Initial commit

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard 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 +1,58 @@
+---
+library_name: stable-baselines3
+tags:
+- MountainCarContinuous-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DDPG
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 93.51 +/- 0.05
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: MountainCarContinuous-v0
+      type: MountainCarContinuous-v0
+---
+
+# **DDPG** Agent playing **MountainCarContinuous-v0**
+This is a trained model of a **DDPG** agent playing **MountainCarContinuous-v0**
+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
+
+```
+# Download model and save it into the logs/ folder
+python -m utils.load_from_hub --algo ddpg --env MountainCarContinuous-v0 -orga sb3 -f logs/
+python enjoy.py --algo ddpg --env MountainCarContinuous-v0  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python train.py --algo ddpg --env MountainCarContinuous-v0 -f logs/
+# Upload the model and generate video (when possible)
+python -m utils.push_to_hub --algo ddpg --env MountainCarContinuous-v0 -f logs/ -orga sb3
+```
+
+## Hyperparameters
+```python
+OrderedDict([('n_timesteps', 300000),
+             ('noise_std', 0.5),
+             ('noise_type', 'ornstein-uhlenbeck'),
+             ('policy', 'MlpPolicy'),
+             ('normalize', False)])
+```

args.yml

@@ -0,0 +1,59 @@
+!!python/object/apply:collections.OrderedDict
+- - - algo
+    - ddpg
+  - - env
+    - MountainCarContinuous-v0
+  - - env_kwargs
+    - null
+  - - eval_episodes
+    - 10
+  - - eval_freq
+    - 10000
+  - - gym_packages
+    - []
+  - - hyperparams
+    - null
+  - - log_folder
+    - rl-trained-agents/
+  - - log_interval
+    - -1
+  - - n_evaluations
+    - 20
+  - - n_jobs
+    - 1
+  - - n_startup_trials
+    - 10
+  - - n_timesteps
+    - -1
+  - - n_trials
+    - 10
+  - - num_threads
+    - -1
+  - - optimize_hyperparameters
+    - false
+  - - pruner
+    - median
+  - - sampler
+    - tpe
+  - - save_freq
+    - -1
+  - - save_replay_buffer
+    - false
+  - - seed
+    - 1788447435
+  - - storage
+    - null
+  - - study_name
+    - null
+  - - tensorboard_log
+    - ''
+  - - trained_agent
+    - ''
+  - - truncate_last_trajectory
+    - true
+  - - uuid
+    - true
+  - - vec_env
+    - dummy
+  - - verbose
+    - 1

config.yml

@@ -0,0 +1,9 @@
+!!python/object/apply:collections.OrderedDict
+- - - n_timesteps
+    - 300000
+  - - noise_std
+    - 0.5
+  - - noise_type
+    - ornstein-uhlenbeck
+  - - policy
+    - MlpPolicy

ddpg-MountainCarContinuous-v0.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2075a39757e28efa842dfaf15ceada90a8f728479675556a819a803cd019b849
+size 3937100

ddpg-MountainCarContinuous-v0/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.1a8

ddpg-MountainCarContinuous-v0/actor.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:032a7a9c861257c2961ad7d82e2f7804713f60c42982d1454f2b63efdf94b07b
+size 977729

ddpg-MountainCarContinuous-v0/critic.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e94a79610906af246dbb0031b8fb0b791d7eef1aeb3a058d9a1a58ab5f2beb24
+size 980929

ddpg-MountainCarContinuous-v0/data

@@ -0,0 +1,122 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gASVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=",
+        "__module__": "stable_baselines3.td3.policies",
+        "__doc__": "\n    Policy class (with both actor and critic) for TD3.\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 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 TD3Policy.__init__ at 0x7fd650f94170>",
+        "_build": "<function TD3Policy._build at 0x7fd650f94200>",
+        "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7fd650f94290>",
+        "make_actor": "<function TD3Policy.make_actor at 0x7fd650f94320>",
+        "make_critic": "<function TD3Policy.make_critic at 0x7fd650f943b0>",
+        "forward": "<function TD3Policy.forward at 0x7fd650f94440>",
+        "_predict": "<function TD3Policy._predict at 0x7fd650f944d0>",
+        "set_training_mode": "<function TD3Policy.set_training_mode at 0x7fd650f94560>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fd650f921b0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        "n_critics": 1
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "low": "[-1.2  -0.07]",
+        "high": "[0.6  0.07]",
+        "bounded_below": "[ True  True]",
+        "bounded_above": "[ True  True]",
+        "_np_random": null,
+        "_shape": [
+            2
+        ]
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "low": "[-1.]",
+        "high": "[1.]",
+        "bounded_below": "[ True]",
+        "bounded_above": "[ True]",
+        "_np_random": "RandomState(MT19937)",
+        "_shape": [
+            1
+        ]
+    },
+    "n_envs": 1,
+    "num_timesteps": 300691,
+    "_total_timesteps": 300000,
+    "_num_timesteps_at_start": 0,
+    "seed": 0,
+    "action_noise": {
+        ":type:": "<class 'stable_baselines3.common.noise.OrnsteinUhlenbeckActionNoise'>",
+        ":serialized:": "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",
+        "_theta": 0.15,
+        "_mu": "[0.]",
+        "_sigma": "[0.5]",
+        "_dt": 0.01,
+        "initial_noise": null,
+        "noise_prev": "[0.]"
+    },
+    "start_time": 1614621347.9187016,
+    "learning_rate": 0.001,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": null,
+    "_last_episode_starts": null,
+    "_last_original_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASVkgAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLAoaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUMId6HVPpCgJD2UdJRiLg=="
+    },
+    "_episode_num": 2831,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.002303333333333324,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 300691,
+    "buffer_size": 1,
+    "batch_size": 100,
+    "learning_starts": 100,
+    "tau": 0.005,
+    "gamma": 0.99,
+    "gradient_steps": -1,
+    "optimize_memory_usage": false,
+    "replay_buffer_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gASVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
+        "__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:\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    :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 0x7fd651411b90>",
+        "add": "<function ReplayBuffer.add at 0x7fd651411c20>",
+        "sample": "<function ReplayBuffer.sample at 0x7fd650f787a0>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fd650f78830>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fd6514695d0>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gASVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "policy_delay": 1,
+    "target_noise_clip": 0.0,
+    "target_policy_noise": 0.1,
+    "_last_dones": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQCUdJRiLg=="
+    },
+    "remove_time_limit_termination": false
+}

ddpg-MountainCarContinuous-v0/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:05d6acb5e533639a55bbb87f82f7de7511b4c3c12743a5fef1c53de3f782b348
+size 1959965

ddpg-MountainCarContinuous-v0/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ddpg-MountainCarContinuous-v0/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.13.0-44-generic-x86_64-with-debian-bullseye-sid #49~20.04.1-Ubuntu SMP Wed May 18 18:44:28 UTC 2022
+Python: 3.7.10
+Stable-Baselines3: 1.5.1a8
+PyTorch: 1.11.0
+GPU Enabled: True
+Numpy: 1.21.2
+Gym: 0.21.0

env_kwargs.yml

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

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:234d19d5b845e8382d0d569874c81123c2255b1032398197ba01fe0ea5ae25f9
+size 273481

results.json

@@ -0,0 +1 @@
+{"mean_reward": 93.5085729, "std_reward": 0.04911273082704637, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T22:44:18.729099"}

train_eval_metrics.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6ee54d2bdf6af072a08896350003292f1ac22feb30b3c01eaf005cf571179d7e
+size 79413