Upload folder using huggingface_hub
Browse files- .gitattributes +5 -0
- .summary/0/events.out.tfevents.1717635033.4a1f19113fa6 +3 -0
- .summary/0/events.out.tfevents.1717700366.c11948e043d9 +3 -0
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- README.md +42 -0
- a100_100x100.mp4 +3 -0
- a20_40x40.mp4 +3 -0
- a20_b4_40x40.mp4 +3 -0
- a20_r4_40x40.mp4 +3 -0
- a5_25x25.mp4 +0 -0
- checkpoint_p0/best_000048446_793739264_reward_0.336.pth +3 -0
- checkpoint_p0/checkpoint_000051451_842973184.pth +3 -0
- checkpoint_p0/checkpoint_000051776_848297984.pth +3 -0
- config.json +161 -0
- git.diff +0 -0
- replay.mp4 +3 -0
- sf_log.txt +0 -0
.gitattributes
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README.md
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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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A(n) **APPO** model trained on the **GDY-MettaGrid** environment.
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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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## Downloading the model
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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.v0.2.1
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```
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## Using the model
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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.v0.2.1
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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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## Training with this model
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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.v0.2.1 --restart_behavior=resume --train_for_env_steps=10000000000
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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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a100_100x100.mp4
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config.json
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{
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"help": false,
|
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"algo": "APPO",
|
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"env": "GDY-MettaGrid",
|
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"experiment": "p2.metta.4",
|
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"train_dir": "/workspace/metta/train_dir",
|
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"restart_behavior": "resume",
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"device": "gpu",
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"seed": 0,
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"num_policies": 1,
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"async_rl": true,
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"serial_mode": false,
|
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"batched_sampling": false,
|
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"num_batches_to_accumulate": 2,
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"worker_num_splits": 2,
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"policy_workers_per_policy": 1,
|
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"max_policy_lag": 50,
|
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"num_workers": 32,
|
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"num_envs_per_worker": 2,
|
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"batch_size": 16384,
|
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"num_batches_per_epoch": 1,
|
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"num_epochs": 1,
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"rollout": 256,
|
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"recurrence": 256,
|
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"shuffle_minibatches": false,
|
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"gamma": 0.99,
|
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"reward_scale": 1.0,
|
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"reward_clip": 1000.0,
|
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"value_bootstrap": false,
|
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"normalize_returns": true,
|
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"exploration_loss_coeff": 0.002,
|
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"value_loss_coeff": 0.976,
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"kl_loss_coeff": 0.0,
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"aux_loss_coeff": 0.0,
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"exploration_loss": "symmetric_kl",
|
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"gae_lambda": 0.95,
|
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"ppo_clip_ratio": 0.1,
|
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"ppo_clip_value": 1.0,
|
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"with_vtrace": false,
|
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"vtrace_rho": 1.0,
|
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"vtrace_c": 1.0,
|
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"optimizer": "adam",
|
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"adam_eps": 1e-06,
|
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"adam_beta1": 0.9,
|
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"adam_beta2": 0.999,
|
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"max_grad_norm": 4.0,
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"learning_rate": 0.0001,
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"lr_schedule": "constant",
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"lr_schedule_kl_threshold": 0.008,
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"lr_adaptive_min": 1e-06,
|
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"lr_adaptive_max": 0.01,
|
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"obs_subtract_mean": 0.0,
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"obs_scale": 1.0,
|
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"normalize_input": false,
|
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"normalize_input_keys": null,
|
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"decorrelate_experience_max_seconds": 150,
|
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"decorrelate_envs_on_one_worker": true,
|
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"actor_worker_gpus": [],
|
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"set_workers_cpu_affinity": true,
|
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"force_envs_single_thread": false,
|
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"default_niceness": 0,
|
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"log_to_file": true,
|
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"experiment_summaries_interval": 10,
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"flush_summaries_interval": 30,
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"stats_avg": 100,
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"summaries_use_frameskip": true,
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"heartbeat_interval": 20,
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"heartbeat_reporting_interval": 180,
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"train_for_env_steps": 9999999999999,
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"train_for_seconds": 10000000000,
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"save_every_sec": 120,
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"keep_checkpoints": 2,
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"load_checkpoint_path": null,
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"init_checkpoint_path": null,
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"load_checkpoint_kind": "latest",
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"save_milestones_sec": -1,
|
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"save_best_every_sec": 5,
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"save_best_metric": "reward",
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"save_best_after": 100000,
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"benchmark": false,
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"encoder_mlp_layers": [
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512,
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512
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],
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"encoder_conv_architecture": "convnet_simple",
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"encoder_conv_mlp_layers": [
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512
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],
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"use_rnn": true,
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"rnn_size": 512,
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"rnn_type": "gru",
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"rnn_num_layers": 1,
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"decoder_mlp_layers": [],
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"nonlinearity": "elu",
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"policy_initialization": "orthogonal",
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"policy_init_gain": 1.0,
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"actor_critic_share_weights": true,
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|
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"pbt_replace_reward_gap_absolute": 1e-06,
|
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|
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"pbt_target_objective": "true_objective",
|
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"pbt_perturb_min": 1.1,
|
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"pbt_perturb_max": 1.5,
|
127 |
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"env_cfg": "{\"name\": \"GDY-MettaGrid\", \"_target_\": \"env.griddly.mettagrid.gym_env.MettaGridGymEnv\", \"max_action_value\": 10, \"game_builder\": {\"_target_\": \"env.griddly.mettagrid.game_builder.MettaGridGameBuilder\", \"obs_width\": 11, \"obs_height\": 11, \"max_steps\": 1000, \"tile_size\": 16, \"num_agents\": 20, \"objects\": {\"agent\": {\"initial_energy\": 100, \"max_energy\": 500, \"max_inventory\": 5, \"freeze_duration\": 10, \"hp\": 1, \"upkeep\": {\"shield\": 1}}, \"altar\": {\"hp\": 30, \"cooldown\": 2, \"cost\": 100}, \"converter\": {\"hp\": 30, \"cooldown\": 2, \"energy_output\": 50, \"cost\": 0}, \"generator\": {\"hp\": 30, \"cooldown\": 5, \"initial_resources\": 30, \"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\": [[\"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}}}}}",
|
128 |
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"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}}, \"fc\": {\"layers\": 3, \"output_dim\": 512}, \"decoder\": {\"_target_\": \"agent.decoder.Decoder\"}, \"core\": {\"_target_\": \"sample_factory.model.core.ModelCoreRNN\", \"rnn_type\": \"gru\", \"rnn_num_layers\": 1, \"rnn_size\": 512}}",
|
129 |
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"command_line": "--aux_loss_coef=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 --nonlinearity=elu --load_checkpoint_kind=latest --normalize_input=False --seed=0 --batch_size=16384 --decorrelate_experience_max_seconds=150 --train_for_env_steps=9999999999999 --with_wandb=True --wandb_user=platypus --wandb_project=metta --experiment=p2.metta.4 --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\", \"game_builder\": {\"_target_\": \"env.griddly.mettagrid.game_builder.MettaGridGameBuilder\", \"obs_width\": 11, \"obs_height\": 11, \"max_steps\": 1000, \"tile_size\": 16, \"width\": 40, \"height\": 40, \"objects\": {\"agent\": {\"count\": 20, \"initial_energy\": 100, \"max_energy\": 500, \"max_inventory\": 5, \"freeze_duration\": 10, \"hp\": 1, \"upkeep\": {\"shield\": 1}}, \"altar\": {\"hp\": 30, \"count\": 5, \"cooldown\": 2, \"cost\": 100}, \"converter\": {\"hp\": 30, \"count\": 10, \"cooldown\": 2, \"energy_output\": 50, \"cost\": 0}, \"generator\": {\"hp\": 30, \"count\": 50, \"cooldown\": 50, \"initial_resources\": 100, \"cost\": 0}, \"wall\": {\"density\": 0.01, \"hp\": 10}, \"charger\": {\"count\": 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}}}, \"global_features\": [\"conf:agent:energy:initial\", \"conf:agent:energy:max\", \"conf:altar:cooldown\", \"conf:altar:cost\", \"conf:attack:damage\", \"conf:attack:freeze_duration\", \"conf:charger:cooldown\", \"conf:charger:energy\", \"conf:cost:attack\", \"conf:cost:frozen\", \"conf:cost:jump\", \"conf:cost:move\", \"conf:cost:rotate\", \"conf:cost:shield:upkeep\", \"conf:cost:shield\", \"conf:generator:cooldown\", \"conf:gift:energy\"], \"grid_features\": [\"agent\", \"altar\", \"charger\", \"generator\", \"wall\", \"agent:dir\", \"agent:energy\", \"agent:frozen\", \"agent:id\", \"agent:inv:1\", \"agent:inv:2\", \"agent:inv:3\", \"agent:shield\", \"agent:species\", \"altar:ready\", \"charger:bonus\", \"charger:input:1\", \"charger:input:2\", \"charger:input:3\", \"charger:output\", \"charger:ready\", \"generator:ready\", \"generator:resource\"], \"actions\": [\"rotate\", \"move\", \"jump\", \"use\", \"gift\", \"shield\", \"attack\"], \"max_action_value\": 10} --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}}, \"fc\": {\"layers\": 3, \"output_dim\": 512}, \"decoder\": {\"_target_\": \"agent.decoder.Decoder\"}, \"core\": {\"_target_\": \"sample_factory.model.core.ModelCoreRNN\", \"rnn_type\": \"gru\", \"rnn_num_layers\": 1, \"rnn_size\": 512}}",
|
130 |
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"cli_args": {
|
131 |
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"env": "GDY-MettaGrid",
|
132 |
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"experiment": "p2.metta.4",
|
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"seed": 0,
|
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"max_policy_lag": 50,
|
135 |
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"batch_size": 16384,
|
136 |
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"rollout": 256,
|
137 |
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"recurrence": 256,
|
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"exploration_loss_coeff": 0.002,
|
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"value_loss_coeff": 0.976,
|
140 |
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"aux_loss_coeff": 0.0,
|
141 |
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"exploration_loss": "symmetric_kl",
|
142 |
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"learning_rate": 0.0001,
|
143 |
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"normalize_input": false,
|
144 |
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"decorrelate_experience_max_seconds": 150,
|
145 |
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"train_for_env_steps": 9999999999999,
|
146 |
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"load_checkpoint_kind": "latest",
|
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"rnn_size": 512,
|
148 |
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"rnn_type": "gru",
|
149 |
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"rnn_num_layers": 1,
|
150 |
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"nonlinearity": "elu",
|
151 |
+
"policy_initialization": "orthogonal",
|
152 |
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"with_wandb": true,
|
153 |
+
"wandb_user": "platypus",
|
154 |
+
"wandb_project": "metta",
|
155 |
+
"env_cfg": "{\"name\": \"GDY-MettaGrid\", \"_target_\": \"env.griddly.mettagrid.gym_env.MettaGridGymEnv\", \"game_builder\": {\"_target_\": \"env.griddly.mettagrid.game_builder.MettaGridGameBuilder\", \"obs_width\": 11, \"obs_height\": 11, \"max_steps\": 1000, \"tile_size\": 16, \"width\": 40, \"height\": 40, \"objects\": {\"agent\": {\"count\": 20, \"initial_energy\": 100, \"max_energy\": 500, \"max_inventory\": 5, \"freeze_duration\": 10, \"hp\": 1, \"upkeep\": {\"shield\": 1}}, \"altar\": {\"hp\": 30, \"count\": 5, \"cooldown\": 2, \"cost\": 100}, \"converter\": {\"hp\": 30, \"count\": 10, \"cooldown\": 2, \"energy_output\": 50, \"cost\": 0}, \"generator\": {\"hp\": 30, \"count\": 50, \"cooldown\": 50, \"initial_resources\": 100, \"cost\": 0}, \"wall\": {\"density\": 0.01, \"hp\": 10}, \"charger\": {\"count\": 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}}}, \"global_features\": [\"conf:agent:energy:initial\", \"conf:agent:energy:max\", \"conf:altar:cooldown\", \"conf:altar:cost\", \"conf:attack:damage\", \"conf:attack:freeze_duration\", \"conf:charger:cooldown\", \"conf:charger:energy\", \"conf:cost:attack\", \"conf:cost:frozen\", \"conf:cost:jump\", \"conf:cost:move\", \"conf:cost:rotate\", \"conf:cost:shield:upkeep\", \"conf:cost:shield\", \"conf:generator:cooldown\", \"conf:gift:energy\"], \"grid_features\": [\"agent\", \"altar\", \"charger\", \"generator\", \"wall\", \"agent:dir\", \"agent:energy\", \"agent:frozen\", \"agent:id\", \"agent:inv:1\", \"agent:inv:2\", \"agent:inv:3\", \"agent:shield\", \"agent:species\", \"altar:ready\", \"charger:bonus\", \"charger:input:1\", \"charger:input:2\", \"charger:input:3\", \"charger:output\", \"charger:ready\", \"generator:ready\", \"generator:resource\"], \"actions\": [\"rotate\", \"move\", \"jump\", \"use\", \"gift\", \"shield\", \"attack\"], \"max_action_value\": 10}",
|
156 |
+
"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}}, \"fc\": {\"layers\": 3, \"output_dim\": 512}, \"decoder\": {\"_target_\": \"agent.decoder.Decoder\"}, \"core\": {\"_target_\": \"sample_factory.model.core.ModelCoreRNN\", \"rnn_type\": \"gru\", \"rnn_num_layers\": 1, \"rnn_size\": 512}}"
|
157 |
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},
|
158 |
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"git_hash": "7864b034e8faa45a8cef257cdd0b4d3b2b2549f3",
|
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"git_repo_name": "https://github.com/daveey/metta.git",
|
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"wandb_unique_id": "p2.metta.4_20240605_175031_058004"
|
161 |
+
}
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sf_log.txt
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