Upload . with huggingface_hub
Browse files- .summary/0/events.out.tfevents.1712425402.gpu3.enst.fr +3 -0
- .summary/0/events.out.tfevents.1712425564.gpu3.enst.fr +3 -0
- README.md +38 -43
- checkpoint_p0/best_000000392_401408_reward_180.827.pth +3 -0
- checkpoint_p0/checkpoint_000000929_951296.pth +3 -0
- checkpoint_p0/checkpoint_000000978_1001472.pth +3 -0
- config.json +134 -0
- git.diff +0 -0
- replay.mp4 +0 -0
.summary/0/events.out.tfevents.1712425402.gpu3.enst.fr
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.summary/0/events.out.tfevents.1712425564.gpu3.enst.fr
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version https://git-lfs.github.com/spec/v1
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README.md
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---
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tags:
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- LunarLander-v2
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- ppo
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- deep-reinforcement-learning
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- reinforcement-learning
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-
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- deep-rl-course
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model-index:
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- name:
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results:
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- task:
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type: reinforcement-learning
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type: LunarLander-v2
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metrics:
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- type: mean_reward
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value:
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name: mean_reward
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verified: false
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---
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'minibatch_size': 128}
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```
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-
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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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model-index:
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- name: APPO
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results:
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- task:
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type: reinforcement-learning
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type: LunarLander-v2
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metrics:
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- type: mean_reward
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value: 205.87 +/- 83.70
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name: mean_reward
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verified: false
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---
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A(n) **APPO** model trained on the **LunarLander-v2** 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 NicolasYn/ppo8-LunarLander-v2
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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=LunarLander-v2 --train_dir=./train_dir --experiment=ppo8-LunarLander-v2
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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=LunarLander-v2 --train_dir=./train_dir --experiment=ppo8-LunarLander-v2 --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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checkpoint_p0/best_000000392_401408_reward_180.827.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:e347dae9c7730c291232b6ec35b31aba51e63bb5ac6be1733af49137ee55e5d2
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size 22166443
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checkpoint_p0/checkpoint_000000929_951296.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:82e3381e063960b28c61f79cd703c81278aba020c731118f0fc991fe511d8e5b
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size 22166773
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checkpoint_p0/checkpoint_000000978_1001472.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:016e4060df1b03b5be7051be6323aaea338ce225854a68011b41f85e15bfb0f7
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size 22166773
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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": "LunarLander-v2",
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+
"experiment": "default_experiment",
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+
"train_dir": "./train_dir_LunarLander-v2",
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+
"restart_behavior": "resume",
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+
"device": "gpu",
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+
"seed": null,
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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": 1000,
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+
"num_workers": 8,
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+
"num_envs_per_worker": 4,
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+
"batch_size": 1024,
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+
"num_batches_per_epoch": 1,
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+
"num_epochs": 1,
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+
"rollout": 32,
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+
"recurrence": 32,
|
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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": 0.003,
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+
"value_loss_coeff": 0.5,
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+
"kl_loss_coeff": 0.0,
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+
"exploration_loss": "entropy",
|
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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": true,
|
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+
"normalize_input_keys": null,
|
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+
"decorrelate_experience_max_seconds": 0,
|
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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": false,
|
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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": 1000000,
|
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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_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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+
"adaptive_stddev": true,
|
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+
"continuous_tanh_scale": 0.0,
|
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+
"initial_stddev": 1.0,
|
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+
"use_env_info_cache": false,
|
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+
"env_gpu_actions": false,
|
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+
"env_gpu_observations": true,
|
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+
"env_frameskip": 1,
|
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+
"env_framestack": 1,
|
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+
"pixel_format": "CHW",
|
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+
"use_record_episode_statistics": false,
|
105 |
+
"with_wandb": false,
|
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+
"wandb_user": null,
|
107 |
+
"wandb_project": "sample_factory",
|
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+
"wandb_group": null,
|
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+
"wandb_job_type": "SF",
|
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+
"wandb_tags": [],
|
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+
"with_pbt": false,
|
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+
"pbt_mix_policies_in_one_env": true,
|
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+
"pbt_period_env_steps": 5000000,
|
114 |
+
"pbt_start_mutation": 20000000,
|
115 |
+
"pbt_replace_fraction": 0.3,
|
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+
"pbt_mutation_rate": 0.15,
|
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"pbt_replace_reward_gap": 0.1,
|
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"pbt_replace_reward_gap_absolute": 1e-06,
|
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"pbt_optimize_gamma": false,
|
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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,
|
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+
"command_line": "--env=LunarLander-v2 --num_workers=8 --num_envs_per_worker=4 --train_for_env_steps=10 --train_dir=./train_dir_LunarLander-v2 --log_to_file=False",
|
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+
"cli_args": {
|
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+
"env": "LunarLander-v2",
|
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+
"train_dir": "./train_dir_LunarLander-v2",
|
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+
"num_workers": 8,
|
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+
"num_envs_per_worker": 4,
|
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+
"log_to_file": false,
|
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+
"train_for_env_steps": 10
|
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+
},
|
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+
"git_hash": "unknown",
|
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+
"git_repo_name": "not a git repository"
|
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+
}
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git.diff
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replay.mp4
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