IlluminatiPudding commited on
Commit
c4b7cb1
1 Parent(s): 53da2f7

Initial commit

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - PandaPickAndPlaceDense-v3
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: A2C
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: PandaPickAndPlaceDense-v3
16
+ type: PandaPickAndPlaceDense-v3
17
+ metrics:
18
+ - type: mean_reward
19
+ value: -50.00 +/- 0.00
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **A2C** Agent playing **PandaPickAndPlaceDense-v3**
25
+ This is a trained model of a **A2C** agent playing **PandaPickAndPlaceDense-v3**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
a2c-PandaPickAndPlaceDense-v3.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2b43b6dedba84e7770d7a8214051cde41384ca4391350a06b4e849a5fd204688
3
+ size 4464602
a2c-PandaPickAndPlaceDense-v3/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.1.0
a2c-PandaPickAndPlaceDense-v3/data ADDED
@@ -0,0 +1,101 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__doc__": "\n MultiInputActorClass policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space (Tuple)\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 ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Uses the CombinedExtractor\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 MultiInputActorCriticPolicy.__init__ at 0x7cad8f027b50>",
8
+ "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7cad8ee2db40>"
10
+ },
11
+ "verbose": 1,
12
+ "policy_kwargs": {
13
+ ":type:": "<class 'dict'>",
14
+ ":serialized:": "gAWVlgAAAAAAAAB9lCiMCG5ldF9hcmNolF2UKE0AAk0AAmWMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=",
15
+ "net_arch": [
16
+ 512,
17
+ 512
18
+ ],
19
+ "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
20
+ "optimizer_kwargs": {
21
+ "alpha": 0.99,
22
+ "eps": 1e-05,
23
+ "weight_decay": 0
24
+ }
25
+ },
26
+ "num_timesteps": 100000,
27
+ "_total_timesteps": 100000,
28
+ "_num_timesteps_at_start": 0,
29
+ "seed": null,
30
+ "action_noise": null,
31
+ "start_time": 1700036918059318801,
32
+ "learning_rate": 0.01,
33
+ "tensorboard_log": null,
34
+ "_last_obs": {
35
+ ":type:": "<class 'collections.OrderedDict'>",
36
+ ":serialized:": "gAWViwIAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAdY2XPjUelb7ljfk9aOmOP9D1+D56ivk9qwePv0AY7j56h/k99cIqvx8DvL5Ga/k9lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA3kBIP0SSlb+Y442/tYibv/cRmL9R79E/nmJnP0AWFL6mXDa/08+Qv+eKXD+XeTc/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWMAEAAAAAAACeyKU+vQmAv/nmW79w2di/ML7YP4yqND9eP0G/dY2XPjUelb7ljfk9LpOVOxPivDwhmSG8AhoGPYgQAjv3cmk9DhyAu7gBXbze+xQ7djnrPjEt3D2aWGK/fLEhP+1HjD80QIS910ZCv2jpjj/Q9fg+eor5PcWjlTsE77s8DecivGylBj0lMQI7TvppPaEEgLt7TU+8UiUVO2MkfT92UFS/sklQvxVkDT/r78Q+vBRcP2JDQr+rB4+/QBjuPnqH+T3BQpY7oKG6PKJBJLwsCgY9L9cJO+5saT3jBYC7raldvCGWETsiIyc/eOwNv6wKKT4YW40/0isCwE7w3r/pUp4/9cIqvx8DvL5Ga/k9jGOIOzdmvzzDwh+8iAAGPWZfvTk55m49XIe4O48PVLzTeBE7lGgOSwRLE4aUaBJ0lFKUdS4=",
37
+ "achieved_goal": "[[ 0.2960011 -0.2912461 0.12185267]\n [ 1.116498 0.4862504 0.12184615]\n [-1.1174215 0.46502876 0.12184043]\n [-0.6670373 -0.3672113 0.12178664]]",
38
+ "desired_goal": "[[ 0.7822398 -1.1685262 -1.1085081 ]\n [-1.2151095 -1.1880482 1.6401159 ]\n [ 0.9038485 -0.14461613 -0.7123512 ]\n [-1.1313423 0.8614945 0.71669906]]",
39
+ "observation": "[[ 3.23796213e-01 -1.00029719e+00 -8.58993113e-01 -1.69413567e+00\n 1.69330406e+00 7.05727339e-01 -7.54873157e-01 2.96001107e-01\n -2.91246086e-01 1.21852674e-01 4.56466433e-03 2.30570193e-02\n -9.86316893e-03 3.27396467e-02 1.98462792e-03 5.69944046e-02\n -3.90959438e-03 -1.34891793e-02 2.27331324e-03]\n [ 4.59422767e-01 1.07508071e-01 -8.84164453e-01 6.31614447e-01\n 1.09594500e+00 -6.45755827e-02 -7.58893430e-01 1.11649799e+00\n 4.86250401e-01 1.21846154e-01 4.56664199e-03 2.29411200e-02\n -9.94278211e-03 3.28726023e-02 1.98657182e-03 5.71234748e-02\n -3.90680181e-03 -1.26527501e-02 2.27578403e-03]\n [ 9.88836467e-01 -8.29352736e-01 -8.13624501e-01 5.52308381e-01\n 3.84642929e-01 8.59691381e-01 -7.58840680e-01 -1.11742151e+00\n 4.65028763e-01 1.21840432e-01 4.58559440e-03 2.27821469e-02\n -1.00254137e-02 3.27245444e-02 2.10328004e-03 5.69886491e-02\n -3.90695175e-03 -1.35292234e-02 2.22147279e-03]\n [ 6.52879834e-01 -5.54389477e-01 1.65079772e-01 1.10434246e+00\n -2.03392458e+00 -1.74170852e+00 1.23690522e+00 -6.67037308e-01\n -3.67211312e-01 1.21786639e-01 4.16225754e-03 2.33641695e-02\n -9.75102466e-03 3.27153504e-02 3.61199665e-04 5.83250262e-02\n 5.63137047e-03 -1.29431626e-02 2.21972610e-03]]"
40
+ },
41
+ "_last_episode_starts": {
42
+ ":type:": "<class 'numpy.ndarray'>",
43
+ ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
44
+ },
45
+ "_last_original_obs": {
46
+ ":type:": "<class 'collections.OrderedDict'>",
47
+ ":serialized:": "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",
48
+ "achieved_goal": "[[ 0.04761137 0.10900217 0.02 ]\n [-0.00390747 0.05689282 0.02 ]\n [ 0.02571593 -0.01103526 0.02 ]\n [ 0.01496781 0.02011522 0.02 ]]",
49
+ "desired_goal": "[[ 0.07480109 -0.04644612 0.02 ]\n [ 0.09397784 -0.05967098 0.05804545]\n [ 0.00049746 -0.02603252 0.1518571 ]\n [ 0.07438047 -0.09177639 0.14068975]]",
50
+ "observation": "[[ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 4.76113707e-02\n 1.09002165e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -3.90747190e-03\n 5.68928234e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 2.57159341e-02\n -1.10352552e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 1.49678104e-02\n 2.01152209e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]]"
51
+ },
52
+ "_episode_num": 0,
53
+ "use_sde": false,
54
+ "sde_sample_freq": -1,
55
+ "_current_progress_remaining": 0.0,
56
+ "_stats_window_size": 100,
57
+ "ep_info_buffer": {
58
+ ":type:": "<class 'collections.deque'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "ep_success_buffer": {
62
+ ":type:": "<class 'collections.deque'>",
63
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
64
+ },
65
+ "_n_updates": 1250,
66
+ "n_steps": 20,
67
+ "gamma": 0.99,
68
+ "gae_lambda": 0.95,
69
+ "ent_coef": 0.1,
70
+ "vf_coef": 0.5,
71
+ "max_grad_norm": 0.5,
72
+ "normalize_advantage": true,
73
+ "observation_space": {
74
+ ":type:": "<class 'gymnasium.spaces.dict.Dict'>",
75
+ ":serialized:": "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",
76
+ "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (19,), float32))])",
77
+ "_shape": null,
78
+ "dtype": null,
79
+ "_np_random": null
80
+ },
81
+ "action_space": {
82
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
83
+ ":serialized:": "gAWVpwEAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWBAAAAAAAAAABAQEBlGgIjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKUjA1ib3VuZGVkX2Fib3ZllGgRKJYEAAAAAAAAAAEBAQGUaBVLBIWUaBl0lFKUjAZfc2hhcGWUSwSFlIwDbG93lGgRKJYQAAAAAAAAAAAAgL8AAIC/AACAvwAAgL+UaAtLBIWUaBl0lFKUjARoaWdolGgRKJYQAAAAAAAAAAAAgD8AAIA/AACAPwAAgD+UaAtLBIWUaBl0lFKUjAhsb3dfcmVwcpSMBC0xLjCUjAloaWdoX3JlcHKUjAMxLjCUjApfbnBfcmFuZG9tlE51Yi4=",
84
+ "dtype": "float32",
85
+ "bounded_below": "[ True True True True]",
86
+ "bounded_above": "[ True True True True]",
87
+ "_shape": [
88
+ 4
89
+ ],
90
+ "low": "[-1. -1. -1. -1.]",
91
+ "high": "[1. 1. 1. 1.]",
92
+ "low_repr": "-1.0",
93
+ "high_repr": "1.0",
94
+ "_np_random": null
95
+ },
96
+ "n_envs": 4,
97
+ "lr_schedule": {
98
+ ":type:": "<class 'function'>",
99
+ ":serialized:": "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"
100
+ }
101
+ }
a2c-PandaPickAndPlaceDense-v3/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1494557679864244fe80f25a4a17e4dfcecbfc7d6d49cbb6414423d3a5b50261
3
+ size 2222063
a2c-PandaPickAndPlaceDense-v3/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e4d0b21b256ca61e33152c8baefea88840279c5e11c3920d4b03092efc9be1e4
3
+ size 2223343
a2c-PandaPickAndPlaceDense-v3/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
a2c-PandaPickAndPlaceDense-v3/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.1.0
4
+ - PyTorch: 2.1.0+cu118
5
+ - GPU Enabled: False
6
+ - Numpy: 1.23.5
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.29.1
9
+ - OpenAI Gym: 0.25.2
config.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVRQAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMG011bHRpSW5wdXRBY3RvckNyaXRpY1BvbGljeZSTlC4=", "__module__": "stable_baselines3.common.policies", "__doc__": "\n MultiInputActorClass policy class for actor-critic algorithms (has both policy and value prediction).\n Used by A2C, PPO and the likes.\n\n :param observation_space: Observation space (Tuple)\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 ortho_init: Whether to use or not orthogonal initialization\n :param use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param full_std: Whether to use (n_features x n_actions) parameters\n for the std instead of only (n_features,) when using gSDE\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Uses the CombinedExtractor\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 MultiInputActorCriticPolicy.__init__ at 0x7cad8f027b50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7cad8ee2db40>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVlgAAAAAAAAB9lCiMCG5ldF9hcmNolF2UKE0AAk0AAmWMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "net_arch": [512, 512], "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 100000, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700036918059318801, "learning_rate": 0.01, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.2960011 -0.2912461 0.12185267]\n [ 1.116498 0.4862504 0.12184615]\n [-1.1174215 0.46502876 0.12184043]\n [-0.6670373 -0.3672113 0.12178664]]", "desired_goal": "[[ 0.7822398 -1.1685262 -1.1085081 ]\n [-1.2151095 -1.1880482 1.6401159 ]\n [ 0.9038485 -0.14461613 -0.7123512 ]\n [-1.1313423 0.8614945 0.71669906]]", "observation": "[[ 3.23796213e-01 -1.00029719e+00 -8.58993113e-01 -1.69413567e+00\n 1.69330406e+00 7.05727339e-01 -7.54873157e-01 2.96001107e-01\n -2.91246086e-01 1.21852674e-01 4.56466433e-03 2.30570193e-02\n -9.86316893e-03 3.27396467e-02 1.98462792e-03 5.69944046e-02\n -3.90959438e-03 -1.34891793e-02 2.27331324e-03]\n [ 4.59422767e-01 1.07508071e-01 -8.84164453e-01 6.31614447e-01\n 1.09594500e+00 -6.45755827e-02 -7.58893430e-01 1.11649799e+00\n 4.86250401e-01 1.21846154e-01 4.56664199e-03 2.29411200e-02\n -9.94278211e-03 3.28726023e-02 1.98657182e-03 5.71234748e-02\n -3.90680181e-03 -1.26527501e-02 2.27578403e-03]\n [ 9.88836467e-01 -8.29352736e-01 -8.13624501e-01 5.52308381e-01\n 3.84642929e-01 8.59691381e-01 -7.58840680e-01 -1.11742151e+00\n 4.65028763e-01 1.21840432e-01 4.58559440e-03 2.27821469e-02\n -1.00254137e-02 3.27245444e-02 2.10328004e-03 5.69886491e-02\n -3.90695175e-03 -1.35292234e-02 2.22147279e-03]\n [ 6.52879834e-01 -5.54389477e-01 1.65079772e-01 1.10434246e+00\n -2.03392458e+00 -1.74170852e+00 1.23690522e+00 -6.67037308e-01\n -3.67211312e-01 1.21786639e-01 4.16225754e-03 2.33641695e-02\n -9.75102466e-03 3.27153504e-02 3.61199665e-04 5.83250262e-02\n 5.63137047e-03 -1.29431626e-02 2.21972610e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.04761137 0.10900217 0.02 ]\n [-0.00390747 0.05689282 0.02 ]\n [ 0.02571593 -0.01103526 0.02 ]\n [ 0.01496781 0.02011522 0.02 ]]", "desired_goal": "[[ 0.07480109 -0.04644612 0.02 ]\n [ 0.09397784 -0.05967098 0.05804545]\n [ 0.00049746 -0.02603252 0.1518571 ]\n [ 0.07438047 -0.09177639 0.14068975]]", "observation": "[[ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 4.76113707e-02\n 1.09002165e-01 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 -3.90747190e-03\n 5.68928234e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 2.57159341e-02\n -1.10352552e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]\n [ 3.84396687e-02 -2.19447225e-12 1.97400138e-01 0.00000000e+00\n -0.00000000e+00 0.00000000e+00 0.00000000e+00 1.49678104e-02\n 2.01152209e-02 1.99999996e-02 0.00000000e+00 -0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n 0.00000000e+00 0.00000000e+00 0.00000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 1250, "n_steps": 20, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.1, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": true, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (19,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True True True True]", "bounded_above": "[ True True True True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.0+cu118", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}
replay.mp4 ADDED
Binary file (882 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": -50.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-15T08:44:18.601159"}
vec_normalize.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:214239642c21aded9bd362cf63d92711d0c86c3f0b98d1d0fe98b466d9a00b54
3
+ size 3013