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sha256:129fc2daa5f66575dd1a3873c4181fa798530ac019f21ecaceb8a14e8f53b7b5 +size 132233 diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..4fbbc36b29acc53fab37f0f63bfb546e02dbfa5a --- /dev/null +++ b/README.md @@ -0,0 +1,35 @@ +--- +library_name: ml-agents +tags: +- Pyramids +- deep-reinforcement-learning +- reinforcement-learning +- ML-Agents-Pyramids +--- + + # **ppo** Agent playing **Pyramids** + This is a trained model of a **ppo** agent playing **Pyramids** + using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents). + + ## Usage (with ML-Agents) + The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/ + + We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub: + - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your + browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction + - A *longer tutorial* to understand how works ML-Agents: + https://huggingface.co/learn/deep-rl-course/unit5/introduction + + ### Resume the training + ```bash + mlagents-learn --run-id= --resume + ``` + + ### Watch your Agent play + You can watch your agent **playing directly in your browser** + + 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity + 2. Step 1: Find your model_id: MTahaB/ppo-Pyramids + 3. Step 2: Select your *.nn /*.onnx file + 4. Click on Watch the agent play 👀 + \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000000000000000000000000000000000000..94181ee295cfdb7f24ab9e8ee1de57fcc962d3e3 --- /dev/null +++ b/config.json @@ -0,0 +1 @@ +{"default_settings": null, "behaviors": {"Pyramids": {"trainer_type": "ppo", "hyperparameters": {"batch_size": 256, "buffer_size": 4096, "learning_rate": 0.0003, "beta": 0.01, "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": 512, "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}}, "rnd": {"gamma": 0.99, "strength": 0.01, "network_settings": {"normalize": false, "hidden_units": 64, "num_layers": 3, "vis_encode_type": "simple", "memory": null, "goal_conditioning_type": "hyper", "deterministic": false}, "learning_rate": 0.0001, "encoding_size": null}}, "init_path": null, "keep_checkpoints": 20, "even_checkpoints": false, "max_steps": 1500000, "time_horizon": 128, "summary_freq": 10000, "threaded": false, "self_play": null, "behavioral_cloning": null}}, "env_settings": {"env_path": "/content/ml-agents/training-envs-executables/linux/Pyramids/Pyramids", "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": "Pyramids2", "initialize_from": null, "load_model": false, "resume": true, "force": false, "train_model": false, "inference": true, "results_dir": "/content/drive/MyDrive/mlagents-results"}, "torch_settings": {"device": null}, "debug": false} \ No newline at end of file diff --git a/configuration.yaml b/configuration.yaml new file mode 100644 index 0000000000000000000000000000000000000000..ae6c687c7a4aec951546c49dd447b0165d66aba1 --- /dev/null +++ b/configuration.yaml @@ -0,0 +1,92 @@ +default_settings: null +behaviors: + Pyramids: + trainer_type: ppo + hyperparameters: + batch_size: 256 + buffer_size: 4096 + learning_rate: 0.0003 + beta: 0.01 + 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: 512 + 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 + rnd: + gamma: 0.99 + strength: 0.01 + network_settings: + normalize: false + hidden_units: 64 + num_layers: 3 + vis_encode_type: simple + memory: null + goal_conditioning_type: hyper + deterministic: false + learning_rate: 0.0001 + encoding_size: null + init_path: null + keep_checkpoints: 20 + even_checkpoints: false + max_steps: 1500000 + time_horizon: 128 + summary_freq: 10000 + threaded: false + self_play: null + behavioral_cloning: null +env_settings: + env_path: /content/ml-agents/training-envs-executables/linux/Pyramids/Pyramids + 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: Pyramids2 + initialize_from: null + load_model: false + resume: true + force: false + train_model: false + inference: true + results_dir: /content/drive/MyDrive/mlagents-results +torch_settings: + device: null +debug: false diff --git a/run_logs/Player-0.log b/run_logs/Player-0.log new file mode 100644 index 0000000000000000000000000000000000000000..334f171db7888cd0ae4da9a86e7f44b0c0794df1 --- /dev/null +++ b/run_logs/Player-0.log @@ -0,0 +1,314 @@ +Mono path[0] = '/content/ml-agents/training-envs-executables/linux/Pyramids/Pyramids_Data/Managed' +Mono config path = '/content/ml-agents/training-envs-executables/linux/Pyramids/Pyramids_Data/MonoBleedingEdge/etc' 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conf.c:5208:(_snd_config_evaluate) function snd_func_concat returned error: No such file or directory +ALSA lib confmisc.c:1342:(snd_func_refer) error evaluating name +ALSA lib conf.c:5208:(_snd_config_evaluate) function snd_func_refer returned error: No such file or directory +ALSA lib conf.c:5731:(snd_config_expand) Evaluate error: No such file or directory +ALSA lib pcm.c:2721:(snd_pcm_open_noupdate) Unknown PCM default +FMOD failed to initialize the output device.: "Error initializing output device. 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