vickyjm commited on
Commit
6b21f13
1 Parent(s): 4f344d1

First trained agent using DQN

Browse files
.gitattributes CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: DQN
10
+ results:
11
+ - metrics:
12
+ - type: mean_reward
13
+ value: -152.66 +/- 155.03
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: LunarLander-v2
20
+ type: LunarLander-v2
21
+ ---
22
+
23
+ # **DQN** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **DQN** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
25
+
26
+ ## Usage (with Stable-baselines3)
27
+ TODO: Add your code
28
+
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__doc__": "\n Policy class with Q-Value Net and target net for 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 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 ", "__init__": "<function DQNPolicy.__init__ at 0x7f6847d39680>", "_build": "<function DQNPolicy._build at 0x7f6847d39710>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7f6847d397a0>", "forward": "<function DQNPolicy.forward at 0x7f6847d39830>", "_predict": "<function DQNPolicy._predict at 0x7f6847d398c0>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7f6847d39950>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7f6847d399e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6847d19de0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "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}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "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", "n": 4, "_shape": [], "dtype": "int64", "_np_random": "RandomState(MT19937)"}, "n_envs": 16, "num_timesteps": 500032, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651717436.173991, "learning_rate": 0.0001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAE3Qsb3Ulas/wfInvC8H+L2ELdU+FkZWPQAAAAAAAAAATfYaPqg5VT8skyw/JmenvqtTMj/jq2Y/AAAAAAAAAABjo4u+hM6PPzg1Oz3qM029UkUpuzqlOT4AAAAAAAAAAB1Dir52dJA/4bKAvSQmsLwRp5k8ViJyvQAAAAAAAAAAEwWsvv5vTj8uCJG98MpOPFdw2D1dg0e+AAAAAAAAAAAqysG+ZyotPubXxDyi7nG+780YPrp4+j0AAAAAAAAAANrNOj5clKA/BviyPeb2l75OFS0/mGGQPgAAAAAAAAAAzQv8vMvjoD/SY2u+biP1PGEf5r1aU9W+AAAAAAAAAACI+8e+H5EgPx6E0L3MXtc8Q3ayvV8IyL0AAAAAAAAAAMrpfb5QKpI/rtdIvf97L70i4Hg95WXvvAAAAAAAAAAAmnOEvV1iaj6vVYK/nWKGv6D0cz96Ft6+AAAAAAAAAABAYkY+D5cGP88tKz5mzXa/swrEPxrilD4AAAAAAAAAAGVMlr6xrI0/6xZ8Oppk6jtwH3y+7xc8PgAAAAAAAAAAcjymvkm5Fj9rGGu/r5ZUvcyp575gyyO/AAAAAAAAAABA9AA+n6KbP4xrLr40JJu+CyEzP5A3P70AAAAAAAAAAM0c+rvAqRs/j78VP63LPr8vl5Q/oqxXPwAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_episode_num": 1882, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -6.4000000000064e-05, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 7032, "buffer_size": 1000000, "batch_size": 32, "learning_starts": 50000, "tau": 1.0, "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:\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 0x7f6847d0e200>", "add": "<function ReplayBuffer.add at 0x7f6847d0e290>", "sample": "<function ReplayBuffer.sample at 0x7f6847d0e320>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7f6847d0e3b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6847d5ccc0>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "actor": null, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 625, "_n_calls": 31252, "max_grad_norm": 10, "exploration_rate": 0.05, "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"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": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
dqn-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:15131ce63446789bae494790d47677a5a8649b3b7d71509569d37db90cb7f383
3
+ size 108590
dqn-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
dqn-LunarLander-v2/data ADDED
@@ -0,0 +1,115 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.dqn.policies",
6
+ "__doc__": "\n Policy class with Q-Value Net and target net for 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 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 ",
7
+ "__init__": "<function DQNPolicy.__init__ at 0x7f6847d39680>",
8
+ "_build": "<function DQNPolicy._build at 0x7f6847d39710>",
9
+ "make_q_net": "<function DQNPolicy.make_q_net at 0x7f6847d397a0>",
10
+ "forward": "<function DQNPolicy.forward at 0x7f6847d39830>",
11
+ "_predict": "<function DQNPolicy._predict at 0x7f6847d398c0>",
12
+ "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7f6847d39950>",
13
+ "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7f6847d399e0>",
14
+ "__abstractmethods__": "frozenset()",
15
+ "_abc_impl": "<_abc_data object at 0x7f6847d19de0>"
16
+ },
17
+ "verbose": 1,
18
+ "policy_kwargs": {},
19
+ "observation_space": {
20
+ ":type:": "<class 'gym.spaces.box.Box'>",
21
+ ":serialized:": "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",
22
+ "dtype": "float32",
23
+ "_shape": [
24
+ 8
25
+ ],
26
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
27
+ "high": "[inf inf inf inf inf inf inf inf]",
28
+ "bounded_below": "[False False False False False False False False]",
29
+ "bounded_above": "[False False False False False False False False]",
30
+ "_np_random": null
31
+ },
32
+ "action_space": {
33
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
34
+ ":serialized:": "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",
35
+ "n": 4,
36
+ "_shape": [],
37
+ "dtype": "int64",
38
+ "_np_random": "RandomState(MT19937)"
39
+ },
40
+ "n_envs": 16,
41
+ "num_timesteps": 500032,
42
+ "_total_timesteps": 500000,
43
+ "_num_timesteps_at_start": 0,
44
+ "seed": null,
45
+ "action_noise": null,
46
+ "start_time": 1651717436.173991,
47
+ "learning_rate": 0.0001,
48
+ "tensorboard_log": null,
49
+ "lr_schedule": {
50
+ ":type:": "<class 'function'>",
51
+ ":serialized:": "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"
52
+ },
53
+ "_last_obs": {
54
+ ":type:": "<class 'numpy.ndarray'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_episode_starts": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
60
+ },
61
+ "_last_original_obs": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "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"
64
+ },
65
+ "_episode_num": 1882,
66
+ "use_sde": false,
67
+ "sde_sample_freq": -1,
68
+ "_current_progress_remaining": -6.4000000000064e-05,
69
+ "ep_info_buffer": {
70
+ ":type:": "<class 'collections.deque'>",
71
+ ":serialized:": "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"
72
+ },
73
+ "ep_success_buffer": {
74
+ ":type:": "<class 'collections.deque'>",
75
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
76
+ },
77
+ "_n_updates": 7032,
78
+ "buffer_size": 1000000,
79
+ "batch_size": 32,
80
+ "learning_starts": 50000,
81
+ "tau": 1.0,
82
+ "gamma": 0.99,
83
+ "gradient_steps": 1,
84
+ "optimize_memory_usage": false,
85
+ "replay_buffer_class": {
86
+ ":type:": "<class 'abc.ABCMeta'>",
87
+ ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
88
+ "__module__": "stable_baselines3.common.buffers",
89
+ "__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 ",
90
+ "__init__": "<function ReplayBuffer.__init__ at 0x7f6847d0e200>",
91
+ "add": "<function ReplayBuffer.add at 0x7f6847d0e290>",
92
+ "sample": "<function ReplayBuffer.sample at 0x7f6847d0e320>",
93
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x7f6847d0e3b0>",
94
+ "__abstractmethods__": "frozenset()",
95
+ "_abc_impl": "<_abc_data object at 0x7f6847d5ccc0>"
96
+ },
97
+ "replay_buffer_kwargs": {},
98
+ "train_freq": {
99
+ ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
100
+ ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
101
+ },
102
+ "actor": null,
103
+ "use_sde_at_warmup": false,
104
+ "exploration_initial_eps": 1.0,
105
+ "exploration_final_eps": 0.05,
106
+ "exploration_fraction": 0.1,
107
+ "target_update_interval": 625,
108
+ "_n_calls": 31252,
109
+ "max_grad_norm": 10,
110
+ "exploration_rate": 0.05,
111
+ "exploration_schedule": {
112
+ ":type:": "<class 'function'>",
113
+ ":serialized:": "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"
114
+ }
115
+ }
dqn-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b08e824dd04547b9acb1c26febfa18d5c062fdc1e85960720a240d278e3319ca
3
+ size 43265
dqn-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1419bbd71dacad0eec755f6da55e36fc5a351c57c5eb51f7db22b734f20404ee
3
+ size 44033
dqn-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
dqn-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.5.0
4
+ PyTorch: 1.11.0+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ea6d1c1e9c29fd23193a55161c0e3f584a2cbc7044842dc3ab28a879e643f653
3
+ size 234614
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -152.65799310686415, "std_reward": 155.03125368431546, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-05T02:37:39.952958"}