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Upload folder using huggingface_hub

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+ ---
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+ library_name: sample-factory
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+ tags:
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+ - deep-reinforcement-learning
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+ - reinforcement-learning
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+ - sample-factory
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+ ---
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+
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+ A(n) **APPO** model trained on the **GDY-MettaGrid** environment.
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+
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+ This model was trained using Sample-Factory 2.0: https://github.com/alex-petrenko/sample-factory.
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+ Documentation for how to use Sample-Factory can be found at https://www.samplefactory.dev/
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+
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+
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+ ## Downloading the model
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+
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+ After installing Sample-Factory, download the model with:
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+ ```
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+ python -m sample_factory.huggingface.load_from_hub -r metta-ai/baseline.v0.5.6
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+ ```
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+
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+
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+ ## Using the model
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+
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+ To run the model after download, use the `enjoy` script corresponding to this environment:
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+ ```
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+ python -m <path.to.enjoy.module> --algo=APPO --env=GDY-MettaGrid --train_dir=./train_dir --experiment=baseline.v0.5.6
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+ ```
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+
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+
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+ You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag.
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+ See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
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+
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+ ## Training with this model
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+
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+ To continue training with this model, use the `train` script corresponding to this environment:
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+ ```
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+ python -m <path.to.train.module> --algo=APPO --env=GDY-MettaGrid --train_dir=./train_dir --experiment=baseline.v0.5.6 --restart_behavior=resume --train_for_env_steps=10000000000
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+ ```
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+
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+ Note, you may have to adjust `--train_for_env_steps` to a suitably high number as the experiment will resume at the number of steps it concluded at.
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+ "pbt_perturb_max": 1.5,
127
+ "env_cfg": "{\"name\": \"GDY-MettaGrid\", \"_target_\": \"env.griddly.mettagrid.gym_env.MettaGridGymEnv\", \"max_action_value\": 10, \"hidden_features\": {\"grid_obs\": [\"agent:energy\", \"agent:hp\"]}, \"game\": {\"obs_width\": 11, \"obs_height\": 11, \"max_steps\": 5000, \"tile_size\": 16, \"num_agents\": 20, \"no_energy_steps\": 500, \"objects\": {\"agent\": {\"initial_energy\": 250, \"max_energy\": 250, \"max_inventory\": 5, \"freeze_duration\": 10, \"energy_reward\": false, \"hp\": 1, \"mortal\": false, \"upkeep\": {\"time\": 0, \"shield\": 1}, \"use_cost\": 0}, \"altar\": {\"hp\": 30, \"cooldown\": 2, \"use_cost\": 100}, \"converter\": {\"hp\": 30, \"cooldown\": 2, \"energy_output\": {\"r1\": 50, \"r2\": 10, \"r3\": 1}}, \"generator\": {\"hp\": 30, \"cooldown\": 5, \"initial_resources\": 30, \"use_cost\": 0}, \"wall\": {\"density\": 0.01, \"hp\": 10}}, \"actions\": {\"move\": {\"cost\": 0}, \"rotate\": {\"cost\": 0}, \"jump\": {\"cost\": 3}, \"shield\": {\"cost\": 0}, \"transfer\": {\"cost\": 10}, \"use\": {\"cost\": 0}, \"attack\": {\"cost\": 5, \"damage\": 5}}, \"map\": {\"layout\": {\"rooms_x\": 1, \"rooms_y\": 1, \"rooms\": [[\"base\", \"wild_1\", \"base\"], [\"wild_2\", \"center\", \"wild_2\"], [\"base\", \"wild_1\", \"base\"]]}, \"room\": {\"width\": 25, \"height\": 25, \"num_agents\": 5, \"objects\": {\"agent\": 5, \"altar\": 1, \"converter\": 3, \"generator\": 15, \"wall\": 10}}, \"wild_1\": {\"width\": 10, \"height\": 15, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 1, \"converter\": 1, \"generator\": 5, \"wall\": 5}}, \"wild_2\": {\"width\": 15, \"height\": 10, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 1, \"converter\": 1, \"generator\": 5, \"wall\": 5}}, \"center\": {\"width\": 10, \"height\": 10, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 2, \"converter\": 5, \"generator\": 10, \"wall\": 20}}, \"base\": {\"width\": 15, \"height\": 15, \"border\": 1, \"objects\": {\"agent\": 5, \"altar\": 1, \"converter\": 3, \"generator\": 5, \"wall\": 5}}}}, \"kinship\": {\"team_size\": 1, \"team_reward\": 0}}",
128
+ "agent_cfg": "{\"_target_\": \"agent.metta_agent.MettaAgent\", \"observation_encoders\": {\"grid_obs\": {\"feature_names\": [], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 512, \"layers\": 4}, \"global_vars\": {\"feature_names\": [], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"last_action\": {\"feature_names\": [\"last_action_id\", \"last_action_val\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"last_reward\": {\"feature_names\": [\"last_reward\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"kinship\": {\"feature_names\": [\"kinship\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}}, \"fc\": {\"layers\": 3, \"output_dim\": 512}, \"decoder\": {\"_target_\": \"agent.decoder.Decoder\"}, \"core\": {\"rnn_type\": \"gru\", \"rnn_num_layers\": 1, \"rnn_size\": 512}}",
129
+ "command_line": "--experiment=p2.sf --train_dir=./train_dir/sample_factory --nonlinearity=elu --load_checkpoint_kind=latest --normalize_input=False --seed=0 --with_wandb=True --aux_loss_coeff=0 --recurrence=256 --rollout=256 --value_loss_coeff=0.976 --exploration_loss=symmetric_kl --exploration_loss_coeff=0.002 --policy_initialization=orthogonal --learning_rate=0.0001 --max_policy_lag=50 --batch_size=16384 --decorrelate_experience_max_seconds=150 --train_for_env_steps=9999999999999 --wandb_user=platypus --wandb_project=metta --rnn_type=gru --rnn_num_layers=1 --rnn_size=512 --env=GDY-MettaGrid --env_cfg={\"name\": \"GDY-MettaGrid\", \"_target_\": \"env.griddly.mettagrid.gym_env.MettaGridGymEnv\", \"max_action_value\": 10, \"hidden_features\": {\"grid_obs\": [\"agent:energy\", \"agent:hp\"]}, \"game\": {\"obs_width\": 11, \"obs_height\": 11, \"max_steps\": 5000, \"tile_size\": 16, \"num_agents\": 20, \"no_energy_steps\": 500, \"objects\": {\"agent\": {\"initial_energy\": 250, \"max_energy\": 250, \"max_inventory\": 5, \"freeze_duration\": 10, \"energy_reward\": false, \"hp\": 1, \"mortal\": false, \"upkeep\": {\"time\": 0, \"shield\": 1}, \"use_cost\": 0}, \"altar\": {\"hp\": 30, \"cooldown\": 2, \"use_cost\": 100}, \"converter\": {\"hp\": 30, \"cooldown\": 2, \"energy_output\": 50, \"use_cost\": 0}, \"generator\": {\"hp\": 30, \"cooldown\": 5, \"initial_resources\": 30, \"use_cost\": 0}, \"wall\": {\"density\": 0.01, \"hp\": 10}}, \"actions\": {\"move\": {\"cost\": 0}, \"rotate\": {\"cost\": 0}, \"jump\": {\"cost\": 3}, \"shield\": {\"cost\": 0}, \"drop\": {\"cost\": 1}, \"use\": {\"cost\": 0}, \"attack\": {\"cost\": 5, \"damage\": 5}}, \"map\": {\"layout\": {\"rooms_x\": 1, \"rooms_y\": 1, \"rooms\": [[\"base\", \"wild_1\", \"base\"], [\"wild_2\", \"center\", \"wild_2\"], [\"base\", \"wild_1\", \"base\"]]}, \"room\": {\"width\": 25, \"height\": 25, \"num_agents\": 5, \"objects\": {\"agent\": 5, \"altar\": 1, \"converter\": 3, \"generator\": 15, \"wall\": 10}}, \"wild_1\": {\"width\": 10, \"height\": 15, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 1, \"converter\": 1, \"generator\": 5, \"wall\": 5}}, \"wild_2\": {\"width\": 15, \"height\": 10, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 1, \"converter\": 1, \"generator\": 5, \"wall\": 5}}, \"center\": {\"width\": 10, \"height\": 10, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 2, \"converter\": 5, \"generator\": 10, \"wall\": 20}}, \"base\": {\"width\": 15, \"height\": 15, \"border\": 1, \"objects\": {\"agent\": 5, \"altar\": 1, \"converter\": 3, \"generator\": 5, \"wall\": 5}}}}, \"kinship\": {\"team_size\": 1, \"team_reward\": 0}} --agent_cfg={\"_target_\": \"agent.metta_agent.MettaAgent\", \"observation_encoders\": {\"grid_obs\": {\"feature_names\": [], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 512, \"layers\": 4}, \"global_vars\": {\"feature_names\": [], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"last_action\": {\"feature_names\": [\"last_action_id\", \"last_action_val\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"last_reward\": {\"feature_names\": [\"last_reward\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"kinship\": {\"feature_names\": [\"kinship\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}}, \"fc\": {\"layers\": 3, \"output_dim\": 512}, \"decoder\": {\"_target_\": \"agent.decoder.Decoder\"}, \"core\": {\"rnn_type\": \"gru\", \"rnn_num_layers\": 1, \"rnn_size\": 512}}",
130
+ "cli_args": {
131
+ "env": "GDY-MettaGrid",
132
+ "experiment": "p2.sf",
133
+ "train_dir": "./train_dir/sample_factory",
134
+ "seed": 0,
135
+ "max_policy_lag": 50,
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+ "batch_size": 16384,
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+ "rollout": 256,
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+ "recurrence": 256,
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+ "exploration_loss_coeff": 0.002,
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+ "value_loss_coeff": 0.976,
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+ "aux_loss_coeff": 0.0,
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+ "exploration_loss": "symmetric_kl",
143
+ "learning_rate": 0.0001,
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+ "normalize_input": false,
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+ "decorrelate_experience_max_seconds": 150,
146
+ "train_for_env_steps": 9999999999999,
147
+ "load_checkpoint_kind": "latest",
148
+ "rnn_size": 512,
149
+ "rnn_type": "gru",
150
+ "rnn_num_layers": 1,
151
+ "nonlinearity": "elu",
152
+ "policy_initialization": "orthogonal",
153
+ "with_wandb": true,
154
+ "wandb_user": "platypus",
155
+ "wandb_project": "metta",
156
+ "env_cfg": "{\"name\": \"GDY-MettaGrid\", \"_target_\": \"env.griddly.mettagrid.gym_env.MettaGridGymEnv\", \"max_action_value\": 10, \"hidden_features\": {\"grid_obs\": [\"agent:energy\", \"agent:hp\"]}, \"game\": {\"obs_width\": 11, \"obs_height\": 11, \"max_steps\": 5000, \"tile_size\": 16, \"num_agents\": 20, \"no_energy_steps\": 500, \"objects\": {\"agent\": {\"initial_energy\": 250, \"max_energy\": 250, \"max_inventory\": 5, \"freeze_duration\": 10, \"energy_reward\": false, \"hp\": 1, \"mortal\": false, \"upkeep\": {\"time\": 0, \"shield\": 1}, \"use_cost\": 0}, \"altar\": {\"hp\": 30, \"cooldown\": 2, \"use_cost\": 100}, \"converter\": {\"hp\": 30, \"cooldown\": 2, \"energy_output\": 50, \"use_cost\": 0}, \"generator\": {\"hp\": 30, \"cooldown\": 5, \"initial_resources\": 30, \"use_cost\": 0}, \"wall\": {\"density\": 0.01, \"hp\": 10}}, \"actions\": {\"move\": {\"cost\": 0}, \"rotate\": {\"cost\": 0}, \"jump\": {\"cost\": 3}, \"shield\": {\"cost\": 0}, \"drop\": {\"cost\": 1}, \"use\": {\"cost\": 0}, \"attack\": {\"cost\": 5, \"damage\": 5}}, \"map\": {\"layout\": {\"rooms_x\": 1, \"rooms_y\": 1, \"rooms\": [[\"base\", \"wild_1\", \"base\"], [\"wild_2\", \"center\", \"wild_2\"], [\"base\", \"wild_1\", \"base\"]]}, \"room\": {\"width\": 25, \"height\": 25, \"num_agents\": 5, \"objects\": {\"agent\": 5, \"altar\": 1, \"converter\": 3, \"generator\": 15, \"wall\": 10}}, \"wild_1\": {\"width\": 10, \"height\": 15, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 1, \"converter\": 1, \"generator\": 5, \"wall\": 5}}, \"wild_2\": {\"width\": 15, \"height\": 10, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 1, \"converter\": 1, \"generator\": 5, \"wall\": 5}}, \"center\": {\"width\": 10, \"height\": 10, \"border\": 0, \"objects\": {\"agent\": 0, \"altar\": 2, \"converter\": 5, \"generator\": 10, \"wall\": 20}}, \"base\": {\"width\": 15, \"height\": 15, \"border\": 1, \"objects\": {\"agent\": 5, \"altar\": 1, \"converter\": 3, \"generator\": 5, \"wall\": 5}}}}, \"kinship\": {\"team_size\": 1, \"team_reward\": 0}}",
157
+ "agent_cfg": "{\"_target_\": \"agent.metta_agent.MettaAgent\", \"observation_encoders\": {\"grid_obs\": {\"feature_names\": [], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 512, \"layers\": 4}, \"global_vars\": {\"feature_names\": [], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"last_action\": {\"feature_names\": [\"last_action_id\", \"last_action_val\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"last_reward\": {\"feature_names\": [\"last_reward\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}, \"kinship\": {\"feature_names\": [\"kinship\"], \"normalize_features\": true, \"label_dim\": 4, \"output_dim\": 8, \"layers\": 2}}, \"fc\": {\"layers\": 3, \"output_dim\": 512}, \"decoder\": {\"_target_\": \"agent.decoder.Decoder\"}, \"core\": {\"rnn_type\": \"gru\", \"rnn_num_layers\": 1, \"rnn_size\": 512}}"
158
+ },
159
+ "git_hash": "791254b53964aa5fac266afe404e2350c892c122",
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+ "git_repo_name": "https://github.com/daveey/metta.git",
161
+ "wandb_unique_id": "p2.sf_20240627_104843_316597"
162
+ }
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