Flynews commited on
Commit
78a1fa3
·
1 Parent(s): 8474ab9

Initial commit

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
- value: -22.25 +/- 7.49
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -4.85 +/- 1.13
20
  name: mean_reward
21
  verified: false
22
  ---
a2c-PandaReachDense-v2.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:15c86acf8533e0f77b5ab850275312f9466f856cba6e5d8465c21b820ccab478
3
- size 108175
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:07531d10cfc8f02329347d7fe911348339412bdaf019d7de2a94a75dbadbefb6
3
+ size 108140
a2c-PandaReachDense-v2/data CHANGED
@@ -4,9 +4,9 @@
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 0x7f322af417e0>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc._abc_data object at 0x7f322af39b00>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
@@ -21,24 +21,24 @@
21
  "weight_decay": 0
22
  }
23
  },
24
- "num_timesteps": 1000000,
25
- "_total_timesteps": 1000000,
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
- "start_time": 1685499151014414992,
30
- "learning_rate": 0.001,
31
  "tensorboard_log": null,
32
  "lr_schedule": {
33
  ":type:": "<class 'function'>",
34
- ":serialized:": "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"
35
  },
36
  "_last_obs": {
37
  ":type:": "<class 'collections.OrderedDict'>",
38
- ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA96SsPprXAj/xNB++96SsPprXAj/xNB++96SsPprXAj/xNB++96SsPprXAj/xNB++lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAmvWCP8e/Lj/iIq8/BfmWP+7rzz8CAaE/MLq0P4G1ir+Lb20/AW4lv+mnf78i3I8+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAAD3pKw+mtcCP/E0H77ZGxc+fwi9PYXbg733pKw+mtcCP/E0H77ZGxc+fwi9PYXbg733pKw+mtcCP/E0H77ZGxc+fwi9PYXbg733pKw+mtcCP/E0H77ZGxc+fwi9PYXbg72UaA5LBEsGhpRoEnSUUpR1Lg==",
39
- "achieved_goal": "[[ 0.33719608 0.5111023 -0.1554754 ]\n [ 0.33719608 0.5111023 -0.1554754 ]\n [ 0.33719608 0.5111023 -0.1554754 ]\n [ 0.33719608 0.5111023 -0.1554754 ]]",
40
- "desired_goal": "[[ 1.0231202 0.6826138 1.368252 ]\n [ 1.1794745 1.6243875 1.2578433 ]\n [ 1.411932 -1.0836641 0.92748326]\n [-0.6462098 -0.99865586 0.28097636]]",
41
- "observation": "[[ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]\n [ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]\n [ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]\n [ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]]"
42
  },
43
  "_last_episode_starts": {
44
  ":type:": "<class 'numpy.ndarray'>",
@@ -46,9 +46,9 @@
46
  },
47
  "_last_original_obs": {
48
  ":type:": "<class 'collections.OrderedDict'>",
49
- ":serialized:": "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",
50
  "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]",
51
- "desired_goal": "[[ 0.04640411 -0.12527552 0.26571733]\n [ 0.00930319 0.07329448 0.05184944]\n [ 0.13922551 -0.01083387 0.22750333]\n [-0.0378626 -0.13950136 0.22246596]]",
52
  "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
53
  },
54
  "_episode_num": 0,
@@ -58,13 +58,13 @@
58
  "_stats_window_size": 100,
59
  "ep_info_buffer": {
60
  ":type:": "<class 'collections.deque'>",
61
- ":serialized:": "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"
62
  },
63
  "ep_success_buffer": {
64
  ":type:": "<class 'collections.deque'>",
65
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
66
  },
67
- "_n_updates": 50000,
68
  "n_steps": 5,
69
  "gamma": 0.99,
70
  "gae_lambda": 1.0,
 
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 0x7f8c8414d990>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7f8c84150340>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
 
21
  "weight_decay": 0
22
  }
23
  },
24
+ "num_timesteps": 1500000,
25
+ "_total_timesteps": 1500000,
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
+ "start_time": 1685589957853626970,
30
+ "learning_rate": 0.0009,
31
  "tensorboard_log": null,
32
  "lr_schedule": {
33
  ":type:": "<class 'function'>",
34
+ ":serialized:": "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"
35
  },
36
  "_last_obs": {
37
  ":type:": "<class 'collections.OrderedDict'>",
38
+ ":serialized:": "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",
39
+ "achieved_goal": "[[0.33106324 0.03239036 0.6774094 ]\n [0.33106324 0.03239036 0.6774094 ]\n [0.33106324 0.03239036 0.6774094 ]\n [0.33106324 0.03239036 0.6774094 ]]",
40
+ "desired_goal": "[[-0.52034277 -0.7979533 -0.74305886]\n [ 1.5005096 -0.6779417 -0.64039516]\n [-1.3034421 1.0241202 0.49833158]\n [ 0.00694187 0.31330428 1.1092832 ]]",
41
+ "observation": "[[0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]\n [0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]\n [0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]\n [0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]]"
42
  },
43
  "_last_episode_starts": {
44
  ":type:": "<class 'numpy.ndarray'>",
 
46
  },
47
  "_last_original_obs": {
48
  ":type:": "<class 'collections.OrderedDict'>",
49
+ ":serialized:": "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",
50
  "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]",
51
+ "desired_goal": "[[ 0.09027738 0.07121442 0.14873855]\n [ 0.13658468 -0.04520737 0.23848324]\n [ 0.1114696 -0.00373721 0.03432718]\n [ 0.10240789 0.14303386 0.26626354]]",
52
  "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
53
  },
54
  "_episode_num": 0,
 
58
  "_stats_window_size": 100,
59
  "ep_info_buffer": {
60
  ":type:": "<class 'collections.deque'>",
61
+ ":serialized:": "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"
62
  },
63
  "ep_success_buffer": {
64
  ":type:": "<class 'collections.deque'>",
65
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
66
  },
67
+ "_n_updates": 75000,
68
  "n_steps": 5,
69
  "gamma": 0.99,
70
  "gae_lambda": 1.0,
a2c-PandaReachDense-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:63e0ab60a3a10fdaccb5db674e8854f0cd7b81d1fdbfa4fc66b00cca541551e3
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9d66d06cbbd9edc1a7d7ffd922059229a4e88fd4dcf01d9436104441bf7dd656
3
  size 44734
a2c-PandaReachDense-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:9ca0588eee506d387dad97b889529fbfb634fe6cf0b3be1d0607377308393790
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f10448e979824cfbda6454d46381b1427b91496961d86fc10440d974fe0dc22e
3
  size 46014
config.json CHANGED
@@ -1 +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 0x7f322af417e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f322af39b00>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685499151014414992, "learning_rate": 0.001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.33719608 0.5111023 -0.1554754 ]\n [ 0.33719608 0.5111023 -0.1554754 ]\n [ 0.33719608 0.5111023 -0.1554754 ]\n [ 0.33719608 0.5111023 -0.1554754 ]]", "desired_goal": "[[ 1.0231202 0.6826138 1.368252 ]\n [ 1.1794745 1.6243875 1.2578433 ]\n [ 1.411932 -1.0836641 0.92748326]\n [-0.6462098 -0.99865586 0.28097636]]", "observation": "[[ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]\n [ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]\n [ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]\n [ 0.33719608 0.5111023 -0.1554754 0.14756717 0.09230136 -0.06438354]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]", "desired_goal": "[[ 0.04640411 -0.12527552 0.26571733]\n [ 0.00930319 0.07329448 0.05184944]\n [ 0.13922551 -0.01083387 0.22750333]\n [-0.0378626 -0.13950136 0.22246596]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+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:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIn+bkRSYYM8CUhpRSlIwBbJRLMowBdJRHQKiPtY1YQrd1fZQoaAZoCWgPQwi0yHa+nwIywJSGlFKUaBVLMmgWR0Coj2DoIOYqdX2UKGgGaAloD0MIopi8AWZ2JcCUhpRSlGgVSzJoFkdAqI8TPyCnP3V9lChoBmgJaA9DCC8YXHNHzyfAlIaUUpRoFUsyaBZHQKiO1mMfigl1fZQoaAZoCWgPQwhevYqMDrA6wJSGlFKUaBVLMmgWR0CokL7W3BpIdX2UKGgGaAloD0MI0ZDxKJXENsCUhpRSlGgVSzJoFkdAqJBqNEPUa3V9lChoBmgJaA9DCEYIjzaO8CrAlIaUUpRoFUsyaBZHQKiQHQE6kqN1fZQoaAZoCWgPQwjlfLH34lMowJSGlFKUaBVLMmgWR0Coj9//m1YydX2UKGgGaAloD0MIpSxDHOsiKcCUhpRSlGgVSzJoFkdAqJHJ8UmD2HV9lChoBmgJaA9DCPDC1mzlDSnAlIaUUpRoFUsyaBZHQKiRdWbPQfJ1fZQoaAZoCWgPQwjAe0eNCbEiwJSGlFKUaBVLMmgWR0CokSgi/wiJdX2UKGgGaAloD0MIVB9I3jmQNsCUhpRSlGgVSzJoFkdAqJDraXa8H3V9lChoBmgJaA9DCJ60cFmFfRfAlIaUUpRoFUsyaBZHQKiS24wRGtp1fZQoaAZoCWgPQwjw3Hu45HgmwJSGlFKUaBVLMmgWR0CokobZ39rHdX2UKGgGaAloD0MI8ia/RSe7J8CUhpRSlGgVSzJoFkdAqJI5eE7GN3V9lChoBmgJaA9DCOUMxR1v2jPAlIaUUpRoFUsyaBZHQKiR/FlTWG11fZQoaAZoCWgPQwh4KuCe53c+wJSGlFKUaBVLMmgWR0Cok8+Ad4mkdX2UKGgGaAloD0MI8N+8OPF1M8CUhpRSlGgVSzJoFkdAqJN6u8scyXV9lChoBmgJaA9DCHY3T3XInS3AlIaUUpRoFUsyaBZHQKiTLUMoc711fZQoaAZoCWgPQwhuMNRhhZs7wJSGlFKUaBVLMmgWR0CokvAYpDu0dX2UKGgGaAloD0MIB2ADIsQlQcCUhpRSlGgVSzJoFkdAqJTJFNL13HV9lChoBmgJaA9DCHYyOEpeFS/AlIaUUpRoFUsyaBZHQKiUdQokRjB1fZQoaAZoCWgPQwivYBvxZHs5wJSGlFKUaBVLMmgWR0ColCiSzPa+dX2UKGgGaAloD0MIYXDNHf2/OsCUhpRSlGgVSzJoFkdAqJPr2lEZznV9lChoBmgJaA9DCOz3xDpVwjDAlIaUUpRoFUsyaBZHQKiV41UlzEJ1fZQoaAZoCWgPQwhHAaJgxuQwwJSGlFKUaBVLMmgWR0ColY5iuuA7dX2UKGgGaAloD0MIhxVu+UiKKMCUhpRSlGgVSzJoFkdAqJVBPbfxc3V9lChoBmgJaA9DCGB3uvPEvzfAlIaUUpRoFUsyaBZHQKiVBDBuXNV1fZQoaAZoCWgPQwjzrKQV3zAvwJSGlFKUaBVLMmgWR0Colu4lyBCldX2UKGgGaAloD0MIwa27eaonPcCUhpRSlGgVSzJoFkdAqJaZYcNpd3V9lChoBmgJaA9DCEz/klSmcCfAlIaUUpRoFUsyaBZHQKiWS7Rv3rV1fZQoaAZoCWgPQwgCgc6kTYUrwJSGlFKUaBVLMmgWR0Colg6xHG0edX2UKGgGaAloD0MIzc03ontOJ8CUhpRSlGgVSzJoFkdAqJfvMEA5rHV9lChoBmgJaA9DCJyMKsO4rzLAlIaUUpRoFUsyaBZHQKiXmmR/3Fl1fZQoaAZoCWgPQwjv/nivWq0xwJSGlFKUaBVLMmgWR0Col00yHmA9dX2UKGgGaAloD0MIutkfKLclI8CUhpRSlGgVSzJoFkdAqJcQIF/x2HV9lChoBmgJaA9DCK0zvi8uhTrAlIaUUpRoFUsyaBZHQKiY9W3jMmp1fZQoaAZoCWgPQwhuopbmVpglwJSGlFKUaBVLMmgWR0ComKCkoF3ZdX2UKGgGaAloD0MIWmjnNAtYNcCUhpRSlGgVSzJoFkdAqJhTPppvgnV9lChoBmgJaA9DCEa0HVN3tTnAlIaUUpRoFUsyaBZHQKiYFh7Vrh11fZQoaAZoCWgPQwiDF30Fae4nwJSGlFKUaBVLMmgWR0ComfwTEit8dX2UKGgGaAloD0MIuAa2SrCALsCUhpRSlGgVSzJoFkdAqJmntIClrXV9lChoBmgJaA9DCKG8j6M5WjfAlIaUUpRoFUsyaBZHQKiZWjTrmhd1fZQoaAZoCWgPQwhNvW4RGP89wJSGlFKUaBVLMmgWR0ComR0js2NvdX2UKGgGaAloD0MIOzlDccfrPMCUhpRSlGgVSzJoFkdAqJrzodMj/3V9lChoBmgJaA9DCCAL0SFwIDXAlIaUUpRoFUsyaBZHQKianrqMWGh1fZQoaAZoCWgPQwi9qx4wDw00wJSGlFKUaBVLMmgWR0ComlE9ECvHdX2UKGgGaAloD0MIV5QSglXpNMCUhpRSlGgVSzJoFkdAqJoUIcBEKHV9lChoBmgJaA9DCHQK8rORaynAlIaUUpRoFUsyaBZHQKib6kqMFU11fZQoaAZoCWgPQwjerwJ8txknwJSGlFKUaBVLMmgWR0Com5WVu76IdX2UKGgGaAloD0MI9Ib7yK0ZKcCUhpRSlGgVSzJoFkdAqJtICMglnnV9lChoBmgJaA9DCEUTKGIRD0DAlIaUUpRoFUsyaBZHQKibCwljVhF1fZQoaAZoCWgPQwi+a9CX3i45wJSGlFKUaBVLMmgWR0ConOm9QGfPdX2UKGgGaAloD0MIk1FlGHdDKMCUhpRSlGgVSzJoFkdAqJyVBa9sanV9lChoBmgJaA9DCNEi2/l+yh3AlIaUUpRoFUsyaBZHQKicR5pJwsJ1fZQoaAZoCWgPQwgKE0azsn02wJSGlFKUaBVLMmgWR0ConApa7mMgdX2UKGgGaAloD0MIBpylZDllNMCUhpRSlGgVSzJoFkdAqJ32S+xnnXV9lChoBmgJaA9DCAjIl1DBOSrAlIaUUpRoFUsyaBZHQKidobPyCnR1fZQoaAZoCWgPQwj3d7ZHbzgnwJSGlFKUaBVLMmgWR0ConVQ53kgfdX2UKGgGaAloD0MIwjQMHxGrNcCUhpRSlGgVSzJoFkdAqJ0XEGZ/kXV9lChoBmgJaA9DCDIge737iz3AlIaUUpRoFUsyaBZHQKie+ZBLPD51fZQoaAZoCWgPQwhxHeOKi7spwJSGlFKUaBVLMmgWR0ConqYRmK64dX2UKGgGaAloD0MITBjNyvYpJMCUhpRSlGgVSzJoFkdAqJ5ZoIv8InV9lChoBmgJaA9DCHZsBOJ1qTzAlIaUUpRoFUsyaBZHQKieHXYlIEt1fZQoaAZoCWgPQwiESIYcW+83wJSGlFKUaBVLMmgWR0Con/V/DtPYdX2UKGgGaAloD0MImDPbFfpgOsCUhpRSlGgVSzJoFkdAqJ+gjUutfXV9lChoBmgJaA9DCPxR1Jl7oDXAlIaUUpRoFUsyaBZHQKifU0v4/NZ1fZQoaAZoCWgPQwjVzcXf9rw0wJSGlFKUaBVLMmgWR0ConxYtxuKodX2UKGgGaAloD0MIowOSsG+nNcCUhpRSlGgVSzJoFkdAqKD1TP0I1XV9lChoBmgJaA9DCHCUvDrHUCzAlIaUUpRoFUsyaBZHQKigoHLzPKN1fZQoaAZoCWgPQwgkuJGyRfoiwJSGlFKUaBVLMmgWR0CooFLgGbCrdX2UKGgGaAloD0MI5Nak2xIZOsCUhpRSlGgVSzJoFkdAqKAVw1ivxHV9lChoBmgJaA9DCMssQrEVNBPAlIaUUpRoFUsyaBZHQKiiVd+ocaR1fZQoaAZoCWgPQwj2evfHewUewJSGlFKUaBVLMmgWR0CoogJo0ygxdX2UKGgGaAloD0MIzehHwylDJsCUhpRSlGgVSzJoFkdAqKG2HxjJ+3V9lChoBmgJaA9DCOs56X3j+ybAlIaUUpRoFUsyaBZHQKihelfJFLF1fZQoaAZoCWgPQwi9UwH3PK8zwJSGlFKUaBVLMmgWR0CopA/PomojdX2UKGgGaAloD0MI4rA08KNaJcCUhpRSlGgVSzJoFkdAqKO8jxCpm3V9lChoBmgJaA9DCBSVDWsqkyrAlIaUUpRoFUsyaBZHQKijb9roGIN1fZQoaAZoCWgPQwiUL2ghAWMVwJSGlFKUaBVLMmgWR0CoozOtwJgLdX2UKGgGaAloD0MIPUUOETeHJcCUhpRSlGgVSzJoFkdAqKW96zE74nV9lChoBmgJaA9DCF6iemtgmy7AlIaUUpRoFUsyaBZHQKilaiMYMv11fZQoaAZoCWgPQwipM/eQ8Lk7wJSGlFKUaBVLMmgWR0CopR2OQyRCdX2UKGgGaAloD0MI1QYnol8rM8CUhpRSlGgVSzJoFkdAqKTg/keZHHV9lChoBmgJaA9DCNo8DoP5YzPAlIaUUpRoFUsyaBZHQKineOSW7e51fZQoaAZoCWgPQwgEVDiCVJopwJSGlFKUaBVLMmgWR0CopyRmseXBdX2UKGgGaAloD0MIMILGTKI+LMCUhpRSlGgVSzJoFkdAqKbXW1+iJ3V9lChoBmgJaA9DCJ6zBYTWrzTAlIaUUpRoFUsyaBZHQKimm59Vmz11fZQoaAZoCWgPQwj0hvvIrcElwJSGlFKUaBVLMmgWR0CoqTqi48U3dX2UKGgGaAloD0MIMe4G0VpJJcCUhpRSlGgVSzJoFkdAqKjmt4iX6nV9lChoBmgJaA9DCM5xbhPuOTnAlIaUUpRoFUsyaBZHQKiomjHGS6l1fZQoaAZoCWgPQwiRJ0nXTII6wJSGlFKUaBVLMmgWR0CoqF4pUgjhdX2UKGgGaAloD0MIFt9Q+GwlKsCUhpRSlGgVSzJoFkdAqKrtcyFfzHV9lChoBmgJaA9DCGABTBk4gkDAlIaUUpRoFUsyaBZHQKiqmeGwiaB1fZQoaAZoCWgPQwjrrYGtEswtwJSGlFKUaBVLMmgWR0Coqk4cvM8pdX2UKGgGaAloD0MI5zi3CfcqPsCUhpRSlGgVSzJoFkdAqKoSHARChXV9lChoBmgJaA9DCP9Cjxg9PyTAlIaUUpRoFUsyaBZHQKist6l+Eyt1fZQoaAZoCWgPQwhCI9i4/oUvwJSGlFKUaBVLMmgWR0CorGLAgxJvdX2UKGgGaAloD0MItfrqqkC9JsCUhpRSlGgVSzJoFkdAqKwVWGRFJHV9lChoBmgJaA9DCK3cC8wK8TXAlIaUUpRoFUsyaBZHQKir2JemelN1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 50000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
 
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 0x7f8c8414d990>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f8c84150340>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1500000, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685589957853626970, "learning_rate": 0.0009, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[0.33106324 0.03239036 0.6774094 ]\n [0.33106324 0.03239036 0.6774094 ]\n [0.33106324 0.03239036 0.6774094 ]\n [0.33106324 0.03239036 0.6774094 ]]", "desired_goal": "[[-0.52034277 -0.7979533 -0.74305886]\n [ 1.5005096 -0.6779417 -0.64039516]\n [-1.3034421 1.0241202 0.49833158]\n [ 0.00694187 0.31330428 1.1092832 ]]", "observation": "[[0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]\n [0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]\n [0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]\n [0.33106324 0.03239036 0.6774094 0.01832036 0.00308829 0.01582236]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01]]", "desired_goal": "[[ 0.09027738 0.07121442 0.14873855]\n [ 0.13658468 -0.04520737 0.23848324]\n [ 0.1114696 -0.00373721 0.03432718]\n [ 0.10240789 0.14303386 0.26626354]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+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": 75000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "bounded_below": "[ True True True]", "bounded_above": "[ True True True]", "_np_random": null}, "n_envs": 4, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": -22.248691538348794, "std_reward": 7.492717199884939, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-31T03:09:52.736189"}
 
1
+ {"mean_reward": -4.8486718840897085, "std_reward": 1.1323561291408646, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-01T04:53:47.949769"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:b6ba7032bc989ec6ba02217a893709e48fbb965057ac95e5257fe246a3927d22
3
  size 2387
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1adbcd3928de1e6809fa75ca3c11e847f26a8c15fba0e9d1c605c1c66df02bc4
3
  size 2387