024-08-01 08:20:05,869][00459] Num frames 5300...
[2024-08-01 08:20:06,009][00459] Avg episode rewards: #0: 20.408, true rewards: #0: 8.908
[2024-08-01 08:20:06,011][00459] Avg episode reward: 20.408, avg true_objective: 8.908
[2024-08-01 08:20:06,112][00459] Num frames 5400...
[2024-08-01 08:20:06,294][00459] Num frames 5500...
[2024-08-01 08:20:06,467][00459] Num frames 5600...
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[2024-08-01 08:20:07,061][00459] Num frames 6000...
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[2024-08-01 08:20:07,444][00459] Num frames 6300...
[2024-08-01 08:20:07,566][00459] Num frames 6400...
[2024-08-01 08:20:07,690][00459] Num frames 6500...
[2024-08-01 08:20:07,812][00459] Num frames 6600...
[2024-08-01 08:20:07,941][00459] Num frames 6700...
[2024-08-01 08:20:08,067][00459] Num frames 6800...
[2024-08-01 08:20:08,201][00459] Num frames 6900...
[2024-08-01 08:20:08,325][00459] Num frames 7000...
[2024-08-01 08:20:08,466][00459] Num frames 7100...
[2024-08-01 08:20:08,592][00459] Num frames 7200...
[2024-08-01 08:20:08,717][00459] Num frames 7300...
[2024-08-01 08:20:08,847][00459] Num frames 7400...
[2024-08-01 08:20:08,959][00459] Avg episode rewards: #0: 25.064, true rewards: #0: 10.636
[2024-08-01 08:20:08,961][00459] Avg episode reward: 25.064, avg true_objective: 10.636
[2024-08-01 08:20:09,031][00459] Num frames 7500...
[2024-08-01 08:20:09,162][00459] Num frames 7600...
[2024-08-01 08:20:09,288][00459] Num frames 7700...
[2024-08-01 08:20:09,421][00459] Num frames 7800...
[2024-08-01 08:20:09,551][00459] Num frames 7900...
[2024-08-01 08:20:09,677][00459] Num frames 8000...
[2024-08-01 08:20:09,802][00459] Num frames 8100...
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[2024-08-01 08:20:10,052][00459] Num frames 8300...
[2024-08-01 08:20:10,187][00459] Num frames 8400...
[2024-08-01 08:20:10,309][00459] Num frames 8500...
[2024-08-01 08:20:10,434][00459] Num frames 8600...
[2024-08-01 08:20:10,560][00459] Num frames 8700...
[2024-08-01 08:20:10,682][00459] Num frames 8800...
[2024-08-01 08:20:10,802][00459] Avg episode rewards: #0: 26.066, true rewards: #0: 11.066
[2024-08-01 08:20:10,804][00459] Avg episode reward: 26.066, avg true_objective: 11.066
[2024-08-01 08:20:10,862][00459] Num frames 8900...
[2024-08-01 08:20:10,985][00459] Num frames 9000...
[2024-08-01 08:20:11,112][00459] Num frames 9100...
[2024-08-01 08:20:11,237][00459] Num frames 9200...
[2024-08-01 08:20:11,361][00459] Num frames 9300...
[2024-08-01 08:20:11,493][00459] Num frames 9400...
[2024-08-01 08:20:11,615][00459] Num frames 9500...
[2024-08-01 08:20:11,740][00459] Num frames 9600...
[2024-08-01 08:20:11,861][00459] Num frames 9700...
[2024-08-01 08:20:11,991][00459] Avg episode rewards: #0: 25.509, true rewards: #0: 10.842
[2024-08-01 08:20:11,993][00459] Avg episode reward: 25.509, avg true_objective: 10.842
[2024-08-01 08:20:12,049][00459] Num frames 9800...
[2024-08-01 08:20:12,177][00459] Num frames 9900...
[2024-08-01 08:20:12,302][00459] Num frames 10000...
[2024-08-01 08:20:12,425][00459] Num frames 10100...
[2024-08-01 08:20:12,557][00459] Num frames 10200...
[2024-08-01 08:20:12,681][00459] Num frames 10300...
[2024-08-01 08:20:12,801][00459] Num frames 10400...
[2024-08-01 08:20:12,923][00459] Num frames 10500...
[2024-08-01 08:20:13,060][00459] Num frames 10600...
[2024-08-01 08:20:13,194][00459] Num frames 10700...
[2024-08-01 08:20:13,320][00459] Num frames 10800...
[2024-08-01 08:20:13,440][00459] Num frames 10900...
[2024-08-01 08:20:13,509][00459] Avg episode rewards: #0: 25.710, true rewards: #0: 10.910
[2024-08-01 08:20:13,511][00459] Avg episode reward: 25.710, avg true_objective: 10.910
[2024-08-01 08:21:22,420][00459] Replay video saved to /content/train_dir/default_experiment/replay.mp4!
[2024-08-01 08:26:10,947][00459] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2024-08-01 08:26:10,949][00459] Overriding arg 'num_workers' with value 1 passed from command line
[2024-08-01 08:26:10,951][00459] Adding new argument 'no_render'=True that is not in the saved config file!
[2024-08-01 08:26:10,953][00459] Adding new argument 'save_video'=True that is not in the saved config file!
[2024-08-01 08:26:10,955][00459] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2024-08-01 08:26:10,956][00459] Adding new argument 'video_name'=None that is not in the saved config file!
[2024-08-01 08:26:10,958][00459] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
[2024-08-01 08:26:10,960][00459] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2024-08-01 08:26:10,961][00459] Adding new argument 'push_to_hub'=True that is not in the saved config file!
[2024-08-01 08:26:10,962][00459] Adding new argument 'hf_repository'='andriJulian/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file!
[2024-08-01 08:26:10,964][00459] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2024-08-01 08:26:10,965][00459] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2024-08-01 08:26:10,966][00459] Adding new argument 'train_script'=None that is not in the saved config file!
[2024-08-01 08:26:10,968][00459] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2024-08-01 08:26:10,969][00459] Using frameskip 1 and render_action_repeat=4 for evaluation
[2024-08-01 08:26:11,000][00459] RunningMeanStd input shape: (3, 72, 128)
[2024-08-01 08:26:11,002][00459] RunningMeanStd input shape: (1,)
[2024-08-01 08:26:11,017][00459] ConvEncoder: input_channels=3
[2024-08-01 08:26:11,055][00459] Conv encoder output size: 512
[2024-08-01 08:26:11,057][00459] Policy head output size: 512
[2024-08-01 08:26:11,075][00459] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000978_4005888.pth...
[2024-08-01 08:26:11,517][00459] Num frames 100...
[2024-08-01 08:26:11,639][00459] Num frames 200...
[2024-08-01 08:26:11,758][00459] Num frames 300...
[2024-08-01 08:26:11,879][00459] Num frames 400...
[2024-08-01 08:26:11,997][00459] Num frames 500...
[2024-08-01 08:26:12,124][00459] Num frames 600...
[2024-08-01 08:26:12,245][00459] Num frames 700...
[2024-08-01 08:26:12,380][00459] Num frames 800...
[2024-08-01 08:26:12,502][00459] Avg episode rewards: #0: 23.560, true rewards: #0: 8.560
[2024-08-01 08:26:12,503][00459] Avg episode reward: 23.560, avg true_objective: 8.560
[2024-08-01 08:26:12,560][00459] Num frames 900...
[2024-08-01 08:26:12,679][00459] Num frames 1000...
[2024-08-01 08:26:12,797][00459] Num frames 1100...
[2024-08-01 08:26:12,919][00459] Num frames 1200...
[2024-08-01 08:26:13,039][00459] Num frames 1300...
[2024-08-01 08:26:13,174][00459] Num frames 1400...
[2024-08-01 08:26:13,302][00459] Num frames 1500...
[2024-08-01 08:26:13,422][00459] Num frames 1600...
[2024-08-01 08:26:13,540][00459] Num frames 1700...
[2024-08-01 08:26:13,660][00459] Num frames 1800...
[2024-08-01 08:26:13,784][00459] Num frames 1900...
[2024-08-01 08:26:13,909][00459] Num frames 2000...
[2024-08-01 08:26:13,998][00459] Avg episode rewards: #0: 26.135, true rewards: #0: 10.135
[2024-08-01 08:26:14,000][00459] Avg episode reward: 26.135, avg true_objective: 10.135
[2024-08-01 08:26:14,095][00459] Num frames 2100...
[2024-08-01 08:26:14,227][00459] Num frames 2200...
[2024-08-01 08:26:14,365][00459] Num frames 2300...
[2024-08-01 08:26:14,488][00459] Num frames 2400...
[2024-08-01 08:26:14,612][00459] Num frames 2500...
[2024-08-01 08:26:14,734][00459] Num frames 2600...
[2024-08-01 08:26:14,858][00459] Num frames 2700...
[2024-08-01 08:26:14,984][00459] Num frames 2800...
[2024-08-01 08:26:15,110][00459] Num frames 2900...
[2024-08-01 08:26:15,235][00459] Num frames 3000...
[2024-08-01 08:26:15,367][00459] Num frames 3100...
[2024-08-01 08:26:15,493][00459] Num frames 3200...
[2024-08-01 08:26:15,615][00459] Num frames 3300...
[2024-08-01 08:26:15,738][00459] Num frames 3400...
[2024-08-01 08:26:15,860][00459] Num frames 3500...
[2024-08-01 08:26:15,987][00459] Num frames 3600...
[2024-08-01 08:26:16,114][00459] Num frames 3700...
[2024-08-01 08:26:16,240][00459] Num frames 3800...
[2024-08-01 08:26:16,368][00459] Num frames 3900...
[2024-08-01 08:26:16,503][00459] Num frames 4000...
[2024-08-01 08:26:16,610][00459] Avg episode rewards: #0: 32.133, true rewards: #0: 13.467
[2024-08-01 08:26:16,611][00459] Avg episode reward: 32.133, avg true_objective: 13.467
[2024-08-01 08:26:16,689][00459] Num frames 4100...
[2024-08-01 08:26:16,809][00459] Num frames 4200...
[2024-08-01 08:26:16,932][00459] Num frames 4300...
[2024-08-01 08:26:17,056][00459] Num frames 4400...
[2024-08-01 08:26:17,185][00459] Num frames 4500...
[2024-08-01 08:26:17,304][00459] Avg episode rewards: #0: 26.630, true rewards: #0: 11.380
[2024-08-01 08:26:17,306][00459] Avg episode reward: 26.630, avg true_objective: 11.380
[2024-08-01 08:26:17,367][00459] Num frames 4600...
[2024-08-01 08:26:17,498][00459] Num frames 4700...
[2024-08-01 08:26:17,622][00459] Num frames 4800...
[2024-08-01 08:26:17,749][00459] Num frames 4900...
[2024-08-01 08:26:17,887][00459] Avg episode rewards: #0: 22.536, true rewards: #0: 9.936
[2024-08-01 08:26:17,889][00459] Avg episode reward: 22.536, avg true_objective: 9.936
[2024-08-01 08:26:17,930][00459] Num frames 5000...
[2024-08-01 08:26:18,047][00459] Num frames 5100...
[2024-08-01 08:26:18,186][00459] Num frames 5200...
[2024-08-01 08:26:18,313][00459] Num frames 5300...
[2024-08-01 08:26:18,439][00459] Num frames 5400...
[2024-08-01 08:26:18,514][00459] Avg episode rewards: #0: 20.193, true rewards: #0: 9.027
[2024-08-01 08:26:18,516][00459] Avg episode reward: 20.193, avg true_objective: 9.027
[2024-08-01 08:26:18,618][00459] Num frames 5500...
[2024-08-01 08:26:18,741][00459] Num frames 5600...
[2024-08-01 08:26:18,862][00459] Num frames 5700...
[2024-08-01 08:26:18,984][00459] Num frames 5800...
[2024-08-01 08:26:19,120][00459] Avg episode rewards: #0: 18.091, true rewards: #0: 8.377
[2024-08-01 08:26:19,122][00459] Avg episode reward: 18.091, avg true_objective: 8.377
[2024-08-01 08:26:19,171][00459] Num frames 5900...
[2024-08-01 08:26:19,293][00459] Num frames 6000...
[2024-08-01 08:26:19,418][00459] Num frames 6100...
[2024-08-01 08:26:19,549][00459] Num frames 6200...
[2024-08-01 08:26:19,676][00459] Num frames 6300...
[2024-08-01 08:26:19,797][00459] Num frames 6400...
[2024-08-01 08:26:19,862][00459] Avg episode rewards: #0: 16.760, true rewards: #0: 8.010
[2024-08-01 08:26:19,864][00459] Avg episode reward: 16.760, avg true_objective: 8.010
[2024-08-01 08:26:19,983][00459] Num frames 6500...
[2024-08-01 08:26:20,133][00459] Num frames 6600...
[2024-08-01 08:26:20,320][00459] Num frames 6700...
[2024-08-01 08:26:20,504][00459] Num frames 6800...
[2024-08-01 08:26:20,674][00459] Num frames 6900...
[2024-08-01 08:26:20,750][00459] Avg episode rewards: #0: 16.010, true rewards: #0: 7.677
[2024-08-01 08:26:20,754][00459] Avg episode reward: 16.010, avg true_objective: 7.677
[2024-08-01 08:26:20,904][00459] Num frames 7000...
[2024-08-01 08:26:21,072][00459] Num frames 7100...
[2024-08-01 08:26:21,242][00459] Num frames 7200...
[2024-08-01 08:26:21,403][00459] Avg episode rewards: #0: 15.161, true rewards: #0: 7.261
[2024-08-01 08:26:21,405][00459] Avg episode reward: 15.161, avg true_objective: 7.261
[2024-08-01 08:27:06,965][00459] Replay video saved to /content/train_dir/default_experiment/replay.mp4!