Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- .summary/0/events.out.tfevents.1710999906.4346465a7ed9 +3 -0
- .summary/0/events.out.tfevents.1710999960.4346465a7ed9 +3 -0
- .summary/0/events.out.tfevents.1711040813.4346465a7ed9 +3 -0
- .summary/0/events.out.tfevents.1711043187.4346465a7ed9 +3 -0
- README.md +42 -0
- checkpoint_p0/best_000043592_1428422656_reward_1.939.pth +3 -0
- checkpoint_p0/checkpoint_000059740_1957560320.pth +3 -0
- checkpoint_p0/checkpoint_000059893_1962573824.pth +3 -0
- config.json +319 -0
- git.diff +7 -0
- replay.mp4 +3 -0
- sf_log.txt +0 -0
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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replay.mp4 filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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| 2 |
+
library_name: sample-factory
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| 3 |
+
tags:
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| 4 |
+
- deep-reinforcement-learning
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| 5 |
+
- reinforcement-learning
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| 6 |
+
- sample-factory
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| 7 |
+
---
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| 8 |
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| 9 |
+
A(n) **APPO** model trained on the **GDY-PowerGrid** environment.
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| 10 |
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| 11 |
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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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| 13 |
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| 14 |
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| 15 |
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## Downloading the model
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| 16 |
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| 17 |
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After installing Sample-Factory, download the model with:
|
| 18 |
+
```
|
| 19 |
+
python -m sample_factory.huggingface.load_from_hub -r daveey/metta
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| 20 |
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```
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| 21 |
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| 22 |
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|
| 23 |
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## Using the model
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| 24 |
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| 25 |
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To run the model after download, use the `enjoy` script corresponding to this environment:
|
| 26 |
+
```
|
| 27 |
+
python -m <path.to.enjoy.module> --algo=APPO --env=GDY-PowerGrid --train_dir=./train_dir --experiment=metta
|
| 28 |
+
```
|
| 29 |
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|
| 30 |
+
|
| 31 |
+
You can also upload models to the Hugging Face Hub using the same script with the `--push_to_hub` flag.
|
| 32 |
+
See https://www.samplefactory.dev/10-huggingface/huggingface/ for more details
|
| 33 |
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|
| 34 |
+
## Training with this model
|
| 35 |
+
|
| 36 |
+
To continue training with this model, use the `train` script corresponding to this environment:
|
| 37 |
+
```
|
| 38 |
+
python -m <path.to.train.module> --algo=APPO --env=GDY-PowerGrid --train_dir=./train_dir --experiment=metta --restart_behavior=resume --train_for_env_steps=10000000000
|
| 39 |
+
```
|
| 40 |
+
|
| 41 |
+
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.
|
| 42 |
+
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checkpoint_p0/best_000043592_1428422656_reward_1.939.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:7baf6f06a38c1c2b20505833750d6306c0ae317135d76eb2fee252d336b7a573
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size 79628218
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checkpoint_p0/checkpoint_000059740_1957560320.pth
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version https://git-lfs.github.com/spec/v1
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size 79629212
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checkpoint_p0/checkpoint_000059893_1962573824.pth
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version https://git-lfs.github.com/spec/v1
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size 79629212
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config.json
ADDED
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|
| 1 |
+
{
|
| 2 |
+
"help": false,
|
| 3 |
+
"algo": "APPO",
|
| 4 |
+
"env": "GDY-PowerGrid",
|
| 5 |
+
"experiment": "p2.objt_atn.4",
|
| 6 |
+
"train_dir": "/workspace/metta/train_dir",
|
| 7 |
+
"restart_behavior": "resume",
|
| 8 |
+
"device": "gpu",
|
| 9 |
+
"seed": null,
|
| 10 |
+
"num_policies": 1,
|
| 11 |
+
"async_rl": true,
|
| 12 |
+
"serial_mode": false,
|
| 13 |
+
"batched_sampling": false,
|
| 14 |
+
"num_batches_to_accumulate": 2,
|
| 15 |
+
"worker_num_splits": 2,
|
| 16 |
+
"policy_workers_per_policy": 1,
|
| 17 |
+
"max_policy_lag": 20000,
|
| 18 |
+
"num_workers": 50,
|
| 19 |
+
"num_envs_per_worker": 2,
|
| 20 |
+
"batch_size": 32768,
|
| 21 |
+
"num_batches_per_epoch": 1,
|
| 22 |
+
"num_epochs": 1,
|
| 23 |
+
"rollout": 256,
|
| 24 |
+
"recurrence": 256,
|
| 25 |
+
"shuffle_minibatches": false,
|
| 26 |
+
"gamma": 0.99,
|
| 27 |
+
"reward_scale": 1.0,
|
| 28 |
+
"reward_clip": 1000.0,
|
| 29 |
+
"value_bootstrap": false,
|
| 30 |
+
"normalize_returns": true,
|
| 31 |
+
"exploration_loss_coeff": 0.002,
|
| 32 |
+
"value_loss_coeff": 0.976,
|
| 33 |
+
"kl_loss_coeff": 0.0,
|
| 34 |
+
"aux_loss_coeff": 0.0,
|
| 35 |
+
"exploration_loss": "symmetric_kl",
|
| 36 |
+
"gae_lambda": 0.95,
|
| 37 |
+
"ppo_clip_ratio": 0.1,
|
| 38 |
+
"ppo_clip_value": 1.0,
|
| 39 |
+
"with_vtrace": false,
|
| 40 |
+
"vtrace_rho": 1.0,
|
| 41 |
+
"vtrace_c": 1.0,
|
| 42 |
+
"optimizer": "adam",
|
| 43 |
+
"adam_eps": 1e-06,
|
| 44 |
+
"adam_beta1": 0.9,
|
| 45 |
+
"adam_beta2": 0.999,
|
| 46 |
+
"max_grad_norm": 4.0,
|
| 47 |
+
"learning_rate": 0.0001,
|
| 48 |
+
"lr_schedule": "constant",
|
| 49 |
+
"lr_schedule_kl_threshold": 0.008,
|
| 50 |
+
"lr_adaptive_min": 1e-06,
|
| 51 |
+
"lr_adaptive_max": 0.01,
|
| 52 |
+
"obs_subtract_mean": 0.0,
|
| 53 |
+
"obs_scale": 1.0,
|
| 54 |
+
"normalize_input": true,
|
| 55 |
+
"normalize_input_keys": null,
|
| 56 |
+
"decorrelate_experience_max_seconds": 150,
|
| 57 |
+
"decorrelate_envs_on_one_worker": true,
|
| 58 |
+
"actor_worker_gpus": [],
|
| 59 |
+
"set_workers_cpu_affinity": true,
|
| 60 |
+
"force_envs_single_thread": false,
|
| 61 |
+
"default_niceness": 0,
|
| 62 |
+
"log_to_file": true,
|
| 63 |
+
"experiment_summaries_interval": 10,
|
| 64 |
+
"flush_summaries_interval": 30,
|
| 65 |
+
"stats_avg": 100,
|
| 66 |
+
"summaries_use_frameskip": true,
|
| 67 |
+
"heartbeat_interval": 20,
|
| 68 |
+
"heartbeat_reporting_interval": 180,
|
| 69 |
+
"train_for_env_steps": 10000000000,
|
| 70 |
+
"train_for_seconds": 10000000000,
|
| 71 |
+
"save_every_sec": 120,
|
| 72 |
+
"keep_checkpoints": 2,
|
| 73 |
+
"load_checkpoint_path": null,
|
| 74 |
+
"init_checkpoint_path": "train_dir/p2.objt_atn.3/checkpoint_p0/checkpoint_000046241_1515225088.pth",
|
| 75 |
+
"load_checkpoint_kind": "latest",
|
| 76 |
+
"save_milestones_sec": -1,
|
| 77 |
+
"save_best_every_sec": 5,
|
| 78 |
+
"save_best_metric": "reward",
|
| 79 |
+
"save_best_after": 100000,
|
| 80 |
+
"benchmark": false,
|
| 81 |
+
"encoder_mlp_layers": [
|
| 82 |
+
512,
|
| 83 |
+
512
|
| 84 |
+
],
|
| 85 |
+
"encoder_conv_architecture": "convnet_simple",
|
| 86 |
+
"encoder_conv_mlp_layers": [
|
| 87 |
+
512
|
| 88 |
+
],
|
| 89 |
+
"use_rnn": true,
|
| 90 |
+
"rnn_size": 512,
|
| 91 |
+
"rnn_type": "gru",
|
| 92 |
+
"rnn_num_layers": 1,
|
| 93 |
+
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|
| 250 |
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|
| 251 |
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| 252 |
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|
| 254 |
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|
| 255 |
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|
| 256 |
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"command_line": "--algo=APPO --env=GDY-PowerGrid --with_wandb=True --num_workers=25 --env_num_agents=5 --env_width=20:40 --env_height=20:40 --env_num_altars=1:5 --env_num_chargers=1:5 --env_num_generators=5:20 --env_wall_density=0:0.15 --env_reward_rank_steps=10 --agent_fc_layers=3 --agent_fc_size=512 --agent_embedding_size=64 --agent_embedding_layers=3 --agent_attention_size=512 --agent_attention_layers=2 --rnn_num_layers=2 --rnn_size=512 --rnn_type=gru --rollout=256 --batch_size=65536 --decorrelate_experience_max_seconds=150 --value_loss_coeff=0.976 --exploration_loss=symmetric_kl --exploration_loss_coeff=0.002 --policy_initialization=orthogonal --learning_rate=0.0001 --max_policy_lag=2000 --nonlinearity=elu --normalize_input=True --env_width=100 --env_height=100 --env_num_agents=100 --env_num_altars=20 --env_num_chargers=30 --env_num_generators=200 --env_wall_density=0.01 --env_reward_rank_steps=1000 --env_altar:cost=100 --env_reward_prestige_weight=0 --env_cost:shield=0 --agent_fc_layers=4 --agent_fc_size=512 --rnn_num_layers=1 --rnn_size=512 --rnn_type=gru --max_policy_lag=20000 --experiment=p2.objt_atn.4 --num_workers=50 --batch_size=32768 --init_checkpoint_path=workspace/metta/train_dir/p2.objt_atn.3/checkpoint_p0/checkpoint_000046241_1515225088.pth",
|
| 257 |
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"cli_args": {
|
| 258 |
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"algo": "APPO",
|
| 259 |
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"env": "GDY-PowerGrid",
|
| 260 |
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"experiment": "p2.objt_atn.4",
|
| 261 |
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"max_policy_lag": 20000,
|
| 262 |
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|
| 263 |
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"batch_size": 32768,
|
| 264 |
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"rollout": 256,
|
| 265 |
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"exploration_loss_coeff": 0.002,
|
| 266 |
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"value_loss_coeff": 0.976,
|
| 267 |
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"exploration_loss": "symmetric_kl",
|
| 268 |
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"learning_rate": 0.0001,
|
| 269 |
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"normalize_input": true,
|
| 270 |
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"decorrelate_experience_max_seconds": 150,
|
| 271 |
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"init_checkpoint_path": "workspace/metta/train_dir/p2.objt_atn.3/checkpoint_p0/checkpoint_000046241_1515225088.pth",
|
| 272 |
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"rnn_size": 512,
|
| 273 |
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"rnn_type": "gru",
|
| 274 |
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"rnn_num_layers": 1,
|
| 275 |
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"nonlinearity": "elu",
|
| 276 |
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"policy_initialization": "orthogonal",
|
| 277 |
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"with_wandb": true,
|
| 278 |
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|
| 279 |
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|
| 280 |
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100.0
|
| 281 |
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],
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],
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| 291 |
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|
| 293 |
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],
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| 294 |
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|
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],
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| 300 |
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],
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| 310 |
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| 311 |
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},
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"git_hash": "960abca49c3c941d43bcf65df909840ad43c6156",
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| 317 |
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"git_repo_name": "https://github.com/daveey/metta.git",
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| 318 |
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"wandb_unique_id": "p2.objt_atn.4_20240320_224453_910734"
|
| 319 |
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}
|
git.diff
ADDED
|
@@ -0,0 +1,7 @@
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|
|
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|
|
|
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|
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|
| 1 |
+
diff --git a/third_party/griddly b/third_party/griddly
|
| 2 |
+
index caf0179..67717ea 160000
|
| 3 |
+
--- a/third_party/griddly
|
| 4 |
+
+++ b/third_party/griddly
|
| 5 |
+
@@ -1 +1 @@
|
| 6 |
+
-Subproject commit caf0179c470084f7c236eee5f4b1eee6634f2351
|
| 7 |
+
+Subproject commit 67717ea344e2ffda18e063e8a13a8709bf0ff3e3
|
replay.mp4
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
|
|
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|
|
|
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|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:dd1990715c9f955fcf319fadf9ff98c8f8da6629ce8c4162e955accc80be0cb4
|
| 3 |
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size 4210290
|
sf_log.txt
ADDED
|
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|
|
|