kingabzpro
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First Pyramids
Browse files- README.md +31 -0
- config.json +1 -0
- configuration.yaml +88 -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-Pyramids
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library_name: ml-agents
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---
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# **ppo** Agent playing **Pyramids**
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This is a trained model of a **ppo** agent playing **Pyramids** 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-Pyramids
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2. Step 1: Write your model_id: kingabzpro/MLAgents-Pyramids2
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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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config.json
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{"default_settings": null, "behaviors": {"Pyramids": {"trainer_type": "ppo", "hyperparameters": {"batch_size": 128, "buffer_size": 2048, "learning_rate": 0.0003, "beta": 0.01, "epsilon": 0.2, "lambd": 0.95, "num_epoch": 3, "learning_rate_schedule": "linear", "beta_schedule": "linear", "epsilon_schedule": "linear"}, "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": 5, "checkpoint_interval": 500000, "max_steps": 3000000, "time_horizon": 128, "summary_freq": 30000, "threaded": false, "self_play": null, "behavioral_cloning": null}}, "env_settings": {"env_path": "./trained-envs-executables/linux/Pyramids/Pyramids", "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": "Pyramids Training", "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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Pyramids:
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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: 0.01
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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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learning_rate_schedule: linear
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beta_schedule: linear
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epsilon_schedule: linear
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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: 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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rnd:
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gamma: 0.99
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strength: 0.01
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network_settings:
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normalize: false
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hidden_units: 64
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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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learning_rate: 0.0001
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encoding_size: null
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init_path: null
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keep_checkpoints: 5
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checkpoint_interval: 500000
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max_steps: 3000000
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time_horizon: 128
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summary_freq: 30000
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threaded: false
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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: ./trained-envs-executables/linux/Pyramids/Pyramids
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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
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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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environment_parameters: null
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checkpoint_settings:
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run_id: Pyramids Training
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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/timers.json
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{
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"name": "root",
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"metadata": {
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"timer_format_version": "0.1.0",
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"start_time_seconds": "1656922304",
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"python_version": "3.7.13 (default, Apr 24 2022, 01:04:09) \n[GCC 7.5.0]",
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"command_line_arguments": "/usr/local/bin/mlagents-learn ./config/ppo/PyramidsRND.yaml --env=./trained-envs-executables/linux/Pyramids/Pyramids --run-id=Pyramids Training --no-graphics",
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"mlagents_version": "0.29.0.dev0",
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"mlagents_envs_version": "0.29.0.dev0",
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"communication_protocol_version": "1.5.0",
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"pytorch_version": "1.8.1+cu102",
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"numpy_version": "1.21.6",
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"end_time_seconds": "1656922304"
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},
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"total": 0.11301503400000001,
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"count": 1,
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"self": 0.01059058200007712,
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"children": {
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"run_training.setup": {
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"total": 0.047670905999893876,
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"count": 1,
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"self": 0.047670905999893876
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},
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"TrainerController.start_learning": {
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"total": 0.05475354600002902,
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"count": 1,
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"self": 0.00044866699954582145,
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"children": {
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"TrainerController._reset_env": {
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"total": 0.05428869100023803,
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"count": 1,
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"self": 0.05428869100023803
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},
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"trainer_threads": {
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"total": 1.9120002434647176e-06,
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"count": 1,
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"self": 1.9120002434647176e-06
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},
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"TrainerController._save_models": {
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"total": 1.4276000001700595e-05,
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"count": 1,
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"self": 1.4276000001700595e-05
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}
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}
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}
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}
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}
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run_logs/training_status.json
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{
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"metadata": {
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"stats_format_version": "0.3.0",
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"mlagents_version": "0.29.0.dev0",
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"torch_version": "1.8.1+cu102"
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}
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}
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