Commit
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Parent(s):
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First Push
Browse files- README.md +35 -0
- SnowballTarget.onnx +3 -0
- SnowballTarget/SnowballTarget-39512.onnx +3 -0
- SnowballTarget/SnowballTarget-39512.pt +3 -0
- SnowballTarget/checkpoint.pt +3 -0
- SnowballTarget/events.out.tfevents.1717145135.369fc379330c.2631.0 +3 -0
- config.json +1 -0
- configuration.yaml +79 -0
- run_logs/Player-0.log +262 -0
- run_logs/timers.json +180 -0
- run_logs/training_status.json +29 -0
README.md
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---
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library_name: ml-agents
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tags:
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- SnowballTarget
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- deep-reinforcement-learning
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- reinforcement-learning
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- ML-Agents-SnowballTarget
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---
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# **ppo** Agent playing **SnowballTarget**
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This is a trained model of a **ppo** agent playing **SnowballTarget**
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using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
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## Usage (with ML-Agents)
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The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
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We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
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- A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
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browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
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- A *longer tutorial* to understand how works ML-Agents:
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https://huggingface.co/learn/deep-rl-course/unit5/introduction
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### Resume the training
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```bash
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mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
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```
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### Watch your Agent play
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You can watch your agent **playing directly in your browser**
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1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
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2. Step 1: Find your model_id: hickman2049/ppo-SnowballTarget
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3. Step 2: Select your *.nn /*.onnx file
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4. Click on Watch the agent play 👀
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SnowballTarget.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:aef4343c17495104d3af9b756ff9c77cbc8c8f8d93c7c0fa8f0988f1d7daf52e
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size 650646
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SnowballTarget/SnowballTarget-39512.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:aef4343c17495104d3af9b756ff9c77cbc8c8f8d93c7c0fa8f0988f1d7daf52e
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size 650646
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SnowballTarget/SnowballTarget-39512.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:c015e089b6a99af405df2fe3fe72aae01f55230aeb513fb3719e7cd42ab31fc4
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size 3850000
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SnowballTarget/checkpoint.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:46c49b45e1f2c23403736119a3e213c64c1d4a9af6af6c82c46922a71d66aab0
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size 3849250
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SnowballTarget/events.out.tfevents.1717145135.369fc379330c.2631.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:752a4e375f4d71db1bf217d849c91f6d954ffc5bfd7e33be2a0b4732410aa49e
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size 13635
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config.json
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{"default_settings": null, "behaviors": {"SnowballTarget": {"trainer_type": "ppo", "hyperparameters": {"batch_size": 128, "buffer_size": 2048, "learning_rate": 0.0003, "beta": 0.005, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 3, "shared_critic": false, "learning_rate_schedule": "linear", "beta_schedule": "linear", "epsilon_schedule": "linear"}, "checkpoint_interval": 50000, "network_settings": {"normalize": false, "hidden_units": 256, "num_layers": 2, "vis_encode_type": "simple", "memory": null, "goal_conditioning_type": "hyper", "deterministic": false}, "reward_signals": {"extrinsic": {"gamma": 0.99, "strength": 1.0, "network_settings": {"normalize": false, "hidden_units": 128, "num_layers": 2, "vis_encode_type": "simple", "memory": null, "goal_conditioning_type": "hyper", "deterministic": false}}}, "init_path": null, "keep_checkpoints": 10, "even_checkpoints": false, "max_steps": 200000, "time_horizon": 64, "summary_freq": 10000, "threaded": true, "self_play": null, "behavioral_cloning": null}}, "env_settings": {"env_path": "./training-envs-executables/linux/SnowballTarget/SnowballTarget", "env_args": null, "base_port": 5005, "num_envs": 1, "num_areas": 1, "timeout_wait": 60, "seed": -1, "max_lifetime_restarts": 10, "restarts_rate_limit_n": 1, "restarts_rate_limit_period_s": 60}, "engine_settings": {"width": 84, "height": 84, "quality_level": 5, "time_scale": 20, "target_frame_rate": -1, "capture_frame_rate": 60, "no_graphics": true, "no_graphics_monitor": false}, "environment_parameters": null, "checkpoint_settings": {"run_id": "SnowballTarget1", "initialize_from": null, "load_model": false, "resume": false, "force": false, "train_model": false, "inference": false, "results_dir": "results"}, "torch_settings": {"device": null}, "debug": false}
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configuration.yaml
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default_settings: null
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behaviors:
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SnowballTarget:
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trainer_type: ppo
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hyperparameters:
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batch_size: 128
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buffer_size: 2048
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learning_rate: 0.0003
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beta: 0.005
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epsilon: 0.2
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lambd: 0.95
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num_epoch: 3
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shared_critic: false
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learning_rate_schedule: linear
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beta_schedule: linear
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epsilon_schedule: linear
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checkpoint_interval: 50000
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network_settings:
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normalize: false
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hidden_units: 256
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num_layers: 2
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vis_encode_type: simple
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memory: null
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goal_conditioning_type: hyper
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deterministic: false
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reward_signals:
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extrinsic:
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gamma: 0.99
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strength: 1.0
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network_settings:
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normalize: false
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hidden_units: 128
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num_layers: 2
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vis_encode_type: simple
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memory: null
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goal_conditioning_type: hyper
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deterministic: false
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init_path: null
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keep_checkpoints: 10
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even_checkpoints: false
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max_steps: 200000
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time_horizon: 64
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summary_freq: 10000
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threaded: true
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self_play: null
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behavioral_cloning: null
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env_settings:
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env_path: ./training-envs-executables/linux/SnowballTarget/SnowballTarget
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env_args: null
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base_port: 5005
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num_envs: 1
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num_areas: 1
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timeout_wait: 60
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seed: -1
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max_lifetime_restarts: 10
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restarts_rate_limit_n: 1
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restarts_rate_limit_period_s: 60
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engine_settings:
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width: 84
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height: 84
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quality_level: 5
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time_scale: 20
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target_frame_rate: -1
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capture_frame_rate: 60
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no_graphics: true
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no_graphics_monitor: false
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environment_parameters: null
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checkpoint_settings:
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run_id: SnowballTarget1
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initialize_from: null
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load_model: false
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resume: false
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force: false
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train_model: false
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inference: false
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results_dir: results
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torch_settings:
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device: null
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debug: false
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run_logs/Player-0.log
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Mono path[0] = '/content/training-envs-executables/linux/SnowballTarget/SnowballTarget_Data/Managed'
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Mono config path = '/content/training-envs-executables/linux/SnowballTarget/SnowballTarget_Data/MonoBleedingEdge/etc'
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Preloaded 'lib_burst_generated.so'
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Preloaded 'libgrpc_csharp_ext.x64.so'
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PlayerPrefs - Creating folder: /root/.config/unity3d/Hugging Face
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PlayerPrefs - Creating folder: /root/.config/unity3d/Hugging Face/SnowballTarget
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Unable to load player prefs
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Initialize engine version: 2021.3.14f1 (eee1884e7226)
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[Subsystems] Discovering subsystems at path /content/training-envs-executables/linux/SnowballTarget/SnowballTarget_Data/UnitySubsystems
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Forcing GfxDevice: Null
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GfxDevice: creating device client; threaded=0; jobified=0
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NullGfxDevice:
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Version: NULL 1.0 [1.0]
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Renderer: Null Device
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Vendor: Unity Technologies
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ALSA lib confmisc.c:855:(parse_card) cannot find card '0'
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ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_card_inum returned error: No such file or directory
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ALSA lib confmisc.c:422:(snd_func_concat) error evaluating strings
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ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory
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ALSA lib confmisc.c:1334:(snd_func_refer) error evaluating name
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ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory
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ALSA lib conf.c:5701:(snd_config_expand) Evaluate error: No such file or directory
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ALSA lib pcm.c:2664:(snd_pcm_open_noupdate) Unknown PCM default
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FMOD failed to initialize the output device.: "Error initializing output device. " (60)
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Forced to initialize FMOD to to the device driver's system output rate 48000, this may impact performance and/or give inconsistent experiences compared to selected sample rate 48000
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ALSA lib confmisc.c:855:(parse_card) cannot find card '0'
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ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_card_inum returned error: No such file or directory
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ALSA lib confmisc.c:422:(snd_func_concat) error evaluating strings
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ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory
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ALSA lib confmisc.c:1334:(snd_func_refer) error evaluating name
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ALSA lib conf.c:5178:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory
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ALSA lib conf.c:5701:(snd_config_expand) Evaluate error: No such file or directory
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ALSA lib pcm.c:2664:(snd_pcm_open_noupdate) Unknown PCM default
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FMOD failed to initialize the output device.: "Error initializing output device. " (60)
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FMOD initialized on nosound output
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Begin MonoManager ReloadAssembly
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- Completed reload, in 0.242 seconds
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ERROR: Shader Sprites/Default shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
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ERROR: Shader Sprites/Mask shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
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ERROR: Shader Legacy Shaders/VertexLit shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
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WARNING: Shader Unsupported: 'Standard' - All subshaders removed
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WARNING: Shader Did you use #pragma only_renderers and omit this platform?
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WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
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ERROR: Shader Standard shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
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WARNING: Shader Unsupported: 'Standard' - All subshaders removed
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WARNING: Shader Did you use #pragma only_renderers and omit this platform?
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WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
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UnloadTime: 0.830288 ms
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ERROR: Shader UI/Default shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
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requesting resize 84 x 84
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Setting up 1 worker threads for Enlighten.
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Memory Statistics:
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[ALLOC_TEMP_TLS] TLS Allocator
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StackAllocators :
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[ALLOC_TEMP_MAIN]
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Peak usage frame count: [8.0 KB-16.0 KB]: 1062 frames, [16.0 KB-32.0 KB]: 18 frames, [2.0 MB-4.0 MB]: 1 frames
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Initial Block Size 4.0 MB
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Current Block Size 4.0 MB
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Peak Allocated Bytes 2.0 MB
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Overflow Count 0
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[ALLOC_TEMP_Loading.AsyncRead]
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Initial Block Size 64.0 KB
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Current Block Size 64.0 KB
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Peak Allocated Bytes 178 B
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Overflow Count 0
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[ALLOC_TEMP_Loading.PreloadManager]
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Initial Block Size 256.0 KB
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Current Block Size 304.0 KB
|
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[ALLOC_CACHEOBJECTS] Dual Thread Allocator
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[ALLOC_BUCKET]
|
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232 |
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233 |
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[ALLOC_CACHEOBJECTS_MAIN]
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235 |
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238 |
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[ALLOC_CACHEOBJECTS_THREAD]
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240 |
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[ALLOC_TYPETREE] Dual Thread Allocator
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|
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254 |
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[ALLOC_TYPETREE_THREAD]
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run_logs/timers.json
ADDED
@@ -0,0 +1,180 @@
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{
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}
|
159 |
+
}
|
160 |
+
}
|
161 |
+
}
|
162 |
+
}
|
163 |
+
}
|
164 |
+
},
|
165 |
+
"TrainerController._save_models": {
|
166 |
+
"total": 0.5915363599999637,
|
167 |
+
"count": 1,
|
168 |
+
"self": 0.00127640200003043,
|
169 |
+
"children": {
|
170 |
+
"RLTrainer._checkpoint": {
|
171 |
+
"total": 0.5902599579999332,
|
172 |
+
"count": 1,
|
173 |
+
"self": 0.5902599579999332
|
174 |
+
}
|
175 |
+
}
|
176 |
+
}
|
177 |
+
}
|
178 |
+
}
|
179 |
+
}
|
180 |
+
}
|
run_logs/training_status.json
ADDED
@@ -0,0 +1,29 @@
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"SnowballTarget": {
|
3 |
+
"checkpoints": [
|
4 |
+
{
|
5 |
+
"steps": 39512,
|
6 |
+
"file_path": "results/SnowballTarget1/SnowballTarget/SnowballTarget-39512.onnx",
|
7 |
+
"reward": null,
|
8 |
+
"creation_time": 1717145225.8258634,
|
9 |
+
"auxillary_file_paths": [
|
10 |
+
"results/SnowballTarget1/SnowballTarget/SnowballTarget-39512.pt"
|
11 |
+
]
|
12 |
+
}
|
13 |
+
],
|
14 |
+
"final_checkpoint": {
|
15 |
+
"steps": 39512,
|
16 |
+
"file_path": "results/SnowballTarget1/SnowballTarget.onnx",
|
17 |
+
"reward": null,
|
18 |
+
"creation_time": 1717145225.8258634,
|
19 |
+
"auxillary_file_paths": [
|
20 |
+
"results/SnowballTarget1/SnowballTarget/SnowballTarget-39512.pt"
|
21 |
+
]
|
22 |
+
}
|
23 |
+
},
|
24 |
+
"metadata": {
|
25 |
+
"stats_format_version": "0.3.0",
|
26 |
+
"mlagents_version": "1.1.0.dev0",
|
27 |
+
"torch_version": "2.3.0+cu121"
|
28 |
+
}
|
29 |
+
}
|