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 +1,67 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: QRDQN
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 61.43 +/- 184.22
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+# **QRDQN** Agent playing **LunarLander-v2**
+This is a trained model of a **QRDQN** agent playing **LunarLander-v2**
+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 qrdqn --env LunarLander-v2 -orga sb3 -f logs/
+python enjoy.py --algo qrdqn --env LunarLander-v2  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python train.py --algo qrdqn --env LunarLander-v2 -f logs/
+# Upload the model and generate video (when possible)
+python -m utils.push_to_hub --algo qrdqn --env LunarLander-v2 -f logs/ -orga sb3
+```
+
+## Hyperparameters
+```python
+OrderedDict([('batch_size', 128),
+             ('buffer_size', 100000),
+             ('exploration_final_eps', 0.18),
+             ('exploration_fraction', 0.24),
+             ('gamma', 0.995),
+             ('gradient_steps', -1),
+             ('learning_rate', 'lin_1.5e-3'),
+             ('learning_starts', 10000),
+             ('n_timesteps', 100000.0),
+             ('policy', 'MlpPolicy'),
+             ('policy_kwargs', 'dict(net_arch=[256, 256], n_quantiles=170)'),
+             ('target_update_interval', 1),
+             ('train_freq', 256),
+             ('normalize', False)])
+```

args.yml

@@ -0,0 +1,59 @@
+!!python/object/apply:collections.OrderedDict
+- - - algo
+    - qrdqn
+  - - env
+    - LunarLander-v2
+  - - 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
+    - 132583394
+  - - storage
+    - null
+  - - study_name
+    - null
+  - - tensorboard_log
+    - ''
+  - - trained_agent
+    - ''
+  - - truncate_last_trajectory
+    - true
+  - - uuid
+    - true
+  - - vec_env
+    - dummy
+  - - verbose
+    - 1

config.yml

@@ -0,0 +1,27 @@
+!!python/object/apply:collections.OrderedDict
+- - - batch_size
+    - 128
+  - - buffer_size
+    - 100000
+  - - exploration_final_eps
+    - 0.18
+  - - exploration_fraction
+    - 0.24
+  - - gamma
+    - 0.995
+  - - gradient_steps
+    - -1
+  - - learning_rate
+    - lin_1.5e-3
+  - - learning_starts
+    - 10000
+  - - n_timesteps
+    - 100000.0
+  - - policy
+    - MlpPolicy
+  - - policy_kwargs
+    - dict(net_arch=[256, 256], n_quantiles=170)
+  - - target_update_interval
+    - 1
+  - - train_freq
+    - 256

env_kwargs.yml

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

qrdqn-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:39b454d3d0305d4472ab4ca0bf22ccf713df36ca3dfc682113bff0bcdbb3965d
+size 3915674

qrdqn-LunarLander-v2/_stable_baselines3_version

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

qrdqn-LunarLander-v2/data

@@ -0,0 +1,129 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gASVLgAAAAAAAACMGnNiM19jb250cmliLnFyZHFuLnBvbGljaWVzlIwLUVJEUU5Qb2xpY3mUk5Qu",
+        "__module__": "sb3_contrib.qrdqn.policies",
+        "__doc__": "\n    Policy class with quantile and target networks for QR-DQN.\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 n_quantiles: Number of quantiles\n    :param net_arch: The specification of the network architecture.\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    ",
+        "__init__": "<function QRDQNPolicy.__init__ at 0x7fb9c6b529e0>",
+        "_build": "<function QRDQNPolicy._build at 0x7fb9c6b52a70>",
+        "make_quantile_net": "<function QRDQNPolicy.make_quantile_net at 0x7fb9c6b52b00>",
+        "forward": "<function QRDQNPolicy.forward at 0x7fb9c6b52b90>",
+        "_predict": "<function QRDQNPolicy._predict at 0x7fb9c6b52c20>",
+        "_get_constructor_parameters": "<function QRDQNPolicy._get_constructor_parameters at 0x7fb9c6b52cb0>",
+        "set_training_mode": "<function QRDQNPolicy.set_training_mode at 0x7fb9c6b52d40>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fb9c6ba1fc0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        ":type:": "<class 'dict'>",
+        ":serialized:": "gASVfQAAAAAAAAB9lCiMCG5ldF9hcmNolF2UKE0AAU0AAWWMC25fcXVhbnRpbGVzlEuqjA9vcHRpbWl6ZXJfY2xhc3OUjBB0b3JjaC5vcHRpbS5hZGFtlIwEQWRhbZSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lIwDZXBzlEc/FHrhR64Ue3N1Lg==",
+        "net_arch": [
+            256,
+            256
+        ],
+        "n_quantiles": 170,
+        "optimizer_class": "<class 'torch.optim.adam.Adam'>",
+        "optimizer_kwargs": {
+            "eps": 7.8125e-05
+        }
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null,
+        "_shape": [
+            8
+        ]
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "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",
+        "n": 4,
+        "dtype": "int64",
+        "_np_random": "RandomState(MT19937)",
+        "_shape": []
+    },
+    "n_envs": 1,
+    "num_timesteps": 100096,
+    "_total_timesteps": 100000,
+    "_num_timesteps_at_start": 0,
+    "seed": 0,
+    "action_noise": null,
+    "start_time": 1614712499.9390948,
+    "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:": "gASVqgAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLCIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUMgAN0FPaHqsT82gCs/gDl1vt6G8LyeHCK+AAAAAAAAAACUdJRiLg=="
+    },
+    "_episode_num": 287,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.0009600000000000719,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gASVaRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI2ucxyrNsckCUhpRSlIwBbJRL9owBdJRHQKs9WnG82751fZQoaAZoCWgPQwjF46JaRAJAQJSGlFKUaBVN6ANoFkdArAk2JWNm2HV9lChoBmgJaA9DCOjAcoQMLDrAlIaUUpRoFUuAaBZHQKwJ0KZ2IO91fZQoaAZoCWgPQwgwhJz3/6tqQJSGlFKUaBVNIQJoFkdArHHVEG7jDXV9lChoBmgJaA9DCAmmmllLbXFAlIaUUpRoFU0KAWgWR0Cs1Pe9alk6dX2UKGgGaAloD0MIDf0TXKxqVUCUhpRSlGgVTegDaBZHQK1t9Cj1wo91fZQoaAZoCWgPQwjqXbwft6ZuQJSGlFKUaBVNAAJoFkdAreFfBLwnY3V9lChoBmgJaA9DCHsvvmiPOGFAlIaUUpRoFU3oA2gWR0Cumwc+RoysdX2UKGgGaAloD0MIym5m9OObcECUhpRSlGgVTV0CaBZHQK8ok4gieNF1fZQoaAZoCWgPQwjDu1zE9/5wQJSGlFKUaBVNlwFoFkdAr1h+YYzi0nV9lChoBmgJaA9DCHKo34WtQSFAlIaUUpRoFUuoaBZHQK+DUeHSF491fZQoaAZoCWgPQwiI9UatsHxgQJSGlFKUaBVN6ANoFkdAsBvP1PFefXV9lChoBmgJaA9DCInTSba6uVdAlIaUUpRoFU3oA2gWR0CwdNghbGFSdX2UKGgGaAloD0MIu0ihLPylbkCUhpRSlGgVTTYCaBZHQLCgLh86V+t1fZQoaAZoCWgPQwjQfw9eu6BxQJSGlFKUaBVNFwJoFkdAsM2MPnSv1XV9lChoBmgJaA9DCA8KStHKVWVAlIaUUpRoFU3oA2gWR0CxIzGQ8wHrdX2UKGgGaAloD0MIXf3YJL/Zb0CUhpRSlGgVTUABaBZHQLE4QJjUd7x1fZQoaAZoCWgPQwh4l4v4zs5wQJSGlFKUaBVNdgFoFkdAsWJu+TNdJXV9lChoBmgJaA9DCG2sxDyrnmRAlIaUUpRoFU3oA2gWR0Cxur2JemeldX2UKGgGaAloD0MIw2aACzJGbECUhpRSlGgVTVYBaBZHQLHPqt+Csfd1fZQoaAZoCWgPQwjkSdI1k9RrQJSGlFKUaBVL9mgWR0Cx5AuNYKYzdX2UKGgGaAloD0MIwy6KHvhqb0CUhpRSlGgVTdUDaBZHQLI65kN4JNV1fZQoaAZoCWgPQwj2XRH8b2hwQJSGlFKUaBVNmQFoFkdAslWU5sCT2XV9lChoBmgJaA9DCLgjnBa8UCzAlIaUUpRoFUuFaBZHQLJqCrcTJyR1fZQoaAZoCWgPQwhU/Urnw0dAwJSGlFKUaBVLbGgWR0CyalCQxN7CdX2UKGgGaAloD0MIorYNo6BecECUhpRSlGgVTeICaBZHQLKqL+JxecB1fZQoaAZoCWgPQwix4H7AAydBwJSGlFKUaBVLZmgWR0Cyv3vszEaVdX2UKGgGaAloD0MI12oPe6GcXsCUhpRSlGgVTZUBaBZHQLLWg8BMi8p1fZQoaAZoCWgPQwjD19e61K9ZQJSGlFKUaBVN6ANoFkdAsyx9KYiPhnV9lChoBmgJaA9DCG1UpwNZZG5AlIaUUpRoFU0xAmgWR0CzV4y7K7qZdX2UKGgGaAloD0MIP5C8c6hZb0CUhpRSlGgVTUgBaBZHQLNtBiZv1lJ1fZQoaAZoCWgPQwinPSXnxHVoQJSGlFKUaBVNdwFoFkdAs5mP6VMVUXV9lChoBmgJaA9DCI2WAz3UYEdAlIaUUpRoFU3oA2gWR0Cz7zsA/9pAdX2UKGgGaAloD0MIO6sF9piRb0CUhpRSlGgVTYgBaBZHQLQEtzLfUF11fZQoaAZoCWgPQwjkht9NN8tyQJSGlFKUaBVNkAFoFkdAtDGTbnHNo3V9lChoBmgJaA9DCHr7c9GQcTNAlIaUUpRoFUt0aBZHQLQx4Pvrnkl1fZQoaAZoCWgPQwguc7osphRuQJSGlFKUaBVNKwFoFkdAtF19JcxCY3V9lChoBmgJaA9DCET8w5Ze2XFAlIaUUpRoFU3mAmgWR0C0iCkNvwVkdX2UKGgGaAloD0MIXVDfMie4b0CUhpRSlGgVTY8DaBZHQLTeiNS619h1fZQoaAZoCWgPQwh154nnbAdmQJSGlFKUaBVN6ANoFkdAtTXUzAN5MXV9lChoBmgJaA9DCN+Hg4QornFAlIaUUpRoFU2BAWgWR0C1SuAcDKYBdX2UKGgGaAloD0MIyk4/qAs4bkCUhpRSlGgVTc8BaBZHQLV1y6bONYN1fZQoaAZoCWgPQwheonpr4JpsQJSGlFKUaBVN1gJoFkdAtcZn5YYBNnV9lChoBmgJaA9DCNRfr7Cgc3FAlIaUUpRoFU1pA2gWR0C2CA4JAt4BdX2UKGgGaAloD0MIe4hGd1BAcUCUhpRSlGgVS/1oFkdAth2xREWqLnV9lChoBmgJaA9DCF7b2y1JFHFAlIaUUpRoFU2PAmgWR0C2YPDmW+oMdX2UKGgGaAloD0MIOL72zJLEa0CUhpRSlGgVTd8DaBZHQLa1gAlfJFN1fZQoaAZoCWgPQwixFTQtsadsQJSGlFKUaBVNfQFoFkdAtswEuL74z3V9lChoBmgJaA9DCO7of7mWknBAlIaUUpRoFU0kA2gWR0C3JJLtVrAQdX2UKGgGaAloD0MIxccnZGdVa0CUhpRSlGgVTSQDaBZHQLdkPYx+KCR1fZQoaAZoCWgPQwha8Q2FTw5gQJSGlFKUaBVN6ANoFkdAt79azQeFL3V9lChoBmgJaA9DCBJNoIhFjkJAlIaUUpRoFUuuaBZHQLe/xsXSBsh1fZQoaAZoCWgPQwgCDTZ1HuFfQJSGlFKUaBVN6ANoFkdAuBXOOtGNJnV9lChoBmgJaA9DCGaH+IctFGBAlIaUUpRoFU3oA2gWR0C4cdLKJVKgdX2UKGgGaAloD0MIhh+cT53abECUhpRSlGgVTbIBaBZHQLigC83dbgV1fZQoaAZoCWgPQwiveOqRBktsQJSGlFKUaBVN0ANoFkdAuP+piUgSvnV9lChoBmgJaA9DCO7uAbovo2JAlIaUUpRoFU3oA2gWR0C5SLEX+ERKdX2UKGgGaAloD0MI8piByjgXckCUhpRSlGgVTYoBaBZHQLl3AGB4D9x1fZQoaAZoCWgPQwhO7KF9LLNzQJSGlFKUaBVNNQFoFkdAuY7zpt78enV9lChoBmgJaA9DCEBs6dFU1mpAlIaUUpRoFU2BA2gWR0C56j4ouwotdX2UKGgGaAloD0MIVG6ilmZ9a0CUhpRSlGgVTWkCaBZHQLoXaCIUJv51fZQoaAZoCWgPQwimYmNeR3NjwJSGlFKUaBVNlwFoFkdAukd42Hck+3V9lChoBmgJaA9DCJChYweV+1hAlIaUUpRoFU3oA2gWR0C6pkqoddVvdX2UKGgGaAloD0MIuyakNQatUMCUhpRSlGgVS4VoFkdAuqagafjCHnV9lChoBmgJaA9DCLg7a7ddvGZAlIaUUpRoFU3oA2gWR0C7B6WEwnIAdX2UKGgGaAloD0MIcHfWbjtGZECUhpRSlGgVTegDaBZHQLtsyLux8lZ1fZQoaAZoCWgPQwiFKF/QQuY2QJSGlFKUaBVLp2gWR0C7hvuzUqhEdX2UKGgGaAloD0MIW7VrQlpFQUCUhpRSlGgVS55oFkdAu4dduTA31nV9lChoBmgJaA9DCC6M9KJ2azNAlIaUUpRoFUtxaBZHQLuhBsz2vjh1fZQoaAZoCWgPQwhgHjLlQ6JSQJSGlFKUaBVLb2gWR0C7oU9QCSzPdX2UKGgGaAloD0MIv+5054mPW0CUhpRSlGgVTegDaBZHQLwJnNhE0BR1fZQoaAZoCWgPQwgWvymsFBtzQJSGlFKUaBVNDgFoFkdAvCMrqVyFPHV9lChoBmgJaA9DCBRAMbLklG1AlIaUUpRoFU1oAmgWR0C8VvIhdMTOdX2UKGgGaAloD0MIOC9OfDVXcUCUhpRSlGgVTTQBaBZHQLyJICTlkpZ1fZQoaAZoCWgPQwjrUiP0s/dnQJSGlFKUaBVNXwJoFkdAvLvV9LHuJHV9lChoBmgJaA9DCKVquwl+YHFAlIaUUpRoFU1TAWgWR0C82ddCE6DHdX2UKGgGaAloD0MIEsKjjSNScUCUhpRSlGgVTRwCaBZHQL0Ob8/lhgF1fZQoaAZoCWgPQwj7OnDOiB5OwJSGlFKUaBVLgGgWR0C9JfxdyDIzdX2UKGgGaAloD0MI+1dWmpRKZECUhpRSlGgVTX0BaBZHQL097JGvwE11fZQoaAZoCWgPQwiLUdfaOzBxQJSGlFKUaBVNCAJoFkdAvYVKmMwUQHV9lChoBmgJaA9DCLfvUX89U3BAlIaUUpRoFU0oAWgWR0C9oGBsANobdX2UKGgGaAloD0MIuoYZGk9eckCUhpRSlGgVTQcBaBZHQL24xwXIlt11fZQoaAZoCWgPQwgc6ndha7YDwJSGlFKUaBVLdGgWR0C9uQ6Zx7zDdX2UKGgGaAloD0MIJJpAEYvIPUCUhpRSlGgVS8VoFkdAvc+pg0CRwXV9lChoBmgJaA9DCKsEi8OZzU5AlIaUUpRoFU3oA2gWR0C+MRDvZyuIdX2UKGgGaAloD0MIh4kGKXjsRsCUhpRSlGgVS9doFkdAvkr8Moc7yXV9lChoBmgJaA9DCEw2HmyxUz7AlIaUUpRoFUt7aBZHQL5LSXeWOZN1fZQoaAZoCWgPQwiAC7JleYtvQJSGlFKUaBVNLwJoFkdAvn6n8DSw4nV9lChoBmgJaA9DCH79EBss7F5AlIaUUpRoFU3oA2gWR0C+5nq2BreqdX2UKGgGaAloD0MISUkPQ2tVckCUhpRSlGgVS+9oFkdAvwDg5NoJzHV9lChoBmgJaA9DCJmByvj3iT9AlIaUUpRoFUu8aBZHQL8aFRXOnl51fZQoaAZoCWgPQwh/TkF+tkhhwJSGlFKUaBVLi2gWR0C/Gmg7xNItdX2UKGgGaAloD0MIq3gj80iLaECUhpRSlGgVTd0CaBZHQL9lecCYCyR1fZQoaAZoCWgPQwgJ+aBnc3NwQJSGlFKUaBVN/wFoFkdAv5o/9FWn0nV9lChoBmgJaA9DCHA/4IGBqnFAlIaUUpRoFU1TAmgWR0C/5wyVv/BFdX2UKGgGaAloD0MIOnr83ibtcUCUhpRSlGgVTVwBaBZHQMAAUWpqASZ1fZQoaAZoCWgPQwgIrYcvEyNxQJSGlFKUaBVNygFoFkdAwBqjYJ3PiXV9lChoBmgJaA9DCGghAaMLWHJAlIaUUpRoFU0wAmgWR0DANJk81XNkdX2UKGgGaAloD0MIP+QtVz/gbcCUhpRSlGgVS9NoFkdAwEFTN8E3bXV9lChoBmgJaA9DCAWnPpC8f29AlIaUUpRoFU2wAWgWR0DAT/6Ss8xLdWUu"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 90112,
+    "buffer_size": 1,
+    "batch_size": 128,
+    "learning_starts": 10000,
+    "tau": 1.0,
+    "gamma": 0.995,
+    "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 0x7fb9c733bb90>",
+        "add": "<function ReplayBuffer.add at 0x7fb9c733bc20>",
+        "sample": "<function ReplayBuffer.sample at 0x7fb9c6ea27a0>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fb9c6ea2830>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fb9c73925d0>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gASVYgAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RNAAFoAIwSVHJhaW5GcmVxdWVuY3lVbml0lJOUjARzdGVwlIWUUpSGlIGULg=="
+    },
+    "actor": null,
+    "use_sde_at_warmup": false,
+    "exploration_initial_eps": 1.0,
+    "exploration_final_eps": 0.18,
+    "exploration_fraction": 0.24,
+    "target_update_interval": 1,
+    "max_grad_norm": null,
+    "exploration_rate": 0.18,
+    "exploration_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_dones": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQCUdJRiLg=="
+    },
+    "remove_time_limit_termination": false,
+    "n_quantiles": 170
+}

qrdqn-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cd93ca91971e6f22cba6aadd3739db434cc4428be4435e9a46fe650f8af28bac
+size 1946177

qrdqn-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b54b60fee16ca9f9a0980b034537f9ba75642a4597ee4c9997eeb0c413be51b1
+size 1947265

qrdqn-LunarLander-v2/pytorch_variables.pth

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

qrdqn-LunarLander-v2/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

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:76624b3f98f2feb858b5d9a0120a5925c7090bcab839589dc7ae110e990e4020
+size 187684

results.json

@@ -0,0 +1 @@
+{"mean_reward": 61.433245, "std_reward": 184.2203374588998, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T16:35:45.216279"}

train_eval_metrics.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a11523310cfdb854ac880a3ff4996853ceb44ac34b8290b84ab10d3a7181415f
+size 10439