[2023-02-23 09:18:22,818][00203] Saving configuration to /content/train_dir/default_experiment/config.json...
[2023-02-23 09:18:22,828][00203] Rollout worker 0 uses device cpu
[2023-02-23 09:18:22,836][00203] Rollout worker 1 uses device cpu
[2023-02-23 09:18:22,841][00203] Rollout worker 2 uses device cpu
[2023-02-23 09:18:22,842][00203] Rollout worker 3 uses device cpu
[2023-02-23 09:18:22,846][00203] Rollout worker 4 uses device cpu
[2023-02-23 09:18:22,850][00203] Rollout worker 5 uses device cpu
[2023-02-23 09:18:22,851][00203] Rollout worker 6 uses device cpu
[2023-02-23 09:18:22,854][00203] Rollout worker 7 uses device cpu
[2023-02-23 09:18:23,159][00203] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-23 09:18:23,161][00203] InferenceWorker_p0-w0: min num requests: 2
[2023-02-23 09:18:23,210][00203] Starting all processes...
[2023-02-23 09:18:23,216][00203] Starting process learner_proc0
[2023-02-23 09:18:23,334][00203] Starting all processes...
[2023-02-23 09:18:23,439][00203] Starting process inference_proc0-0
[2023-02-23 09:18:23,440][00203] Starting process rollout_proc0
[2023-02-23 09:18:23,441][00203] Starting process rollout_proc1
[2023-02-23 09:18:23,441][00203] Starting process rollout_proc2
[2023-02-23 09:18:23,441][00203] Starting process rollout_proc3
[2023-02-23 09:18:23,442][00203] Starting process rollout_proc4
[2023-02-23 09:18:23,442][00203] Starting process rollout_proc5
[2023-02-23 09:18:23,442][00203] Starting process rollout_proc6
[2023-02-23 09:18:23,442][00203] Starting process rollout_proc7
[2023-02-23 09:18:36,930][10448] Worker 3 uses CPU cores [1]
[2023-02-23 09:18:37,706][10430] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-23 09:18:37,725][10430] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for learning process 0
[2023-02-23 09:18:37,945][10430] Num visible devices: 1
[2023-02-23 09:18:38,003][10430] Starting seed is not provided
[2023-02-23 09:18:38,005][10430] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-23 09:18:38,007][10430] Initializing actor-critic model on device cuda:0
[2023-02-23 09:18:38,008][10430] RunningMeanStd input shape: (3, 72, 128)
[2023-02-23 09:18:38,015][10430] RunningMeanStd input shape: (1,)
[2023-02-23 09:18:38,079][10445] Worker 0 uses CPU cores [0]
[2023-02-23 09:18:38,101][10430] ConvEncoder: input_channels=3
[2023-02-23 09:18:38,341][10446] Worker 1 uses CPU cores [1]
[2023-02-23 09:18:38,436][10456] Worker 6 uses CPU cores [0]
[2023-02-23 09:18:38,435][10447] Worker 2 uses CPU cores [0]
[2023-02-23 09:18:38,471][10450] Worker 4 uses CPU cores [0]
[2023-02-23 09:18:38,534][10444] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-23 09:18:38,534][10444] Set environment var CUDA_VISIBLE_DEVICES to '0' (GPU indices [0]) for inference process 0
[2023-02-23 09:18:38,572][10449] Worker 5 uses CPU cores [1]
[2023-02-23 09:18:38,584][10455] Worker 7 uses CPU cores [1]
[2023-02-23 09:18:38,593][10444] Num visible devices: 1
[2023-02-23 09:18:38,881][10430] Conv encoder output size: 512
[2023-02-23 09:18:38,882][10430] Policy head output size: 512
[2023-02-23 09:18:38,967][10430] Created Actor Critic model with architecture:
[2023-02-23 09:18:38,969][10430] ActorCriticSharedWeights(
  (obs_normalizer): ObservationNormalizer(
    (running_mean_std): RunningMeanStdDictInPlace(
      (running_mean_std): ModuleDict(
        (obs): RunningMeanStdInPlace()
      )
    )
  )
  (returns_normalizer): RecursiveScriptModule(original_name=RunningMeanStdInPlace)
  (encoder): VizdoomEncoder(
    (basic_encoder): ConvEncoder(
      (enc): RecursiveScriptModule(
        original_name=ConvEncoderImpl
        (conv_head): RecursiveScriptModule(
          original_name=Sequential
          (0): RecursiveScriptModule(original_name=Conv2d)
          (1): RecursiveScriptModule(original_name=ELU)
          (2): RecursiveScriptModule(original_name=Conv2d)
          (3): RecursiveScriptModule(original_name=ELU)
          (4): RecursiveScriptModule(original_name=Conv2d)
          (5): RecursiveScriptModule(original_name=ELU)
        )
        (mlp_layers): RecursiveScriptModule(
          original_name=Sequential
          (0): RecursiveScriptModule(original_name=Linear)
          (1): RecursiveScriptModule(original_name=ELU)
        )
      )
    )
  )
  (core): ModelCoreRNN(
    (core): GRU(512, 512)
  )
  (decoder): MlpDecoder(
    (mlp): Identity()
  )
  (critic_linear): Linear(in_features=512, out_features=1, bias=True)
  (action_parameterization): ActionParameterizationDefault(
    (distribution_linear): Linear(in_features=512, out_features=5, bias=True)
  )
)
[2023-02-23 09:18:43,149][00203] Heartbeat connected on Batcher_0
[2023-02-23 09:18:43,159][00203] Heartbeat connected on InferenceWorker_p0-w0
[2023-02-23 09:18:43,182][00203] Heartbeat connected on RolloutWorker_w1
[2023-02-23 09:18:43,184][00203] Heartbeat connected on RolloutWorker_w0
[2023-02-23 09:18:43,188][00203] Heartbeat connected on RolloutWorker_w2
[2023-02-23 09:18:43,194][00203] Heartbeat connected on RolloutWorker_w3
[2023-02-23 09:18:43,198][00203] Heartbeat connected on RolloutWorker_w4
[2023-02-23 09:18:43,203][00203] Heartbeat connected on RolloutWorker_w5
[2023-02-23 09:18:43,212][00203] Heartbeat connected on RolloutWorker_w6
[2023-02-23 09:18:43,214][00203] Heartbeat connected on RolloutWorker_w7
[2023-02-23 09:18:48,080][10430] Using optimizer <class 'torch.optim.adam.Adam'>
[2023-02-23 09:18:48,081][10430] No checkpoints found
[2023-02-23 09:18:48,082][10430] Did not load from checkpoint, starting from scratch!
[2023-02-23 09:18:48,082][10430] Initialized policy 0 weights for model version 0
[2023-02-23 09:18:48,086][10430] LearnerWorker_p0 finished initialization!
[2023-02-23 09:18:48,087][00203] Heartbeat connected on LearnerWorker_p0
[2023-02-23 09:18:48,095][10430] Using GPUs [0] for process 0 (actually maps to GPUs [0])
[2023-02-23 09:18:48,223][00203] Fps is (10 sec: nan, 60 sec: nan, 300 sec: nan). Total num frames: 0. Throughput: 0: nan. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-23 09:18:48,322][10444] RunningMeanStd input shape: (3, 72, 128)
[2023-02-23 09:18:48,323][10444] RunningMeanStd input shape: (1,)
[2023-02-23 09:18:48,336][10444] ConvEncoder: input_channels=3
[2023-02-23 09:18:48,466][10444] Conv encoder output size: 512
[2023-02-23 09:18:48,466][10444] Policy head output size: 512
[2023-02-23 09:18:50,845][00203] Inference worker 0-0 is ready!
[2023-02-23 09:18:50,847][00203] All inference workers are ready! Signal rollout workers to start!
[2023-02-23 09:18:50,970][10447] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:50,964][10445] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:50,980][10456] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:50,998][10450] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:51,035][10449] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:51,040][10455] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:51,037][10448] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:51,042][10446] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 09:18:51,247][10445] VizDoom game.init() threw an exception ViZDoomUnexpectedExitException('Controlled ViZDoom instance exited unexpectedly.'). Terminate process...
[2023-02-23 09:18:51,247][10456] VizDoom game.init() threw an exception ViZDoomUnexpectedExitException('Controlled ViZDoom instance exited unexpectedly.'). Terminate process...
[2023-02-23 09:18:51,253][10445] EvtLoop [rollout_proc0_evt_loop, process=rollout_proc0] 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/python3.8/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/python3.8/dist-packages/signal_slot/signal_slot.py", line 355, in _process_signal
    slot_callable(*args)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/sampling/rollout_worker.py", line 150, in init
    env_runner.init(self.timing)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/sampling/non_batched_sampling.py", line 418, in init
    self._reset()
  File "/usr/local/lib/python3.8/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/python3.8/dist-packages/gym/core.py", line 323, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/utils/make_env.py", line 125, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/utils/make_env.py", line 110, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/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/python3.8/dist-packages/gym/core.py", line 379, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/envs/env_wrappers.py", line 84, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/gym/core.py", line 323, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/wrappers/multiplayer_stats.py", line 51, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 323, in reset
    self._ensure_initialized()
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 274, in _ensure_initialized
    self.initialize()
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 269, in initialize
    self._game_init()
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 244, in _game_init
    raise EnvCriticalError()
sample_factory.envs.env_utils.EnvCriticalError
[2023-02-23 09:18:51,251][10456] EvtLoop [rollout_proc6_evt_loop, process=rollout_proc6] 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/python3.8/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/python3.8/dist-packages/signal_slot/signal_slot.py", line 355, in _process_signal
    slot_callable(*args)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/sampling/rollout_worker.py", line 150, in init
    env_runner.init(self.timing)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/sampling/non_batched_sampling.py", line 418, in init
    self._reset()
  File "/usr/local/lib/python3.8/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/python3.8/dist-packages/gym/core.py", line 323, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/utils/make_env.py", line 125, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/algo/utils/make_env.py", line 110, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/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/python3.8/dist-packages/gym/core.py", line 379, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sample_factory/envs/env_wrappers.py", line 84, in reset
    obs, info = self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/gym/core.py", line 323, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/wrappers/multiplayer_stats.py", line 51, in reset
    return self.env.reset(**kwargs)
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 323, in reset
    self._ensure_initialized()
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 274, in _ensure_initialized
    self.initialize()
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 269, in initialize
    self._game_init()
  File "/usr/local/lib/python3.8/dist-packages/sf_examples/vizdoom/doom/doom_gym.py", line 244, in _game_init
    raise EnvCriticalError()
sample_factory.envs.env_utils.EnvCriticalError
[2023-02-23 09:18:51,259][10445] Unhandled exception  in evt loop rollout_proc0_evt_loop
[2023-02-23 09:18:51,259][10456] Unhandled exception  in evt loop rollout_proc6_evt_loop
[2023-02-23 09:18:52,279][10455] Decorrelating experience for 0 frames...
[2023-02-23 09:18:52,280][10448] Decorrelating experience for 0 frames...
[2023-02-23 09:18:52,283][10446] Decorrelating experience for 0 frames...
[2023-02-23 09:18:52,570][10447] Decorrelating experience for 0 frames...
[2023-02-23 09:18:52,577][10450] Decorrelating experience for 0 frames...
[2023-02-23 09:18:53,062][10450] Decorrelating experience for 32 frames...
[2023-02-23 09:18:53,222][00203] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-23 09:18:53,277][10455] Decorrelating experience for 32 frames...
[2023-02-23 09:18:53,282][10446] Decorrelating experience for 32 frames...
[2023-02-23 09:18:53,491][10450] Decorrelating experience for 64 frames...
[2023-02-23 09:18:53,840][10449] Decorrelating experience for 0 frames...
[2023-02-23 09:18:53,931][10450] Decorrelating experience for 96 frames...
[2023-02-23 09:18:54,391][10448] Decorrelating experience for 32 frames...
[2023-02-23 09:18:54,442][10447] Decorrelating experience for 32 frames...
[2023-02-23 09:18:54,801][10446] Decorrelating experience for 64 frames...
[2023-02-23 09:18:55,115][10447] Decorrelating experience for 64 frames...
[2023-02-23 09:18:55,124][10449] Decorrelating experience for 32 frames...
[2023-02-23 09:18:55,658][10455] Decorrelating experience for 64 frames...
[2023-02-23 09:18:55,878][10446] Decorrelating experience for 96 frames...
[2023-02-23 09:18:56,018][10448] Decorrelating experience for 64 frames...
[2023-02-23 09:18:56,906][10455] Decorrelating experience for 96 frames...
[2023-02-23 09:18:57,130][10449] Decorrelating experience for 64 frames...
[2023-02-23 09:18:57,223][10448] Decorrelating experience for 96 frames...
[2023-02-23 09:18:57,741][10447] Decorrelating experience for 96 frames...
[2023-02-23 09:18:58,223][00203] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 0.0. Samples: 0. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-23 09:18:58,368][10449] Decorrelating experience for 96 frames...
[2023-02-23 09:19:03,223][00203] Fps is (10 sec: 0.0, 60 sec: 0.0, 300 sec: 0.0). Total num frames: 0. Throughput: 0: 141.5. Samples: 2122. Policy #0 lag: (min: -1.0, avg: -1.0, max: -1.0)
[2023-02-23 09:19:03,227][00203] Avg episode reward: [(0, '2.395')]
[2023-02-23 09:19:03,812][10430] Signal inference workers to stop experience collection...
[2023-02-23 09:19:03,838][10444] InferenceWorker_p0-w0: stopping experience collection
[2023-02-23 09:19:06,129][10430] Signal inference workers to resume experience collection...
[2023-02-23 09:19:06,131][10444] InferenceWorker_p0-w0: resuming experience collection
[2023-02-23 09:19:08,223][00203] Fps is (10 sec: 1228.8, 60 sec: 614.4, 300 sec: 614.4). Total num frames: 12288. Throughput: 0: 124.1. Samples: 2482. Policy #0 lag: (min: 0.0, avg: 0.0, max: 0.0)
[2023-02-23 09:19:08,230][00203] Avg episode reward: [(0, '3.334')]
[2023-02-23 09:19:13,223][00203] Fps is (10 sec: 3276.9, 60 sec: 1310.7, 300 sec: 1310.7). Total num frames: 32768. Throughput: 0: 299.1. Samples: 7478. Policy #0 lag: (min: 0.0, avg: 0.1, max: 1.0)
[2023-02-23 09:19:13,228][00203] Avg episode reward: [(0, '3.977')]
[2023-02-23 09:19:14,873][10444] Updated weights for policy 0, policy_version 10 (0.0013)
[2023-02-23 09:19:18,222][00203] Fps is (10 sec: 3276.9, 60 sec: 1501.9, 300 sec: 1501.9). Total num frames: 45056. Throughput: 0: 409.7. Samples: 12292. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:19:18,228][00203] Avg episode reward: [(0, '4.287')]
[2023-02-23 09:19:23,225][00203] Fps is (10 sec: 2866.5, 60 sec: 1755.3, 300 sec: 1755.3). Total num frames: 61440. Throughput: 0: 402.8. Samples: 14100. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:19:23,228][00203] Avg episode reward: [(0, '4.246')]
[2023-02-23 09:19:28,223][00203] Fps is (10 sec: 3276.8, 60 sec: 1945.6, 300 sec: 1945.6). Total num frames: 77824. Throughput: 0: 480.0. Samples: 19202. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:19:28,231][00203] Avg episode reward: [(0, '4.430')]
[2023-02-23 09:19:28,498][10444] Updated weights for policy 0, policy_version 20 (0.0034)
[2023-02-23 09:19:33,222][00203] Fps is (10 sec: 3687.3, 60 sec: 2184.5, 300 sec: 2184.5). Total num frames: 98304. Throughput: 0: 548.9. Samples: 24700. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:19:33,228][00203] Avg episode reward: [(0, '4.432')]
[2023-02-23 09:19:38,225][00203] Fps is (10 sec: 3276.0, 60 sec: 2211.7, 300 sec: 2211.7). Total num frames: 110592. Throughput: 0: 604.1. Samples: 27184. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:19:38,228][00203] Avg episode reward: [(0, '4.275')]
[2023-02-23 09:19:38,244][10430] Saving new best policy, reward=4.275!
[2023-02-23 09:19:41,856][10444] Updated weights for policy 0, policy_version 30 (0.0020)
[2023-02-23 09:19:43,223][00203] Fps is (10 sec: 2457.6, 60 sec: 2234.2, 300 sec: 2234.2). Total num frames: 122880. Throughput: 0: 689.3. Samples: 31018. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:19:43,230][00203] Avg episode reward: [(0, '4.305')]
[2023-02-23 09:19:43,233][10430] Saving new best policy, reward=4.305!
[2023-02-23 09:19:48,223][00203] Fps is (10 sec: 3277.7, 60 sec: 2389.3, 300 sec: 2389.3). Total num frames: 143360. Throughput: 0: 755.8. Samples: 36132. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:19:48,231][00203] Avg episode reward: [(0, '4.392')]
[2023-02-23 09:19:48,243][10430] Saving new best policy, reward=4.392!
[2023-02-23 09:19:53,223][00203] Fps is (10 sec: 3686.4, 60 sec: 2662.4, 300 sec: 2457.6). Total num frames: 159744. Throughput: 0: 809.9. Samples: 38926. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:19:53,228][00203] Avg episode reward: [(0, '4.437')]
[2023-02-23 09:19:53,233][10430] Saving new best policy, reward=4.437!
[2023-02-23 09:19:53,526][10444] Updated weights for policy 0, policy_version 40 (0.0013)
[2023-02-23 09:19:58,222][00203] Fps is (10 sec: 2867.2, 60 sec: 2867.2, 300 sec: 2457.6). Total num frames: 172032. Throughput: 0: 799.6. Samples: 43460. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:19:58,231][00203] Avg episode reward: [(0, '4.400')]
[2023-02-23 09:20:03,222][00203] Fps is (10 sec: 2867.3, 60 sec: 3140.3, 300 sec: 2512.2). Total num frames: 188416. Throughput: 0: 779.2. Samples: 47356. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:20:03,224][00203] Avg episode reward: [(0, '4.428')]
[2023-02-23 09:20:07,429][10444] Updated weights for policy 0, policy_version 50 (0.0014)
[2023-02-23 09:20:08,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3208.6, 300 sec: 2560.0). Total num frames: 204800. Throughput: 0: 801.2. Samples: 50154. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:20:08,229][00203] Avg episode reward: [(0, '4.487')]
[2023-02-23 09:20:08,239][10430] Saving new best policy, reward=4.487!
[2023-02-23 09:20:13,222][00203] Fps is (10 sec: 3686.3, 60 sec: 3208.5, 300 sec: 2650.4). Total num frames: 225280. Throughput: 0: 818.0. Samples: 56014. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:20:13,228][00203] Avg episode reward: [(0, '4.530')]
[2023-02-23 09:20:13,235][10430] Saving new best policy, reward=4.530!
[2023-02-23 09:20:18,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3208.5, 300 sec: 2639.6). Total num frames: 237568. Throughput: 0: 787.4. Samples: 60132. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:20:18,225][00203] Avg episode reward: [(0, '4.574')]
[2023-02-23 09:20:18,240][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000058_237568.pth...
[2023-02-23 09:20:18,476][10430] Saving new best policy, reward=4.574!
[2023-02-23 09:20:20,739][10444] Updated weights for policy 0, policy_version 60 (0.0015)
[2023-02-23 09:20:23,232][00203] Fps is (10 sec: 2864.6, 60 sec: 3208.2, 300 sec: 2672.9). Total num frames: 253952. Throughput: 0: 771.7. Samples: 61914. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:20:23,237][00203] Avg episode reward: [(0, '4.604')]
[2023-02-23 09:20:23,243][10430] Saving new best policy, reward=4.604!
[2023-02-23 09:20:28,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3276.8, 300 sec: 2744.3). Total num frames: 274432. Throughput: 0: 813.0. Samples: 67602. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:20:28,225][00203] Avg episode reward: [(0, '4.444')]
[2023-02-23 09:20:31,507][10444] Updated weights for policy 0, policy_version 70 (0.0027)
[2023-02-23 09:20:33,223][00203] Fps is (10 sec: 3689.8, 60 sec: 3208.5, 300 sec: 2769.7). Total num frames: 290816. Throughput: 0: 823.5. Samples: 73188. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:20:33,229][00203] Avg episode reward: [(0, '4.524')]
[2023-02-23 09:20:38,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3208.7, 300 sec: 2755.5). Total num frames: 303104. Throughput: 0: 803.5. Samples: 75084. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:20:38,225][00203] Avg episode reward: [(0, '4.637')]
[2023-02-23 09:20:38,236][10430] Saving new best policy, reward=4.637!
[2023-02-23 09:20:43,225][00203] Fps is (10 sec: 2866.5, 60 sec: 3276.7, 300 sec: 2778.1). Total num frames: 319488. Throughput: 0: 792.1. Samples: 79108. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:20:43,230][00203] Avg episode reward: [(0, '4.532')]
[2023-02-23 09:20:44,841][10444] Updated weights for policy 0, policy_version 80 (0.0016)
[2023-02-23 09:20:48,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3276.8, 300 sec: 2833.1). Total num frames: 339968. Throughput: 0: 842.0. Samples: 85246. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:20:48,224][00203] Avg episode reward: [(0, '4.516')]
[2023-02-23 09:20:53,223][00203] Fps is (10 sec: 3687.1, 60 sec: 3276.8, 300 sec: 2850.8). Total num frames: 356352. Throughput: 0: 849.3. Samples: 88374. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:20:53,230][00203] Avg episode reward: [(0, '4.698')]
[2023-02-23 09:20:53,232][10430] Saving new best policy, reward=4.698!
[2023-02-23 09:20:56,822][10444] Updated weights for policy 0, policy_version 90 (0.0019)
[2023-02-23 09:20:58,223][00203] Fps is (10 sec: 2867.1, 60 sec: 3276.8, 300 sec: 2835.7). Total num frames: 368640. Throughput: 0: 809.8. Samples: 92454. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:20:58,228][00203] Avg episode reward: [(0, '4.615')]
[2023-02-23 09:21:03,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3345.0, 300 sec: 2882.4). Total num frames: 389120. Throughput: 0: 829.3. Samples: 97452. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:21:03,227][00203] Avg episode reward: [(0, '4.452')]
[2023-02-23 09:21:08,222][00203] Fps is (10 sec: 3686.5, 60 sec: 3345.1, 300 sec: 2896.5). Total num frames: 405504. Throughput: 0: 856.4. Samples: 100442. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:21:08,227][00203] Avg episode reward: [(0, '4.274')]
[2023-02-23 09:21:08,315][10444] Updated weights for policy 0, policy_version 100 (0.0017)
[2023-02-23 09:21:13,223][00203] Fps is (10 sec: 3277.1, 60 sec: 3276.8, 300 sec: 2909.6). Total num frames: 421888. Throughput: 0: 854.5. Samples: 106056. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:21:13,226][00203] Avg episode reward: [(0, '4.478')]
[2023-02-23 09:21:18,224][00203] Fps is (10 sec: 3276.2, 60 sec: 3345.0, 300 sec: 2921.8). Total num frames: 438272. Throughput: 0: 820.3. Samples: 110102. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:21:18,227][00203] Avg episode reward: [(0, '4.481')]
[2023-02-23 09:21:21,328][10444] Updated weights for policy 0, policy_version 110 (0.0028)
[2023-02-23 09:21:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3345.6, 300 sec: 2933.3). Total num frames: 454656. Throughput: 0: 832.4. Samples: 112544. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:21:23,225][00203] Avg episode reward: [(0, '4.584')]
[2023-02-23 09:21:28,223][00203] Fps is (10 sec: 3687.0, 60 sec: 3345.1, 300 sec: 2969.6). Total num frames: 475136. Throughput: 0: 874.8. Samples: 118474. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:21:28,225][00203] Avg episode reward: [(0, '4.663')]
[2023-02-23 09:21:32,518][10444] Updated weights for policy 0, policy_version 120 (0.0012)
[2023-02-23 09:21:33,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3345.1, 300 sec: 2978.9). Total num frames: 491520. Throughput: 0: 848.0. Samples: 123406. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:21:33,225][00203] Avg episode reward: [(0, '4.661')]
[2023-02-23 09:21:38,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3345.1, 300 sec: 2963.6). Total num frames: 503808. Throughput: 0: 823.5. Samples: 125430. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:21:38,230][00203] Avg episode reward: [(0, '4.788')]
[2023-02-23 09:21:38,241][10430] Saving new best policy, reward=4.788!
[2023-02-23 09:21:43,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.5, 300 sec: 2995.9). Total num frames: 524288. Throughput: 0: 847.7. Samples: 130598. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:21:43,231][00203] Avg episode reward: [(0, '4.763')]
[2023-02-23 09:21:44,627][10444] Updated weights for policy 0, policy_version 130 (0.0013)
[2023-02-23 09:21:48,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3413.3, 300 sec: 3026.5). Total num frames: 544768. Throughput: 0: 872.1. Samples: 136694. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:21:48,226][00203] Avg episode reward: [(0, '4.723')]
[2023-02-23 09:21:53,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3345.1, 300 sec: 3011.1). Total num frames: 557056. Throughput: 0: 852.6. Samples: 138810. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:21:53,227][00203] Avg episode reward: [(0, '4.644')]
[2023-02-23 09:21:57,999][10444] Updated weights for policy 0, policy_version 140 (0.0018)
[2023-02-23 09:21:58,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.4, 300 sec: 3018.1). Total num frames: 573440. Throughput: 0: 818.8. Samples: 142900. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:21:58,225][00203] Avg episode reward: [(0, '4.720')]
[2023-02-23 09:22:03,222][00203] Fps is (10 sec: 3686.5, 60 sec: 3413.4, 300 sec: 3045.7). Total num frames: 593920. Throughput: 0: 857.6. Samples: 148692. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:22:03,230][00203] Avg episode reward: [(0, '4.699')]
[2023-02-23 09:22:08,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3051.5). Total num frames: 610304. Throughput: 0: 870.8. Samples: 151730. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:22:08,225][00203] Avg episode reward: [(0, '5.082')]
[2023-02-23 09:22:08,313][10430] Saving new best policy, reward=5.082!
[2023-02-23 09:22:08,323][10444] Updated weights for policy 0, policy_version 150 (0.0012)
[2023-02-23 09:22:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3057.0). Total num frames: 626688. Throughput: 0: 840.8. Samples: 156312. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:22:13,233][00203] Avg episode reward: [(0, '5.183')]
[2023-02-23 09:22:13,236][10430] Saving new best policy, reward=5.183!
[2023-02-23 09:22:18,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3345.2, 300 sec: 3042.7). Total num frames: 638976. Throughput: 0: 829.3. Samples: 160724. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:22:18,225][00203] Avg episode reward: [(0, '5.343')]
[2023-02-23 09:22:18,236][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000156_638976.pth...
[2023-02-23 09:22:18,363][10430] Saving new best policy, reward=5.343!
[2023-02-23 09:22:21,743][10444] Updated weights for policy 0, policy_version 160 (0.0016)
[2023-02-23 09:22:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3067.2). Total num frames: 659456. Throughput: 0: 845.1. Samples: 163458. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:22:23,225][00203] Avg episode reward: [(0, '5.249')]
[2023-02-23 09:22:28,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3345.1, 300 sec: 3072.0). Total num frames: 675840. Throughput: 0: 854.8. Samples: 169066. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:22:28,225][00203] Avg episode reward: [(0, '5.023')]
[2023-02-23 09:22:33,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3276.8, 300 sec: 3058.3). Total num frames: 688128. Throughput: 0: 802.5. Samples: 172806. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:22:33,231][00203] Avg episode reward: [(0, '5.188')]
[2023-02-23 09:22:35,455][10444] Updated weights for policy 0, policy_version 170 (0.0029)
[2023-02-23 09:22:38,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3345.1, 300 sec: 3063.1). Total num frames: 704512. Throughput: 0: 799.6. Samples: 174792. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:22:38,225][00203] Avg episode reward: [(0, '5.155')]
[2023-02-23 09:22:43,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3345.1, 300 sec: 3085.1). Total num frames: 724992. Throughput: 0: 838.7. Samples: 180640. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:22:43,231][00203] Avg episode reward: [(0, '4.858')]
[2023-02-23 09:22:46,136][10444] Updated weights for policy 0, policy_version 180 (0.0014)
[2023-02-23 09:22:48,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3276.8, 300 sec: 3089.1). Total num frames: 741376. Throughput: 0: 828.8. Samples: 185986. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:22:48,229][00203] Avg episode reward: [(0, '4.941')]
[2023-02-23 09:22:53,223][00203] Fps is (10 sec: 2867.0, 60 sec: 3276.8, 300 sec: 3076.2). Total num frames: 753664. Throughput: 0: 805.4. Samples: 187972. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:22:53,225][00203] Avg episode reward: [(0, '5.123')]
[2023-02-23 09:22:58,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3345.1, 300 sec: 3096.6). Total num frames: 774144. Throughput: 0: 811.5. Samples: 192830. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:22:58,226][00203] Avg episode reward: [(0, '5.051')]
[2023-02-23 09:22:58,984][10444] Updated weights for policy 0, policy_version 190 (0.0020)
[2023-02-23 09:23:03,222][00203] Fps is (10 sec: 4096.3, 60 sec: 3345.1, 300 sec: 3116.2). Total num frames: 794624. Throughput: 0: 848.2. Samples: 198894. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:23:03,224][00203] Avg episode reward: [(0, '5.050')]
[2023-02-23 09:23:08,225][00203] Fps is (10 sec: 3685.6, 60 sec: 3344.9, 300 sec: 3119.2). Total num frames: 811008. Throughput: 0: 846.7. Samples: 201560. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:23:08,228][00203] Avg episode reward: [(0, '5.138')]
[2023-02-23 09:23:11,528][10444] Updated weights for policy 0, policy_version 200 (0.0028)
[2023-02-23 09:23:13,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3276.8, 300 sec: 3106.8). Total num frames: 823296. Throughput: 0: 810.0. Samples: 205516. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:23:13,226][00203] Avg episode reward: [(0, '5.225')]
[2023-02-23 09:23:18,223][00203] Fps is (10 sec: 3277.6, 60 sec: 3413.3, 300 sec: 3125.1). Total num frames: 843776. Throughput: 0: 853.0. Samples: 211192. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:23:18,228][00203] Avg episode reward: [(0, '4.802')]
[2023-02-23 09:23:22,109][10444] Updated weights for policy 0, policy_version 210 (0.0013)
[2023-02-23 09:23:23,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3413.3, 300 sec: 3142.8). Total num frames: 864256. Throughput: 0: 876.3. Samples: 214224. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:23:23,230][00203] Avg episode reward: [(0, '5.026')]
[2023-02-23 09:23:28,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3345.1, 300 sec: 3130.5). Total num frames: 876544. Throughput: 0: 852.0. Samples: 218980. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:23:28,228][00203] Avg episode reward: [(0, '5.213')]
[2023-02-23 09:23:33,228][00203] Fps is (10 sec: 2456.2, 60 sec: 3344.8, 300 sec: 3118.6). Total num frames: 888832. Throughput: 0: 827.6. Samples: 223232. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:23:33,231][00203] Avg episode reward: [(0, '5.406')]
[2023-02-23 09:23:33,234][10430] Saving new best policy, reward=5.406!
[2023-02-23 09:23:35,322][10444] Updated weights for policy 0, policy_version 220 (0.0017)
[2023-02-23 09:23:38,223][00203] Fps is (10 sec: 3276.9, 60 sec: 3413.3, 300 sec: 3135.6). Total num frames: 909312. Throughput: 0: 852.4. Samples: 226328. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:23:38,231][00203] Avg episode reward: [(0, '5.685')]
[2023-02-23 09:23:38,242][10430] Saving new best policy, reward=5.685!
[2023-02-23 09:23:43,222][00203] Fps is (10 sec: 4098.3, 60 sec: 3413.3, 300 sec: 3151.8). Total num frames: 929792. Throughput: 0: 878.1. Samples: 232346. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:23:43,225][00203] Avg episode reward: [(0, '6.056')]
[2023-02-23 09:23:43,235][10430] Saving new best policy, reward=6.056!
[2023-02-23 09:23:47,122][10444] Updated weights for policy 0, policy_version 230 (0.0014)
[2023-02-23 09:23:48,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3345.1, 300 sec: 3193.5). Total num frames: 942080. Throughput: 0: 831.6. Samples: 236316. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:23:48,227][00203] Avg episode reward: [(0, '5.987')]
[2023-02-23 09:23:53,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.4, 300 sec: 3249.0). Total num frames: 958464. Throughput: 0: 818.2. Samples: 238376. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:23:53,230][00203] Avg episode reward: [(0, '6.110')]
[2023-02-23 09:23:53,234][10430] Saving new best policy, reward=6.110!
[2023-02-23 09:23:58,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3318.5). Total num frames: 978944. Throughput: 0: 863.3. Samples: 244364. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:23:58,231][00203] Avg episode reward: [(0, '6.202')]
[2023-02-23 09:23:58,242][10430] Saving new best policy, reward=6.202!
[2023-02-23 09:23:58,824][10444] Updated weights for policy 0, policy_version 240 (0.0030)
[2023-02-23 09:24:03,231][00203] Fps is (10 sec: 3683.4, 60 sec: 3344.6, 300 sec: 3332.2). Total num frames: 995328. Throughput: 0: 855.8. Samples: 249712. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:24:03,234][00203] Avg episode reward: [(0, '6.049')]
[2023-02-23 09:24:08,225][00203] Fps is (10 sec: 3276.0, 60 sec: 3345.1, 300 sec: 3318.4). Total num frames: 1011712. Throughput: 0: 832.9. Samples: 251706. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:24:08,229][00203] Avg episode reward: [(0, '5.956')]
[2023-02-23 09:24:11,785][10444] Updated weights for policy 0, policy_version 250 (0.0015)
[2023-02-23 09:24:13,225][00203] Fps is (10 sec: 3278.8, 60 sec: 3413.2, 300 sec: 3332.3). Total num frames: 1028096. Throughput: 0: 833.0. Samples: 256466. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:24:13,227][00203] Avg episode reward: [(0, '5.787')]
[2023-02-23 09:24:18,223][00203] Fps is (10 sec: 3687.3, 60 sec: 3413.3, 300 sec: 3346.3). Total num frames: 1048576. Throughput: 0: 878.5. Samples: 262760. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:24:18,225][00203] Avg episode reward: [(0, '5.760')]
[2023-02-23 09:24:18,235][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000256_1048576.pth...
[2023-02-23 09:24:18,346][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000058_237568.pth
[2023-02-23 09:24:22,569][10444] Updated weights for policy 0, policy_version 260 (0.0013)
[2023-02-23 09:24:23,222][00203] Fps is (10 sec: 3687.2, 60 sec: 3345.1, 300 sec: 3346.2). Total num frames: 1064960. Throughput: 0: 870.5. Samples: 265500. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:24:23,226][00203] Avg episode reward: [(0, '5.960')]
[2023-02-23 09:24:28,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3345.1, 300 sec: 3318.5). Total num frames: 1077248. Throughput: 0: 828.4. Samples: 269624. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:24:28,232][00203] Avg episode reward: [(0, '5.901')]
[2023-02-23 09:24:33,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.9, 300 sec: 3346.3). Total num frames: 1097728. Throughput: 0: 861.1. Samples: 275064. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:24:33,225][00203] Avg episode reward: [(0, '5.987')]
[2023-02-23 09:24:34,642][10444] Updated weights for policy 0, policy_version 270 (0.0013)
[2023-02-23 09:24:38,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3374.0). Total num frames: 1118208. Throughput: 0: 884.0. Samples: 278156. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:24:38,231][00203] Avg episode reward: [(0, '6.124')]
[2023-02-23 09:24:43,228][00203] Fps is (10 sec: 3684.3, 60 sec: 3413.0, 300 sec: 3360.0). Total num frames: 1134592. Throughput: 0: 864.8. Samples: 283286. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:24:43,233][00203] Avg episode reward: [(0, '6.491')]
[2023-02-23 09:24:43,235][10430] Saving new best policy, reward=6.491!
[2023-02-23 09:24:47,625][10444] Updated weights for policy 0, policy_version 280 (0.0017)
[2023-02-23 09:24:48,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3346.2). Total num frames: 1146880. Throughput: 0: 836.2. Samples: 287332. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:24:48,228][00203] Avg episode reward: [(0, '6.880')]
[2023-02-23 09:24:48,242][10430] Saving new best policy, reward=6.880!
[2023-02-23 09:24:53,223][00203] Fps is (10 sec: 3278.5, 60 sec: 3481.6, 300 sec: 3374.0). Total num frames: 1167360. Throughput: 0: 857.3. Samples: 290282. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:24:53,226][00203] Avg episode reward: [(0, '7.427')]
[2023-02-23 09:24:53,229][10430] Saving new best policy, reward=7.427!
[2023-02-23 09:24:57,687][10444] Updated weights for policy 0, policy_version 290 (0.0012)
[2023-02-23 09:24:58,223][00203] Fps is (10 sec: 4095.9, 60 sec: 3481.6, 300 sec: 3387.9). Total num frames: 1187840. Throughput: 0: 886.8. Samples: 296370. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:24:58,232][00203] Avg episode reward: [(0, '7.731')]
[2023-02-23 09:24:58,247][10430] Saving new best policy, reward=7.731!
[2023-02-23 09:25:03,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3413.8, 300 sec: 3374.0). Total num frames: 1200128. Throughput: 0: 845.8. Samples: 300822. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:25:03,226][00203] Avg episode reward: [(0, '8.029')]
[2023-02-23 09:25:03,231][10430] Saving new best policy, reward=8.029!
[2023-02-23 09:25:08,223][00203] Fps is (10 sec: 2867.3, 60 sec: 3413.5, 300 sec: 3360.1). Total num frames: 1216512. Throughput: 0: 827.7. Samples: 302748. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:25:08,228][00203] Avg episode reward: [(0, '8.015')]
[2023-02-23 09:25:10,935][10444] Updated weights for policy 0, policy_version 300 (0.0021)
[2023-02-23 09:25:13,222][00203] Fps is (10 sec: 3686.7, 60 sec: 3481.7, 300 sec: 3387.9). Total num frames: 1236992. Throughput: 0: 864.4. Samples: 308520. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:25:13,225][00203] Avg episode reward: [(0, '8.383')]
[2023-02-23 09:25:13,228][10430] Saving new best policy, reward=8.383!
[2023-02-23 09:25:18,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3388.0). Total num frames: 1253376. Throughput: 0: 869.7. Samples: 314202. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:25:18,224][00203] Avg episode reward: [(0, '8.490')]
[2023-02-23 09:25:18,243][10430] Saving new best policy, reward=8.490!
[2023-02-23 09:25:23,227][10444] Updated weights for policy 0, policy_version 310 (0.0020)
[2023-02-23 09:25:23,238][00203] Fps is (10 sec: 3271.7, 60 sec: 3412.5, 300 sec: 3373.8). Total num frames: 1269760. Throughput: 0: 843.2. Samples: 316112. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:25:23,244][00203] Avg episode reward: [(0, '8.668')]
[2023-02-23 09:25:23,248][10430] Saving new best policy, reward=8.668!
[2023-02-23 09:25:28,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3360.1). Total num frames: 1282048. Throughput: 0: 823.0. Samples: 320318. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:25:28,228][00203] Avg episode reward: [(0, '7.961')]
[2023-02-23 09:25:33,223][00203] Fps is (10 sec: 3281.9, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 1302528. Throughput: 0: 869.3. Samples: 326450. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:25:33,229][00203] Avg episode reward: [(0, '7.786')]
[2023-02-23 09:25:34,533][10444] Updated weights for policy 0, policy_version 320 (0.0014)
[2023-02-23 09:25:38,223][00203] Fps is (10 sec: 4095.9, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 1323008. Throughput: 0: 871.3. Samples: 329492. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:25:38,230][00203] Avg episode reward: [(0, '8.788')]
[2023-02-23 09:25:38,238][10430] Saving new best policy, reward=8.788!
[2023-02-23 09:25:43,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3345.4, 300 sec: 3374.0). Total num frames: 1335296. Throughput: 0: 829.2. Samples: 333684. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:25:43,225][00203] Avg episode reward: [(0, '9.296')]
[2023-02-23 09:25:43,227][10430] Saving new best policy, reward=9.296!
[2023-02-23 09:25:47,675][10444] Updated weights for policy 0, policy_version 330 (0.0013)
[2023-02-23 09:25:48,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3374.0). Total num frames: 1351680. Throughput: 0: 836.6. Samples: 338470. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:25:48,226][00203] Avg episode reward: [(0, '9.246')]
[2023-02-23 09:25:53,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.4, 300 sec: 3401.8). Total num frames: 1372160. Throughput: 0: 862.6. Samples: 341564. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:25:53,225][00203] Avg episode reward: [(0, '8.644')]
[2023-02-23 09:25:58,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3345.1, 300 sec: 3387.9). Total num frames: 1388544. Throughput: 0: 863.4. Samples: 347372. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:25:58,228][00203] Avg episode reward: [(0, '8.504')]
[2023-02-23 09:25:58,666][10444] Updated weights for policy 0, policy_version 340 (0.0025)
[2023-02-23 09:26:03,223][00203] Fps is (10 sec: 3276.5, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 1404928. Throughput: 0: 828.3. Samples: 351478. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:03,231][00203] Avg episode reward: [(0, '8.796')]
[2023-02-23 09:26:08,224][00203] Fps is (10 sec: 3276.3, 60 sec: 3413.2, 300 sec: 3387.9). Total num frames: 1421312. Throughput: 0: 842.9. Samples: 354030. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:08,230][00203] Avg episode reward: [(0, '9.225')]
[2023-02-23 09:26:10,385][10444] Updated weights for policy 0, policy_version 350 (0.0022)
[2023-02-23 09:26:13,222][00203] Fps is (10 sec: 3686.8, 60 sec: 3413.3, 300 sec: 3401.8). Total num frames: 1441792. Throughput: 0: 887.8. Samples: 360270. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:26:13,230][00203] Avg episode reward: [(0, '9.092')]
[2023-02-23 09:26:18,224][00203] Fps is (10 sec: 3686.5, 60 sec: 3413.3, 300 sec: 3401.7). Total num frames: 1458176. Throughput: 0: 861.4. Samples: 365212. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:26:18,229][00203] Avg episode reward: [(0, '9.324')]
[2023-02-23 09:26:18,244][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000356_1458176.pth...
[2023-02-23 09:26:18,400][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000156_638976.pth
[2023-02-23 09:26:18,413][10430] Saving new best policy, reward=9.324!
[2023-02-23 09:26:23,224][00203] Fps is (10 sec: 2866.9, 60 sec: 3345.9, 300 sec: 3374.0). Total num frames: 1470464. Throughput: 0: 836.6. Samples: 367140. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:23,229][00203] Avg episode reward: [(0, '8.842')]
[2023-02-23 09:26:23,414][10444] Updated weights for policy 0, policy_version 360 (0.0025)
[2023-02-23 09:26:28,223][00203] Fps is (10 sec: 3277.2, 60 sec: 3481.6, 300 sec: 3387.9). Total num frames: 1490944. Throughput: 0: 862.9. Samples: 372516. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:26:28,228][00203] Avg episode reward: [(0, '9.651')]
[2023-02-23 09:26:28,241][10430] Saving new best policy, reward=9.651!
[2023-02-23 09:26:33,223][00203] Fps is (10 sec: 4096.5, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 1511424. Throughput: 0: 896.5. Samples: 378814. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:33,234][00203] Avg episode reward: [(0, '9.707')]
[2023-02-23 09:26:33,319][10444] Updated weights for policy 0, policy_version 370 (0.0021)
[2023-02-23 09:26:33,326][10430] Saving new best policy, reward=9.707!
[2023-02-23 09:26:38,224][00203] Fps is (10 sec: 3685.8, 60 sec: 3413.2, 300 sec: 3401.7). Total num frames: 1527808. Throughput: 0: 876.2. Samples: 380996. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:38,227][00203] Avg episode reward: [(0, '9.921')]
[2023-02-23 09:26:38,242][10430] Saving new best policy, reward=9.921!
[2023-02-23 09:26:43,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3374.0). Total num frames: 1540096. Throughput: 0: 837.7. Samples: 385068. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:26:43,225][00203] Avg episode reward: [(0, '10.351')]
[2023-02-23 09:26:43,233][10430] Saving new best policy, reward=10.351!
[2023-02-23 09:26:46,401][10444] Updated weights for policy 0, policy_version 380 (0.0024)
[2023-02-23 09:26:48,222][00203] Fps is (10 sec: 3687.0, 60 sec: 3549.9, 300 sec: 3415.7). Total num frames: 1564672. Throughput: 0: 882.4. Samples: 391184. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:48,228][00203] Avg episode reward: [(0, '11.310')]
[2023-02-23 09:26:48,237][10430] Saving new best policy, reward=11.310!
[2023-02-23 09:26:53,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 1581056. Throughput: 0: 893.8. Samples: 394250. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:53,227][00203] Avg episode reward: [(0, '11.998')]
[2023-02-23 09:26:53,230][10430] Saving new best policy, reward=11.998!
[2023-02-23 09:26:58,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3387.9). Total num frames: 1593344. Throughput: 0: 855.0. Samples: 398746. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:26:58,226][00203] Avg episode reward: [(0, '11.732')]
[2023-02-23 09:26:58,360][10444] Updated weights for policy 0, policy_version 390 (0.0027)
[2023-02-23 09:27:03,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.7, 300 sec: 3401.8). Total num frames: 1613824. Throughput: 0: 849.0. Samples: 403414. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:27:03,228][00203] Avg episode reward: [(0, '10.579')]
[2023-02-23 09:27:08,222][00203] Fps is (10 sec: 4096.1, 60 sec: 3550.0, 300 sec: 3415.6). Total num frames: 1634304. Throughput: 0: 877.0. Samples: 406606. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:27:08,228][00203] Avg episode reward: [(0, '9.606')]
[2023-02-23 09:27:09,376][10444] Updated weights for policy 0, policy_version 400 (0.0017)
[2023-02-23 09:27:13,224][00203] Fps is (10 sec: 3685.8, 60 sec: 3481.5, 300 sec: 3429.5). Total num frames: 1650688. Throughput: 0: 892.2. Samples: 412666. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:27:13,232][00203] Avg episode reward: [(0, '9.498')]
[2023-02-23 09:27:18,224][00203] Fps is (10 sec: 2866.7, 60 sec: 3413.3, 300 sec: 3401.7). Total num frames: 1662976. Throughput: 0: 841.9. Samples: 416702. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:27:18,228][00203] Avg episode reward: [(0, '9.444')]
[2023-02-23 09:27:22,120][10444] Updated weights for policy 0, policy_version 410 (0.0018)
[2023-02-23 09:27:23,222][00203] Fps is (10 sec: 3277.3, 60 sec: 3549.9, 300 sec: 3415.6). Total num frames: 1683456. Throughput: 0: 844.9. Samples: 419016. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:27:23,225][00203] Avg episode reward: [(0, '10.414')]
[2023-02-23 09:27:28,223][00203] Fps is (10 sec: 4096.7, 60 sec: 3549.9, 300 sec: 3443.4). Total num frames: 1703936. Throughput: 0: 891.7. Samples: 425196. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:27:28,225][00203] Avg episode reward: [(0, '12.017')]
[2023-02-23 09:27:28,236][10430] Saving new best policy, reward=12.017!
[2023-02-23 09:27:33,037][10444] Updated weights for policy 0, policy_version 420 (0.0012)
[2023-02-23 09:27:33,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3443.4). Total num frames: 1720320. Throughput: 0: 872.3. Samples: 430438. Policy #0 lag: (min: 0.0, avg: 0.3, max: 2.0)
[2023-02-23 09:27:33,228][00203] Avg episode reward: [(0, '12.742')]
[2023-02-23 09:27:33,232][10430] Saving new best policy, reward=12.742!
[2023-02-23 09:27:38,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.4, 300 sec: 3415.6). Total num frames: 1732608. Throughput: 0: 848.8. Samples: 432444. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:27:38,228][00203] Avg episode reward: [(0, '13.107')]
[2023-02-23 09:27:38,242][10430] Saving new best policy, reward=13.107!
[2023-02-23 09:27:43,225][00203] Fps is (10 sec: 2866.6, 60 sec: 3481.5, 300 sec: 3415.6). Total num frames: 1748992. Throughput: 0: 855.4. Samples: 437242. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:27:43,227][00203] Avg episode reward: [(0, '12.537')]
[2023-02-23 09:27:45,415][10444] Updated weights for policy 0, policy_version 430 (0.0013)
[2023-02-23 09:27:48,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3443.4). Total num frames: 1769472. Throughput: 0: 889.2. Samples: 443426. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:27:48,230][00203] Avg episode reward: [(0, '10.721')]
[2023-02-23 09:27:53,222][00203] Fps is (10 sec: 3687.2, 60 sec: 3413.3, 300 sec: 3429.5). Total num frames: 1785856. Throughput: 0: 874.9. Samples: 445976. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:27:53,225][00203] Avg episode reward: [(0, '10.567')]
[2023-02-23 09:27:58,194][10444] Updated weights for policy 0, policy_version 440 (0.0014)
[2023-02-23 09:27:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3415.6). Total num frames: 1802240. Throughput: 0: 828.0. Samples: 449924. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:27:58,225][00203] Avg episode reward: [(0, '10.183')]
[2023-02-23 09:28:03,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3415.7). Total num frames: 1818624. Throughput: 0: 864.3. Samples: 455596. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:28:03,225][00203] Avg episode reward: [(0, '10.236')]
[2023-02-23 09:28:08,223][00203] Fps is (10 sec: 3686.3, 60 sec: 3413.3, 300 sec: 3443.4). Total num frames: 1839104. Throughput: 0: 880.9. Samples: 458656. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:28:08,228][00203] Avg episode reward: [(0, '10.566')]
[2023-02-23 09:28:08,275][10444] Updated weights for policy 0, policy_version 450 (0.0014)
[2023-02-23 09:28:13,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.4, 300 sec: 3429.5). Total num frames: 1855488. Throughput: 0: 855.2. Samples: 463680. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:28:13,226][00203] Avg episode reward: [(0, '11.475')]
[2023-02-23 09:28:18,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.4, 300 sec: 3401.8). Total num frames: 1867776. Throughput: 0: 832.9. Samples: 467920. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:28:18,225][00203] Avg episode reward: [(0, '12.641')]
[2023-02-23 09:28:18,239][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000456_1867776.pth...
[2023-02-23 09:28:18,337][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000256_1048576.pth
[2023-02-23 09:28:21,415][10444] Updated weights for policy 0, policy_version 460 (0.0020)
[2023-02-23 09:28:23,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3429.5). Total num frames: 1888256. Throughput: 0: 855.2. Samples: 470928. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:28:23,228][00203] Avg episode reward: [(0, '13.519')]
[2023-02-23 09:28:23,231][10430] Saving new best policy, reward=13.519!
[2023-02-23 09:28:28,225][00203] Fps is (10 sec: 4095.0, 60 sec: 3413.2, 300 sec: 3457.3). Total num frames: 1908736. Throughput: 0: 882.9. Samples: 476972. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:28:28,229][00203] Avg episode reward: [(0, '14.099')]
[2023-02-23 09:28:28,245][10430] Saving new best policy, reward=14.099!
[2023-02-23 09:28:33,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3345.1, 300 sec: 3429.5). Total num frames: 1921024. Throughput: 0: 842.8. Samples: 481352. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:28:33,228][00203] Avg episode reward: [(0, '14.803')]
[2023-02-23 09:28:33,232][10430] Saving new best policy, reward=14.803!
[2023-02-23 09:28:33,687][10444] Updated weights for policy 0, policy_version 470 (0.0012)
[2023-02-23 09:28:38,223][00203] Fps is (10 sec: 2868.0, 60 sec: 3413.3, 300 sec: 3415.6). Total num frames: 1937408. Throughput: 0: 830.7. Samples: 483358. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:28:38,225][00203] Avg episode reward: [(0, '14.358')]
[2023-02-23 09:28:43,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.7, 300 sec: 3443.4). Total num frames: 1957888. Throughput: 0: 876.8. Samples: 489378. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:28:43,230][00203] Avg episode reward: [(0, '13.894')]
[2023-02-23 09:28:44,359][10444] Updated weights for policy 0, policy_version 480 (0.0020)
[2023-02-23 09:28:48,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 1978368. Throughput: 0: 880.7. Samples: 495226. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-23 09:28:48,225][00203] Avg episode reward: [(0, '14.546')]
[2023-02-23 09:28:53,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3429.5). Total num frames: 1990656. Throughput: 0: 858.5. Samples: 497290. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:28:53,228][00203] Avg episode reward: [(0, '14.199')]
[2023-02-23 09:28:57,410][10444] Updated weights for policy 0, policy_version 490 (0.0026)
[2023-02-23 09:28:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3443.5). Total num frames: 2011136. Throughput: 0: 848.0. Samples: 501842. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:28:58,225][00203] Avg episode reward: [(0, '14.744')]
[2023-02-23 09:29:03,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3443.4). Total num frames: 2027520. Throughput: 0: 891.0. Samples: 508014. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:29:03,224][00203] Avg episode reward: [(0, '15.145')]
[2023-02-23 09:29:03,312][10430] Saving new best policy, reward=15.145!
[2023-02-23 09:29:07,992][10444] Updated weights for policy 0, policy_version 500 (0.0015)
[2023-02-23 09:29:08,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2048000. Throughput: 0: 889.0. Samples: 510934. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:29:08,233][00203] Avg episode reward: [(0, '14.952')]
[2023-02-23 09:29:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3429.5). Total num frames: 2060288. Throughput: 0: 844.6. Samples: 514976. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:29:13,225][00203] Avg episode reward: [(0, '15.436')]
[2023-02-23 09:29:13,229][10430] Saving new best policy, reward=15.436!
[2023-02-23 09:29:18,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3443.4). Total num frames: 2080768. Throughput: 0: 867.5. Samples: 520390. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:29:18,224][00203] Avg episode reward: [(0, '15.707')]
[2023-02-23 09:29:18,246][10430] Saving new best policy, reward=15.707!
[2023-02-23 09:29:20,107][10444] Updated weights for policy 0, policy_version 510 (0.0014)
[2023-02-23 09:29:23,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 2101248. Throughput: 0: 891.1. Samples: 523458. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:29:23,231][00203] Avg episode reward: [(0, '15.047')]
[2023-02-23 09:29:28,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.5, 300 sec: 3443.4). Total num frames: 2113536. Throughput: 0: 875.3. Samples: 528768. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:29:28,232][00203] Avg episode reward: [(0, '13.951')]
[2023-02-23 09:29:33,044][10444] Updated weights for policy 0, policy_version 520 (0.0018)
[2023-02-23 09:29:33,223][00203] Fps is (10 sec: 2867.1, 60 sec: 3481.6, 300 sec: 3429.5). Total num frames: 2129920. Throughput: 0: 834.8. Samples: 532790. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:29:33,227][00203] Avg episode reward: [(0, '14.850')]
[2023-02-23 09:29:38,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3443.5). Total num frames: 2150400. Throughput: 0: 855.0. Samples: 535766. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:29:38,225][00203] Avg episode reward: [(0, '14.767')]
[2023-02-23 09:29:42,998][10444] Updated weights for policy 0, policy_version 530 (0.0014)
[2023-02-23 09:29:43,222][00203] Fps is (10 sec: 4096.1, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 2170880. Throughput: 0: 891.3. Samples: 541952. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:29:43,230][00203] Avg episode reward: [(0, '15.394')]
[2023-02-23 09:29:48,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3443.4). Total num frames: 2183168. Throughput: 0: 855.8. Samples: 546524. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:29:48,227][00203] Avg episode reward: [(0, '15.771')]
[2023-02-23 09:29:48,241][10430] Saving new best policy, reward=15.771!
[2023-02-23 09:29:53,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3429.5). Total num frames: 2199552. Throughput: 0: 835.8. Samples: 548546. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:29:53,225][00203] Avg episode reward: [(0, '16.806')]
[2023-02-23 09:29:53,233][10430] Saving new best policy, reward=16.806!
[2023-02-23 09:29:55,901][10444] Updated weights for policy 0, policy_version 540 (0.0016)
[2023-02-23 09:29:58,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2220032. Throughput: 0: 876.3. Samples: 554410. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:29:58,225][00203] Avg episode reward: [(0, '17.491')]
[2023-02-23 09:29:58,238][10430] Saving new best policy, reward=17.491!
[2023-02-23 09:30:03,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2236416. Throughput: 0: 886.4. Samples: 560278. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:30:03,226][00203] Avg episode reward: [(0, '17.352')]
[2023-02-23 09:30:07,838][10444] Updated weights for policy 0, policy_version 550 (0.0012)
[2023-02-23 09:30:08,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3443.4). Total num frames: 2252800. Throughput: 0: 863.8. Samples: 562330. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:30:08,230][00203] Avg episode reward: [(0, '17.399')]
[2023-02-23 09:30:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3443.4). Total num frames: 2269184. Throughput: 0: 843.5. Samples: 566726. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:30:13,225][00203] Avg episode reward: [(0, '16.380')]
[2023-02-23 09:30:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3457.5). Total num frames: 2289664. Throughput: 0: 894.0. Samples: 573018. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:30:18,229][00203] Avg episode reward: [(0, '15.794')]
[2023-02-23 09:30:18,242][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000559_2289664.pth...
[2023-02-23 09:30:18,347][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000356_1458176.pth
[2023-02-23 09:30:18,739][10444] Updated weights for policy 0, policy_version 560 (0.0027)
[2023-02-23 09:30:23,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 2310144. Throughput: 0: 896.3. Samples: 576098. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:30:23,227][00203] Avg episode reward: [(0, '15.827')]
[2023-02-23 09:30:28,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2322432. Throughput: 0: 852.5. Samples: 580314. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:30:28,225][00203] Avg episode reward: [(0, '16.381')]
[2023-02-23 09:30:31,549][10444] Updated weights for policy 0, policy_version 570 (0.0024)
[2023-02-23 09:30:33,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3443.4). Total num frames: 2338816. Throughput: 0: 865.7. Samples: 585480. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:30:33,232][00203] Avg episode reward: [(0, '16.590')]
[2023-02-23 09:30:38,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3471.2). Total num frames: 2359296. Throughput: 0: 891.6. Samples: 588668. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:30:38,229][00203] Avg episode reward: [(0, '16.296')]
[2023-02-23 09:30:41,926][10444] Updated weights for policy 0, policy_version 580 (0.0018)
[2023-02-23 09:30:43,228][00203] Fps is (10 sec: 3684.3, 60 sec: 3413.0, 300 sec: 3471.1). Total num frames: 2375680. Throughput: 0: 887.2. Samples: 594340. Policy #0 lag: (min: 0.0, avg: 0.3, max: 2.0)
[2023-02-23 09:30:43,233][00203] Avg episode reward: [(0, '15.731')]
[2023-02-23 09:30:48,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2392064. Throughput: 0: 851.2. Samples: 598580. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:30:48,229][00203] Avg episode reward: [(0, '16.154')]
[2023-02-23 09:30:53,222][00203] Fps is (10 sec: 3278.6, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2408448. Throughput: 0: 863.2. Samples: 601176. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:30:53,225][00203] Avg episode reward: [(0, '15.791')]
[2023-02-23 09:30:54,117][10444] Updated weights for policy 0, policy_version 590 (0.0016)
[2023-02-23 09:30:58,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3471.2). Total num frames: 2428928. Throughput: 0: 902.1. Samples: 607322. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-23 09:30:58,231][00203] Avg episode reward: [(0, '15.725')]
[2023-02-23 09:31:03,224][00203] Fps is (10 sec: 3685.8, 60 sec: 3481.5, 300 sec: 3471.2). Total num frames: 2445312. Throughput: 0: 871.1. Samples: 612220. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:31:03,230][00203] Avg episode reward: [(0, '15.533')]
[2023-02-23 09:31:06,702][10444] Updated weights for policy 0, policy_version 600 (0.0016)
[2023-02-23 09:31:08,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2461696. Throughput: 0: 847.8. Samples: 614250. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:31:08,228][00203] Avg episode reward: [(0, '15.817')]
[2023-02-23 09:31:13,223][00203] Fps is (10 sec: 3687.0, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 2482176. Throughput: 0: 874.1. Samples: 619650. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-23 09:31:13,225][00203] Avg episode reward: [(0, '15.773')]
[2023-02-23 09:31:16,845][10444] Updated weights for policy 0, policy_version 610 (0.0012)
[2023-02-23 09:31:18,223][00203] Fps is (10 sec: 4096.2, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 2502656. Throughput: 0: 901.4. Samples: 626042. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:31:18,225][00203] Avg episode reward: [(0, '16.747')]
[2023-02-23 09:31:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 2514944. Throughput: 0: 878.1. Samples: 628184. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:31:23,226][00203] Avg episode reward: [(0, '17.161')]
[2023-02-23 09:31:28,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2531328. Throughput: 0: 843.2. Samples: 632278. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:31:28,225][00203] Avg episode reward: [(0, '17.511')]
[2023-02-23 09:31:28,238][10430] Saving new best policy, reward=17.511!
[2023-02-23 09:31:30,006][10444] Updated weights for policy 0, policy_version 620 (0.0013)
[2023-02-23 09:31:33,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 2551808. Throughput: 0: 883.5. Samples: 638338. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:31:33,229][00203] Avg episode reward: [(0, '18.775')]
[2023-02-23 09:31:33,233][10430] Saving new best policy, reward=18.775!
[2023-02-23 09:31:38,222][00203] Fps is (10 sec: 4096.1, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 2572288. Throughput: 0: 893.2. Samples: 641372. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:31:38,235][00203] Avg episode reward: [(0, '18.204')]
[2023-02-23 09:31:41,079][10444] Updated weights for policy 0, policy_version 630 (0.0012)
[2023-02-23 09:31:43,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.9, 300 sec: 3457.3). Total num frames: 2584576. Throughput: 0: 861.8. Samples: 646104. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-23 09:31:43,225][00203] Avg episode reward: [(0, '17.502')]
[2023-02-23 09:31:48,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2600960. Throughput: 0: 855.9. Samples: 650734. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:31:48,231][00203] Avg episode reward: [(0, '17.319')]
[2023-02-23 09:31:52,845][10444] Updated weights for policy 0, policy_version 640 (0.0012)
[2023-02-23 09:31:53,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3485.1). Total num frames: 2621440. Throughput: 0: 879.7. Samples: 653834. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:31:53,225][00203] Avg episode reward: [(0, '17.321')]
[2023-02-23 09:31:58,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3485.1). Total num frames: 2641920. Throughput: 0: 897.7. Samples: 660046. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:31:58,226][00203] Avg episode reward: [(0, '17.634')]
[2023-02-23 09:32:03,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.7, 300 sec: 3457.3). Total num frames: 2654208. Throughput: 0: 845.6. Samples: 664092. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:32:03,228][00203] Avg episode reward: [(0, '18.398')]
[2023-02-23 09:32:05,443][10444] Updated weights for policy 0, policy_version 650 (0.0012)
[2023-02-23 09:32:08,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2670592. Throughput: 0: 847.1. Samples: 666302. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:32:08,226][00203] Avg episode reward: [(0, '18.608')]
[2023-02-23 09:32:13,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 2691072. Throughput: 0: 891.5. Samples: 672394. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:32:13,228][00203] Avg episode reward: [(0, '19.676')]
[2023-02-23 09:32:13,235][10430] Saving new best policy, reward=19.676!
[2023-02-23 09:32:15,664][10444] Updated weights for policy 0, policy_version 660 (0.0012)
[2023-02-23 09:32:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 2707456. Throughput: 0: 875.8. Samples: 677748. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:32:18,225][00203] Avg episode reward: [(0, '19.474')]
[2023-02-23 09:32:18,246][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000661_2707456.pth...
[2023-02-23 09:32:18,393][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000456_1867776.pth
[2023-02-23 09:32:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2723840. Throughput: 0: 852.4. Samples: 679730. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:32:23,226][00203] Avg episode reward: [(0, '19.214')]
[2023-02-23 09:32:28,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 2740224. Throughput: 0: 857.5. Samples: 684690. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:32:28,231][00203] Avg episode reward: [(0, '18.330')]
[2023-02-23 09:32:28,557][10444] Updated weights for policy 0, policy_version 670 (0.0019)
[2023-02-23 09:32:33,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 2760704. Throughput: 0: 892.8. Samples: 690910. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:32:33,230][00203] Avg episode reward: [(0, '18.298')]
[2023-02-23 09:32:38,225][00203] Fps is (10 sec: 3685.6, 60 sec: 3413.2, 300 sec: 3485.1). Total num frames: 2777088. Throughput: 0: 882.9. Samples: 693568. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:32:38,229][00203] Avg episode reward: [(0, '18.848')]
[2023-02-23 09:32:40,547][10444] Updated weights for policy 0, policy_version 680 (0.0018)
[2023-02-23 09:32:43,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3457.3). Total num frames: 2789376. Throughput: 0: 836.3. Samples: 697678. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:32:43,225][00203] Avg episode reward: [(0, '19.538')]
[2023-02-23 09:32:48,227][00203] Fps is (10 sec: 3276.0, 60 sec: 3481.3, 300 sec: 3471.1). Total num frames: 2809856. Throughput: 0: 875.4. Samples: 703490. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:32:48,229][00203] Avg episode reward: [(0, '20.026')]
[2023-02-23 09:32:48,266][10430] Saving new best policy, reward=20.026!
[2023-02-23 09:32:51,251][10444] Updated weights for policy 0, policy_version 690 (0.0016)
[2023-02-23 09:32:53,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 2830336. Throughput: 0: 893.9. Samples: 706528. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:32:53,225][00203] Avg episode reward: [(0, '19.235')]
[2023-02-23 09:32:58,223][00203] Fps is (10 sec: 3688.1, 60 sec: 3413.3, 300 sec: 3485.1). Total num frames: 2846720. Throughput: 0: 868.0. Samples: 711454. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:32:58,228][00203] Avg episode reward: [(0, '20.004')]
[2023-02-23 09:33:03,237][00203] Fps is (10 sec: 2863.2, 60 sec: 3412.5, 300 sec: 3457.1). Total num frames: 2859008. Throughput: 0: 845.2. Samples: 715794. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:33:03,239][00203] Avg episode reward: [(0, '19.173')]
[2023-02-23 09:33:04,360][10444] Updated weights for policy 0, policy_version 700 (0.0026)
[2023-02-23 09:33:08,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3485.1). Total num frames: 2883584. Throughput: 0: 869.3. Samples: 718850. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:33:08,225][00203] Avg episode reward: [(0, '18.337')]
[2023-02-23 09:33:13,222][00203] Fps is (10 sec: 4101.8, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 2899968. Throughput: 0: 900.6. Samples: 725218. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:33:13,225][00203] Avg episode reward: [(0, '18.528')]
[2023-02-23 09:33:14,932][10444] Updated weights for policy 0, policy_version 710 (0.0028)
[2023-02-23 09:33:18,224][00203] Fps is (10 sec: 3276.2, 60 sec: 3481.5, 300 sec: 3485.1). Total num frames: 2916352. Throughput: 0: 856.9. Samples: 729474. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:33:18,228][00203] Avg episode reward: [(0, '18.329')]
[2023-02-23 09:33:23,224][00203] Fps is (10 sec: 3276.5, 60 sec: 3481.5, 300 sec: 3471.2). Total num frames: 2932736. Throughput: 0: 842.1. Samples: 731460. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:33:23,229][00203] Avg episode reward: [(0, '18.863')]
[2023-02-23 09:33:27,054][10444] Updated weights for policy 0, policy_version 720 (0.0017)
[2023-02-23 09:33:28,223][00203] Fps is (10 sec: 3687.0, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 2953216. Throughput: 0: 886.0. Samples: 737550. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:33:28,226][00203] Avg episode reward: [(0, '20.020')]
[2023-02-23 09:33:33,222][00203] Fps is (10 sec: 3686.8, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 2969600. Throughput: 0: 879.9. Samples: 743082. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:33:33,229][00203] Avg episode reward: [(0, '19.864')]
[2023-02-23 09:33:38,223][00203] Fps is (10 sec: 2867.1, 60 sec: 3413.4, 300 sec: 3471.2). Total num frames: 2981888. Throughput: 0: 856.2. Samples: 745058. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:33:38,228][00203] Avg episode reward: [(0, '19.221')]
[2023-02-23 09:33:39,809][10444] Updated weights for policy 0, policy_version 730 (0.0018)
[2023-02-23 09:33:43,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 3002368. Throughput: 0: 858.1. Samples: 750068. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:33:43,225][00203] Avg episode reward: [(0, '19.299')]
[2023-02-23 09:33:48,223][00203] Fps is (10 sec: 4096.2, 60 sec: 3550.1, 300 sec: 3499.0). Total num frames: 3022848. Throughput: 0: 900.1. Samples: 756286. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:33:48,228][00203] Avg episode reward: [(0, '19.981')]
[2023-02-23 09:33:49,892][10444] Updated weights for policy 0, policy_version 740 (0.0012)
[2023-02-23 09:33:53,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 3039232. Throughput: 0: 890.4. Samples: 758918. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:33:53,226][00203] Avg episode reward: [(0, '19.026')]
[2023-02-23 09:33:58,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 3051520. Throughput: 0: 838.4. Samples: 762946. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:33:58,233][00203] Avg episode reward: [(0, '19.900')]
[2023-02-23 09:34:02,496][10444] Updated weights for policy 0, policy_version 750 (0.0016)
[2023-02-23 09:34:03,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3550.7, 300 sec: 3471.2). Total num frames: 3072000. Throughput: 0: 873.6. Samples: 768786. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:34:03,224][00203] Avg episode reward: [(0, '20.344')]
[2023-02-23 09:34:03,227][10430] Saving new best policy, reward=20.344!
[2023-02-23 09:34:08,224][00203] Fps is (10 sec: 4095.2, 60 sec: 3481.5, 300 sec: 3498.9). Total num frames: 3092480. Throughput: 0: 897.0. Samples: 771824. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:34:08,227][00203] Avg episode reward: [(0, '20.521')]
[2023-02-23 09:34:08,250][10430] Saving new best policy, reward=20.521!
[2023-02-23 09:34:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 3104768. Throughput: 0: 867.2. Samples: 776574. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:34:13,231][00203] Avg episode reward: [(0, '21.264')]
[2023-02-23 09:34:13,235][10430] Saving new best policy, reward=21.264!
[2023-02-23 09:34:14,915][10444] Updated weights for policy 0, policy_version 760 (0.0019)
[2023-02-23 09:34:18,223][00203] Fps is (10 sec: 2867.7, 60 sec: 3413.4, 300 sec: 3457.3). Total num frames: 3121152. Throughput: 0: 844.7. Samples: 781092. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:34:18,225][00203] Avg episode reward: [(0, '21.441')]
[2023-02-23 09:34:18,234][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000762_3121152.pth...
[2023-02-23 09:34:18,392][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000559_2289664.pth
[2023-02-23 09:34:18,399][10430] Saving new best policy, reward=21.441!
[2023-02-23 09:34:23,225][00203] Fps is (10 sec: 3685.6, 60 sec: 3481.5, 300 sec: 3485.0). Total num frames: 3141632. Throughput: 0: 865.1. Samples: 783990. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:34:23,231][00203] Avg episode reward: [(0, '20.666')]
[2023-02-23 09:34:25,524][10444] Updated weights for policy 0, policy_version 770 (0.0012)
[2023-02-23 09:34:28,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 3162112. Throughput: 0: 894.2. Samples: 790308. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:34:28,228][00203] Avg episode reward: [(0, '19.965')]
[2023-02-23 09:34:33,223][00203] Fps is (10 sec: 3277.4, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 3174400. Throughput: 0: 845.1. Samples: 794318. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:34:33,227][00203] Avg episode reward: [(0, '20.062')]
[2023-02-23 09:34:38,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 3190784. Throughput: 0: 834.8. Samples: 796484. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:34:38,229][00203] Avg episode reward: [(0, '19.688')]
[2023-02-23 09:34:38,294][10444] Updated weights for policy 0, policy_version 780 (0.0019)
[2023-02-23 09:34:43,223][00203] Fps is (10 sec: 3686.5, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 3211264. Throughput: 0: 885.8. Samples: 802806. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:34:43,230][00203] Avg episode reward: [(0, '18.389')]
[2023-02-23 09:34:48,223][00203] Fps is (10 sec: 4095.7, 60 sec: 3481.6, 300 sec: 3498.9). Total num frames: 3231744. Throughput: 0: 877.7. Samples: 808284. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:34:48,227][00203] Avg episode reward: [(0, '18.875')]
[2023-02-23 09:34:49,567][10444] Updated weights for policy 0, policy_version 790 (0.0013)
[2023-02-23 09:34:53,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 3244032. Throughput: 0: 855.2. Samples: 810306. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:34:53,227][00203] Avg episode reward: [(0, '19.411')]
[2023-02-23 09:34:58,222][00203] Fps is (10 sec: 3277.0, 60 sec: 3549.9, 300 sec: 3485.1). Total num frames: 3264512. Throughput: 0: 858.5. Samples: 815206. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:34:58,225][00203] Avg episode reward: [(0, '19.512')]
[2023-02-23 09:35:01,094][10444] Updated weights for policy 0, policy_version 800 (0.0013)
[2023-02-23 09:35:03,222][00203] Fps is (10 sec: 4096.3, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 3284992. Throughput: 0: 896.2. Samples: 821420. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:35:03,225][00203] Avg episode reward: [(0, '20.227')]
[2023-02-23 09:35:08,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.4, 300 sec: 3485.1). Total num frames: 3297280. Throughput: 0: 892.0. Samples: 824126. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:35:08,226][00203] Avg episode reward: [(0, '20.837')]
[2023-02-23 09:35:13,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3471.2). Total num frames: 3313664. Throughput: 0: 842.3. Samples: 828210. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:35:13,225][00203] Avg episode reward: [(0, '20.406')]
[2023-02-23 09:35:13,899][10444] Updated weights for policy 0, policy_version 810 (0.0014)
[2023-02-23 09:35:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 3334144. Throughput: 0: 880.2. Samples: 833928. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-23 09:35:18,225][00203] Avg episode reward: [(0, '18.764')]
[2023-02-23 09:35:23,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3550.0, 300 sec: 3499.0). Total num frames: 3354624. Throughput: 0: 900.5. Samples: 837006. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:35:23,231][00203] Avg episode reward: [(0, '18.596')]
[2023-02-23 09:35:23,697][10444] Updated weights for policy 0, policy_version 820 (0.0020)
[2023-02-23 09:35:28,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3413.3, 300 sec: 3485.1). Total num frames: 3366912. Throughput: 0: 873.9. Samples: 842132. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:35:28,229][00203] Avg episode reward: [(0, '18.379')]
[2023-02-23 09:35:33,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3471.2). Total num frames: 3383296. Throughput: 0: 849.7. Samples: 846518. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:35:33,225][00203] Avg episode reward: [(0, '18.498')]
[2023-02-23 09:35:36,376][10444] Updated weights for policy 0, policy_version 830 (0.0012)
[2023-02-23 09:35:38,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3485.1). Total num frames: 3403776. Throughput: 0: 875.1. Samples: 849684. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:35:38,225][00203] Avg episode reward: [(0, '19.362')]
[2023-02-23 09:35:43,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 3424256. Throughput: 0: 906.5. Samples: 855998. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:35:43,229][00203] Avg episode reward: [(0, '20.591')]
[2023-02-23 09:35:48,043][10444] Updated weights for policy 0, policy_version 840 (0.0019)
[2023-02-23 09:35:48,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 3440640. Throughput: 0: 867.2. Samples: 860446. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:35:48,226][00203] Avg episode reward: [(0, '21.810')]
[2023-02-23 09:35:48,240][10430] Saving new best policy, reward=21.810!
[2023-02-23 09:35:53,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3471.2). Total num frames: 3452928. Throughput: 0: 851.6. Samples: 862446. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:35:53,228][00203] Avg episode reward: [(0, '22.228')]
[2023-02-23 09:35:53,233][10430] Saving new best policy, reward=22.228!
[2023-02-23 09:35:58,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 3473408. Throughput: 0: 892.2. Samples: 868360. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:35:58,224][00203] Avg episode reward: [(0, '23.605')]
[2023-02-23 09:35:58,241][10430] Saving new best policy, reward=23.605!
[2023-02-23 09:35:59,291][10444] Updated weights for policy 0, policy_version 850 (0.0030)
[2023-02-23 09:36:03,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 3493888. Throughput: 0: 890.1. Samples: 873984. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:36:03,227][00203] Avg episode reward: [(0, '23.827')]
[2023-02-23 09:36:03,230][10430] Saving new best policy, reward=23.827!
[2023-02-23 09:36:08,224][00203] Fps is (10 sec: 3276.4, 60 sec: 3481.5, 300 sec: 3471.2). Total num frames: 3506176. Throughput: 0: 865.9. Samples: 875974. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:36:08,230][00203] Avg episode reward: [(0, '24.062')]
[2023-02-23 09:36:08,243][10430] Saving new best policy, reward=24.062!
[2023-02-23 09:36:12,286][10444] Updated weights for policy 0, policy_version 860 (0.0016)
[2023-02-23 09:36:13,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3457.3). Total num frames: 3522560. Throughput: 0: 855.7. Samples: 880638. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:36:13,230][00203] Avg episode reward: [(0, '23.063')]
[2023-02-23 09:36:18,223][00203] Fps is (10 sec: 3686.8, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 3543040. Throughput: 0: 898.0. Samples: 886928. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:36:18,230][00203] Avg episode reward: [(0, '23.117')]
[2023-02-23 09:36:18,258][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000866_3547136.pth...
[2023-02-23 09:36:18,388][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000661_2707456.pth
[2023-02-23 09:36:23,028][10444] Updated weights for policy 0, policy_version 870 (0.0012)
[2023-02-23 09:36:23,226][00203] Fps is (10 sec: 4094.7, 60 sec: 3481.4, 300 sec: 3498.9). Total num frames: 3563520. Throughput: 0: 892.1. Samples: 889830. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:36:23,232][00203] Avg episode reward: [(0, '20.664')]
[2023-02-23 09:36:28,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3471.2). Total num frames: 3575808. Throughput: 0: 843.3. Samples: 893946. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:36:28,229][00203] Avg episode reward: [(0, '19.845')]
[2023-02-23 09:36:33,223][00203] Fps is (10 sec: 3277.8, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 3596288. Throughput: 0: 872.2. Samples: 899694. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:36:33,230][00203] Avg episode reward: [(0, '18.867')]
[2023-02-23 09:36:34,734][10444] Updated weights for policy 0, policy_version 880 (0.0031)
[2023-02-23 09:36:38,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 3616768. Throughput: 0: 896.1. Samples: 902772. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:36:38,229][00203] Avg episode reward: [(0, '18.756')]
[2023-02-23 09:36:43,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 3633152. Throughput: 0: 881.6. Samples: 908034. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:36:43,232][00203] Avg episode reward: [(0, '18.554')]
[2023-02-23 09:36:47,191][10444] Updated weights for policy 0, policy_version 890 (0.0020)
[2023-02-23 09:36:48,224][00203] Fps is (10 sec: 2866.8, 60 sec: 3413.3, 300 sec: 3471.2). Total num frames: 3645440. Throughput: 0: 849.6. Samples: 912216. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:36:48,229][00203] Avg episode reward: [(0, '19.433')]
[2023-02-23 09:36:53,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3471.2). Total num frames: 3665920. Throughput: 0: 875.3. Samples: 915360. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:36:53,228][00203] Avg episode reward: [(0, '20.261')]
[2023-02-23 09:36:57,232][10444] Updated weights for policy 0, policy_version 900 (0.0014)
[2023-02-23 09:36:58,222][00203] Fps is (10 sec: 4506.2, 60 sec: 3618.1, 300 sec: 3512.8). Total num frames: 3690496. Throughput: 0: 912.0. Samples: 921680. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:36:58,238][00203] Avg episode reward: [(0, '20.469')]
[2023-02-23 09:37:03,224][00203] Fps is (10 sec: 3685.9, 60 sec: 3481.5, 300 sec: 3498.9). Total num frames: 3702784. Throughput: 0: 872.5. Samples: 926194. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:37:03,229][00203] Avg episode reward: [(0, '20.076')]
[2023-02-23 09:37:08,225][00203] Fps is (10 sec: 2866.6, 60 sec: 3549.8, 300 sec: 3485.0). Total num frames: 3719168. Throughput: 0: 852.9. Samples: 928208. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:37:08,233][00203] Avg episode reward: [(0, '20.050')]
[2023-02-23 09:37:09,929][10444] Updated weights for policy 0, policy_version 910 (0.0019)
[2023-02-23 09:37:13,223][00203] Fps is (10 sec: 3687.0, 60 sec: 3618.1, 300 sec: 3499.0). Total num frames: 3739648. Throughput: 0: 895.3. Samples: 934236. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:37:13,231][00203] Avg episode reward: [(0, '20.451')]
[2023-02-23 09:37:18,227][00203] Fps is (10 sec: 3685.5, 60 sec: 3549.6, 300 sec: 3498.9). Total num frames: 3756032. Throughput: 0: 894.9. Samples: 939970. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:37:18,232][00203] Avg episode reward: [(0, '21.255')]
[2023-02-23 09:37:21,762][10444] Updated weights for policy 0, policy_version 920 (0.0031)
[2023-02-23 09:37:23,225][00203] Fps is (10 sec: 3276.0, 60 sec: 3481.6, 300 sec: 3498.9). Total num frames: 3772416. Throughput: 0: 870.4. Samples: 941942. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:37:23,227][00203] Avg episode reward: [(0, '21.175')]
[2023-02-23 09:37:28,223][00203] Fps is (10 sec: 3278.2, 60 sec: 3549.8, 300 sec: 3485.1). Total num frames: 3788800. Throughput: 0: 854.8. Samples: 946502. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:37:28,226][00203] Avg episode reward: [(0, '21.099')]
[2023-02-23 09:37:32,800][10444] Updated weights for policy 0, policy_version 930 (0.0012)
[2023-02-23 09:37:33,223][00203] Fps is (10 sec: 3687.3, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 3809280. Throughput: 0: 900.5. Samples: 952736. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:37:33,231][00203] Avg episode reward: [(0, '22.216')]
[2023-02-23 09:37:38,222][00203] Fps is (10 sec: 3686.6, 60 sec: 3481.6, 300 sec: 3512.8). Total num frames: 3825664. Throughput: 0: 898.5. Samples: 955794. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:37:38,229][00203] Avg episode reward: [(0, '21.416')]
[2023-02-23 09:37:43,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 3842048. Throughput: 0: 851.3. Samples: 959990. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:37:43,229][00203] Avg episode reward: [(0, '21.701')]
[2023-02-23 09:37:45,577][10444] Updated weights for policy 0, policy_version 940 (0.0014)
[2023-02-23 09:37:48,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3485.1). Total num frames: 3858432. Throughput: 0: 870.4. Samples: 965360. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:37:48,228][00203] Avg episode reward: [(0, '20.809')]
[2023-02-23 09:37:53,223][00203] Fps is (10 sec: 3686.5, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 3878912. Throughput: 0: 893.6. Samples: 968420. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:37:53,225][00203] Avg episode reward: [(0, '20.336')]
[2023-02-23 09:37:55,769][10444] Updated weights for policy 0, policy_version 950 (0.0014)
[2023-02-23 09:37:58,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3413.3, 300 sec: 3513.0). Total num frames: 3895296. Throughput: 0: 880.4. Samples: 973854. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:37:58,229][00203] Avg episode reward: [(0, '20.496')]
[2023-02-23 09:38:03,224][00203] Fps is (10 sec: 3276.5, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 3911680. Throughput: 0: 844.2. Samples: 977958. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:38:03,226][00203] Avg episode reward: [(0, '20.350')]
[2023-02-23 09:38:08,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.7, 300 sec: 3485.1). Total num frames: 3928064. Throughput: 0: 866.8. Samples: 980946. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:38:08,225][00203] Avg episode reward: [(0, '20.561')]
[2023-02-23 09:38:08,389][10444] Updated weights for policy 0, policy_version 960 (0.0016)
[2023-02-23 09:38:13,222][00203] Fps is (10 sec: 3686.8, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 3948544. Throughput: 0: 901.7. Samples: 987080. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:38:13,225][00203] Avg episode reward: [(0, '23.477')]
[2023-02-23 09:38:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.9, 300 sec: 3499.0). Total num frames: 3964928. Throughput: 0: 865.6. Samples: 991690. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:38:18,233][00203] Avg episode reward: [(0, '22.733')]
[2023-02-23 09:38:18,245][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000968_3964928.pth...
[2023-02-23 09:38:18,244][00203] No heartbeat for components: RolloutWorker_w0 (1175 seconds), RolloutWorker_w6 (1175 seconds)
[2023-02-23 09:38:18,384][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000762_3121152.pth
[2023-02-23 09:38:20,673][10444] Updated weights for policy 0, policy_version 970 (0.0014)
[2023-02-23 09:38:23,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3413.5, 300 sec: 3471.2). Total num frames: 3977216. Throughput: 0: 842.4. Samples: 993704. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:38:23,225][00203] Avg episode reward: [(0, '23.285')]
[2023-02-23 09:38:28,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 4001792. Throughput: 0: 877.6. Samples: 999484. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:38:28,226][00203] Avg episode reward: [(0, '22.145')]
[2023-02-23 09:38:31,124][10444] Updated weights for policy 0, policy_version 980 (0.0016)
[2023-02-23 09:38:33,230][00203] Fps is (10 sec: 4502.2, 60 sec: 3549.4, 300 sec: 3526.6). Total num frames: 4022272. Throughput: 0: 899.4. Samples: 1005838. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:38:33,233][00203] Avg episode reward: [(0, '19.993')]
[2023-02-23 09:38:38,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 4034560. Throughput: 0: 877.4. Samples: 1007904. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:38:38,230][00203] Avg episode reward: [(0, '17.882')]
[2023-02-23 09:38:43,222][00203] Fps is (10 sec: 2869.4, 60 sec: 3481.6, 300 sec: 3485.1). Total num frames: 4050944. Throughput: 0: 852.8. Samples: 1012232. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:38:43,231][00203] Avg episode reward: [(0, '18.166')]
[2023-02-23 09:38:43,687][10444] Updated weights for policy 0, policy_version 990 (0.0017)
[2023-02-23 09:38:48,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 4071424. Throughput: 0: 906.0. Samples: 1018728. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:38:48,231][00203] Avg episode reward: [(0, '18.360')]
[2023-02-23 09:38:53,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3526.7). Total num frames: 4091904. Throughput: 0: 909.4. Samples: 1021868. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:38:53,225][00203] Avg episode reward: [(0, '18.136')]
[2023-02-23 09:38:54,157][10444] Updated weights for policy 0, policy_version 1000 (0.0012)
[2023-02-23 09:38:58,223][00203] Fps is (10 sec: 3276.6, 60 sec: 3481.6, 300 sec: 3498.9). Total num frames: 4104192. Throughput: 0: 871.8. Samples: 1026310. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:38:58,226][00203] Avg episode reward: [(0, '17.893')]
[2023-02-23 09:39:03,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.7, 300 sec: 3485.1). Total num frames: 4120576. Throughput: 0: 878.2. Samples: 1031208. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:39:03,229][00203] Avg episode reward: [(0, '18.001')]
[2023-02-23 09:39:06,288][10444] Updated weights for policy 0, policy_version 1010 (0.0012)
[2023-02-23 09:39:08,223][00203] Fps is (10 sec: 4096.2, 60 sec: 3618.1, 300 sec: 3526.7). Total num frames: 4145152. Throughput: 0: 902.5. Samples: 1034316. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:39:08,229][00203] Avg episode reward: [(0, '17.514')]
[2023-02-23 09:39:13,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3526.7). Total num frames: 4161536. Throughput: 0: 905.6. Samples: 1040234. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:39:13,226][00203] Avg episode reward: [(0, '17.420')]
[2023-02-23 09:39:18,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3499.0). Total num frames: 4173824. Throughput: 0: 858.9. Samples: 1044482. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:39:18,226][00203] Avg episode reward: [(0, '18.226')]
[2023-02-23 09:39:18,341][10444] Updated weights for policy 0, policy_version 1020 (0.0019)
[2023-02-23 09:39:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3499.0). Total num frames: 4194304. Throughput: 0: 870.7. Samples: 1047084. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:39:23,231][00203] Avg episode reward: [(0, '19.320')]
[2023-02-23 09:39:28,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3526.7). Total num frames: 4214784. Throughput: 0: 917.7. Samples: 1053528. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:39:28,226][00203] Avg episode reward: [(0, '19.803')]
[2023-02-23 09:39:28,463][10444] Updated weights for policy 0, policy_version 1030 (0.0014)
[2023-02-23 09:39:33,225][00203] Fps is (10 sec: 3685.5, 60 sec: 3481.9, 300 sec: 3526.7). Total num frames: 4231168. Throughput: 0: 887.8. Samples: 1058682. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:39:33,230][00203] Avg episode reward: [(0, '20.394')]
[2023-02-23 09:39:38,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3512.8). Total num frames: 4247552. Throughput: 0: 864.4. Samples: 1060764. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:39:38,231][00203] Avg episode reward: [(0, '20.691')]
[2023-02-23 09:39:41,175][10444] Updated weights for policy 0, policy_version 1040 (0.0014)
[2023-02-23 09:39:43,226][00203] Fps is (10 sec: 3685.9, 60 sec: 3617.9, 300 sec: 3512.8). Total num frames: 4268032. Throughput: 0: 886.6. Samples: 1066208. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:39:43,234][00203] Avg episode reward: [(0, '21.079')]
[2023-02-23 09:39:48,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3540.6). Total num frames: 4288512. Throughput: 0: 919.2. Samples: 1072572. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:39:48,233][00203] Avg episode reward: [(0, '22.126')]
[2023-02-23 09:39:52,149][10444] Updated weights for policy 0, policy_version 1050 (0.0014)
[2023-02-23 09:39:53,226][00203] Fps is (10 sec: 3276.9, 60 sec: 3481.4, 300 sec: 3512.8). Total num frames: 4300800. Throughput: 0: 899.7. Samples: 1074806. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:39:53,232][00203] Avg episode reward: [(0, '22.109')]
[2023-02-23 09:39:58,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3499.0). Total num frames: 4317184. Throughput: 0: 860.7. Samples: 1078966. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:39:58,225][00203] Avg episode reward: [(0, '22.514')]
[2023-02-23 09:40:03,222][00203] Fps is (10 sec: 3687.7, 60 sec: 3618.1, 300 sec: 3526.7). Total num frames: 4337664. Throughput: 0: 904.4. Samples: 1085178. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:40:03,226][00203] Avg episode reward: [(0, '22.501')]
[2023-02-23 09:40:03,481][10444] Updated weights for policy 0, policy_version 1060 (0.0027)
[2023-02-23 09:40:08,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3540.6). Total num frames: 4358144. Throughput: 0: 917.1. Samples: 1088354. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:40:08,229][00203] Avg episode reward: [(0, '22.370')]
[2023-02-23 09:40:13,228][00203] Fps is (10 sec: 3275.0, 60 sec: 3481.3, 300 sec: 3512.8). Total num frames: 4370432. Throughput: 0: 875.4. Samples: 1092924. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:40:13,231][00203] Avg episode reward: [(0, '21.003')]
[2023-02-23 09:40:16,279][10444] Updated weights for policy 0, policy_version 1070 (0.0024)
[2023-02-23 09:40:18,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3512.8). Total num frames: 4390912. Throughput: 0: 871.6. Samples: 1097902. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:40:18,225][00203] Avg episode reward: [(0, '20.718')]
[2023-02-23 09:40:18,241][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001072_4390912.pth...
[2023-02-23 09:40:18,367][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000866_3547136.pth
[2023-02-23 09:40:23,224][00203] Fps is (10 sec: 4097.6, 60 sec: 3618.0, 300 sec: 3540.6). Total num frames: 4411392. Throughput: 0: 894.8. Samples: 1101030. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:40:23,227][00203] Avg episode reward: [(0, '21.177')]
[2023-02-23 09:40:26,068][10444] Updated weights for policy 0, policy_version 1080 (0.0019)
[2023-02-23 09:40:28,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3540.6). Total num frames: 4427776. Throughput: 0: 907.4. Samples: 1107040. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:40:28,227][00203] Avg episode reward: [(0, '20.479')]
[2023-02-23 09:40:33,223][00203] Fps is (10 sec: 2867.6, 60 sec: 3481.7, 300 sec: 3512.8). Total num frames: 4440064. Throughput: 0: 855.8. Samples: 1111084. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:40:33,231][00203] Avg episode reward: [(0, '20.691')]
[2023-02-23 09:40:38,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3512.8). Total num frames: 4460544. Throughput: 0: 866.9. Samples: 1113812. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:40:38,225][00203] Avg episode reward: [(0, '19.292')]
[2023-02-23 09:40:38,662][10444] Updated weights for policy 0, policy_version 1090 (0.0016)
[2023-02-23 09:40:43,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3550.1, 300 sec: 3526.7). Total num frames: 4481024. Throughput: 0: 916.5. Samples: 1120208. Policy #0 lag: (min: 0.0, avg: 0.3, max: 2.0)
[2023-02-23 09:40:43,228][00203] Avg episode reward: [(0, '19.590')]
[2023-02-23 09:40:48,234][00203] Fps is (10 sec: 4091.4, 60 sec: 3549.2, 300 sec: 3554.4). Total num frames: 4501504. Throughput: 0: 896.9. Samples: 1125550. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:40:48,241][00203] Avg episode reward: [(0, '19.277')]
[2023-02-23 09:40:49,796][10444] Updated weights for policy 0, policy_version 1100 (0.0014)
[2023-02-23 09:40:53,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3550.1, 300 sec: 3526.7). Total num frames: 4513792. Throughput: 0: 873.5. Samples: 1127660. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:40:53,229][00203] Avg episode reward: [(0, '18.489')]
[2023-02-23 09:40:58,223][00203] Fps is (10 sec: 3280.5, 60 sec: 3618.1, 300 sec: 3526.7). Total num frames: 4534272. Throughput: 0: 896.4. Samples: 1133258. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:40:58,231][00203] Avg episode reward: [(0, '18.525')]
[2023-02-23 09:41:00,492][10444] Updated weights for policy 0, policy_version 1110 (0.0027)
[2023-02-23 09:41:03,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 4554752. Throughput: 0: 929.3. Samples: 1139720. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:41:03,230][00203] Avg episode reward: [(0, '18.774')]
[2023-02-23 09:41:08,227][00203] Fps is (10 sec: 3684.7, 60 sec: 3549.6, 300 sec: 3554.4). Total num frames: 4571136. Throughput: 0: 911.0. Samples: 1142028. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:41:08,230][00203] Avg episode reward: [(0, '20.119')]
[2023-02-23 09:41:12,938][10444] Updated weights for policy 0, policy_version 1120 (0.0013)
[2023-02-23 09:41:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.5, 300 sec: 3540.6). Total num frames: 4587520. Throughput: 0: 872.5. Samples: 1146302. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:41:13,230][00203] Avg episode reward: [(0, '21.381')]
[2023-02-23 09:41:18,223][00203] Fps is (10 sec: 3688.1, 60 sec: 3618.1, 300 sec: 3540.6). Total num frames: 4608000. Throughput: 0: 922.8. Samples: 1152612. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:41:18,231][00203] Avg episode reward: [(0, '22.082')]
[2023-02-23 09:41:22,761][10444] Updated weights for policy 0, policy_version 1130 (0.0012)
[2023-02-23 09:41:23,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 4628480. Throughput: 0: 932.4. Samples: 1155772. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:41:23,225][00203] Avg episode reward: [(0, '22.369')]
[2023-02-23 09:41:28,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3540.6). Total num frames: 4640768. Throughput: 0: 895.7. Samples: 1160516. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:41:28,225][00203] Avg episode reward: [(0, '22.608')]
[2023-02-23 09:41:33,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3686.4, 300 sec: 3540.6). Total num frames: 4661248. Throughput: 0: 886.1. Samples: 1165416. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:41:33,226][00203] Avg episode reward: [(0, '23.837')]
[2023-02-23 09:41:35,109][10444] Updated weights for policy 0, policy_version 1140 (0.0012)
[2023-02-23 09:41:38,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3554.5). Total num frames: 4681728. Throughput: 0: 908.9. Samples: 1168562. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:41:38,228][00203] Avg episode reward: [(0, '22.842')]
[2023-02-23 09:41:43,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 4698112. Throughput: 0: 916.6. Samples: 1174504. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:41:43,225][00203] Avg episode reward: [(0, '22.214')]
[2023-02-23 09:41:46,652][10444] Updated weights for policy 0, policy_version 1150 (0.0017)
[2023-02-23 09:41:48,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3482.3, 300 sec: 3540.6). Total num frames: 4710400. Throughput: 0: 868.0. Samples: 1178780. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:41:48,229][00203] Avg episode reward: [(0, '23.182')]
[2023-02-23 09:41:53,224][00203] Fps is (10 sec: 3276.2, 60 sec: 3618.0, 300 sec: 3526.7). Total num frames: 4730880. Throughput: 0: 876.9. Samples: 1181488. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:41:53,235][00203] Avg episode reward: [(0, '23.047')]
[2023-02-23 09:41:57,197][10444] Updated weights for policy 0, policy_version 1160 (0.0012)
[2023-02-23 09:41:58,223][00203] Fps is (10 sec: 4505.5, 60 sec: 3686.4, 300 sec: 3568.4). Total num frames: 4755456. Throughput: 0: 926.3. Samples: 1187986. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:41:58,225][00203] Avg episode reward: [(0, '23.099')]
[2023-02-23 09:42:03,224][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.8, 300 sec: 3554.5). Total num frames: 4767744. Throughput: 0: 898.5. Samples: 1193048. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:42:03,227][00203] Avg episode reward: [(0, '23.293')]
[2023-02-23 09:42:08,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3550.1, 300 sec: 3540.6). Total num frames: 4784128. Throughput: 0: 873.4. Samples: 1195074. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:42:08,230][00203] Avg episode reward: [(0, '22.910')]
[2023-02-23 09:42:09,635][10444] Updated weights for policy 0, policy_version 1170 (0.0020)
[2023-02-23 09:42:13,223][00203] Fps is (10 sec: 3687.0, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 4804608. Throughput: 0: 895.2. Samples: 1200800. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:42:13,226][00203] Avg episode reward: [(0, '21.978')]
[2023-02-23 09:42:18,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 4825088. Throughput: 0: 927.6. Samples: 1207156. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:42:18,225][00203] Avg episode reward: [(0, '21.900')]
[2023-02-23 09:42:18,241][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001178_4825088.pth...
[2023-02-23 09:42:18,353][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000000968_3964928.pth
[2023-02-23 09:42:20,107][10444] Updated weights for policy 0, policy_version 1180 (0.0020)
[2023-02-23 09:42:23,222][00203] Fps is (10 sec: 3276.9, 60 sec: 3481.6, 300 sec: 3554.5). Total num frames: 4837376. Throughput: 0: 902.6. Samples: 1209178. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:42:23,231][00203] Avg episode reward: [(0, '21.463')]
[2023-02-23 09:42:28,223][00203] Fps is (10 sec: 2867.1, 60 sec: 3549.8, 300 sec: 3540.6). Total num frames: 4853760. Throughput: 0: 865.5. Samples: 1213450. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:42:28,228][00203] Avg episode reward: [(0, '20.938')]
[2023-02-23 09:42:32,130][10444] Updated weights for policy 0, policy_version 1190 (0.0018)
[2023-02-23 09:42:33,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 4878336. Throughput: 0: 911.9. Samples: 1219816. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:42:33,224][00203] Avg episode reward: [(0, '19.893')]
[2023-02-23 09:42:38,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.8, 300 sec: 3568.4). Total num frames: 4894720. Throughput: 0: 922.1. Samples: 1222980. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-23 09:42:38,231][00203] Avg episode reward: [(0, '20.148')]
[2023-02-23 09:42:43,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 4911104. Throughput: 0: 876.3. Samples: 1227420. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:42:43,230][00203] Avg episode reward: [(0, '19.494')]
[2023-02-23 09:42:44,310][10444] Updated weights for policy 0, policy_version 1200 (0.0016)
[2023-02-23 09:42:48,223][00203] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 4927488. Throughput: 0: 873.1. Samples: 1232334. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:42:48,228][00203] Avg episode reward: [(0, '19.512')]
[2023-02-23 09:42:53,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 4947968. Throughput: 0: 897.6. Samples: 1235464. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:42:53,226][00203] Avg episode reward: [(0, '22.117')]
[2023-02-23 09:42:54,623][10444] Updated weights for policy 0, policy_version 1210 (0.0020)
[2023-02-23 09:42:58,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3568.4). Total num frames: 4964352. Throughput: 0: 903.7. Samples: 1241466. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:42:58,227][00203] Avg episode reward: [(0, '22.565')]
[2023-02-23 09:43:03,224][00203] Fps is (10 sec: 3276.4, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 4980736. Throughput: 0: 856.1. Samples: 1245682. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:43:03,232][00203] Avg episode reward: [(0, '23.186')]
[2023-02-23 09:43:07,162][10444] Updated weights for policy 0, policy_version 1220 (0.0021)
[2023-02-23 09:43:08,223][00203] Fps is (10 sec: 3686.3, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 5001216. Throughput: 0: 871.7. Samples: 1248404. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:43:08,226][00203] Avg episode reward: [(0, '24.718')]
[2023-02-23 09:43:08,241][10430] Saving new best policy, reward=24.718!
[2023-02-23 09:43:13,223][00203] Fps is (10 sec: 4096.5, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 5021696. Throughput: 0: 918.3. Samples: 1254772. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:43:13,226][00203] Avg episode reward: [(0, '25.713')]
[2023-02-23 09:43:13,228][10430] Saving new best policy, reward=25.713!
[2023-02-23 09:43:17,832][10444] Updated weights for policy 0, policy_version 1230 (0.0014)
[2023-02-23 09:43:18,223][00203] Fps is (10 sec: 3686.5, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 5038080. Throughput: 0: 890.9. Samples: 1259908. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:43:18,230][00203] Avg episode reward: [(0, '26.291')]
[2023-02-23 09:43:18,253][10430] Saving new best policy, reward=26.291!
[2023-02-23 09:43:23,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 5050368. Throughput: 0: 864.6. Samples: 1261888. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:43:23,230][00203] Avg episode reward: [(0, '25.134')]
[2023-02-23 09:43:28,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3554.6). Total num frames: 5070848. Throughput: 0: 884.8. Samples: 1267238. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:43:28,225][00203] Avg episode reward: [(0, '23.973')]
[2023-02-23 09:43:29,731][10444] Updated weights for policy 0, policy_version 1240 (0.0020)
[2023-02-23 09:43:33,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 5091328. Throughput: 0: 916.1. Samples: 1273560. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:43:33,225][00203] Avg episode reward: [(0, '24.075')]
[2023-02-23 09:43:38,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 5107712. Throughput: 0: 901.8. Samples: 1276046. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:43:38,224][00203] Avg episode reward: [(0, '24.073')]
[2023-02-23 09:43:41,947][10444] Updated weights for policy 0, policy_version 1250 (0.0011)
[2023-02-23 09:43:43,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5124096. Throughput: 0: 865.1. Samples: 1280394. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:43:43,225][00203] Avg episode reward: [(0, '23.780')]
[2023-02-23 09:43:48,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 5144576. Throughput: 0: 907.0. Samples: 1286496. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:43:48,230][00203] Avg episode reward: [(0, '23.250')]
[2023-02-23 09:43:51,556][10444] Updated weights for policy 0, policy_version 1260 (0.0020)
[2023-02-23 09:43:53,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3596.2). Total num frames: 5165056. Throughput: 0: 919.7. Samples: 1289792. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:43:53,230][00203] Avg episode reward: [(0, '23.386')]
[2023-02-23 09:43:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 5177344. Throughput: 0: 885.8. Samples: 1294634. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:43:58,229][00203] Avg episode reward: [(0, '24.605')]
[2023-02-23 09:44:03,224][00203] Fps is (10 sec: 2866.7, 60 sec: 3549.8, 300 sec: 3554.5). Total num frames: 5193728. Throughput: 0: 879.0. Samples: 1299466. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:44:03,229][00203] Avg episode reward: [(0, '24.531')]
[2023-02-23 09:44:04,169][10444] Updated weights for policy 0, policy_version 1270 (0.0014)
[2023-02-23 09:44:08,222][00203] Fps is (10 sec: 4096.1, 60 sec: 3618.2, 300 sec: 3582.3). Total num frames: 5218304. Throughput: 0: 905.2. Samples: 1302622. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:44:08,230][00203] Avg episode reward: [(0, '25.275')]
[2023-02-23 09:44:13,222][00203] Fps is (10 sec: 4096.7, 60 sec: 3549.9, 300 sec: 3596.2). Total num frames: 5234688. Throughput: 0: 920.8. Samples: 1308672. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:44:13,228][00203] Avg episode reward: [(0, '25.939')]
[2023-02-23 09:44:15,673][10444] Updated weights for policy 0, policy_version 1280 (0.0013)
[2023-02-23 09:44:18,225][00203] Fps is (10 sec: 2866.6, 60 sec: 3481.5, 300 sec: 3568.4). Total num frames: 5246976. Throughput: 0: 871.5. Samples: 1312778. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:44:18,230][00203] Avg episode reward: [(0, '25.123')]
[2023-02-23 09:44:18,355][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001282_5251072.pth...
[2023-02-23 09:44:18,481][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001072_4390912.pth
[2023-02-23 09:44:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 5267456. Throughput: 0: 870.5. Samples: 1315220. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:44:23,225][00203] Avg episode reward: [(0, '26.208')]
[2023-02-23 09:44:26,646][10444] Updated weights for policy 0, policy_version 1290 (0.0015)
[2023-02-23 09:44:28,222][00203] Fps is (10 sec: 4096.9, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 5287936. Throughput: 0: 916.8. Samples: 1321650. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:44:28,226][00203] Avg episode reward: [(0, '25.292')]
[2023-02-23 09:44:33,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 5304320. Throughput: 0: 898.2. Samples: 1326914. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:44:33,224][00203] Avg episode reward: [(0, '24.308')]
[2023-02-23 09:44:38,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5320704. Throughput: 0: 871.0. Samples: 1328988. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:44:38,234][00203] Avg episode reward: [(0, '23.497')]
[2023-02-23 09:44:39,219][10444] Updated weights for policy 0, policy_version 1300 (0.0020)
[2023-02-23 09:44:43,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 5341184. Throughput: 0: 884.2. Samples: 1334422. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:44:43,225][00203] Avg episode reward: [(0, '22.967')]
[2023-02-23 09:44:48,223][00203] Fps is (10 sec: 4096.1, 60 sec: 3618.1, 300 sec: 3596.2). Total num frames: 5361664. Throughput: 0: 916.9. Samples: 1340724. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:44:48,225][00203] Avg episode reward: [(0, '23.070')]
[2023-02-23 09:44:49,248][10444] Updated weights for policy 0, policy_version 1310 (0.0011)
[2023-02-23 09:44:53,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3582.3). Total num frames: 5373952. Throughput: 0: 898.8. Samples: 1343070. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:44:53,235][00203] Avg episode reward: [(0, '23.973')]
[2023-02-23 09:44:58,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5390336. Throughput: 0: 859.6. Samples: 1347352. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:44:58,228][00203] Avg episode reward: [(0, '23.402')]
[2023-02-23 09:45:01,419][10444] Updated weights for policy 0, policy_version 1320 (0.0015)
[2023-02-23 09:45:03,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 5410816. Throughput: 0: 907.6. Samples: 1353616. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:45:03,232][00203] Avg episode reward: [(0, '22.770')]
[2023-02-23 09:45:08,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3596.2). Total num frames: 5431296. Throughput: 0: 922.4. Samples: 1356728. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:45:08,229][00203] Avg episode reward: [(0, '22.474')]
[2023-02-23 09:45:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3568.4). Total num frames: 5443584. Throughput: 0: 884.0. Samples: 1361428. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:45:13,225][00203] Avg episode reward: [(0, '23.821')]
[2023-02-23 09:45:13,373][10444] Updated weights for policy 0, policy_version 1330 (0.0014)
[2023-02-23 09:45:18,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.3, 300 sec: 3568.4). Total num frames: 5464064. Throughput: 0: 874.2. Samples: 1366254. Policy #0 lag: (min: 0.0, avg: 0.5, max: 2.0)
[2023-02-23 09:45:18,232][00203] Avg episode reward: [(0, '22.995')]
[2023-02-23 09:45:23,226][00203] Fps is (10 sec: 4094.5, 60 sec: 3617.9, 300 sec: 3582.2). Total num frames: 5484544. Throughput: 0: 897.7. Samples: 1369388. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:45:23,229][00203] Avg episode reward: [(0, '23.021')]
[2023-02-23 09:45:23,864][10444] Updated weights for policy 0, policy_version 1340 (0.0021)
[2023-02-23 09:45:28,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 5500928. Throughput: 0: 912.6. Samples: 1375490. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:45:28,226][00203] Avg episode reward: [(0, '23.057')]
[2023-02-23 09:45:33,223][00203] Fps is (10 sec: 3277.7, 60 sec: 3549.8, 300 sec: 3582.3). Total num frames: 5517312. Throughput: 0: 864.1. Samples: 1379610. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:45:33,231][00203] Avg episode reward: [(0, '25.185')]
[2023-02-23 09:45:36,419][10444] Updated weights for policy 0, policy_version 1350 (0.0019)
[2023-02-23 09:45:38,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5533696. Throughput: 0: 866.2. Samples: 1382048. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:45:38,225][00203] Avg episode reward: [(0, '25.370')]
[2023-02-23 09:45:43,223][00203] Fps is (10 sec: 3686.7, 60 sec: 3549.9, 300 sec: 3568.5). Total num frames: 5554176. Throughput: 0: 912.4. Samples: 1388410. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:45:43,226][00203] Avg episode reward: [(0, '25.537')]
[2023-02-23 09:45:46,824][10444] Updated weights for policy 0, policy_version 1360 (0.0015)
[2023-02-23 09:45:48,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 5574656. Throughput: 0: 895.1. Samples: 1393894. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:45:48,225][00203] Avg episode reward: [(0, '24.707')]
[2023-02-23 09:45:53,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5586944. Throughput: 0: 872.5. Samples: 1395990. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:45:53,230][00203] Avg episode reward: [(0, '24.258')]
[2023-02-23 09:45:58,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 5607424. Throughput: 0: 882.3. Samples: 1401132. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:45:58,228][00203] Avg episode reward: [(0, '24.575')]
[2023-02-23 09:45:59,131][10444] Updated weights for policy 0, policy_version 1370 (0.0014)
[2023-02-23 09:46:03,222][00203] Fps is (10 sec: 4096.1, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 5627904. Throughput: 0: 914.1. Samples: 1407390. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:46:03,227][00203] Avg episode reward: [(0, '23.123')]
[2023-02-23 09:46:08,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 5644288. Throughput: 0: 900.6. Samples: 1409912. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:46:08,229][00203] Avg episode reward: [(0, '23.193')]
[2023-02-23 09:46:11,141][10444] Updated weights for policy 0, policy_version 1380 (0.0013)
[2023-02-23 09:46:13,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 5656576. Throughput: 0: 859.7. Samples: 1414176. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:46:13,231][00203] Avg episode reward: [(0, '22.128')]
[2023-02-23 09:46:18,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 5677056. Throughput: 0: 898.4. Samples: 1420036. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:46:18,225][00203] Avg episode reward: [(0, '22.221')]
[2023-02-23 09:46:18,241][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001386_5677056.pth...
[2023-02-23 09:46:18,365][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001178_4825088.pth
[2023-02-23 09:46:21,546][10444] Updated weights for policy 0, policy_version 1390 (0.0013)
[2023-02-23 09:46:23,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3550.1, 300 sec: 3582.3). Total num frames: 5697536. Throughput: 0: 912.3. Samples: 1423100. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:46:23,225][00203] Avg episode reward: [(0, '22.185')]
[2023-02-23 09:46:28,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5713920. Throughput: 0: 882.0. Samples: 1428102. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:46:28,227][00203] Avg episode reward: [(0, '21.359')]
[2023-02-23 09:46:33,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 5730304. Throughput: 0: 861.4. Samples: 1432658. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:46:33,230][00203] Avg episode reward: [(0, '21.750')]
[2023-02-23 09:46:34,097][10444] Updated weights for policy 0, policy_version 1400 (0.0015)
[2023-02-23 09:46:38,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 5750784. Throughput: 0: 883.6. Samples: 1435754. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:46:38,226][00203] Avg episode reward: [(0, '21.035')]
[2023-02-23 09:46:43,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 5767168. Throughput: 0: 910.4. Samples: 1442102. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:46:43,232][00203] Avg episode reward: [(0, '20.899')]
[2023-02-23 09:46:44,954][10444] Updated weights for policy 0, policy_version 1410 (0.0013)
[2023-02-23 09:46:48,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3568.4). Total num frames: 5783552. Throughput: 0: 864.4. Samples: 1446288. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:46:48,231][00203] Avg episode reward: [(0, '20.977')]
[2023-02-23 09:46:53,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3540.6). Total num frames: 5799936. Throughput: 0: 854.5. Samples: 1448366. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:46:53,225][00203] Avg episode reward: [(0, '20.831')]
[2023-02-23 09:46:56,675][10444] Updated weights for policy 0, policy_version 1420 (0.0019)
[2023-02-23 09:46:58,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5820416. Throughput: 0: 901.8. Samples: 1454758. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:46:58,226][00203] Avg episode reward: [(0, '21.670')]
[2023-02-23 09:47:03,223][00203] Fps is (10 sec: 3686.2, 60 sec: 3481.6, 300 sec: 3568.4). Total num frames: 5836800. Throughput: 0: 895.6. Samples: 1460340. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:47:03,226][00203] Avg episode reward: [(0, '22.022')]
[2023-02-23 09:47:08,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3481.6, 300 sec: 3554.5). Total num frames: 5853184. Throughput: 0: 874.2. Samples: 1462440. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:47:08,226][00203] Avg episode reward: [(0, '21.673')]
[2023-02-23 09:47:09,112][10444] Updated weights for policy 0, policy_version 1430 (0.0013)
[2023-02-23 09:47:13,222][00203] Fps is (10 sec: 3686.6, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 5873664. Throughput: 0: 879.3. Samples: 1467672. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:47:13,225][00203] Avg episode reward: [(0, '21.589')]
[2023-02-23 09:47:18,223][00203] Fps is (10 sec: 4095.9, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 5894144. Throughput: 0: 919.6. Samples: 1474042. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:47:18,229][00203] Avg episode reward: [(0, '21.264')]
[2023-02-23 09:47:18,724][10444] Updated weights for policy 0, policy_version 1440 (0.0015)
[2023-02-23 09:47:23,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 5910528. Throughput: 0: 909.5. Samples: 1476682. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:47:23,229][00203] Avg episode reward: [(0, '20.625')]
[2023-02-23 09:47:28,225][00203] Fps is (10 sec: 2866.6, 60 sec: 3481.5, 300 sec: 3540.6). Total num frames: 5922816. Throughput: 0: 864.4. Samples: 1481002. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:47:28,227][00203] Avg episode reward: [(0, '21.015')]
[2023-02-23 09:47:31,311][10444] Updated weights for policy 0, policy_version 1450 (0.0016)
[2023-02-23 09:47:33,223][00203] Fps is (10 sec: 3686.3, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 5947392. Throughput: 0: 902.5. Samples: 1486900. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:47:33,225][00203] Avg episode reward: [(0, '21.277')]
[2023-02-23 09:47:38,223][00203] Fps is (10 sec: 4506.6, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 5967872. Throughput: 0: 928.1. Samples: 1490130. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:47:38,229][00203] Avg episode reward: [(0, '22.649')]
[2023-02-23 09:47:42,329][10444] Updated weights for policy 0, policy_version 1460 (0.0023)
[2023-02-23 09:47:43,223][00203] Fps is (10 sec: 3276.9, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 5980160. Throughput: 0: 896.1. Samples: 1495082. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:47:43,226][00203] Avg episode reward: [(0, '23.474')]
[2023-02-23 09:47:48,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 5996544. Throughput: 0: 871.7. Samples: 1499566. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:47:48,225][00203] Avg episode reward: [(0, '24.676')]
[2023-02-23 09:47:53,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 6017024. Throughput: 0: 895.4. Samples: 1502734. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:47:53,225][00203] Avg episode reward: [(0, '24.218')]
[2023-02-23 09:47:53,646][10444] Updated weights for policy 0, policy_version 1470 (0.0015)
[2023-02-23 09:47:58,226][00203] Fps is (10 sec: 4094.5, 60 sec: 3617.9, 300 sec: 3582.2). Total num frames: 6037504. Throughput: 0: 920.8. Samples: 1509110. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:47:58,229][00203] Avg episode reward: [(0, '24.650')]
[2023-02-23 09:48:03,224][00203] Fps is (10 sec: 3276.3, 60 sec: 3549.8, 300 sec: 3554.5). Total num frames: 6049792. Throughput: 0: 877.0. Samples: 1513510. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:48:03,228][00203] Avg episode reward: [(0, '23.835')]
[2023-02-23 09:48:06,172][10444] Updated weights for policy 0, policy_version 1480 (0.0022)
[2023-02-23 09:48:08,222][00203] Fps is (10 sec: 3278.0, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 6070272. Throughput: 0: 865.7. Samples: 1515638. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:48:08,231][00203] Avg episode reward: [(0, '24.743')]
[2023-02-23 09:48:13,222][00203] Fps is (10 sec: 4096.6, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 6090752. Throughput: 0: 909.6. Samples: 1521934. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:48:13,225][00203] Avg episode reward: [(0, '23.869')]
[2023-02-23 09:48:15,881][10444] Updated weights for policy 0, policy_version 1490 (0.0018)
[2023-02-23 09:48:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 6107136. Throughput: 0: 909.5. Samples: 1527826. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:48:18,225][00203] Avg episode reward: [(0, '23.477')]
[2023-02-23 09:48:18,244][00203] No heartbeat for components: RolloutWorker_w0 (1775 seconds), RolloutWorker_w6 (1775 seconds)
[2023-02-23 09:48:18,308][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001492_6111232.pth...
[2023-02-23 09:48:18,427][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001282_5251072.pth
[2023-02-23 09:48:23,226][00203] Fps is (10 sec: 3275.6, 60 sec: 3549.6, 300 sec: 3568.3). Total num frames: 6123520. Throughput: 0: 883.3. Samples: 1529882. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:48:23,234][00203] Avg episode reward: [(0, '23.838')]
[2023-02-23 09:48:28,225][00203] Fps is (10 sec: 3276.1, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 6139904. Throughput: 0: 885.2. Samples: 1534918. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:48:28,227][00203] Avg episode reward: [(0, '23.713')]
[2023-02-23 09:48:28,335][10444] Updated weights for policy 0, policy_version 1500 (0.0016)
[2023-02-23 09:48:33,222][00203] Fps is (10 sec: 4097.5, 60 sec: 3618.2, 300 sec: 3582.3). Total num frames: 6164480. Throughput: 0: 926.4. Samples: 1541252. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:48:33,224][00203] Avg episode reward: [(0, '21.661')]
[2023-02-23 09:48:38,227][00203] Fps is (10 sec: 4095.0, 60 sec: 3549.6, 300 sec: 3582.2). Total num frames: 6180864. Throughput: 0: 919.7. Samples: 1544124. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:48:38,234][00203] Avg episode reward: [(0, '21.165')]
[2023-02-23 09:48:39,482][10444] Updated weights for policy 0, policy_version 1510 (0.0011)
[2023-02-23 09:48:43,223][00203] Fps is (10 sec: 2867.1, 60 sec: 3549.9, 300 sec: 3554.5). Total num frames: 6193152. Throughput: 0: 873.2. Samples: 1548402. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:48:43,230][00203] Avg episode reward: [(0, '20.888')]
[2023-02-23 09:48:48,223][00203] Fps is (10 sec: 3278.3, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 6213632. Throughput: 0: 901.6. Samples: 1554082. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:48:48,231][00203] Avg episode reward: [(0, '20.139')]
[2023-02-23 09:48:50,574][10444] Updated weights for policy 0, policy_version 1520 (0.0013)
[2023-02-23 09:48:53,222][00203] Fps is (10 sec: 4096.1, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 6234112. Throughput: 0: 926.7. Samples: 1557340. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:48:53,229][00203] Avg episode reward: [(0, '20.142')]
[2023-02-23 09:48:58,223][00203] Fps is (10 sec: 3686.1, 60 sec: 3550.0, 300 sec: 3582.3). Total num frames: 6250496. Throughput: 0: 904.7. Samples: 1562646. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:48:58,226][00203] Avg episode reward: [(0, '21.864')]
[2023-02-23 09:49:02,839][10444] Updated weights for policy 0, policy_version 1530 (0.0027)
[2023-02-23 09:49:03,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.2, 300 sec: 3554.5). Total num frames: 6266880. Throughput: 0: 873.7. Samples: 1567144. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:49:03,226][00203] Avg episode reward: [(0, '22.141')]
[2023-02-23 09:49:08,223][00203] Fps is (10 sec: 3686.7, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 6287360. Throughput: 0: 899.8. Samples: 1570368. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:49:08,225][00203] Avg episode reward: [(0, '24.158')]
[2023-02-23 09:49:12,540][10444] Updated weights for policy 0, policy_version 1540 (0.0015)
[2023-02-23 09:49:13,230][00203] Fps is (10 sec: 4092.9, 60 sec: 3617.7, 300 sec: 3596.1). Total num frames: 6307840. Throughput: 0: 928.5. Samples: 1576706. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:49:13,236][00203] Avg episode reward: [(0, '24.152')]
[2023-02-23 09:49:18,224][00203] Fps is (10 sec: 3276.2, 60 sec: 3549.8, 300 sec: 3568.4). Total num frames: 6320128. Throughput: 0: 884.2. Samples: 1581044. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:49:18,229][00203] Avg episode reward: [(0, '24.899')]
[2023-02-23 09:49:23,223][00203] Fps is (10 sec: 2869.4, 60 sec: 3550.1, 300 sec: 3554.5). Total num frames: 6336512. Throughput: 0: 866.0. Samples: 1583092. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:49:23,224][00203] Avg episode reward: [(0, '23.779')]
[2023-02-23 09:49:25,410][10444] Updated weights for policy 0, policy_version 1550 (0.0012)
[2023-02-23 09:49:28,224][00203] Fps is (10 sec: 3686.5, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 6356992. Throughput: 0: 907.1. Samples: 1589222. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:49:28,227][00203] Avg episode reward: [(0, '23.027')]
[2023-02-23 09:49:33,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 6377472. Throughput: 0: 906.7. Samples: 1594884. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:49:33,225][00203] Avg episode reward: [(0, '22.670')]
[2023-02-23 09:49:37,030][10444] Updated weights for policy 0, policy_version 1560 (0.0012)
[2023-02-23 09:49:38,223][00203] Fps is (10 sec: 3277.0, 60 sec: 3481.8, 300 sec: 3554.5). Total num frames: 6389760. Throughput: 0: 882.0. Samples: 1597032. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:49:38,232][00203] Avg episode reward: [(0, '23.423')]
[2023-02-23 09:49:43,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3554.5). Total num frames: 6410240. Throughput: 0: 871.7. Samples: 1601872. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:49:43,225][00203] Avg episode reward: [(0, '23.394')]
[2023-02-23 09:49:47,768][10444] Updated weights for policy 0, policy_version 1570 (0.0027)
[2023-02-23 09:49:48,223][00203] Fps is (10 sec: 4096.3, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 6430720. Throughput: 0: 912.9. Samples: 1608226. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:49:48,228][00203] Avg episode reward: [(0, '22.685')]
[2023-02-23 09:49:53,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 6447104. Throughput: 0: 905.3. Samples: 1611108. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:49:53,225][00203] Avg episode reward: [(0, '22.424')]
[2023-02-23 09:49:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 6463488. Throughput: 0: 858.4. Samples: 1615326. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:49:58,229][00203] Avg episode reward: [(0, '22.412')]
[2023-02-23 09:50:00,357][10444] Updated weights for policy 0, policy_version 1580 (0.0026)
[2023-02-23 09:50:03,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 6483968. Throughput: 0: 887.9. Samples: 1620996. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:50:03,224][00203] Avg episode reward: [(0, '21.759')]
[2023-02-23 09:50:08,223][00203] Fps is (10 sec: 4096.1, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 6504448. Throughput: 0: 914.2. Samples: 1624230. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:50:08,224][00203] Avg episode reward: [(0, '20.535')]
[2023-02-23 09:50:10,189][10444] Updated weights for policy 0, policy_version 1590 (0.0012)
[2023-02-23 09:50:13,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3550.3, 300 sec: 3582.3). Total num frames: 6520832. Throughput: 0: 899.9. Samples: 1629718. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:50:13,225][00203] Avg episode reward: [(0, '20.171')]
[2023-02-23 09:50:18,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3550.0, 300 sec: 3554.5). Total num frames: 6533120. Throughput: 0: 873.2. Samples: 1634180. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:50:18,228][00203] Avg episode reward: [(0, '21.027')]
[2023-02-23 09:50:18,238][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001595_6533120.pth...
[2023-02-23 09:50:18,358][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001386_5677056.pth
[2023-02-23 09:50:22,249][10444] Updated weights for policy 0, policy_version 1600 (0.0019)
[2023-02-23 09:50:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 6553600. Throughput: 0: 892.6. Samples: 1637198. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:50:23,225][00203] Avg episode reward: [(0, '22.671')]
[2023-02-23 09:50:28,224][00203] Fps is (10 sec: 4504.8, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 6578176. Throughput: 0: 928.5. Samples: 1643654. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:50:28,227][00203] Avg episode reward: [(0, '22.202')]
[2023-02-23 09:50:33,228][00203] Fps is (10 sec: 3684.3, 60 sec: 3549.5, 300 sec: 3582.2). Total num frames: 6590464. Throughput: 0: 891.6. Samples: 1648354. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:50:33,231][00203] Avg episode reward: [(0, '22.604')]
[2023-02-23 09:50:33,974][10444] Updated weights for policy 0, policy_version 1610 (0.0021)
[2023-02-23 09:50:38,223][00203] Fps is (10 sec: 2867.7, 60 sec: 3618.2, 300 sec: 3568.4). Total num frames: 6606848. Throughput: 0: 874.4. Samples: 1650458. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:50:38,225][00203] Avg episode reward: [(0, '23.693')]
[2023-02-23 09:50:43,222][00203] Fps is (10 sec: 3688.5, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 6627328. Throughput: 0: 914.2. Samples: 1656466. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:50:43,230][00203] Avg episode reward: [(0, '24.752')]
[2023-02-23 09:50:44,518][10444] Updated weights for policy 0, policy_version 1620 (0.0018)
[2023-02-23 09:50:48,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 6647808. Throughput: 0: 923.4. Samples: 1662548. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:50:48,226][00203] Avg episode reward: [(0, '26.271')]
[2023-02-23 09:50:53,225][00203] Fps is (10 sec: 3276.0, 60 sec: 3549.7, 300 sec: 3568.3). Total num frames: 6660096. Throughput: 0: 898.3. Samples: 1664654. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:50:53,227][00203] Avg episode reward: [(0, '26.072')]
[2023-02-23 09:50:56,969][10444] Updated weights for policy 0, policy_version 1630 (0.0025)
[2023-02-23 09:50:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 6680576. Throughput: 0: 882.5. Samples: 1669430. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:50:58,225][00203] Avg episode reward: [(0, '27.261')]
[2023-02-23 09:50:58,241][10430] Saving new best policy, reward=27.261!
[2023-02-23 09:51:03,222][00203] Fps is (10 sec: 4097.1, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 6701056. Throughput: 0: 923.5. Samples: 1675736. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:51:03,224][00203] Avg episode reward: [(0, '26.371')]
[2023-02-23 09:51:07,184][10444] Updated weights for policy 0, policy_version 1640 (0.0012)
[2023-02-23 09:51:08,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 6717440. Throughput: 0: 924.0. Samples: 1678776. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:51:08,225][00203] Avg episode reward: [(0, '26.050')]
[2023-02-23 09:51:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 6733824. Throughput: 0: 876.5. Samples: 1683096. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:51:13,232][00203] Avg episode reward: [(0, '24.971')]
[2023-02-23 09:51:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3582.3). Total num frames: 6754304. Throughput: 0: 901.1. Samples: 1688898. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:51:18,225][00203] Avg episode reward: [(0, '23.085')]
[2023-02-23 09:51:18,930][10444] Updated weights for policy 0, policy_version 1650 (0.0015)
[2023-02-23 09:51:23,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 6774784. Throughput: 0: 925.4. Samples: 1692102. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:51:23,231][00203] Avg episode reward: [(0, '22.677')]
[2023-02-23 09:51:28,223][00203] Fps is (10 sec: 3686.3, 60 sec: 3550.0, 300 sec: 3596.1). Total num frames: 6791168. Throughput: 0: 912.9. Samples: 1697548. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:51:28,231][00203] Avg episode reward: [(0, '22.268')]
[2023-02-23 09:51:30,693][10444] Updated weights for policy 0, policy_version 1660 (0.0012)
[2023-02-23 09:51:33,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3550.2, 300 sec: 3568.4). Total num frames: 6803456. Throughput: 0: 873.7. Samples: 1701866. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:51:33,225][00203] Avg episode reward: [(0, '23.785')]
[2023-02-23 09:51:38,223][00203] Fps is (10 sec: 3686.5, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 6828032. Throughput: 0: 897.5. Samples: 1705040. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:51:38,233][00203] Avg episode reward: [(0, '23.625')]
[2023-02-23 09:51:40,727][10444] Updated weights for policy 0, policy_version 1670 (0.0019)
[2023-02-23 09:51:43,223][00203] Fps is (10 sec: 4505.4, 60 sec: 3686.4, 300 sec: 3610.0). Total num frames: 6848512. Throughput: 0: 937.7. Samples: 1711628. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:51:43,225][00203] Avg episode reward: [(0, '24.338')]
[2023-02-23 09:51:48,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 6860800. Throughput: 0: 900.0. Samples: 1716234. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:51:48,229][00203] Avg episode reward: [(0, '23.015')]
[2023-02-23 09:51:53,222][00203] Fps is (10 sec: 2867.4, 60 sec: 3618.3, 300 sec: 3582.3). Total num frames: 6877184. Throughput: 0: 879.6. Samples: 1718360. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:51:53,229][00203] Avg episode reward: [(0, '23.015')]
[2023-02-23 09:51:53,286][10444] Updated weights for policy 0, policy_version 1680 (0.0018)
[2023-02-23 09:51:58,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3610.0). Total num frames: 6901760. Throughput: 0: 919.6. Samples: 1724478. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:51:58,231][00203] Avg episode reward: [(0, '21.778')]
[2023-02-23 09:52:03,225][00203] Fps is (10 sec: 4094.9, 60 sec: 3618.0, 300 sec: 3610.0). Total num frames: 6918144. Throughput: 0: 925.8. Samples: 1730562. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:52:03,231][00203] Avg episode reward: [(0, '21.542')]
[2023-02-23 09:52:03,612][10444] Updated weights for policy 0, policy_version 1690 (0.0014)
[2023-02-23 09:52:08,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 6934528. Throughput: 0: 901.9. Samples: 1732686. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:52:08,224][00203] Avg episode reward: [(0, '20.415')]
[2023-02-23 09:52:13,222][00203] Fps is (10 sec: 3277.7, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 6950912. Throughput: 0: 887.8. Samples: 1737498. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:52:13,226][00203] Avg episode reward: [(0, '20.022')]
[2023-02-23 09:52:15,328][10444] Updated weights for policy 0, policy_version 1700 (0.0012)
[2023-02-23 09:52:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 6971392. Throughput: 0: 934.9. Samples: 1743936. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:52:18,225][00203] Avg episode reward: [(0, '19.781')]
[2023-02-23 09:52:18,281][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001703_6975488.pth...
[2023-02-23 09:52:18,398][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001492_6111232.pth
[2023-02-23 09:52:23,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 6991872. Throughput: 0: 928.1. Samples: 1746806. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:52:23,225][00203] Avg episode reward: [(0, '19.943')]
[2023-02-23 09:52:27,460][10444] Updated weights for policy 0, policy_version 1710 (0.0017)
[2023-02-23 09:52:28,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 7004160. Throughput: 0: 875.5. Samples: 1751024. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:52:28,225][00203] Avg episode reward: [(0, '20.609')]
[2023-02-23 09:52:33,225][00203] Fps is (10 sec: 3276.0, 60 sec: 3686.3, 300 sec: 3582.2). Total num frames: 7024640. Throughput: 0: 897.1. Samples: 1756606. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:52:33,228][00203] Avg episode reward: [(0, '20.859')]
[2023-02-23 09:52:37,567][10444] Updated weights for policy 0, policy_version 1720 (0.0016)
[2023-02-23 09:52:38,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3610.0). Total num frames: 7045120. Throughput: 0: 920.4. Samples: 1759778. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:52:38,226][00203] Avg episode reward: [(0, '21.512')]
[2023-02-23 09:52:43,226][00203] Fps is (10 sec: 3685.9, 60 sec: 3549.7, 300 sec: 3610.0). Total num frames: 7061504. Throughput: 0: 904.6. Samples: 1765190. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:52:43,229][00203] Avg episode reward: [(0, '22.269')]
[2023-02-23 09:52:48,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 7077888. Throughput: 0: 868.9. Samples: 1769658. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:52:48,234][00203] Avg episode reward: [(0, '23.135')]
[2023-02-23 09:52:50,081][10444] Updated weights for policy 0, policy_version 1730 (0.0012)
[2023-02-23 09:52:53,222][00203] Fps is (10 sec: 3687.7, 60 sec: 3686.4, 300 sec: 3596.2). Total num frames: 7098368. Throughput: 0: 889.5. Samples: 1772712. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:52:53,228][00203] Avg episode reward: [(0, '21.614')]
[2023-02-23 09:52:58,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 7118848. Throughput: 0: 924.9. Samples: 1779120. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:52:58,226][00203] Avg episode reward: [(0, '22.103')]
[2023-02-23 09:53:00,582][10444] Updated weights for policy 0, policy_version 1740 (0.0013)
[2023-02-23 09:53:03,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3596.2). Total num frames: 7131136. Throughput: 0: 885.2. Samples: 1783770. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:53:03,224][00203] Avg episode reward: [(0, '22.237')]
[2023-02-23 09:53:08,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 7147520. Throughput: 0: 871.2. Samples: 1786010. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:53:08,225][00203] Avg episode reward: [(0, '21.825')]
[2023-02-23 09:53:12,188][10444] Updated weights for policy 0, policy_version 1750 (0.0020)
[2023-02-23 09:53:13,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3610.0). Total num frames: 7172096. Throughput: 0: 912.6. Samples: 1792092. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:53:13,224][00203] Avg episode reward: [(0, '21.988')]
[2023-02-23 09:53:18,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3610.1). Total num frames: 7188480. Throughput: 0: 923.5. Samples: 1798162. Policy #0 lag: (min: 0.0, avg: 0.6, max: 1.0)
[2023-02-23 09:53:18,230][00203] Avg episode reward: [(0, '22.745')]
[2023-02-23 09:53:23,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3610.1). Total num frames: 7204864. Throughput: 0: 899.3. Samples: 1800246. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:53:23,225][00203] Avg episode reward: [(0, '22.625')]
[2023-02-23 09:53:24,569][10444] Updated weights for policy 0, policy_version 1760 (0.0013)
[2023-02-23 09:53:28,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 7221248. Throughput: 0: 879.4. Samples: 1804758. Policy #0 lag: (min: 0.0, avg: 0.3, max: 2.0)
[2023-02-23 09:53:28,224][00203] Avg episode reward: [(0, '23.379')]
[2023-02-23 09:53:33,224][00203] Fps is (10 sec: 3685.8, 60 sec: 3618.2, 300 sec: 3596.2). Total num frames: 7241728. Throughput: 0: 921.9. Samples: 1811146. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:53:33,229][00203] Avg episode reward: [(0, '23.308')]
[2023-02-23 09:53:34,438][10444] Updated weights for policy 0, policy_version 1770 (0.0012)
[2023-02-23 09:53:38,225][00203] Fps is (10 sec: 3685.5, 60 sec: 3549.7, 300 sec: 3610.0). Total num frames: 7258112. Throughput: 0: 922.5. Samples: 1814226. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:53:38,230][00203] Avg episode reward: [(0, '24.578')]
[2023-02-23 09:53:43,224][00203] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3596.1). Total num frames: 7274496. Throughput: 0: 872.8. Samples: 1818396. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:53:43,233][00203] Avg episode reward: [(0, '23.792')]
[2023-02-23 09:53:47,066][10444] Updated weights for policy 0, policy_version 1780 (0.0018)
[2023-02-23 09:53:48,222][00203] Fps is (10 sec: 3687.3, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 7294976. Throughput: 0: 893.2. Samples: 1823962. Policy #0 lag: (min: 0.0, avg: 0.4, max: 2.0)
[2023-02-23 09:53:48,230][00203] Avg episode reward: [(0, '22.847')]
[2023-02-23 09:53:53,222][00203] Fps is (10 sec: 4096.7, 60 sec: 3618.1, 300 sec: 3610.0). Total num frames: 7315456. Throughput: 0: 916.2. Samples: 1827240. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:53:53,225][00203] Avg episode reward: [(0, '22.507')]
[2023-02-23 09:53:57,728][10444] Updated weights for policy 0, policy_version 1790 (0.0015)
[2023-02-23 09:53:58,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 7331840. Throughput: 0: 904.0. Samples: 1832774. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:53:58,231][00203] Avg episode reward: [(0, '22.290')]
[2023-02-23 09:54:03,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 7344128. Throughput: 0: 865.9. Samples: 1837126. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:54:03,225][00203] Avg episode reward: [(0, '22.689')]
[2023-02-23 09:54:08,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3582.4). Total num frames: 7364608. Throughput: 0: 886.8. Samples: 1840154. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:54:08,225][00203] Avg episode reward: [(0, '22.795')]
[2023-02-23 09:54:09,036][10444] Updated weights for policy 0, policy_version 1800 (0.0014)
[2023-02-23 09:54:13,222][00203] Fps is (10 sec: 4505.6, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 7389184. Throughput: 0: 929.7. Samples: 1846596. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:54:13,225][00203] Avg episode reward: [(0, '23.559')]
[2023-02-23 09:54:18,223][00203] Fps is (10 sec: 3686.3, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 7401472. Throughput: 0: 891.7. Samples: 1851270. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:54:18,228][00203] Avg episode reward: [(0, '23.605')]
[2023-02-23 09:54:18,240][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001807_7401472.pth...
[2023-02-23 09:54:18,387][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001595_6533120.pth
[2023-02-23 09:54:21,539][10444] Updated weights for policy 0, policy_version 1810 (0.0014)
[2023-02-23 09:54:23,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3596.2). Total num frames: 7417856. Throughput: 0: 869.4. Samples: 1853346. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:54:23,224][00203] Avg episode reward: [(0, '23.066')]
[2023-02-23 09:54:28,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 7438336. Throughput: 0: 910.7. Samples: 1859374. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:54:28,225][00203] Avg episode reward: [(0, '21.924')]
[2023-02-23 09:54:31,263][10444] Updated weights for policy 0, policy_version 1820 (0.0011)
[2023-02-23 09:54:33,223][00203] Fps is (10 sec: 4095.9, 60 sec: 3618.2, 300 sec: 3623.9). Total num frames: 7458816. Throughput: 0: 922.4. Samples: 1865472. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:54:33,225][00203] Avg episode reward: [(0, '20.872')]
[2023-02-23 09:54:38,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.3, 300 sec: 3610.0). Total num frames: 7475200. Throughput: 0: 895.8. Samples: 1867552. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:54:38,226][00203] Avg episode reward: [(0, '21.884')]
[2023-02-23 09:54:43,222][00203] Fps is (10 sec: 3276.9, 60 sec: 3618.2, 300 sec: 3596.2). Total num frames: 7491584. Throughput: 0: 880.5. Samples: 1872396. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:54:43,230][00203] Avg episode reward: [(0, '22.350')]
[2023-02-23 09:54:43,577][10444] Updated weights for policy 0, policy_version 1830 (0.0014)
[2023-02-23 09:54:48,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3610.0). Total num frames: 7512064. Throughput: 0: 927.2. Samples: 1878848. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:54:48,224][00203] Avg episode reward: [(0, '23.014')]
[2023-02-23 09:54:53,223][00203] Fps is (10 sec: 4095.9, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 7532544. Throughput: 0: 929.0. Samples: 1881960. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:54:53,231][00203] Avg episode reward: [(0, '23.549')]
[2023-02-23 09:54:54,433][10444] Updated weights for policy 0, policy_version 1840 (0.0013)
[2023-02-23 09:54:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 7544832. Throughput: 0: 879.1. Samples: 1886154. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:54:58,232][00203] Avg episode reward: [(0, '23.526')]
[2023-02-23 09:55:03,222][00203] Fps is (10 sec: 3276.9, 60 sec: 3686.4, 300 sec: 3596.2). Total num frames: 7565312. Throughput: 0: 896.3. Samples: 1891602. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:55:03,233][00203] Avg episode reward: [(0, '25.202')]
[2023-02-23 09:55:05,909][10444] Updated weights for policy 0, policy_version 1850 (0.0028)
[2023-02-23 09:55:08,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3610.0). Total num frames: 7585792. Throughput: 0: 919.5. Samples: 1894722. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:55:08,225][00203] Avg episode reward: [(0, '25.074')]
[2023-02-23 09:55:13,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3623.9). Total num frames: 7602176. Throughput: 0: 912.4. Samples: 1900434. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:55:13,230][00203] Avg episode reward: [(0, '24.318')]
[2023-02-23 09:55:18,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 7614464. Throughput: 0: 872.2. Samples: 1904722. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:55:18,228][00203] Avg episode reward: [(0, '24.742')]
[2023-02-23 09:55:18,239][10444] Updated weights for policy 0, policy_version 1860 (0.0017)
[2023-02-23 09:55:23,224][00203] Fps is (10 sec: 3276.3, 60 sec: 3618.0, 300 sec: 3582.3). Total num frames: 7634944. Throughput: 0: 890.7. Samples: 1907634. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:55:23,227][00203] Avg episode reward: [(0, '23.634')]
[2023-02-23 09:55:28,054][10444] Updated weights for policy 0, policy_version 1870 (0.0013)
[2023-02-23 09:55:28,223][00203] Fps is (10 sec: 4505.5, 60 sec: 3686.4, 300 sec: 3624.0). Total num frames: 7659520. Throughput: 0: 924.1. Samples: 1913980. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:55:28,225][00203] Avg episode reward: [(0, '23.877')]
[2023-02-23 09:55:33,224][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.8, 300 sec: 3610.0). Total num frames: 7671808. Throughput: 0: 888.9. Samples: 1918848. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:55:33,232][00203] Avg episode reward: [(0, '23.945')]
[2023-02-23 09:55:38,223][00203] Fps is (10 sec: 2867.3, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 7688192. Throughput: 0: 868.8. Samples: 1921058. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:55:38,225][00203] Avg episode reward: [(0, '24.224')]
[2023-02-23 09:55:40,573][10444] Updated weights for policy 0, policy_version 1880 (0.0021)
[2023-02-23 09:55:43,223][00203] Fps is (10 sec: 3686.9, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 7708672. Throughput: 0: 904.6. Samples: 1926862. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:55:43,225][00203] Avg episode reward: [(0, '24.516')]
[2023-02-23 09:55:48,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3624.0). Total num frames: 7729152. Throughput: 0: 925.4. Samples: 1933244. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:55:48,225][00203] Avg episode reward: [(0, '22.968')]
[2023-02-23 09:55:51,353][10444] Updated weights for policy 0, policy_version 1890 (0.0015)
[2023-02-23 09:55:53,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 7745536. Throughput: 0: 902.1. Samples: 1935318. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:55:53,238][00203] Avg episode reward: [(0, '23.636')]
[2023-02-23 09:55:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 7761920. Throughput: 0: 876.9. Samples: 1939894. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:55:58,225][00203] Avg episode reward: [(0, '23.670')]
[2023-02-23 09:56:02,769][10444] Updated weights for policy 0, policy_version 1900 (0.0019)
[2023-02-23 09:56:03,224][00203] Fps is (10 sec: 3685.7, 60 sec: 3618.0, 300 sec: 3610.0). Total num frames: 7782400. Throughput: 0: 920.9. Samples: 1946164. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:03,227][00203] Avg episode reward: [(0, '23.290')]
[2023-02-23 09:56:08,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3623.9). Total num frames: 7802880. Throughput: 0: 927.1. Samples: 1949352. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:56:08,231][00203] Avg episode reward: [(0, '23.741')]
[2023-02-23 09:56:13,222][00203] Fps is (10 sec: 3277.4, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 7815168. Throughput: 0: 882.4. Samples: 1953686. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:13,228][00203] Avg episode reward: [(0, '23.060')]
[2023-02-23 09:56:15,337][10444] Updated weights for policy 0, policy_version 1910 (0.0022)
[2023-02-23 09:56:18,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 7831552. Throughput: 0: 891.8. Samples: 1958980. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:18,225][00203] Avg episode reward: [(0, '24.035')]
[2023-02-23 09:56:18,247][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001913_7835648.pth...
[2023-02-23 09:56:18,364][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001703_6975488.pth
[2023-02-23 09:56:23,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.2, 300 sec: 3596.2). Total num frames: 7852032. Throughput: 0: 909.2. Samples: 1961970. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:23,234][00203] Avg episode reward: [(0, '24.815')]
[2023-02-23 09:56:25,284][10444] Updated weights for policy 0, policy_version 1920 (0.0019)
[2023-02-23 09:56:28,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3481.6, 300 sec: 3610.0). Total num frames: 7868416. Throughput: 0: 903.7. Samples: 1967530. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:56:28,230][00203] Avg episode reward: [(0, '24.858')]
[2023-02-23 09:56:33,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3550.0, 300 sec: 3582.3). Total num frames: 7884800. Throughput: 0: 856.7. Samples: 1971794. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:33,228][00203] Avg episode reward: [(0, '25.248')]
[2023-02-23 09:56:37,784][10444] Updated weights for policy 0, policy_version 1930 (0.0021)
[2023-02-23 09:56:38,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 7905280. Throughput: 0: 874.8. Samples: 1974682. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:38,228][00203] Avg episode reward: [(0, '25.591')]
[2023-02-23 09:56:43,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3610.0). Total num frames: 7925760. Throughput: 0: 914.0. Samples: 1981024. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:43,227][00203] Avg episode reward: [(0, '25.729')]
[2023-02-23 09:56:48,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 7942144. Throughput: 0: 881.5. Samples: 1985832. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:56:48,226][00203] Avg episode reward: [(0, '24.697')]
[2023-02-23 09:56:49,364][10444] Updated weights for policy 0, policy_version 1940 (0.0015)
[2023-02-23 09:56:53,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3568.4). Total num frames: 7954432. Throughput: 0: 858.0. Samples: 1987964. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:56:53,226][00203] Avg episode reward: [(0, '24.852')]
[2023-02-23 09:56:58,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3596.2). Total num frames: 7979008. Throughput: 0: 892.8. Samples: 1993864. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:56:58,224][00203] Avg episode reward: [(0, '24.772')]
[2023-02-23 09:57:00,129][10444] Updated weights for policy 0, policy_version 1950 (0.0019)
[2023-02-23 09:57:03,228][00203] Fps is (10 sec: 4093.7, 60 sec: 3549.6, 300 sec: 3596.1). Total num frames: 7995392. Throughput: 0: 913.8. Samples: 2000104. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:03,236][00203] Avg episode reward: [(0, '24.679')]
[2023-02-23 09:57:08,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3481.6, 300 sec: 3596.1). Total num frames: 8011776. Throughput: 0: 894.7. Samples: 2002234. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:08,228][00203] Avg episode reward: [(0, '24.134')]
[2023-02-23 09:57:12,550][10444] Updated weights for policy 0, policy_version 1960 (0.0014)
[2023-02-23 09:57:13,222][00203] Fps is (10 sec: 3278.6, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8028160. Throughput: 0: 870.9. Samples: 2006722. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:13,228][00203] Avg episode reward: [(0, '24.298')]
[2023-02-23 09:57:18,222][00203] Fps is (10 sec: 4096.2, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 8052736. Throughput: 0: 919.8. Samples: 2013186. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:18,229][00203] Avg episode reward: [(0, '23.874')]
[2023-02-23 09:57:22,598][10444] Updated weights for policy 0, policy_version 1970 (0.0012)
[2023-02-23 09:57:23,234][00203] Fps is (10 sec: 4091.4, 60 sec: 3617.5, 300 sec: 3609.9). Total num frames: 8069120. Throughput: 0: 926.0. Samples: 2016364. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:57:23,240][00203] Avg episode reward: [(0, '22.453')]
[2023-02-23 09:57:28,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8081408. Throughput: 0: 880.2. Samples: 2020632. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:57:28,231][00203] Avg episode reward: [(0, '22.178')]
[2023-02-23 09:57:33,222][00203] Fps is (10 sec: 3280.5, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 8101888. Throughput: 0: 891.7. Samples: 2025960. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:57:33,228][00203] Avg episode reward: [(0, '22.363')]
[2023-02-23 09:57:34,679][10444] Updated weights for policy 0, policy_version 1980 (0.0013)
[2023-02-23 09:57:38,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3596.2). Total num frames: 8122368. Throughput: 0: 915.0. Samples: 2029138. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:38,225][00203] Avg episode reward: [(0, '24.303')]
[2023-02-23 09:57:43,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 8138752. Throughput: 0: 908.9. Samples: 2034764. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:43,231][00203] Avg episode reward: [(0, '25.197')]
[2023-02-23 09:57:46,907][10444] Updated weights for policy 0, policy_version 1990 (0.0020)
[2023-02-23 09:57:48,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8155136. Throughput: 0: 864.3. Samples: 2038994. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:48,226][00203] Avg episode reward: [(0, '24.427')]
[2023-02-23 09:57:53,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3686.4, 300 sec: 3582.3). Total num frames: 8175616. Throughput: 0: 882.1. Samples: 2041930. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:53,225][00203] Avg episode reward: [(0, '25.792')]
[2023-02-23 09:57:56,947][10444] Updated weights for policy 0, policy_version 2000 (0.0012)
[2023-02-23 09:57:58,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3610.0). Total num frames: 8196096. Throughput: 0: 924.5. Samples: 2048326. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:57:58,225][00203] Avg episode reward: [(0, '27.031')]
[2023-02-23 09:58:03,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3550.2, 300 sec: 3596.1). Total num frames: 8208384. Throughput: 0: 887.7. Samples: 2053134. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:58:03,225][00203] Avg episode reward: [(0, '27.062')]
[2023-02-23 09:58:08,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 8224768. Throughput: 0: 863.4. Samples: 2055208. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:58:08,225][00203] Avg episode reward: [(0, '26.714')]
[2023-02-23 09:58:09,577][10444] Updated weights for policy 0, policy_version 2010 (0.0016)
[2023-02-23 09:58:13,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 8245248. Throughput: 0: 896.1. Samples: 2060956. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:58:13,225][00203] Avg episode reward: [(0, '23.890')]
[2023-02-23 09:58:18,223][00203] Fps is (10 sec: 4095.9, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 8265728. Throughput: 0: 922.2. Samples: 2067458. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:58:18,233][00203] Avg episode reward: [(0, '24.375')]
[2023-02-23 09:58:18,243][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002018_8265728.pth...
[2023-02-23 09:58:18,241][00203] No heartbeat for components: RolloutWorker_w0 (2375 seconds), RolloutWorker_w6 (2375 seconds)
[2023-02-23 09:58:18,437][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001807_7401472.pth
[2023-02-23 09:58:20,157][10444] Updated weights for policy 0, policy_version 2020 (0.0013)
[2023-02-23 09:58:23,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3550.5, 300 sec: 3596.2). Total num frames: 8282112. Throughput: 0: 894.5. Samples: 2069390. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:58:23,228][00203] Avg episode reward: [(0, '23.937')]
[2023-02-23 09:58:28,223][00203] Fps is (10 sec: 3276.9, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 8298496. Throughput: 0: 867.6. Samples: 2073806. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:58:28,225][00203] Avg episode reward: [(0, '24.225')]
[2023-02-23 09:58:31,912][10444] Updated weights for policy 0, policy_version 2030 (0.0014)
[2023-02-23 09:58:33,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3596.2). Total num frames: 8318976. Throughput: 0: 915.3. Samples: 2080182. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:58:33,233][00203] Avg episode reward: [(0, '24.284')]
[2023-02-23 09:58:38,225][00203] Fps is (10 sec: 4095.2, 60 sec: 3618.0, 300 sec: 3610.0). Total num frames: 8339456. Throughput: 0: 922.2. Samples: 2083430. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:58:38,227][00203] Avg episode reward: [(0, '23.343')]
[2023-02-23 09:58:43,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8351744. Throughput: 0: 878.1. Samples: 2087840. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:58:43,228][00203] Avg episode reward: [(0, '24.742')]
[2023-02-23 09:58:43,938][10444] Updated weights for policy 0, policy_version 2040 (0.0036)
[2023-02-23 09:58:48,224][00203] Fps is (10 sec: 3276.9, 60 sec: 3618.0, 300 sec: 3582.2). Total num frames: 8372224. Throughput: 0: 889.2. Samples: 2093148. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 09:58:48,227][00203] Avg episode reward: [(0, '24.703')]
[2023-02-23 09:58:53,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 8392704. Throughput: 0: 913.8. Samples: 2096330. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:58:53,226][00203] Avg episode reward: [(0, '24.458')]
[2023-02-23 09:58:53,864][10444] Updated weights for policy 0, policy_version 2050 (0.0013)
[2023-02-23 09:58:58,222][00203] Fps is (10 sec: 3687.0, 60 sec: 3549.9, 300 sec: 3610.0). Total num frames: 8409088. Throughput: 0: 916.2. Samples: 2102184. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:58:58,230][00203] Avg episode reward: [(0, '24.164')]
[2023-02-23 09:59:03,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8421376. Throughput: 0: 866.8. Samples: 2106464. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:59:03,224][00203] Avg episode reward: [(0, '24.466')]
[2023-02-23 09:59:06,609][10444] Updated weights for policy 0, policy_version 2060 (0.0019)
[2023-02-23 09:59:08,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 8441856. Throughput: 0: 884.3. Samples: 2109182. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:59:08,225][00203] Avg episode reward: [(0, '24.283')]
[2023-02-23 09:59:13,223][00203] Fps is (10 sec: 4505.6, 60 sec: 3686.4, 300 sec: 3610.0). Total num frames: 8466432. Throughput: 0: 928.1. Samples: 2115570. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:59:13,230][00203] Avg episode reward: [(0, '23.624')]
[2023-02-23 09:59:16,888][10444] Updated weights for policy 0, policy_version 2070 (0.0013)
[2023-02-23 09:59:18,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 8478720. Throughput: 0: 900.8. Samples: 2120716. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:59:18,225][00203] Avg episode reward: [(0, '23.265')]
[2023-02-23 09:59:23,222][00203] Fps is (10 sec: 2867.2, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8495104. Throughput: 0: 875.0. Samples: 2122802. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 09:59:23,228][00203] Avg episode reward: [(0, '23.541')]
[2023-02-23 09:59:28,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 8515584. Throughput: 0: 904.6. Samples: 2128546. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:59:28,230][00203] Avg episode reward: [(0, '23.786')]
[2023-02-23 09:59:28,637][10444] Updated weights for policy 0, policy_version 2080 (0.0013)
[2023-02-23 09:59:33,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 8536064. Throughput: 0: 928.4. Samples: 2134924. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:59:33,229][00203] Avg episode reward: [(0, '23.019')]
[2023-02-23 09:59:38,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3550.0, 300 sec: 3596.1). Total num frames: 8552448. Throughput: 0: 905.2. Samples: 2137062. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:59:38,228][00203] Avg episode reward: [(0, '23.021')]
[2023-02-23 09:59:40,911][10444] Updated weights for policy 0, policy_version 2090 (0.0021)
[2023-02-23 09:59:43,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 8568832. Throughput: 0: 870.6. Samples: 2141362. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:59:43,230][00203] Avg episode reward: [(0, '24.376')]
[2023-02-23 09:59:48,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.2, 300 sec: 3582.3). Total num frames: 8589312. Throughput: 0: 917.1. Samples: 2147732. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 09:59:48,225][00203] Avg episode reward: [(0, '24.729')]
[2023-02-23 09:59:50,778][10444] Updated weights for policy 0, policy_version 2100 (0.0013)
[2023-02-23 09:59:53,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 8605696. Throughput: 0: 927.2. Samples: 2150904. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:59:53,234][00203] Avg episode reward: [(0, '25.160')]
[2023-02-23 09:59:58,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8622080. Throughput: 0: 884.0. Samples: 2155352. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 09:59:58,225][00203] Avg episode reward: [(0, '24.963')]
[2023-02-23 10:00:03,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 8638464. Throughput: 0: 880.5. Samples: 2160338. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:00:03,224][00203] Avg episode reward: [(0, '27.818')]
[2023-02-23 10:00:03,235][10430] Saving new best policy, reward=27.818!
[2023-02-23 10:00:03,580][10444] Updated weights for policy 0, policy_version 2110 (0.0012)
[2023-02-23 10:00:08,223][00203] Fps is (10 sec: 3686.4, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 8658944. Throughput: 0: 903.3. Samples: 2163452. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 10:00:08,228][00203] Avg episode reward: [(0, '26.465')]
[2023-02-23 10:00:13,229][00203] Fps is (10 sec: 4093.2, 60 sec: 3549.5, 300 sec: 3610.0). Total num frames: 8679424. Throughput: 0: 906.6. Samples: 2169350. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 10:00:13,238][00203] Avg episode reward: [(0, '26.013')]
[2023-02-23 10:00:14,786][10444] Updated weights for policy 0, policy_version 2120 (0.0013)
[2023-02-23 10:00:18,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8691712. Throughput: 0: 858.5. Samples: 2173556. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 10:00:18,231][00203] Avg episode reward: [(0, '26.193')]
[2023-02-23 10:00:18,246][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002122_8691712.pth...
[2023-02-23 10:00:18,390][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000001913_7835648.pth
[2023-02-23 10:00:23,222][00203] Fps is (10 sec: 3279.0, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 8712192. Throughput: 0: 870.8. Samples: 2176246. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:00:23,225][00203] Avg episode reward: [(0, '24.843')]
[2023-02-23 10:00:25,858][10444] Updated weights for policy 0, policy_version 2130 (0.0014)
[2023-02-23 10:00:28,223][00203] Fps is (10 sec: 4096.0, 60 sec: 3618.1, 300 sec: 3596.2). Total num frames: 8732672. Throughput: 0: 913.7. Samples: 2182478. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 10:00:28,225][00203] Avg episode reward: [(0, '22.765')]
[2023-02-23 10:00:33,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3596.2). Total num frames: 8749056. Throughput: 0: 883.2. Samples: 2187476. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:00:33,232][00203] Avg episode reward: [(0, '23.444')]
[2023-02-23 10:00:38,223][00203] Fps is (10 sec: 2867.2, 60 sec: 3481.6, 300 sec: 3568.4). Total num frames: 8761344. Throughput: 0: 859.0. Samples: 2189560. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:00:38,225][00203] Avg episode reward: [(0, '23.674')]
[2023-02-23 10:00:38,456][10444] Updated weights for policy 0, policy_version 2140 (0.0022)
[2023-02-23 10:00:43,223][00203] Fps is (10 sec: 3276.7, 60 sec: 3549.9, 300 sec: 3568.4). Total num frames: 8781824. Throughput: 0: 887.9. Samples: 2195306. Policy #0 lag: (min: 0.0, avg: 0.2, max: 1.0)
[2023-02-23 10:00:43,226][00203] Avg episode reward: [(0, '23.774')]
[2023-02-23 10:00:47,936][10444] Updated weights for policy 0, policy_version 2150 (0.0018)
[2023-02-23 10:00:48,223][00203] Fps is (10 sec: 4505.6, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 8806400. Throughput: 0: 925.0. Samples: 2201964. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 10:00:48,229][00203] Avg episode reward: [(0, '22.764')]
[2023-02-23 10:00:53,227][00203] Fps is (10 sec: 3684.8, 60 sec: 3549.6, 300 sec: 3582.2). Total num frames: 8818688. Throughput: 0: 901.6. Samples: 2204030. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:00:53,234][00203] Avg episode reward: [(0, '23.419')]
[2023-02-23 10:00:58,225][00203] Fps is (10 sec: 2866.6, 60 sec: 3549.7, 300 sec: 3568.4). Total num frames: 8835072. Throughput: 0: 868.0. Samples: 2208404. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 10:00:58,234][00203] Avg episode reward: [(0, '25.110')]
[2023-02-23 10:01:00,489][10444] Updated weights for policy 0, policy_version 2160 (0.0014)
[2023-02-23 10:01:03,222][00203] Fps is (10 sec: 3688.1, 60 sec: 3618.1, 300 sec: 3568.4). Total num frames: 8855552. Throughput: 0: 915.4. Samples: 2214750. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:01:03,225][00203] Avg episode reward: [(0, '24.067')]
[2023-02-23 10:01:08,223][00203] Fps is (10 sec: 4096.9, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 8876032. Throughput: 0: 926.0. Samples: 2217914. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:01:08,227][00203] Avg episode reward: [(0, '24.118')]
[2023-02-23 10:01:11,824][10444] Updated weights for policy 0, policy_version 2170 (0.0012)
[2023-02-23 10:01:13,222][00203] Fps is (10 sec: 3276.8, 60 sec: 3482.0, 300 sec: 3582.3). Total num frames: 8888320. Throughput: 0: 889.1. Samples: 2222486. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:01:13,229][00203] Avg episode reward: [(0, '24.256')]
[2023-02-23 10:01:18,223][00203] Fps is (10 sec: 3276.8, 60 sec: 3618.1, 300 sec: 3582.3). Total num frames: 8908800. Throughput: 0: 893.3. Samples: 2227676. Policy #0 lag: (min: 0.0, avg: 0.4, max: 1.0)
[2023-02-23 10:01:18,233][00203] Avg episode reward: [(0, '24.030')]
[2023-02-23 10:01:22,581][10444] Updated weights for policy 0, policy_version 2180 (0.0017)
[2023-02-23 10:01:23,223][00203] Fps is (10 sec: 4095.7, 60 sec: 3618.1, 300 sec: 3596.1). Total num frames: 8929280. Throughput: 0: 916.5. Samples: 2230802. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 10:01:23,226][00203] Avg episode reward: [(0, '25.541')]
[2023-02-23 10:01:28,222][00203] Fps is (10 sec: 3686.4, 60 sec: 3549.9, 300 sec: 3596.1). Total num frames: 8945664. Throughput: 0: 919.0. Samples: 2236660. Policy #0 lag: (min: 0.0, avg: 0.5, max: 1.0)
[2023-02-23 10:01:28,228][00203] Avg episode reward: [(0, '26.080')]
[2023-02-23 10:01:33,223][00203] Fps is (10 sec: 3277.0, 60 sec: 3549.9, 300 sec: 3582.3). Total num frames: 8962048. Throughput: 0: 863.0. Samples: 2240798. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 10:01:33,231][00203] Avg episode reward: [(0, '26.300')]
[2023-02-23 10:01:35,435][10444] Updated weights for policy 0, policy_version 2190 (0.0027)
[2023-02-23 10:01:38,224][00203] Fps is (10 sec: 3685.9, 60 sec: 3686.3, 300 sec: 3582.2). Total num frames: 8982528. Throughput: 0: 878.5. Samples: 2243560. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 10:01:38,227][00203] Avg episode reward: [(0, '26.504')]
[2023-02-23 10:01:43,222][00203] Fps is (10 sec: 4096.0, 60 sec: 3686.4, 300 sec: 3596.1). Total num frames: 9003008. Throughput: 0: 925.2. Samples: 2250038. Policy #0 lag: (min: 0.0, avg: 0.3, max: 1.0)
[2023-02-23 10:01:43,225][00203] Avg episode reward: [(0, '27.076')]
[2023-02-23 10:01:44,020][10430] Stopping Batcher_0...
[2023-02-23 10:01:44,021][10430] Loop batcher_evt_loop terminating...
[2023-02-23 10:01:44,022][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002199_9007104.pth...
[2023-02-23 10:01:44,022][00203] Component Batcher_0 stopped!
[2023-02-23 10:01:44,030][00203] Component RolloutWorker_w0 process died already! Don't wait for it.
[2023-02-23 10:01:44,033][00203] Component RolloutWorker_w6 process died already! Don't wait for it.
[2023-02-23 10:01:44,111][10455] Stopping RolloutWorker_w7...
[2023-02-23 10:01:44,112][00203] Component RolloutWorker_w7 stopped!
[2023-02-23 10:01:44,121][10444] Weights refcount: 2 0
[2023-02-23 10:01:44,136][10448] Stopping RolloutWorker_w3...
[2023-02-23 10:01:44,137][10448] Loop rollout_proc3_evt_loop terminating...
[2023-02-23 10:01:44,118][10455] Loop rollout_proc7_evt_loop terminating...
[2023-02-23 10:01:44,142][10446] Stopping RolloutWorker_w1...
[2023-02-23 10:01:44,138][10450] Stopping RolloutWorker_w4...
[2023-02-23 10:01:44,139][00203] Component RolloutWorker_w3 stopped!
[2023-02-23 10:01:44,147][00203] Component RolloutWorker_w4 stopped!
[2023-02-23 10:01:44,146][10446] Loop rollout_proc1_evt_loop terminating...
[2023-02-23 10:01:44,149][00203] Component RolloutWorker_w1 stopped!
[2023-02-23 10:01:44,156][10444] Stopping InferenceWorker_p0-w0...
[2023-02-23 10:01:44,157][10444] Loop inference_proc0-0_evt_loop terminating...
[2023-02-23 10:01:44,159][10449] Stopping RolloutWorker_w5...
[2023-02-23 10:01:44,157][00203] Component InferenceWorker_p0-w0 stopped!
[2023-02-23 10:01:44,161][00203] Component RolloutWorker_w5 stopped!
[2023-02-23 10:01:44,174][10450] Loop rollout_proc4_evt_loop terminating...
[2023-02-23 10:01:44,174][10449] Loop rollout_proc5_evt_loop terminating...
[2023-02-23 10:01:44,201][00203] Component RolloutWorker_w2 stopped!
[2023-02-23 10:01:44,206][10447] Stopping RolloutWorker_w2...
[2023-02-23 10:01:44,206][10447] Loop rollout_proc2_evt_loop terminating...
[2023-02-23 10:01:44,218][10430] Removing /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002018_8265728.pth
[2023-02-23 10:01:44,246][10430] Saving /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002199_9007104.pth...
[2023-02-23 10:01:44,511][00203] Component LearnerWorker_p0 stopped!
[2023-02-23 10:01:44,516][00203] Waiting for process learner_proc0 to stop...
[2023-02-23 10:01:44,520][10430] Stopping LearnerWorker_p0...
[2023-02-23 10:01:44,521][10430] Loop learner_proc0_evt_loop terminating...
[2023-02-23 10:01:46,925][00203] Waiting for process inference_proc0-0 to join...
[2023-02-23 10:01:47,504][00203] Waiting for process rollout_proc0 to join...
[2023-02-23 10:01:47,506][00203] Waiting for process rollout_proc1 to join...
[2023-02-23 10:01:47,795][00203] Waiting for process rollout_proc2 to join...
[2023-02-23 10:01:47,904][00203] Waiting for process rollout_proc3 to join...
[2023-02-23 10:01:47,906][00203] Waiting for process rollout_proc4 to join...
[2023-02-23 10:01:47,908][00203] Waiting for process rollout_proc5 to join...
[2023-02-23 10:01:47,909][00203] Waiting for process rollout_proc6 to join...
[2023-02-23 10:01:47,910][00203] Waiting for process rollout_proc7 to join...
[2023-02-23 10:01:47,911][00203] Batcher 0 profile tree view:
batching: 52.0515, releasing_batches: 0.0595
[2023-02-23 10:01:47,915][00203] InferenceWorker_p0-w0 profile tree view:
wait_policy: 0.0000
  wait_policy_total: 1165.1578
update_model: 19.7624
  weight_update: 0.0012
one_step: 0.0064
  handle_policy_step: 1287.6124
    deserialize: 36.1741, stack: 8.0072, obs_to_device_normalize: 294.4160, forward: 629.8489, send_messages: 54.5756
    prepare_outputs: 197.9137
      to_cpu: 122.1418
[2023-02-23 10:01:47,917][00203] Learner 0 profile tree view:
misc: 0.0126, prepare_batch: 31.3233
train: 163.8806
  epoch_init: 0.0191, minibatch_init: 0.0499, losses_postprocess: 1.2823, kl_divergence: 1.3219, after_optimizer: 72.9405
  calculate_losses: 57.2429
    losses_init: 0.0171, forward_head: 3.6380, bptt_initial: 38.6092, tail: 2.2226, advantages_returns: 0.5567, losses: 6.7906
    bptt: 4.8070
      bptt_forward_core: 4.6214
  update: 29.7224
    clip: 3.2129
[2023-02-23 10:01:47,918][00203] RolloutWorker_w7 profile tree view:
wait_for_trajectories: 0.8155, enqueue_policy_requests: 285.5522, env_step: 2015.9739, overhead: 55.9826, complete_rollouts: 19.1098
save_policy_outputs: 53.2379
  split_output_tensors: 25.8067
[2023-02-23 10:01:47,919][00203] Loop Runner_EvtLoop terminating...
[2023-02-23 10:01:47,923][00203] Runner profile tree view:
main_loop: 2604.7133
[2023-02-23 10:01:47,924][00203] Collected {0: 9007104}, FPS: 3458.0
[2023-02-23 10:01:48,085][00203] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2023-02-23 10:01:48,089][00203] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-23 10:01:48,092][00203] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-23 10:01:48,097][00203] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-23 10:01:48,100][00203] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-23 10:01:48,101][00203] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-23 10:01:48,102][00203] Adding new argument 'max_num_frames'=1000000000.0 that is not in the saved config file!
[2023-02-23 10:01:48,106][00203] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-23 10:01:48,108][00203] Adding new argument 'push_to_hub'=False that is not in the saved config file!
[2023-02-23 10:01:48,110][00203] Adding new argument 'hf_repository'=None that is not in the saved config file!
[2023-02-23 10:01:48,112][00203] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-23 10:01:48,113][00203] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-23 10:01:48,116][00203] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-23 10:01:48,117][00203] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-23 10:01:48,118][00203] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-23 10:01:48,157][00203] Doom resolution: 160x120, resize resolution: (128, 72)
[2023-02-23 10:01:48,160][00203] RunningMeanStd input shape: (3, 72, 128)
[2023-02-23 10:01:48,163][00203] RunningMeanStd input shape: (1,)
[2023-02-23 10:01:48,191][00203] ConvEncoder: input_channels=3
[2023-02-23 10:01:49,008][00203] Conv encoder output size: 512
[2023-02-23 10:01:49,011][00203] Policy head output size: 512
[2023-02-23 10:01:51,522][00203] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002199_9007104.pth...
[2023-02-23 10:01:52,816][00203] Num frames 100...
[2023-02-23 10:01:52,929][00203] Num frames 200...
[2023-02-23 10:01:53,046][00203] Num frames 300...
[2023-02-23 10:01:53,168][00203] Num frames 400...
[2023-02-23 10:01:53,289][00203] Num frames 500...
[2023-02-23 10:01:53,431][00203] Avg episode rewards: #0: 9.760, true rewards: #0: 5.760
[2023-02-23 10:01:53,432][00203] Avg episode reward: 9.760, avg true_objective: 5.760
[2023-02-23 10:01:53,465][00203] Num frames 600...
[2023-02-23 10:01:53,578][00203] Num frames 700...
[2023-02-23 10:01:53,698][00203] Num frames 800...
[2023-02-23 10:01:53,819][00203] Num frames 900...
[2023-02-23 10:01:53,937][00203] Num frames 1000...
[2023-02-23 10:01:54,051][00203] Num frames 1100...
[2023-02-23 10:01:54,164][00203] Num frames 1200...
[2023-02-23 10:01:54,280][00203] Num frames 1300...
[2023-02-23 10:01:54,353][00203] Avg episode rewards: #0: 13.580, true rewards: #0: 6.580
[2023-02-23 10:01:54,356][00203] Avg episode reward: 13.580, avg true_objective: 6.580
[2023-02-23 10:01:54,456][00203] Num frames 1400...
[2023-02-23 10:01:54,568][00203] Num frames 1500...
[2023-02-23 10:01:54,680][00203] Num frames 1600...
[2023-02-23 10:01:54,805][00203] Num frames 1700...
[2023-02-23 10:01:54,921][00203] Num frames 1800...
[2023-02-23 10:01:55,033][00203] Num frames 1900...
[2023-02-23 10:01:55,153][00203] Num frames 2000...
[2023-02-23 10:01:55,265][00203] Num frames 2100...
[2023-02-23 10:01:55,384][00203] Num frames 2200...
[2023-02-23 10:01:55,508][00203] Num frames 2300...
[2023-02-23 10:01:55,626][00203] Num frames 2400...
[2023-02-23 10:01:55,744][00203] Num frames 2500...
[2023-02-23 10:01:55,867][00203] Num frames 2600...
[2023-02-23 10:01:55,987][00203] Num frames 2700...
[2023-02-23 10:01:56,107][00203] Num frames 2800...
[2023-02-23 10:01:56,230][00203] Avg episode rewards: #0: 22.533, true rewards: #0: 9.533
[2023-02-23 10:01:56,232][00203] Avg episode reward: 22.533, avg true_objective: 9.533
[2023-02-23 10:01:56,283][00203] Num frames 2900...
[2023-02-23 10:01:56,398][00203] Num frames 3000...
[2023-02-23 10:01:56,525][00203] Num frames 3100...
[2023-02-23 10:01:56,637][00203] Num frames 3200...
[2023-02-23 10:01:56,751][00203] Num frames 3300...
[2023-02-23 10:01:56,857][00203] Avg episode rewards: #0: 18.600, true rewards: #0: 8.350
[2023-02-23 10:01:56,859][00203] Avg episode reward: 18.600, avg true_objective: 8.350
[2023-02-23 10:01:56,930][00203] Num frames 3400...
[2023-02-23 10:01:57,045][00203] Num frames 3500...
[2023-02-23 10:01:57,165][00203] Num frames 3600...
[2023-02-23 10:01:57,278][00203] Num frames 3700...
[2023-02-23 10:01:57,439][00203] Avg episode rewards: #0: 15.976, true rewards: #0: 7.576
[2023-02-23 10:01:57,440][00203] Avg episode reward: 15.976, avg true_objective: 7.576
[2023-02-23 10:01:57,460][00203] Num frames 3800...
[2023-02-23 10:01:57,583][00203] Num frames 3900...
[2023-02-23 10:01:57,696][00203] Num frames 4000...
[2023-02-23 10:01:57,817][00203] Num frames 4100...
[2023-02-23 10:01:57,930][00203] Num frames 4200...
[2023-02-23 10:01:58,048][00203] Num frames 4300...
[2023-02-23 10:01:58,162][00203] Num frames 4400...
[2023-02-23 10:01:58,280][00203] Num frames 4500...
[2023-02-23 10:01:58,437][00203] Avg episode rewards: #0: 16.315, true rewards: #0: 7.648
[2023-02-23 10:01:58,439][00203] Avg episode reward: 16.315, avg true_objective: 7.648
[2023-02-23 10:01:58,456][00203] Num frames 4600...
[2023-02-23 10:01:58,571][00203] Num frames 4700...
[2023-02-23 10:01:58,684][00203] Num frames 4800...
[2023-02-23 10:01:58,801][00203] Num frames 4900...
[2023-02-23 10:01:58,919][00203] Num frames 5000...
[2023-02-23 10:01:59,029][00203] Num frames 5100...
[2023-02-23 10:01:59,141][00203] Num frames 5200...
[2023-02-23 10:01:59,258][00203] Num frames 5300...
[2023-02-23 10:01:59,378][00203] Num frames 5400...
[2023-02-23 10:01:59,460][00203] Avg episode rewards: #0: 16.316, true rewards: #0: 7.744
[2023-02-23 10:01:59,462][00203] Avg episode reward: 16.316, avg true_objective: 7.744
[2023-02-23 10:01:59,585][00203] Num frames 5500...
[2023-02-23 10:01:59,763][00203] Num frames 5600...
[2023-02-23 10:01:59,939][00203] Num frames 5700...
[2023-02-23 10:02:00,102][00203] Num frames 5800...
[2023-02-23 10:02:00,269][00203] Num frames 5900...
[2023-02-23 10:02:00,434][00203] Num frames 6000...
[2023-02-23 10:02:00,597][00203] Num frames 6100...
[2023-02-23 10:02:00,762][00203] Num frames 6200...
[2023-02-23 10:02:00,936][00203] Num frames 6300...
[2023-02-23 10:02:01,034][00203] Avg episode rewards: #0: 17.030, true rewards: #0: 7.905
[2023-02-23 10:02:01,040][00203] Avg episode reward: 17.030, avg true_objective: 7.905
[2023-02-23 10:02:01,163][00203] Num frames 6400...
[2023-02-23 10:02:01,327][00203] Num frames 6500...
[2023-02-23 10:02:01,485][00203] Num frames 6600...
[2023-02-23 10:02:01,653][00203] Num frames 6700...
[2023-02-23 10:02:01,820][00203] Num frames 6800...
[2023-02-23 10:02:01,993][00203] Num frames 6900...
[2023-02-23 10:02:02,170][00203] Num frames 7000...
[2023-02-23 10:02:02,336][00203] Num frames 7100...
[2023-02-23 10:02:02,507][00203] Num frames 7200...
[2023-02-23 10:02:02,675][00203] Num frames 7300...
[2023-02-23 10:02:02,841][00203] Num frames 7400...
[2023-02-23 10:02:03,007][00203] Num frames 7500...
[2023-02-23 10:02:03,128][00203] Avg episode rewards: #0: 18.156, true rewards: #0: 8.378
[2023-02-23 10:02:03,130][00203] Avg episode reward: 18.156, avg true_objective: 8.378
[2023-02-23 10:02:03,200][00203] Num frames 7600...
[2023-02-23 10:02:03,309][00203] Num frames 7700...
[2023-02-23 10:02:03,425][00203] Num frames 7800...
[2023-02-23 10:02:03,534][00203] Num frames 7900...
[2023-02-23 10:02:03,649][00203] Num frames 8000...
[2023-02-23 10:02:03,760][00203] Num frames 8100...
[2023-02-23 10:02:03,872][00203] Num frames 8200...
[2023-02-23 10:02:03,987][00203] Num frames 8300...
[2023-02-23 10:02:04,096][00203] Num frames 8400...
[2023-02-23 10:02:04,213][00203] Num frames 8500...
[2023-02-23 10:02:04,324][00203] Num frames 8600...
[2023-02-23 10:02:04,440][00203] Num frames 8700...
[2023-02-23 10:02:04,555][00203] Num frames 8800...
[2023-02-23 10:02:04,730][00203] Avg episode rewards: #0: 19.699, true rewards: #0: 8.899
[2023-02-23 10:02:04,732][00203] Avg episode reward: 19.699, avg true_objective: 8.899
[2023-02-23 10:02:04,737][00203] Num frames 8900...
[2023-02-23 10:02:58,499][00203] Replay video saved to /content/train_dir/default_experiment/replay.mp4!
[2023-02-23 10:07:25,139][00203] Loading existing experiment configuration from /content/train_dir/default_experiment/config.json
[2023-02-23 10:07:25,141][00203] Overriding arg 'num_workers' with value 1 passed from command line
[2023-02-23 10:07:25,144][00203] Adding new argument 'no_render'=True that is not in the saved config file!
[2023-02-23 10:07:25,146][00203] Adding new argument 'save_video'=True that is not in the saved config file!
[2023-02-23 10:07:25,149][00203] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
[2023-02-23 10:07:25,150][00203] Adding new argument 'video_name'=None that is not in the saved config file!
[2023-02-23 10:07:25,152][00203] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
[2023-02-23 10:07:25,153][00203] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
[2023-02-23 10:07:25,154][00203] Adding new argument 'push_to_hub'=True that is not in the saved config file!
[2023-02-23 10:07:25,156][00203] Adding new argument 'hf_repository'='Rowehn/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file!
[2023-02-23 10:07:25,157][00203] Adding new argument 'policy_index'=0 that is not in the saved config file!
[2023-02-23 10:07:25,159][00203] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
[2023-02-23 10:07:25,160][00203] Adding new argument 'train_script'=None that is not in the saved config file!
[2023-02-23 10:07:25,162][00203] Adding new argument 'enjoy_script'=None that is not in the saved config file!
[2023-02-23 10:07:25,163][00203] Using frameskip 1 and render_action_repeat=4 for evaluation
[2023-02-23 10:07:25,192][00203] RunningMeanStd input shape: (3, 72, 128)
[2023-02-23 10:07:25,194][00203] RunningMeanStd input shape: (1,)
[2023-02-23 10:07:25,209][00203] ConvEncoder: input_channels=3
[2023-02-23 10:07:25,247][00203] Conv encoder output size: 512
[2023-02-23 10:07:25,249][00203] Policy head output size: 512
[2023-02-23 10:07:25,270][00203] Loading state from checkpoint /content/train_dir/default_experiment/checkpoint_p0/checkpoint_000002199_9007104.pth...
[2023-02-23 10:07:25,743][00203] Num frames 100...
[2023-02-23 10:07:25,868][00203] Num frames 200...
[2023-02-23 10:07:25,997][00203] Num frames 300...
[2023-02-23 10:07:26,119][00203] Num frames 400...
[2023-02-23 10:07:26,236][00203] Num frames 500...
[2023-02-23 10:07:26,362][00203] Num frames 600...
[2023-02-23 10:07:26,477][00203] Num frames 700...
[2023-02-23 10:07:26,590][00203] Num frames 800...
[2023-02-23 10:07:26,706][00203] Num frames 900...
[2023-02-23 10:07:26,822][00203] Num frames 1000...
[2023-02-23 10:07:26,941][00203] Num frames 1100...
[2023-02-23 10:07:27,066][00203] Num frames 1200...
[2023-02-23 10:07:27,184][00203] Num frames 1300...
[2023-02-23 10:07:27,255][00203] Avg episode rewards: #0: 31.120, true rewards: #0: 13.120
[2023-02-23 10:07:27,258][00203] Avg episode reward: 31.120, avg true_objective: 13.120
[2023-02-23 10:07:27,368][00203] Num frames 1400...
[2023-02-23 10:07:27,483][00203] Num frames 1500...
[2023-02-23 10:07:27,600][00203] Num frames 1600...
[2023-02-23 10:07:27,723][00203] Num frames 1700...
[2023-02-23 10:07:27,841][00203] Num frames 1800...
[2023-02-23 10:07:27,965][00203] Num frames 1900...
[2023-02-23 10:07:28,086][00203] Num frames 2000...
[2023-02-23 10:07:28,214][00203] Num frames 2100...
[2023-02-23 10:07:28,331][00203] Num frames 2200...
[2023-02-23 10:07:28,454][00203] Num frames 2300...
[2023-02-23 10:07:28,551][00203] Avg episode rewards: #0: 28.180, true rewards: #0: 11.680
[2023-02-23 10:07:28,552][00203] Avg episode reward: 28.180, avg true_objective: 11.680
[2023-02-23 10:07:28,629][00203] Num frames 2400...
[2023-02-23 10:07:28,747][00203] Num frames 2500...
[2023-02-23 10:07:28,873][00203] Num frames 2600...
[2023-02-23 10:07:28,990][00203] Num frames 2700...
[2023-02-23 10:07:29,088][00203] Avg episode rewards: #0: 22.100, true rewards: #0: 9.100
[2023-02-23 10:07:29,090][00203] Avg episode reward: 22.100, avg true_objective: 9.100
[2023-02-23 10:07:29,173][00203] Num frames 2800...
[2023-02-23 10:07:29,289][00203] Num frames 2900...
[2023-02-23 10:07:29,407][00203] Num frames 3000...
[2023-02-23 10:07:29,522][00203] Num frames 3100...
[2023-02-23 10:07:29,638][00203] Num frames 3200...
[2023-02-23 10:07:29,760][00203] Num frames 3300...
[2023-02-23 10:07:29,883][00203] Num frames 3400...
[2023-02-23 10:07:30,002][00203] Num frames 3500...
[2023-02-23 10:07:30,134][00203] Num frames 3600...
[2023-02-23 10:07:30,257][00203] Num frames 3700...
[2023-02-23 10:07:30,386][00203] Num frames 3800...
[2023-02-23 10:07:30,563][00203] Num frames 3900...
[2023-02-23 10:07:30,632][00203] Avg episode rewards: #0: 23.015, true rewards: #0: 9.765
[2023-02-23 10:07:30,634][00203] Avg episode reward: 23.015, avg true_objective: 9.765
[2023-02-23 10:07:30,786][00203] Num frames 4000...
[2023-02-23 10:07:30,946][00203] Num frames 4100...
[2023-02-23 10:07:31,117][00203] Num frames 4200...
[2023-02-23 10:07:31,274][00203] Num frames 4300...
[2023-02-23 10:07:31,436][00203] Num frames 4400...
[2023-02-23 10:07:31,606][00203] Num frames 4500...
[2023-02-23 10:07:31,770][00203] Num frames 4600...
[2023-02-23 10:07:31,930][00203] Num frames 4700...
[2023-02-23 10:07:32,093][00203] Num frames 4800...
[2023-02-23 10:07:32,268][00203] Num frames 4900...
[2023-02-23 10:07:32,427][00203] Num frames 5000...
[2023-02-23 10:07:32,605][00203] Num frames 5100...
[2023-02-23 10:07:32,792][00203] Num frames 5200...
[2023-02-23 10:07:32,960][00203] Num frames 5300...
[2023-02-23 10:07:33,133][00203] Num frames 5400...
[2023-02-23 10:07:33,306][00203] Num frames 5500...
[2023-02-23 10:07:33,470][00203] Num frames 5600...
[2023-02-23 10:07:33,640][00203] Num frames 5700...
[2023-02-23 10:07:33,809][00203] Num frames 5800...
[2023-02-23 10:07:33,966][00203] Num frames 5900...
[2023-02-23 10:07:34,079][00203] Num frames 6000...
[2023-02-23 10:07:34,143][00203] Avg episode rewards: #0: 30.012, true rewards: #0: 12.012
[2023-02-23 10:07:34,145][00203] Avg episode reward: 30.012, avg true_objective: 12.012
[2023-02-23 10:07:34,269][00203] Num frames 6100...
[2023-02-23 10:07:34,386][00203] Num frames 6200...
[2023-02-23 10:07:34,499][00203] Num frames 6300...
[2023-02-23 10:07:34,625][00203] Num frames 6400...
[2023-02-23 10:07:34,744][00203] Num frames 6500...
[2023-02-23 10:07:34,861][00203] Num frames 6600...
[2023-02-23 10:07:34,983][00203] Num frames 6700...
[2023-02-23 10:07:35,097][00203] Num frames 6800...
[2023-02-23 10:07:35,233][00203] Num frames 6900...
[2023-02-23 10:07:35,373][00203] Num frames 7000...
[2023-02-23 10:07:35,493][00203] Num frames 7100...
[2023-02-23 10:07:35,608][00203] Num frames 7200...
[2023-02-23 10:07:35,722][00203] Num frames 7300...
[2023-02-23 10:07:35,841][00203] Num frames 7400...
[2023-02-23 10:07:35,961][00203] Num frames 7500...
[2023-02-23 10:07:36,087][00203] Num frames 7600...
[2023-02-23 10:07:36,205][00203] Num frames 7700...
[2023-02-23 10:07:36,333][00203] Num frames 7800...
[2023-02-23 10:07:36,454][00203] Num frames 7900...
[2023-02-23 10:07:36,576][00203] Num frames 8000...
[2023-02-23 10:07:36,696][00203] Num frames 8100...
[2023-02-23 10:07:36,761][00203] Avg episode rewards: #0: 34.176, true rewards: #0: 13.510
[2023-02-23 10:07:36,763][00203] Avg episode reward: 34.176, avg true_objective: 13.510
[2023-02-23 10:07:36,874][00203] Num frames 8200...
[2023-02-23 10:07:36,984][00203] Num frames 8300...
[2023-02-23 10:07:37,099][00203] Num frames 8400...
[2023-02-23 10:07:37,217][00203] Num frames 8500...
[2023-02-23 10:07:37,356][00203] Num frames 8600...
[2023-02-23 10:07:37,479][00203] Num frames 8700...
[2023-02-23 10:07:37,634][00203] Avg episode rewards: #0: 31.254, true rewards: #0: 12.540
[2023-02-23 10:07:37,636][00203] Avg episode reward: 31.254, avg true_objective: 12.540
[2023-02-23 10:07:37,662][00203] Num frames 8800...
[2023-02-23 10:07:37,793][00203] Num frames 8900...
[2023-02-23 10:07:37,917][00203] Num frames 9000...
[2023-02-23 10:07:38,034][00203] Num frames 9100...
[2023-02-23 10:07:38,169][00203] Avg episode rewards: #0: 28.205, true rewards: #0: 11.455
[2023-02-23 10:07:38,171][00203] Avg episode reward: 28.205, avg true_objective: 11.455
[2023-02-23 10:07:38,218][00203] Num frames 9200...
[2023-02-23 10:07:38,344][00203] Num frames 9300...
[2023-02-23 10:07:38,458][00203] Num frames 9400...
[2023-02-23 10:07:38,581][00203] Num frames 9500...
[2023-02-23 10:07:38,694][00203] Num frames 9600...
[2023-02-23 10:07:38,813][00203] Num frames 9700...
[2023-02-23 10:07:38,926][00203] Num frames 9800...
[2023-02-23 10:07:39,043][00203] Num frames 9900...
[2023-02-23 10:07:39,160][00203] Num frames 10000...
[2023-02-23 10:07:39,283][00203] Num frames 10100...
[2023-02-23 10:07:39,407][00203] Num frames 10200...
[2023-02-23 10:07:39,495][00203] Avg episode rewards: #0: 27.698, true rewards: #0: 11.364
[2023-02-23 10:07:39,496][00203] Avg episode reward: 27.698, avg true_objective: 11.364
[2023-02-23 10:07:39,583][00203] Num frames 10300...
[2023-02-23 10:07:39,701][00203] Num frames 10400...
[2023-02-23 10:07:39,812][00203] Num frames 10500...
[2023-02-23 10:07:39,931][00203] Num frames 10600...
[2023-02-23 10:07:40,043][00203] Num frames 10700...
[2023-02-23 10:07:40,165][00203] Num frames 10800...
[2023-02-23 10:07:40,282][00203] Num frames 10900...
[2023-02-23 10:07:40,404][00203] Num frames 11000...
[2023-02-23 10:07:40,534][00203] Num frames 11100...
[2023-02-23 10:07:40,653][00203] Num frames 11200...
[2023-02-23 10:07:40,773][00203] Num frames 11300...
[2023-02-23 10:07:40,887][00203] Num frames 11400...
[2023-02-23 10:07:41,030][00203] Avg episode rewards: #0: 27.676, true rewards: #0: 11.476
[2023-02-23 10:07:41,032][00203] Avg episode reward: 27.676, avg true_objective: 11.476
[2023-02-23 10:08:53,002][00203] Replay video saved to /content/train_dir/default_experiment/replay.mp4!