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 +1,75 @@
+---
+library_name: stable-baselines3
+tags:
+- AcrobotSwingupDMC-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DDPG
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: AcrobotSwingupDMC-v0
+      type: AcrobotSwingupDMC-v0
+    metrics:
+    - type: mean_reward
+      value: 96.89 +/- 64.09
+      name: mean_reward
+      verified: false
+---
+
+# **DDPG** Agent playing **AcrobotSwingupDMC-v0**
+This is a trained model of a **DDPG** agent playing **AcrobotSwingupDMC-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
+
+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 ddpg --env AcrobotSwingupDMC-v0 -orga qgallouedec -f logs/
+python -m rl_zoo3.enjoy --algo ddpg --env AcrobotSwingupDMC-v0  -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 ddpg --env AcrobotSwingupDMC-v0 -orga qgallouedec -f logs/
+python -m rl_zoo3.enjoy --algo ddpg --env AcrobotSwingupDMC-v0  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python -m rl_zoo3.train --algo ddpg --env AcrobotSwingupDMC-v0 -f logs/
+# Upload the model and generate video (when possible)
+python -m rl_zoo3.push_to_hub --algo ddpg --env AcrobotSwingupDMC-v0 -f logs/ -orga qgallouedec
+```
+
+## Hyperparameters
+```python
+OrderedDict([('batch_size', 64),
+             ('gamma', 0.99),
+             ('learning_rate', 0.0001),
+             ('n_timesteps', 1000000.0),
+             ('noise_std', 0.3),
+             ('noise_type', 'ornstein-uhlenbeck'),
+             ('policy', 'MlpPolicy'),
+             ('policy_kwargs',
+              'dict(net_arch=dict(pi=[300, 200], qf=[400, 300]))'),
+             ('normalize', False)])
+```

args.yml

@@ -0,0 +1,83 @@
+!!python/object/apply:collections.OrderedDict
+- - - algo
+    - ddpg
+  - - conf_file
+    - null
+  - - device
+    - auto
+  - - env
+    - AcrobotSwingupDMC-v0
+  - - env_kwargs
+    - null
+  - - eval_episodes
+    - 20
+  - - eval_freq
+    - 25000
+  - - gym_packages
+    - []
+  - - hyperparams
+    - null
+  - - log_folder
+    - logs
+  - - log_interval
+    - -1
+  - - max_total_trials
+    - null
+  - - n_eval_envs
+    - 5
+  - - 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
+    - 3785955249
+  - - storage
+    - null
+  - - study_name
+    - null
+  - - tensorboard_log
+    - runs/AcrobotSwingupDMC-v0__ddpg__3785955249__1673810878
+  - - track
+    - true
+  - - trained_agent
+    - ''
+  - - truncate_last_trajectory
+    - true
+  - - uuid
+    - false
+  - - vec_env
+    - dummy
+  - - verbose
+    - 1
+  - - wandb_entity
+    - qgallouedec
+  - - wandb_project_name
+    - dmc
+  - - wandb_tags
+    - []
+  - - yaml_file
+    - null

config.yml

@@ -0,0 +1,17 @@
+!!python/object/apply:collections.OrderedDict
+- - - batch_size
+    - 64
+  - - gamma
+    - 0.99
+  - - learning_rate
+    - 0.0001
+  - - n_timesteps
+    - 1000000.0
+  - - noise_std
+    - 0.3
+  - - noise_type
+    - ornstein-uhlenbeck
+  - - policy
+    - MlpPolicy
+  - - policy_kwargs
+    - dict(net_arch=dict(pi=[300, 200], qf=[400, 300]))

ddpg-AcrobotSwingupDMC-v0.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:53ed8a68377ed3c3db3d85386ca97f5b4a05cf7e5c5c34d66bd452830b3229bc
+size 3021849

ddpg-AcrobotSwingupDMC-v0/_stable_baselines3_version

@@ -0,0 +1 @@
+1.7.0

ddpg-AcrobotSwingupDMC-v0/actor.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:679468e32c743a7eaa4e37c24d6e9225b66463ddb5c101db1bf3641fd4198d46
+size 504751

ddpg-AcrobotSwingupDMC-v0/critic.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd05941ac5fca8239f0ad994f2e9d75afc21b0ffad0eb6fb283259cbc4193bf0
+size 995055

ddpg-AcrobotSwingupDMC-v0/data

@@ -0,0 +1,137 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=",
+        "__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 0x135f98280>",
+        "_build": "<function TD3Policy._build at 0x135f98310>",
+        "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x135f983a0>",
+        "make_actor": "<function TD3Policy.make_actor at 0x135f98430>",
+        "make_critic": "<function TD3Policy.make_critic at 0x135f984c0>",
+        "forward": "<function TD3Policy.forward at 0x135f98550>",
+        "_predict": "<function TD3Policy._predict at 0x135f985e0>",
+        "set_training_mode": "<function TD3Policy.set_training_mode at 0x135f98670>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x135f91fc0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        "net_arch": {
+            "pi": [
+                300,
+                200
+            ],
+            "qf": [
+                400,
+                300
+            ]
+        },
+        "n_critics": 1
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            6
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False]",
+        "bounded_above": "[False False False False False False]",
+        "_np_random": "RandomState(MT19937)"
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            1
+        ],
+        "low": "[-1.]",
+        "high": "[1.]",
+        "bounded_below": "[ True]",
+        "bounded_above": "[ True]",
+        "_np_random": "RandomState(MT19937)"
+    },
+    "n_envs": 1,
+    "num_timesteps": 1000000,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": 0,
+    "action_noise": {
+        ":type:": "<class 'stable_baselines3.common.noise.OrnsteinUhlenbeckActionNoise'>",
+        ":serialized:": "gAWVVQEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMHE9ybnN0ZWluVWhsZW5iZWNrQWN0aW9uTm9pc2WUk5QpgZR9lCiMBl90aGV0YZRHP8MzMzMzMzOMA19tdZSMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBhZSMAUOUdJRSlIwGX3NpZ21hlGgJKJYIAAAAAAAAADMzMzMzM9M/lGgQSwGFlGgUdJRSlIwDX2R0lEc/hHrhR64Ue4wNaW5pdGlhbF9ub2lzZZROjApub2lzZV9wcmV2lGgJKJYIAAAAAAAAAAAAAAAAAAAAlGgQSwGFlGgUdJRSlHViLg==",
+        "_theta": 0.15,
+        "_mu": "[0.]",
+        "_sigma": "[0.3]",
+        "_dt": 0.01,
+        "initial_noise": null,
+        "noise_prev": "[0.]"
+    },
+    "start_time": 1673810881171603198,
+    "learning_rate": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVCQMAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMay9ncGZzZHN3b3JrL3Byb2plY3RzL3JlY2gvdWxpL3VwZjgyc3AvZW52X2RtYy9saWIvcHl0aG9uMy45L3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgkMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxrL2dwZnNkc3dvcmsvcHJvamVjdHMvcmVjaC91bGkvdXBmODJzcC9lbnZfZG1jL2xpYi9weXRob24zLjkvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPxo24uscQy2FlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
+    },
+    "tensorboard_log": "runs/AcrobotSwingupDMC-v0__ddpg__3785955249__1673810878/AcrobotSwingupDMC-v0",
+    "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:": "gAWVjQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYYAAAAAAAAAJH7ez+n13U/lbI0PjfLjj6FycbAILwEQZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsGhpSMAUOUdJRSlC4="
+    },
+    "_episode_num": 1000,
+    "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": 1000000,
+    "buffer_size": 1,
+    "batch_size": 64,
+    "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 0x135f96dd0>",
+        "add": "<function ReplayBuffer.add at 0x135f96e60>",
+        "sample": "<function ReplayBuffer.sample at 0x135f96ef0>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x135f96f80>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x135f3d540>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "policy_delay": 1,
+    "target_noise_clip": 0.0,
+    "target_policy_noise": 0.1,
+    "actor_batch_norm_stats": [],
+    "critic_batch_norm_stats": [],
+    "actor_batch_norm_stats_target": [],
+    "critic_batch_norm_stats_target": []
+}

ddpg-AcrobotSwingupDMC-v0/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3d61fce2e60d29a9b6acad96eacea4580f3bae5b21109e1cb448e53fbf3c2009
+size 1498141

ddpg-AcrobotSwingupDMC-v0/pytorch_variables.pth

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

ddpg-AcrobotSwingupDMC-v0/system_info.txt

@@ -0,0 +1,7 @@
+- OS: macOS-13.0.1-arm64-arm-64bit Darwin Kernel Version 22.1.0: Sun Oct  9 20:14:30 PDT 2022; root:xnu-8792.41.9~2/RELEASE_ARM64_T8103
+- Python: 3.10.9
+- Stable-Baselines3: 1.7.0
+- PyTorch: 1.13.1
+- GPU Enabled: False
+- Numpy: 1.24.1
+- 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:df8fdca582abd595a1f0a7f35b5855d686514796c21941c7c2d5ae7075e286aa
+size 263148

results.json

@@ -0,0 +1 @@
+{"mean_reward": 96.8920822, "std_reward": 64.0942718002846, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-15T23:06:03.227002"}

train_eval_metrics.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a429e8dd8007a2d2db0018357a8fd3ef3f4d4d1b85929d160e502c29d7d2e491
+size 41331