First Push
Browse files- README.md +31 -0
- SoccerTwos/SoccerTwos-18499970.onnx +3 -0
- SoccerTwos/SoccerTwos-18499970.pt +3 -0
- SoccerTwos/SoccerTwos-18999884.onnx +3 -0
- SoccerTwos/SoccerTwos-18999884.pt +3 -0
- SoccerTwos/SoccerTwos-19499998.onnx +3 -0
- SoccerTwos/SoccerTwos-19499998.pt +3 -0
- SoccerTwos/SoccerTwos-19999996.onnx +3 -0
- SoccerTwos/SoccerTwos-19999996.pt +3 -0
- SoccerTwos/SoccerTwos-20499973.onnx +3 -0
- SoccerTwos/SoccerTwos-20499973.pt +3 -0
- SoccerTwos/SoccerTwos-7999972.onnx +3 -0
- SoccerTwos/SoccerTwos-7999972.pt +3 -0
- SoccerTwos/SoccerTwos-8499988.onnx +3 -0
- SoccerTwos/SoccerTwos-8499988.pt +3 -0
- SoccerTwos/SoccerTwos-8999945.onnx +3 -0
- SoccerTwos/SoccerTwos-8999945.pt +3 -0
- SoccerTwos/SoccerTwos-9499928.onnx +3 -0
- SoccerTwos/SoccerTwos-9499928.pt +3 -0
- SoccerTwos/SoccerTwos-9999962.onnx +3 -0
- SoccerTwos/SoccerTwos-9999962.pt +3 -0
- SoccerTwos/checkpoint.pt +3 -0
- SoccerTwos/events.out.tfevents.1679067364.maxence.342.0 +3 -0
- SoccerTwos/events.out.tfevents.1679120436.maxence.58.0 +3 -0
- config.json +1 -0
- configuration.yaml +82 -0
- run_logs/Player-0.log +65 -0
- run_logs/timers.json +47 -0
- run_logs/training_status.json +7 -0
README.md
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---
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tags:
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- unity-ml-agents
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- ml-agents
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- deep-reinforcement-learning
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- reinforcement-learning
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- ML-Agents-SoccerTwos
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library_name: ml-agents
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---
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# **poca** Agent playing **SoccerTwos**
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This is a trained model of a **poca** agent playing **SoccerTwos** 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://github.com/huggingface/ml-agents#get-started
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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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### Resume the training
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```
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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. Go to https://huggingface.co/spaces/unity/ML-Agents-SoccerTwos
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2. Step 1: Write your model_id: Max100ce/poca-SoccerTwos
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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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SoccerTwos/SoccerTwos-18499970.onnx
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SoccerTwos/SoccerTwos-9999962.onnx
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SoccerTwos/checkpoint.pt
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config.json
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{"default_settings": null, "behaviors": {"SoccerTwos": {"trainer_type": "poca", "hyperparameters": {"batch_size": 2048, "buffer_size": 20480, "learning_rate": 0.0003, "beta": 0.005, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 5, "learning_rate_schedule": "constant", "beta_schedule": "constant", "epsilon_schedule": "constant"}, "checkpoint_interval": 500000, "network_settings": {"normalize": false, "hidden_units": 512, "num_layers": 3, "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": 5, "even_checkpoints": false, "max_steps": 100000000, "time_horizon": 1000, "summary_freq": 10000, "threaded": false, "self_play": {"save_steps": 50000, "team_change": 200000, "swap_steps": 2000, "window": 10, "play_against_latest_model_ratio": 0.5, "initial_elo": 1200.0}, "behavioral_cloning": null}}, "env_settings": {"env_path": "./ml-agents/training-envs-executables/SoccerTwos/SoccerTwos.x86_64", "env_args": null, "base_port": 5005, "num_envs": 1, "num_areas": 1, "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}, "environment_parameters": null, "checkpoint_settings": {"run_id": "SoccerTwos", "initialize_from": null, "load_model": false, "resume": false, "force": true, "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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SoccerTwos:
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trainer_type: poca
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hyperparameters:
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batch_size: 2048
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buffer_size: 20480
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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: 5
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+
learning_rate_schedule: constant
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beta_schedule: constant
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epsilon_schedule: constant
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checkpoint_interval: 500000
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network_settings:
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normalize: false
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hidden_units: 512
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num_layers: 3
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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: 5
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even_checkpoints: false
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max_steps: 100000000
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time_horizon: 1000
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summary_freq: 10000
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threaded: false
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self_play:
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save_steps: 50000
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team_change: 200000
|
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swap_steps: 2000
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window: 10
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+
play_against_latest_model_ratio: 0.5
|
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initial_elo: 1200.0
|
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behavioral_cloning: null
|
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env_settings:
|
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env_path: ./ml-agents/training-envs-executables/SoccerTwos/SoccerTwos.x86_64
|
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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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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
|
65 |
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quality_level: 5
|
66 |
+
time_scale: 20
|
67 |
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target_frame_rate: -1
|
68 |
+
capture_frame_rate: 60
|
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no_graphics: true
|
70 |
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environment_parameters: null
|
71 |
+
checkpoint_settings:
|
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run_id: SoccerTwos
|
73 |
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initialize_from: null
|
74 |
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load_model: false
|
75 |
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resume: false
|
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force: true
|
77 |
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train_model: false
|
78 |
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inference: false
|
79 |
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results_dir: results
|
80 |
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torch_settings:
|
81 |
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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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1 |
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Mono path[0] = '/home/maxence/Documents/mook_reinforcement_learning/ml-agents/training-envs-executables/SoccerTwos/SoccerTwos_Data/Managed'
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2 |
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Mono config path = '/home/maxence/Documents/mook_reinforcement_learning/ml-agents/training-envs-executables/SoccerTwos/SoccerTwos_Data/MonoBleedingEdge/etc'
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3 |
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Preloaded 'lib_burst_generated.so'
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Preloaded 'libgrpc_csharp_ext.x64.so'
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5 |
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PlayerPrefs - Creating folder: /root/.config/unity3d/Unity Technologies
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PlayerPrefs - Creating folder: /root/.config/unity3d/Unity Technologies/SoccerTwos
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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 /home/maxence/Documents/mook_reinforcement_learning/ml-agents/training-envs-executables/SoccerTwos/SoccerTwos_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:767:(parse_card) cannot find card '0'
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ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_card_driver returned error: No such file or directory
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ALSA lib confmisc.c:392:(snd_func_concat) error evaluating strings
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ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory
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ALSA lib confmisc.c:1246:(snd_func_refer) error evaluating name
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ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory
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ALSA lib conf.c:5220:(snd_config_expand) Evaluate error: No such file or directory
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ALSA lib pcm.c:2642:(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:767:(parse_card) cannot find card '0'
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ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_card_driver returned error: No such file or directory
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ALSA lib confmisc.c:392:(snd_func_concat) error evaluating strings
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ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory
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ALSA lib confmisc.c:1246:(snd_func_refer) error evaluating name
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+
ALSA lib conf.c:4732:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory
|
32 |
+
ALSA lib conf.c:5220:(snd_config_expand) Evaluate error: No such file or directory
|
33 |
+
ALSA lib pcm.c:2642:(snd_pcm_open_noupdate) Unknown PCM default
|
34 |
+
FMOD failed to initialize the output device.: "Error initializing output device. " (60)
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FMOD initialized on nosound output
|
36 |
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Begin MonoManager ReloadAssembly
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- Completed reload, in 0.814 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 (Specular setup)' - All subshaders removed
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+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
43 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
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+
ERROR: Shader Standard (Specular setup) shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
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+
WARNING: Shader Unsupported: 'Standard (Specular setup)' - All subshaders removed
|
46 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
47 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
48 |
+
WARNING: Shader Unsupported: 'Autodesk Interactive' - All subshaders removed
|
49 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
50 |
+
WARNING: Shader If subshaders removal was intentional, you may have forgotten turning Fallback off?
|
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+
ERROR: Shader Autodesk Interactive shader is not supported on this GPU (none of subshaders/fallbacks are suitable)
|
52 |
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WARNING: Shader Unsupported: 'Autodesk Interactive' - 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?
|
55 |
+
WARNING: Shader Unsupported: 'Standard' - All subshaders removed
|
56 |
+
WARNING: Shader Did you use #pragma only_renderers and omit this platform?
|
57 |
+
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)
|
59 |
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WARNING: Shader Unsupported: 'Standard' - All subshaders removed
|
60 |
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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: 1.088556 ms
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Registered Communicator in Agent.
|
64 |
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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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run_logs/timers.json
ADDED
@@ -0,0 +1,47 @@
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{
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"name": "root",
|
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"metadata": {
|
4 |
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"timer_format_version": "0.1.0",
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5 |
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"start_time_seconds": "1679067340",
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6 |
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"python_version": "3.8.16 (default, Jan 17 2023, 23:13:24) \n[GCC 11.2.0]",
|
7 |
+
"command_line_arguments": "/anaconda/bin//mlagents-learn ./ml-agents/config/poca/SoccerTwos.yaml --force --env=./ml-agents/training-envs-executables/SoccerTwos/SoccerTwos.x86_64 --run-id=SoccerTwos --no-graphics",
|
8 |
+
"mlagents_version": "0.31.0.dev0",
|
9 |
+
"mlagents_envs_version": "0.31.0.dev0",
|
10 |
+
"communication_protocol_version": "1.5.0",
|
11 |
+
"pytorch_version": "1.8.1+cu102",
|
12 |
+
"numpy_version": "1.21.2",
|
13 |
+
"end_time_seconds": "1679067340"
|
14 |
+
},
|
15 |
+
"total": 0.05132555900127045,
|
16 |
+
"count": 1,
|
17 |
+
"self": 0.008548834000976058,
|
18 |
+
"children": {
|
19 |
+
"run_training.setup": {
|
20 |
+
"total": 0.017042807001416804,
|
21 |
+
"count": 1,
|
22 |
+
"self": 0.017042807001416804
|
23 |
+
},
|
24 |
+
"TrainerController.start_learning": {
|
25 |
+
"total": 0.025733917998877587,
|
26 |
+
"count": 1,
|
27 |
+
"self": 0.00047004899897729047,
|
28 |
+
"children": {
|
29 |
+
"TrainerController._reset_env": {
|
30 |
+
"total": 0.025242455998522928,
|
31 |
+
"count": 1,
|
32 |
+
"self": 0.025242455998522928
|
33 |
+
},
|
34 |
+
"trainer_threads": {
|
35 |
+
"total": 1.8280006770510226e-06,
|
36 |
+
"count": 1,
|
37 |
+
"self": 1.8280006770510226e-06
|
38 |
+
},
|
39 |
+
"TrainerController._save_models": {
|
40 |
+
"total": 1.9585000700317323e-05,
|
41 |
+
"count": 1,
|
42 |
+
"self": 1.9585000700317323e-05
|
43 |
+
}
|
44 |
+
}
|
45 |
+
}
|
46 |
+
}
|
47 |
+
}
|
run_logs/training_status.json
ADDED
@@ -0,0 +1,7 @@
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|
1 |
+
{
|
2 |
+
"metadata": {
|
3 |
+
"stats_format_version": "0.3.0",
|
4 |
+
"mlagents_version": "0.31.0.dev0",
|
5 |
+
"torch_version": "1.8.1+cu102"
|
6 |
+
}
|
7 |
+
}
|