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 +1,65 @@
+---
+library_name: stable-baselines3
+tags:
+- Pendulum-v1
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: TD3
+  results:
+  - metrics:
+    - type: mean_reward
+      value: -195.99 +/- 119.03
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: Pendulum-v1
+      type: Pendulum-v1
+---
+
+# **TD3** Agent playing **Pendulum-v1**
+This is a trained model of a **TD3** 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
+
+```
+# Download model and save it into the logs/ folder
+python -m utils.load_from_hub --algo td3 --env Pendulum-v1 -orga sb3 -f logs/
+python enjoy.py --algo td3 --env Pendulum-v1  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python train.py --algo td3 --env Pendulum-v1 -f logs/
+# Upload the model and generate video (when possible)
+python -m utils.push_to_hub --algo td3 --env Pendulum-v1 -f logs/ -orga sb3
+```
+
+## Hyperparameters
+```python
+OrderedDict([('buffer_size', 200000),
+             ('gamma', 0.98),
+             ('gradient_steps', -1),
+             ('learning_rate', 0.001),
+             ('learning_starts', 10000),
+             ('n_timesteps', 20000),
+             ('noise_std', 0.1),
+             ('noise_type', 'normal'),
+             ('policy', 'MlpPolicy'),
+             ('policy_kwargs', 'dict(net_arch=[400, 300])'),
+             ('train_freq', [1, 'episode']),
+             ('normalize', False)])
+```

args.yml

@@ -0,0 +1,59 @@
+!!python/object/apply:collections.OrderedDict
+- - - algo
+    - td3
+  - - env
+    - Pendulum-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
+    - 4156017648
+  - - storage
+    - null
+  - - study_name
+    - null
+  - - tensorboard_log
+    - ''
+  - - trained_agent
+    - ''
+  - - truncate_last_trajectory
+    - true
+  - - uuid
+    - true
+  - - vec_env
+    - dummy
+  - - verbose
+    - 1

config.yml

@@ -0,0 +1,24 @@
+!!python/object/apply:collections.OrderedDict
+- - - buffer_size
+    - 200000
+  - - gamma
+    - 0.98
+  - - gradient_steps
+    - -1
+  - - learning_rate
+    - 0.001
+  - - learning_starts
+    - 10000
+  - - n_timesteps
+    - 20000
+  - - noise_std
+    - 0.1
+  - - noise_type
+    - normal
+  - - policy
+    - MlpPolicy
+  - - policy_kwargs
+    - dict(net_arch=[400, 300])
+  - - train_freq
+    - - 1
+      - episode

env_kwargs.yml

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

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fcc20910ec9875683b3fb2d450f765628ae671fae2aa114fe29275a0e443b95e
+size 293958

results.json

@@ -0,0 +1 @@
+{"mean_reward": -195.9938827, "std_reward": 119.03262048201839, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T15:09:36.336078"}

td3-Pendulum-v1.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9597e5a20703d74786afc8e5f48d98b378816ad8743ee62e2a278483bc565823
+size 5920968

td3-Pendulum-v1/_stable_baselines3_version

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

td3-Pendulum-v1/actor.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8401dc938f1e12e797922cc6f570daa746041f72e7821f9ae8d156efac545b01
+size 980929

td3-Pendulum-v1/critic.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:874916fadb411303e7a3ad9cccecebf6aac72019c88c3b906cf7125cc49bb45d
+size 1967965

td3-Pendulum-v1/data

@@ -0,0 +1,124 @@
+{
+    "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 0x7fd6839e0170>",
+        "_build": "<function TD3Policy._build at 0x7fd6839e0200>",
+        "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7fd6839e0290>",
+        "make_actor": "<function TD3Policy.make_actor at 0x7fd6839e0320>",
+        "make_critic": "<function TD3Policy.make_critic at 0x7fd6839e03b0>",
+        "forward": "<function TD3Policy.forward at 0x7fd6839e0440>",
+        "_predict": "<function TD3Policy._predict at 0x7fd6839e04d0>",
+        "set_training_mode": "<function TD3Policy.set_training_mode at 0x7fd6839e0560>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fd6839de1e0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        "net_arch": [
+            400,
+            300
+        ]
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "low": "[-1. -1. -8.]",
+        "high": "[1. 1. 8.]",
+        "bounded_below": "[ True  True  True]",
+        "bounded_above": "[ True  True  True]",
+        "_np_random": null,
+        "_shape": [
+            3
+        ]
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "low": "[-2.]",
+        "high": "[2.]",
+        "bounded_below": "[ True]",
+        "bounded_above": "[ True]",
+        "_np_random": "RandomState(MT19937)",
+        "_shape": [
+            1
+        ]
+    },
+    "n_envs": 1,
+    "num_timesteps": 20000,
+    "_total_timesteps": 20000,
+    "_num_timesteps_at_start": 0,
+    "seed": 0,
+    "action_noise": {
+        ":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>",
+        ":serialized:": "gASVBAEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBVudW1weS5jb3JlLm11bHRpYXJyYXmUjAxfcmVjb25zdHJ1Y3SUk5SMBW51bXB5lIwHbmRhcnJheZSTlEsAhZRDAWKUh5RSlChLAUsBhZRoCYwFZHR5cGWUk5SMAmY4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKJQwgAAAAAAAAAAJR0lGKMBl9zaWdtYZRoCGgLSwCFlGgNh5RSlChLAUsBhZRoFYlDCJqZmZmZmbk/lHSUYnViLg==",
+        "_mu": "[0.]",
+        "_sigma": "[0.1]"
+    },
+    "start_time": 1614621345.191944,
+    "learning_rate": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "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:": "gASVlgAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLA4aUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUMMbu9/P0c2uLwPLhW9lHSUYi4="
+    },
+    "_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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 10000,
+    "buffer_size": 1,
+    "batch_size": 100,
+    "learning_starts": 10000,
+    "tau": 0.005,
+    "gamma": 0.98,
+    "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 0x7fd683e5db90>",
+        "add": "<function ReplayBuffer.add at 0x7fd683e5dc20>",
+        "sample": "<function ReplayBuffer.sample at 0x7fd6839c47a0>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fd6839c4830>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fd683eb55d0>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gASVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "policy_delay": 2,
+    "target_noise_clip": 0.5,
+    "target_policy_noise": 0.2,
+    "_last_dones": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQCUdJRiLg=="
+    },
+    "remove_time_limit_termination": false
+}

td3-Pendulum-v1/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8793693a0db571c5f9ee5df192ea18d4e6aee70989e5a0e26a91b1a3d9df592
+size 2951289

td3-Pendulum-v1/pytorch_variables.pth

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

td3-Pendulum-v1/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

train_eval_metrics.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:668860a76a08a8f769fd2f754d68dcb141774a52a3d4b8db20609a0d470d2c52
+size 4072