Initial commit

.gitattributes

@@ -29,3 +29,4 @@ 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 +1,67 @@
+---
+library_name: stable-baselines3
+tags:
+- CartPole-v1
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: QRDQN
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 500.00 +/- 0.00
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: CartPole-v1
+      type: CartPole-v1
+---
+
+# **QRDQN** Agent playing **CartPole-v1**
+This is a trained model of a **QRDQN** agent playing **CartPole-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 qrdqn --env CartPole-v1 -orga jackoyoungblood -f logs/
+python enjoy.py --algo qrdqn --env CartPole-v1  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python train.py --algo qrdqn --env CartPole-v1 -f logs/
+# Upload the model and generate video (when possible)
+python -m utils.push_to_hub --algo qrdqn --env CartPole-v1 -f logs/ -orga jackoyoungblood
+```
+
+## Hyperparameters
+```python
+OrderedDict([('batch_size', 64),
+             ('buffer_size', 100000),
+             ('exploration_final_eps', 0.04),
+             ('exploration_fraction', 0.16),
+             ('gamma', 0.99),
+             ('gradient_steps', 128),
+             ('learning_rate', 0.0023),
+             ('learning_starts', 1000),
+             ('n_timesteps', 50000.0),
+             ('policy', 'MlpPolicy'),
+             ('policy_kwargs', 'dict(net_arch=[256, 256], n_quantiles=10)'),
+             ('target_update_interval', 10),
+             ('train_freq', 256),
+             ('normalize', False)])
+```

args.yml

@@ -0,0 +1,75 @@
+!!python/object/apply:collections.OrderedDict
+- - - algo
+    - qrdqn
+  - - device
+    - auto
+  - - env
+    - CartPole-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
+  - - pruner
+    - median
+  - - sampler
+    - tpe
+  - - save_freq
+    - -1
+  - - save_replay_buffer
+    - false
+  - - seed
+    - 954031387
+  - - 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

config.yml

@@ -0,0 +1,27 @@
+!!python/object/apply:collections.OrderedDict
+- - - batch_size
+    - 64
+  - - buffer_size
+    - 100000
+  - - exploration_final_eps
+    - 0.04
+  - - exploration_fraction
+    - 0.16
+  - - gamma
+    - 0.99
+  - - gradient_steps
+    - 128
+  - - learning_rate
+    - 0.0023
+  - - learning_starts
+    - 1000
+  - - n_timesteps
+    - 50000.0
+  - - policy
+    - MlpPolicy
+  - - policy_kwargs
+    - dict(net_arch=[256, 256], n_quantiles=10)
+  - - target_update_interval
+    - 10
+  - - train_freq
+    - 256

env_kwargs.yml

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

qrdqn-CartPole-v1.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:db4ad370ad82252ed7587db7eedd4a7dcb9298d5e75b648ddcb98d100f31e3f1
+size 1184899

qrdqn-CartPole-v1/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.0

qrdqn-CartPole-v1/data

@@ -0,0 +1,127 @@
+{
+    "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 0x7fc6de66dc20>",
+        "_build": "<function QRDQNPolicy._build at 0x7fc6de66dcb0>",
+        "make_quantile_net": "<function QRDQNPolicy.make_quantile_net at 0x7fc6de66dd40>",
+        "forward": "<function QRDQNPolicy.forward at 0x7fc6de66ddd0>",
+        "_predict": "<function QRDQNPolicy._predict at 0x7fc6de66de60>",
+        "_get_constructor_parameters": "<function QRDQNPolicy._get_constructor_parameters at 0x7fc6de66def0>",
+        "set_training_mode": "<function QRDQNPolicy.set_training_mode at 0x7fc6de66df80>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fc6de66c1b0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        ":type:": "<class 'dict'>",
+        ":serialized:": "gASVfQAAAAAAAAB9lCiMCG5ldF9hcmNolF2UKE0AAU0AAWWMC25fcXVhbnRpbGVzlEsKjA9vcHRpbWl6ZXJfY2xhc3OUjBB0b3JjaC5vcHRpbS5hZGFtlIwEQWRhbZSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lIwDZXBzlEc/JHrhR64Ue3N1Lg==",
+        "net_arch": [
+            256,
+            256
+        ],
+        "n_quantiles": 10,
+        "optimizer_class": "<class 'torch.optim.adam.Adam'>",
+        "optimizer_kwargs": {
+            "eps": 0.00015625
+        }
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "gASVmwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLBIWUjANsb3eUjBVudW1weS5jb3JlLm11bHRpYXJyYXmUjAxfcmVjb25zdHJ1Y3SUk5RoBowHbmRhcnJheZSTlEsAhZRDAWKUh5RSlChLAUsEhZRoColDEJqZmcD//3//UHfWvv//f/+UdJRijARoaWdolGgSaBRLAIWUaBaHlFKUKEsBSwSFlGgKiUMQmpmZQP//f39Qd9Y+//9/f5R0lGKMDWJvdW5kZWRfYmVsb3eUaBJoFEsAhZRoFoeUUpQoSwFLBIWUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGKJQwQBAQEBlHSUYowNYm91bmRlZF9hYm92ZZRoEmgUSwCFlGgWh5RSlChLAUsEhZRoKolDBAEBAQGUdJRijApfbnBfcmFuZG9tlE51Yi4=",
+        "dtype": "float32",
+        "_shape": [
+            4
+        ],
+        "low": "[-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38]",
+        "high": "[4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38]",
+        "bounded_below": "[ True  True  True  True]",
+        "bounded_above": "[ True  True  True  True]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "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",
+        "n": 2,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": "RandomState(MT19937)"
+    },
+    "n_envs": 1,
+    "num_timesteps": 50176,
+    "_total_timesteps": 50000,
+    "_num_timesteps_at_start": 0,
+    "seed": 0,
+    "action_noise": null,
+    "start_time": 1660940826.4835405,
+    "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": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQGUdJRiLg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASVmgAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLBIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUMQABwHP0n5Z74cmd02VAuePpR0lGIu"
+    },
+    "_episode_num": 329,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.0035199999999999676,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 24704,
+    "buffer_size": 1,
+    "batch_size": 64,
+    "learning_starts": 1000,
+    "tau": 1.0,
+    "gamma": 0.99,
+    "gradient_steps": 128,
+    "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        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 0x7fc6deec47a0>",
+        "add": "<function ReplayBuffer.add at 0x7fc6deec4830>",
+        "sample": "<function ReplayBuffer.sample at 0x7fc6deeb1830>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fc6deeb18c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fc6def2c060>"
+    },
+    "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": 0.04,
+    "exploration_fraction": 0.16,
+    "target_update_interval": 10,
+    "max_grad_norm": null,
+    "exploration_rate": 0.04,
+    "exploration_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "n_quantiles": 10
+}

qrdqn-CartPole-v1/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d1c9cfd0bc1fb39a0d735743a13786de57552e69afb8985120d910888c86f455
+size 582703

qrdqn-CartPole-v1/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd0f70f89722c8f13cace188dc22bcefa3db7aca1405455ad1ff0f4617b17f42
+size 582145

qrdqn-CartPole-v1/pytorch_variables.pth

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

qrdqn-CartPole-v1/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.6.0
+PyTorch: 1.12.1+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5899f808360727250caae83207d3c8040dc1d274685a68b71bd844c916eef8bd
+size 97148

results.json

@@ -0,0 +1 @@
+{"mean_reward": 500.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-19T20:33:08.288855"}

train_eval_metrics.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6c0122d1e420041d390b18f6110986173c4dd19445396ffe0ba7cfda9de70e5
+size 7624