hmatzner commited on
Commit
b153c01
·
1 Parent(s): d6f9096

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: -5.54 +/- 1.98
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -2.60 +/- 0.31
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:a0425755472f4c6602427cbc14223e9ac1e66f08089575de634db70aee368c2e
3
- size 108112
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2530647ee9662bb166ad8d5019b73be6b58fd1defb50fe6678e837bc863164bb
3
+ size 108031
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 0x7f68048a3ca0>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc._abc_data object at 0x7f68048a4840>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
@@ -41,12 +41,12 @@
41
  "_np_random": null
42
  },
43
  "n_envs": 4,
44
- "num_timesteps": 1000000,
45
- "_total_timesteps": 1000000,
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
- "start_time": 1678833656119836102,
50
  "learning_rate": 0.0007,
51
  "tensorboard_log": null,
52
  "lr_schedule": {
@@ -55,35 +55,35 @@
55
  },
56
  "_last_obs": {
57
  ":type:": "<class 'collections.OrderedDict'>",
58
- ":serialized:": "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",
59
- "achieved_goal": "[[ 0.42895767 -0.01364501 0.5681501 ]\n [ 0.42895767 -0.01364501 0.5681501 ]\n [ 0.42895767 -0.01364501 0.5681501 ]\n [ 0.42895767 -0.01364501 0.5681501 ]]",
60
- "desired_goal": "[[ 0.8519468 0.8977332 -1.6962115 ]\n [-0.47663745 0.08586018 1.7218342 ]\n [ 1.0816345 1.0456562 -0.49753037]\n [ 1.3278255 -1.5712098 -1.3336046 ]]",
61
- "observation": "[[ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]\n [ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]\n [ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]\n [ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]]"
62
  },
63
  "_last_episode_starts": {
64
  ":type:": "<class 'numpy.ndarray'>",
65
- ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
66
  },
67
  "_last_original_obs": {
68
  ":type:": "<class 'collections.OrderedDict'>",
69
- ":serialized:": "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",
70
  "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]]",
71
- "desired_goal": "[[ 0.08729581 0.01930482 0.15064453]\n [ 0.06469046 0.1315761 0.2495755 ]\n [-0.00449805 -0.08541884 0.1368721 ]\n [-0.0383497 -0.13406707 0.14166191]]",
72
  "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]]"
73
  },
74
  "_episode_num": 0,
75
  "use_sde": false,
76
  "sde_sample_freq": -1,
77
- "_current_progress_remaining": 0.0,
78
  "ep_info_buffer": {
79
  ":type:": "<class 'collections.deque'>",
80
- ":serialized:": "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"
81
  },
82
  "ep_success_buffer": {
83
  ":type:": "<class 'collections.deque'>",
84
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
85
  },
86
- "_n_updates": 50000,
87
  "n_steps": 5,
88
  "gamma": 0.99,
89
  "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 0x7efdbfa08940>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7efdbfa07b80>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
 
41
  "_np_random": null
42
  },
43
  "n_envs": 4,
44
+ "num_timesteps": 565328,
45
+ "_total_timesteps": 2000000,
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
+ "start_time": 1678881008777321831,
50
  "learning_rate": 0.0007,
51
  "tensorboard_log": null,
52
  "lr_schedule": {
 
55
  },
56
  "_last_obs": {
57
  ":type:": "<class 'collections.OrderedDict'>",
58
+ ":serialized:": "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",
59
+ "achieved_goal": "[[ 0.9313481 -0.59487677 1.3146749 ]\n [ 1.4816362 -0.731883 1.3189118 ]\n [ 1.2300248 1.1648902 1.3348217 ]\n [-0.22794023 1.9976226 -1.4753538 ]]",
60
+ "desired_goal": "[[ 0.75207084 0.05955319 1.2870045 ]\n [ 1.1278942 -0.15353139 1.188598 ]\n [ 1.283051 1.5947603 0.9386373 ]\n [ 0.53671366 1.2534524 -1.7419766 ]]",
61
+ "observation": "[[ 0.9313481 -0.59487677 1.3146749 0.06016719 0.85709846 -0.4712574 ]\n [ 1.4816362 -0.731883 1.3189118 0.19356732 -1.3663099 0.32619026]\n [ 1.2300248 1.1648902 1.3348217 -0.0647987 0.09409437 -0.10547093]\n [-0.22794023 1.9976226 -1.4753538 0.11196173 -0.17313528 0.09368642]]"
62
  },
63
  "_last_episode_starts": {
64
  ":type:": "<class 'numpy.ndarray'>",
65
+ ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
66
  },
67
  "_last_original_obs": {
68
  ":type:": "<class 'collections.OrderedDict'>",
69
+ ":serialized:": "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",
70
  "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]]",
71
+ "desired_goal": "[[ 0.08920029 0.01652903 0.2350542 ]\n [-0.08932706 0.0776669 0.2866473 ]\n [-0.07434526 -0.09890816 0.25848582]\n [-0.0938732 0.05775383 0.26806515]]",
72
  "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]]"
73
  },
74
  "_episode_num": 0,
75
  "use_sde": false,
76
  "sde_sample_freq": -1,
77
+ "_current_progress_remaining": 0.71734,
78
  "ep_info_buffer": {
79
  ":type:": "<class 'collections.deque'>",
80
+ ":serialized:": "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"
81
  },
82
  "ep_success_buffer": {
83
  ":type:": "<class 'collections.deque'>",
84
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
85
  },
86
+ "_n_updates": 28266,
87
  "n_steps": 5,
88
  "gamma": 0.99,
89
  "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 sha256:55b09fc2c350d13bee1637d4a8a6ac446d3c396bcb236d8b2c8b8f43a3f2eaa6
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:71436daa3c8f4b78935a9b940a9d7ab45da66bbf39a2c229e688ffaf44babdbd
3
  size 44734
a2c-PandaReachDense-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8e0e3189daa91a10f34bb98d1ccc21f9031eb2ea8a493832882cda1048503363
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:22753ea630f85978ffa99d37d6951e4df7d9a1e6bf4093b74fc81e2414aaccf7
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 0x7f68048a3ca0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f68048a4840>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "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, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678833656119836102, "learning_rate": 0.0007, "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": "[[ 0.42895767 -0.01364501 0.5681501 ]\n [ 0.42895767 -0.01364501 0.5681501 ]\n [ 0.42895767 -0.01364501 0.5681501 ]\n [ 0.42895767 -0.01364501 0.5681501 ]]", "desired_goal": "[[ 0.8519468 0.8977332 -1.6962115 ]\n [-0.47663745 0.08586018 1.7218342 ]\n [ 1.0816345 1.0456562 -0.49753037]\n [ 1.3278255 -1.5712098 -1.3336046 ]]", "observation": "[[ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]\n [ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]\n [ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]\n [ 4.2895767e-01 -1.3645006e-02 5.6815010e-01 -8.4613040e-03\n -9.4519506e-05 -1.2648076e-02]]"}, "_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": "[[ 0.08729581 0.01930482 0.15064453]\n [ 0.06469046 0.1315761 0.2495755 ]\n [-0.00449805 -0.08541884 0.1368721 ]\n [-0.0383497 -0.13406707 0.14166191]]", "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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "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 0x7efdbfa08940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7efdbfa07b80>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "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, "num_timesteps": 565328, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1678881008777321831, "learning_rate": 0.0007, "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": "[[ 0.9313481 -0.59487677 1.3146749 ]\n [ 1.4816362 -0.731883 1.3189118 ]\n [ 1.2300248 1.1648902 1.3348217 ]\n [-0.22794023 1.9976226 -1.4753538 ]]", "desired_goal": "[[ 0.75207084 0.05955319 1.2870045 ]\n [ 1.1278942 -0.15353139 1.188598 ]\n [ 1.283051 1.5947603 0.9386373 ]\n [ 0.53671366 1.2534524 -1.7419766 ]]", "observation": "[[ 0.9313481 -0.59487677 1.3146749 0.06016719 0.85709846 -0.4712574 ]\n [ 1.4816362 -0.731883 1.3189118 0.19356732 -1.3663099 0.32619026]\n [ 1.2300248 1.1648902 1.3348217 -0.0647987 0.09409437 -0.10547093]\n [-0.22794023 1.9976226 -1.4753538 0.11196173 -0.17313528 0.09368642]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAApK62PeNnhzwMsnA+G/G2vdMPnz1vw5I+VEKYvV2Qyr1BWIQ+l0DAvUiPbD3WP4k+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[ 0.08920029 0.01652903 0.2350542 ]\n [-0.08932706 0.0776669 0.2866473 ]\n [-0.07434526 -0.09890816 0.25848582]\n [-0.0938732 0.05775383 0.26806515]]", "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": 0.71734, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIcHuCxHZ3CMCUhpRSlIwBbJRLMowBdJRHQJsE/ADaGpN1fZQoaAZoCWgPQwiAYI4ev8cQwJSGlFKUaBVLMmgWR0CbBH+ZPVNIdX2UKGgGaAloD0MIRzzZzYw+CsCUhpRSlGgVSzJoFkdAmwP5oTPBznV9lChoBmgJaA9DCBOaJJaUOxHAlIaUUpRoFUsyaBZHQJsDeQ7tAs11fZQoaAZoCWgPQwgHsTOFzisNwJSGlFKUaBVLMmgWR0CbCDBWPtD2dX2UKGgGaAloD0MIUd7H0Rw5EsCUhpRSlGgVSzJoFkdAmwezSgGr0nV9lChoBmgJaA9DCBQjS+ZYngXAlIaUUpRoFUsyaBZHQJsHLibUgB91fZQoaAZoCWgPQwhjfm5oyg4IwJSGlFKUaBVLMmgWR0CbBq2tdRixdX2UKGgGaAloD0MIKh2s/3MYBcCUhpRSlGgVSzJoFkdAmwuB99c8knV9lChoBmgJaA9DCKwDIO7qdQXAlIaUUpRoFUsyaBZHQJsLBa5f+jx1fZQoaAZoCWgPQwgbZ9MRwM0DwJSGlFKUaBVLMmgWR0CbCn/gzguRdX2UKGgGaAloD0MIcZNRZRg3BsCUhpRSlGgVSzJoFkdAmwn+j2zv7XV9lChoBmgJaA9DCGDl0CLb+QPAlIaUUpRoFUsyaBZHQJsNmo5xR2t1fZQoaAZoCWgPQwgmHHqLhxcOwJSGlFKUaBVLMmgWR0CbDRxXGOuJdX2UKGgGaAloD0MIpivYRjw5CcCUhpRSlGgVSzJoFkdAmwyVVYISlHV9lChoBmgJaA9DCLclcsEZvAjAlIaUUpRoFUsyaBZHQJsMEl9jPOZ1fZQoaAZoCWgPQwg6dlCJ69gIwJSGlFKUaBVLMmgWR0CbD4QSi/O/dX2UKGgGaAloD0MI6/1GO27YCMCUhpRSlGgVSzJoFkdAmw8Flbu+iHV9lChoBmgJaA9DCN7Jp8e2DATAlIaUUpRoFUsyaBZHQJsOflGPPs11fZQoaAZoCWgPQwhZMVwdAGEQwJSGlFKUaBVLMmgWR0CbDfupjtojdX2UKGgGaAloD0MIJm4VxEBXAsCUhpRSlGgVSzJoFkdAmxFpGOMl1XV9lChoBmgJaA9DCORlTSzwNQbAlIaUUpRoFUsyaBZHQJsQ6qLjxTd1fZQoaAZoCWgPQwgRHQJHAs0KwJSGlFKUaBVLMmgWR0CbEGNR3u/ldX2UKGgGaAloD0MIk40HW+wWCMCUhpRSlGgVSzJoFkdAmw/gnQY1pHV9lChoBmgJaA9DCDdRS3MrhAfAlIaUUpRoFUsyaBZHQJsTZFNL1291fZQoaAZoCWgPQwgpsWt7uzUTwJSGlFKUaBVLMmgWR0CbEuXkYGdJdX2UKGgGaAloD0MIxCKGHcbkC8CUhpRSlGgVSzJoFkdAmxJemelKsnV9lChoBmgJaA9DCEQ0uoPYGQfAlIaUUpRoFUsyaBZHQJsR3IKc/dJ1fZQoaAZoCWgPQwgYJlMFoxIGwJSGlFKUaBVLMmgWR0CbFVGBFuvVdX2UKGgGaAloD0MI+3WnO0+8DsCUhpRSlGgVSzJoFkdAmxTTMFEApHV9lChoBmgJaA9DCG4164zvCwPAlIaUUpRoFUsyaBZHQJsUS+VTrE91fZQoaAZoCWgPQwj4ja89swQMwJSGlFKUaBVLMmgWR0CbE8koF3Y+dX2UKGgGaAloD0MIBfwaSYIwEMCUhpRSlGgVSzJoFkdAmxcqyfL9uXV9lChoBmgJaA9DCL3+JD53ggXAlIaUUpRoFUsyaBZHQJsWrCMxXXB1fZQoaAZoCWgPQwgXm1YKgfwKwJSGlFKUaBVLMmgWR0CbFiS7GvOhdX2UKGgGaAloD0MI7zob8s/MBsCUhpRSlGgVSzJoFkdAmxWhyS3b23V9lChoBmgJaA9DCNBjlGdeLg3AlIaUUpRoFUsyaBZHQJsZLTH80k51fZQoaAZoCWgPQwgnZyjueBMDwJSGlFKUaBVLMmgWR0CbGK70Fr2ydX2UKGgGaAloD0MINZiG4SNCAcCUhpRSlGgVSzJoFkdAmxgnjdYW+HV9lChoBmgJaA9DCJlFKLaCBhDAlIaUUpRoFUsyaBZHQJsXpKRMewN1fZQoaAZoCWgPQwh7hnDMskcKwJSGlFKUaBVLMmgWR0CbGyOIZZSvdX2UKGgGaAloD0MIHZCEfTsJA8CUhpRSlGgVSzJoFkdAmxqlEJBw/HV9lChoBmgJaA9DCFU01v7ONgPAlIaUUpRoFUsyaBZHQJsaHmV7hNx1fZQoaAZoCWgPQwg5s12hDzYBwJSGlFKUaBVLMmgWR0CbGZulXRw7dX2UKGgGaAloD0MI9KljldKzDMCUhpRSlGgVSzJoFkdAmxzx//echHV9lChoBmgJaA9DCHOh8q/lhRDAlIaUUpRoFUsyaBZHQJscc3PzFuN1fZQoaAZoCWgPQwiCx7d3DfoCwJSGlFKUaBVLMmgWR0CbG+vmHP/rdX2UKGgGaAloD0MIDhE3p5IBCcCUhpRSlGgVSzJoFkdAmxtozSCvo3V9lChoBmgJaA9DCKZDp+fdWAfAlIaUUpRoFUsyaBZHQJsewzZYgaF1fZQoaAZoCWgPQwikp8gh4sYKwJSGlFKUaBVLMmgWR0CbHkYx+KCQdX2UKGgGaAloD0MIkLxzKEMVBcCUhpRSlGgVSzJoFkdAmx3AUcn3L3V9lChoBmgJaA9DCFTFVPoJZwjAlIaUUpRoFUsyaBZHQJsdPv7WNFV1fZQoaAZoCWgPQwjjOPBquVMOwJSGlFKUaBVLMmgWR0CbILT6BRQ8dX2UKGgGaAloD0MIn+OjxRnjB8CUhpRSlGgVSzJoFkdAmyA2kzoECHV9lChoBmgJaA9DCDPC24MQsALAlIaUUpRoFUsyaBZHQJsfryPMjeN1fZQoaAZoCWgPQwhgVijS/RwLwJSGlFKUaBVLMmgWR0CbHywe/5+IdX2UKGgGaAloD0MI6LtbWaIzA8CUhpRSlGgVSzJoFkdAmyKRiPQv6HV9lChoBmgJaA9DCNBk/zwN2AbAlIaUUpRoFUsyaBZHQJsiEtyxRl91fZQoaAZoCWgPQwgyc4HLY60OwJSGlFKUaBVLMmgWR0CbIYt03fhudX2UKGgGaAloD0MIARO4dTevBcCUhpRSlGgVSzJoFkdAmyEIouwos3V9lChoBmgJaA9DCFr1udqKHQfAlIaUUpRoFUsyaBZHQJskh0V8CxN1fZQoaAZoCWgPQwiC4VzDDA3+v5SGlFKUaBVLMmgWR0CbJAixmkFfdX2UKGgGaAloD0MIyaze4XbIAsCUhpRSlGgVSzJoFkdAmyOB2KVIJHV9lChoBmgJaA9DCKg0YmafxwTAlIaUUpRoFUsyaBZHQJsi/3XZoPF1fZQoaAZoCWgPQwhi2cwhqQUIwJSGlFKUaBVLMmgWR0CbJm1QqI8AdX2UKGgGaAloD0MIoFT7dDx2EcCUhpRSlGgVSzJoFkdAmyXur6tT1nV9lChoBmgJaA9DCNi8qrNa4ATAlIaUUpRoFUsyaBZHQJslZ1jiGWV1fZQoaAZoCWgPQwh1P6cgP1sEwJSGlFKUaBVLMmgWR0CbJORceKbbdX2UKGgGaAloD0MIvJAOD2F8BMCUhpRSlGgVSzJoFkdAmyhGrGR3eXV9lChoBmgJaA9DCN7n+GhxRgzAlIaUUpRoFUsyaBZHQJsnyATZg5R1fZQoaAZoCWgPQwhNwK+RJEgKwJSGlFKUaBVLMmgWR0CbJ0Cwr1/UdX2UKGgGaAloD0MIwFlKlpMQAcCUhpRSlGgVSzJoFkdAmya9q+JxenV9lChoBmgJaA9DCC4AjdKlvwbAlIaUUpRoFUsyaBZHQJsqI8PnSv11fZQoaAZoCWgPQwhbfXVVoPYHwJSGlFKUaBVLMmgWR0CbKaU1hsqKdX2UKGgGaAloD0MICAYQPpQIBsCUhpRSlGgVSzJoFkdAmykd6HCXQnV9lChoBmgJaA9DCAoS290DdAnAlIaUUpRoFUsyaBZHQJsom8dxQzl1fZQoaAZoCWgPQwgGgCpu3KIPwJSGlFKUaBVLMmgWR0CbLB7VawEAdX2UKGgGaAloD0MIw7zHmSbMB8CUhpRSlGgVSzJoFkdAmyuguEmICXV9lChoBmgJaA9DCIHrihnhTQXAlIaUUpRoFUsyaBZHQJsrGfbsWwh1fZQoaAZoCWgPQwjgEKrU7MH+v5SGlFKUaBVLMmgWR0CbKpbwSamXdX2UKGgGaAloD0MIF0UPfAw2AsCUhpRSlGgVSzJoFkdAmy35UT+NtXV9lChoBmgJaA9DCB2vQPSkjALAlIaUUpRoFUsyaBZHQJste01IiC91fZQoaAZoCWgPQwhtVn2utkIIwJSGlFKUaBVLMmgWR0CbLPPldTo/dX2UKGgGaAloD0MIm44AbhZvA8CUhpRSlGgVSzJoFkdAmyxxIFvAGnV9lChoBmgJaA9DCGdiuhCrnwbAlIaUUpRoFUsyaBZHQJsv8uEmICV1fZQoaAZoCWgPQwi1/wHWqh0HwJSGlFKUaBVLMmgWR0CbL3Q+EAYIdX2UKGgGaAloD0MI5MCr5c7MA8CUhpRSlGgVSzJoFkdAmy7s1XNkfHV9lChoBmgJaA9DCI4B2evdvwfAlIaUUpRoFUsyaBZHQJsuadK/VRV1fZQoaAZoCWgPQwiJ6xhXXHwFwJSGlFKUaBVLMmgWR0CbMeG47Rv4dX2UKGgGaAloD0MICeI8nMAUAcCUhpRSlGgVSzJoFkdAmzFjKLbYb3V9lChoBmgJaA9DCAkX8ghuZP+/lIaUUpRoFUsyaBZHQJsw299MK1J1fZQoaAZoCWgPQwgejNgngOIDwJSGlFKUaBVLMmgWR0CbMFkVeruIdX2UKGgGaAloD0MImKWdmsttA8CUhpRSlGgVSzJoFkdAmzPLFn7HhnV9lChoBmgJaA9DCE5+i06WegnAlIaUUpRoFUsyaBZHQJszTSlWOp91fZQoaAZoCWgPQwjHSWHe48wDwJSGlFKUaBVLMmgWR0CbMsXE61b8dX2UKGgGaAloD0MIDf0TXKwIB8CUhpRSlGgVSzJoFkdAmzJC3XqZ+nV9lChoBmgJaA9DCGSvd3+8NwTAlIaUUpRoFUsyaBZHQJs22kUKzAx1fZQoaAZoCWgPQwgH8BZIUNwBwJSGlFKUaBVLMmgWR0CbNl1XvH94dX2UKGgGaAloD0MIyZOkaya/BcCUhpRSlGgVSzJoFkdAmzXYJ3PiUHV9lChoBmgJaA9DCJuOAG4WbwfAlIaUUpRoFUsyaBZHQJs1VvHcUM51ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 28266, "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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "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": -5.540831868909299, "std_reward": 1.982845244466299, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-14T23:35:42.878685"}
 
1
+ {"mean_reward": -2.599236565735191, "std_reward": 0.3073447141721416, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-15T12:20:16.569897"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d8fa0eac54f98e36cc1ae86011c21ad2d20c44d7a26a968e99de7bbdde8e3840
3
  size 3056
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:621cbcf2d20e5fd16f92057fc842baab1c1df443ae84a0d550a9fa38cdd0a8e6
3
  size 3056