Initial commit

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,69 @@
+---
+library_name: stable-baselines3
+tags:
+- Pendulum-v1
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: SAC
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: Pendulum-v1
+      type: Pendulum-v1
+    metrics:
+    - type: mean_reward
+      value: -185.45 +/- 109.81
+      name: mean_reward
+      verified: false
+---
+
+# **SAC** Agent playing **Pendulum-v1**
+This is a trained model of a **SAC** agent playing **Pendulum-v1**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
+and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
+
+The RL Zoo is a training framework for Stable Baselines3
+reinforcement learning agents,
+with hyperparameter optimization and pre-trained agents included.
+
+## Usage (with SB3 RL Zoo)
+
+RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
+SB3: https://github.com/DLR-RM/stable-baselines3<br/>
+SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
+
+Install the RL Zoo (with SB3 and SB3-Contrib):
+```bash
+pip install rl_zoo3
+```
+
+```
+# Download model and save it into the logs/ folder
+python -m rl_zoo3.load_from_hub --algo sac --env Pendulum-v1 -orga qgallouedec -f logs/
+python -m rl_zoo3.enjoy --algo sac --env Pendulum-v1  -f logs/
+```
+
+If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
+```
+python -m rl_zoo3.load_from_hub --algo sac --env Pendulum-v1 -orga qgallouedec -f logs/
+python -m rl_zoo3.enjoy --algo sac --env Pendulum-v1  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python -m rl_zoo3.train --algo sac --env Pendulum-v1 -f logs/
+# Upload the model and generate video (when possible)
+python -m rl_zoo3.push_to_hub --algo sac --env Pendulum-v1 -f logs/ -orga qgallouedec
+```
+
+## Hyperparameters
+```python
+OrderedDict([('learning_rate', 0.001),
+             ('n_timesteps', 20000),
+             ('policy', 'MlpPolicy'),
+             ('normalize', False)])
+```

args.yml

@@ -0,0 +1,81 @@
+!!python/object/apply:collections.OrderedDict
+- - - algo
+    - sac
+  - - conf_file
+    - null
+  - - device
+    - auto
+  - - env
+    - Pendulum-v1
+  - - env_kwargs
+    - null
+  - - eval_episodes
+    - 5
+  - - eval_freq
+    - 25000
+  - - gym_packages
+    - []
+  - - hyperparams
+    - null
+  - - log_folder
+    - logs
+  - - log_interval
+    - -1
+  - - max_total_trials
+    - null
+  - - n_eval_envs
+    - 1
+  - - n_evaluations
+    - null
+  - - n_jobs
+    - 1
+  - - n_startup_trials
+    - 10
+  - - n_timesteps
+    - -1
+  - - n_trials
+    - 500
+  - - no_optim_plots
+    - false
+  - - num_threads
+    - -1
+  - - optimization_log_path
+    - null
+  - - optimize_hyperparameters
+    - false
+  - - progress
+    - false
+  - - pruner
+    - median
+  - - sampler
+    - tpe
+  - - save_freq
+    - -1
+  - - save_replay_buffer
+    - false
+  - - seed
+    - 1470884819
+  - - storage
+    - null
+  - - study_name
+    - null
+  - - tensorboard_log
+    - ''
+  - - track
+    - false
+  - - trained_agent
+    - ''
+  - - truncate_last_trajectory
+    - true
+  - - uuid
+    - false
+  - - vec_env
+    - dummy
+  - - verbose
+    - 1
+  - - wandb_entity
+    - null
+  - - wandb_project_name
+    - sb3
+  - - yaml_file
+    - null

config.yml

@@ -0,0 +1,7 @@
+!!python/object/apply:collections.OrderedDict
+- - - learning_rate
+    - 0.001
+  - - n_timesteps
+    - 20000
+  - - policy
+    - MlpPolicy

env_kwargs.yml

@@ -0,0 +1 @@
+{}

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dcf574cb4a5f6044389c7b83f78ec341a035463c32c4fcf79360fd35a77151ac
+size 125311

results.json

@@ -0,0 +1 @@
+{"mean_reward": -185.4470566, "std_reward": 109.80606340107906, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-27T15:35:42.484150"}

sac-Pendulum-v1.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d019c3964e93ebbe0fc6ce173c7395d349a9ea2bf09f9daee0de54c83f3e8def
+size 3012413

sac-Pendulum-v1/_stable_baselines3_version

@@ -0,0 +1 @@
+1.8.0a6

sac-Pendulum-v1/actor.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d07377ff815383de46ad03a853bb89899f7ac99c5a23853113622eb8752feb2b
+size 545181

sac-Pendulum-v1/critic.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44c42990d8157fc8584da34b3bd5a9efab6c2ef4f871786421d55983913a88f2
+size 1086969

sac-Pendulum-v1/data

@@ -0,0 +1,117 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnNhYy5wb2xpY2llc5SMCVNBQ1BvbGljeZSTlC4=",
+        "__module__": "stable_baselines3.sac.policies",
+        "__doc__": "\n    Policy class (with both actor and critic) for SAC.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    :param n_critics: Number of critic networks to create.\n    :param share_features_extractor: Whether to share or not the features extractor\n        between the actor and the critic (this saves computation time)\n    ",
+        "__init__": "<function SACPolicy.__init__ at 0x7fb4e0fd2ca0>",
+        "_build": "<function SACPolicy._build at 0x7fb4e0fd2d30>",
+        "_get_constructor_parameters": "<function SACPolicy._get_constructor_parameters at 0x7fb4e0fd2dc0>",
+        "reset_noise": "<function SACPolicy.reset_noise at 0x7fb4e0fd2e50>",
+        "make_actor": "<function SACPolicy.make_actor at 0x7fb4e0fd2ee0>",
+        "make_critic": "<function SACPolicy.make_critic at 0x7fb4e0fd2f70>",
+        "forward": "<function SACPolicy.forward at 0x7fb4e0fdb040>",
+        "_predict": "<function SACPolicy._predict at 0x7fb4e0fdb0d0>",
+        "set_training_mode": "<function SACPolicy.set_training_mode at 0x7fb4e0fdb160>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fb4e0fda380>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        "use_sde": false
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            3
+        ],
+        "low": "[-1. -1. -8.]",
+        "high": "[1. 1. 8.]",
+        "bounded_below": "[ True  True  True]",
+        "bounded_above": "[ True  True  True]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            1
+        ],
+        "low": "[-2.]",
+        "high": "[2.]",
+        "bounded_below": "[ True]",
+        "bounded_above": "[ True]",
+        "_np_random": "RandomState(MT19937)"
+    },
+    "n_envs": 1,
+    "num_timesteps": 20000,
+    "_total_timesteps": 20000,
+    "_num_timesteps_at_start": 0,
+    "seed": 0,
+    "action_noise": null,
+    "start_time": 1671720071985985589,
+    "learning_rate": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVvQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMRS9ob21lL3FnYWxsb3VlZGVjL3N0YWJsZS1iYXNlbGluZXMzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMRS9ob21lL3FnYWxsb3VlZGVjL3N0YWJsZS1iYXNlbGluZXMzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/UGJN0vGp/IWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
+    },
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": null,
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYMAAAAAAAAAOKjfz8VGVm94QpPvZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsDhpSMAUOUdJRSlC4="
+    },
+    "_episode_num": 100,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": 0.0,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 19900,
+    "buffer_size": 1,
+    "batch_size": 256,
+    "learning_starts": 100,
+    "tau": 0.005,
+    "gamma": 0.99,
+    "gradient_steps": 1,
+    "optimize_memory_usage": false,
+    "replay_buffer_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
+        "__module__": "stable_baselines3.common.buffers",
+        "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7fb4e102a430>",
+        "add": "<function ReplayBuffer.add at 0x7fb4e102a4c0>",
+        "sample": "<function ReplayBuffer.sample at 0x7fb4e102a550>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fb4e102a5e0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fb4e14ca480>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "target_entropy": -1.0,
+    "ent_coef": "auto",
+    "target_update_interval": 1,
+    "batch_norm_stats": [],
+    "batch_norm_stats_target": []
+}

sac-Pendulum-v1/ent_coef_optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c2931e7712f5bae6b2e8ceeb5ed63908c45b68d7516fdaa2e03df0d9013bb5b
+size 1507

sac-Pendulum-v1/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4fa2599eee1801f72e447d4efa87aa7900fa4af9404ac83de7bac51beb8dd002
+size 1357573

sac-Pendulum-v1/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c1d603b1bb9a6d65c41b351266af381a27fdec8e42c6b889e8cd4c6ae10fc695
+size 747

sac-Pendulum-v1/system_info.txt

@@ -0,0 +1,7 @@
+- OS: Linux-5.19.0-32-generic-x86_64-with-glibc2.35 # 33~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Jan 30 17:03:34 UTC 2
+- Python: 3.9.12
+- Stable-Baselines3: 1.8.0a6
+- PyTorch: 1.13.1+cu117
+- GPU Enabled: True
+- Numpy: 1.24.1
+- Gym: 0.21.0

train_eval_metrics.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1bf4752142f7eee93c4b4f3d0ea423cffdc53d45bcd97e5d8da70a78b376a414
+size 2892