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rgtjf
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ppo-Pyramids

Reinforcement Learning
ml-agents
TensorBoard
ONNX
Pyramids
deep-reinforcement-learning
ML-Agents-Pyramids
Model card Files Metrics Community
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  1. Pyramids.onnx +3 -0
  2. Pyramids/Pyramids-0.onnx +3 -0
  3. Pyramids/Pyramids-0.pt +3 -0
  4. Pyramids/Pyramids-1000091.onnx +3 -0
  5. Pyramids/Pyramids-1000091.pt +3 -0
  6. Pyramids/Pyramids-24192.pt +3 -0
  7. Pyramids/Pyramids-499906.onnx +3 -0
  8. Pyramids/Pyramids-499906.pt +3 -0
  9. Pyramids/Pyramids-999963.onnx +3 -0
  10. Pyramids/Pyramids-999963.pt +3 -0
  11. Pyramids/checkpoint.pt +3 -0
  12. Pyramids/events.out.tfevents.1729237815.dsw-149305-7f99dc7665-w7zmb.427572.0 +3 -0
  13. README.md +35 -0
  14. config.json +1 -0
  15. configuration.yaml +92 -0
  16. run_logs/Player-0.log +869 -0
  17. run_logs/timers.json +624 -0
  18. run_logs/training_status.json +47 -0
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README.md ADDED
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+ ---
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+ library_name: ml-agents
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+ tags:
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+ - Pyramids
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+ - deep-reinforcement-learning
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+ - reinforcement-learning
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+ - ML-Agents-Pyramids
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+ ---
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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**
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+ using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
13
+
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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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+
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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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+
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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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+
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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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+
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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: rgtjf/ppo-Pyramids
33
+ 3. Step 2: Select your *.nn /*.onnx file
34
+ 4. Click on Watch the agent play 👀
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+
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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, "shared_critic": false, "learning_rate_schedule": "linear", "beta_schedule": "linear", "epsilon_schedule": "linear"}, "checkpoint_interval": 500000, "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, "even_checkpoints": false, "max_steps": 1000000, "time_horizon": 128, "summary_freq": 30000, "threaded": false, "self_play": null, "behavioral_cloning": null}}, "env_settings": {"env_path": "./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": "Pyramids Training", "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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+ 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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+ 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: 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: 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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+ even_checkpoints: false
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+ max_steps: 1000000
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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: ./training-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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+ 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: 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: true
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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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270
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272
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273
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274
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280
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293
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294
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299
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300
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308
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311
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313
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314
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316
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317
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318
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322
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328
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333
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383
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385
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387
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390
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392
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402
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432
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433
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438
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452
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453
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454
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463
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472
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473
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474
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475
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476
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477
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478
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479
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482
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483
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487
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488
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489
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492
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493
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494
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497
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499
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503
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504
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508
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509
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510
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512
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513
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517
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518
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519
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522
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523
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527
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528
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530
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531
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532
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533
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534
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536
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537
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538
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541
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542
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543
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547
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548
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549
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552
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553
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554
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557
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558
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559
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560
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562
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563
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564
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565
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566
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567
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568
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569
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570
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572
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573
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574
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576
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577
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578
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579
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581
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582
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583
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584
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585
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586
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587
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588
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589
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592
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593
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594
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597
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598
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600
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602
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603
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604
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607
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608
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609
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610
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611
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612
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613
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614
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615
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616
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617
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618
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619
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620
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621
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622
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623
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624
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625
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626
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627
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628
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629
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630
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631
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632
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633
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634
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635
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637
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638
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639
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640
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641
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642
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643
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644
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645
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647
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648
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649
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650
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651
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652
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653
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654
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657
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658
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659
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660
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662
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663
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664
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665
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667
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668
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669
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670
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672
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673
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674
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675
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677
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678
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679
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680
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682
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683
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684
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685
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687
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688
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689
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690
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692
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693
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694
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695
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697
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698
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699
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700
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701
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702
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703
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704
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705
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706
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707
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708
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709
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710
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711
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712
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713
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714
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715
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716
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717
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718
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719
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720
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721
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722
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723
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724
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725
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726
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727
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728
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729
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730
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731
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732
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733
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734
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735
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736
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737
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738
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739
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740
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741
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742
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743
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