NickThe1 commited on
Commit
9a3b536
1 Parent(s): 45c640b

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: -3.08 +/- 1.53
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -5.59 +/- 3.62
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:f701e91054d838a8bf555bdf3799cc80db3ad945b78ef6291d3fcea00bcd4d44
3
- size 108145
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aab229709e32ce12ce280f042b6483c5201b4f748e6cbde7537c190f11bbcbb3
3
+ size 108159
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 0x7fb6f8f68160>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc._abc_data object at 0x7fb6f8f60a40>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
@@ -19,12 +19,12 @@
19
  "weight_decay": 0
20
  }
21
  },
22
- "num_timesteps": 500000,
23
- "_total_timesteps": 500000,
24
  "_num_timesteps_at_start": 0,
25
  "seed": null,
26
  "action_noise": null,
27
- "start_time": 1685606367336388728,
28
  "learning_rate": 0.0007,
29
  "tensorboard_log": null,
30
  "lr_schedule": {
@@ -33,10 +33,10 @@
33
  },
34
  "_last_obs": {
35
  ":type:": "<class 'collections.OrderedDict'>",
36
- ":serialized:": "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",
37
- "achieved_goal": "[[0.39087132 0.00779197 0.56476694]\n [0.39087132 0.00779197 0.56476694]\n [0.39087132 0.00779197 0.56476694]\n [0.39087132 0.00779197 0.56476694]]",
38
- "desired_goal": "[[-0.79070944 0.14558263 1.4974031 ]\n [-0.70436347 -1.6602337 0.67345864]\n [-1.2630389 0.07662245 1.1246547 ]\n [ 1.4038363 -1.6714408 -0.12650357]]",
39
- "observation": "[[ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]\n [ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]\n [ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]\n [ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]]"
40
  },
41
  "_last_episode_starts": {
42
  ":type:": "<class 'numpy.ndarray'>",
@@ -44,9 +44,9 @@
44
  },
45
  "_last_original_obs": {
46
  ":type:": "<class 'collections.OrderedDict'>",
47
- ":serialized:": "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",
48
  "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]]",
49
- "desired_goal": "[[-0.103332 0.1263849 0.07514145]\n [-0.00135882 -0.09005462 0.06946192]\n [ 0.0215342 0.11130078 0.26077673]\n [ 0.07303688 0.11749144 0.16495506]]",
50
  "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]]"
51
  },
52
  "_episode_num": 0,
@@ -56,13 +56,13 @@
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": 25000,
66
  "n_steps": 5,
67
  "gamma": 0.99,
68
  "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 0x7fe181ee4040>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7fe181edc440>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
 
19
  "weight_decay": 0
20
  }
21
  },
22
+ "num_timesteps": 1000000,
23
+ "_total_timesteps": 1000000,
24
  "_num_timesteps_at_start": 0,
25
  "seed": null,
26
  "action_noise": null,
27
+ "start_time": 1685681235316143548,
28
  "learning_rate": 0.0007,
29
  "tensorboard_log": null,
30
  "lr_schedule": {
 
33
  },
34
  "_last_obs": {
35
  ":type:": "<class 'collections.OrderedDict'>",
36
+ ":serialized:": "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",
37
+ "achieved_goal": "[[ 0.41690218 -0.03534747 0.44359198]\n [ 0.41690218 -0.03534747 0.44359198]\n [ 0.41690218 -0.03534747 0.44359198]\n [ 0.41690218 -0.03534747 0.44359198]]",
38
+ "desired_goal": "[[ 1.2809356 -0.72696525 1.2876161 ]\n [ 1.3672246 -0.83578235 -1.4654179 ]\n [-0.23957615 1.6576132 -1.6999475 ]\n [ 0.17911981 -0.69506955 -1.059173 ]]",
39
+ "observation": "[[ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]\n [ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]\n [ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]\n [ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]]"
40
  },
41
  "_last_episode_starts": {
42
  ":type:": "<class 'numpy.ndarray'>",
 
44
  },
45
  "_last_original_obs": {
46
  ":type:": "<class 'collections.OrderedDict'>",
47
+ ":serialized:": "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",
48
  "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]]",
49
+ "desired_goal": "[[-0.0933798 0.11345476 0.1172279 ]\n [ 0.11070094 0.01264753 0.04787728]\n [ 0.02198941 -0.12328199 0.28748766]\n [ 0.07578752 -0.10977025 0.2052681 ]]",
50
  "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]]"
51
  },
52
  "_episode_num": 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": 50000,
66
  "n_steps": 5,
67
  "gamma": 0.99,
68
  "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:f80ef157eccbca115395a352f850ff77e1d91ba29d828cfb1386d5605b2f6c01
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:644164b002216637709111023329349b326a5ee448b9896350f0a8c782cd0db3
3
  size 44734
a2c-PandaReachDense-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:2eff61a90c524fa8698264a48082858f0cc8796669606cf1f63c4e73703723a7
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:855264090181c70da43559a0c23323624b2b6e20aad3d47c056fa1b670b968cb
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 0x7fb6f8f68160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fb6f8f60a40>"}, "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}}, "num_timesteps": 500000, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685606367336388728, "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": "[[0.39087132 0.00779197 0.56476694]\n [0.39087132 0.00779197 0.56476694]\n [0.39087132 0.00779197 0.56476694]\n [0.39087132 0.00779197 0.56476694]]", "desired_goal": "[[-0.79070944 0.14558263 1.4974031 ]\n [-0.70436347 -1.6602337 0.67345864]\n [-1.2630389 0.07662245 1.1246547 ]\n [ 1.4038363 -1.6714408 -0.12650357]]", "observation": "[[ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]\n [ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]\n [ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]\n [ 3.9087132e-01 7.7919718e-03 5.6476694e-01 -5.7650078e-03\n 2.4803740e-04 1.6791893e-03]]"}, "_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": "[[-0.103332 0.1263849 0.07514145]\n [-0.00135882 -0.09005462 0.06946192]\n [ 0.0215342 0.11130078 0.26077673]\n [ 0.07303688 0.11749144 0.16495506]]", "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": 25000, "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 0x7fe181ee4040>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fe181edc440>"}, "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}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685681235316143548, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAANHTVPoHIEL19HuM+NHTVPoHIEL19HuM+NHTVPoHIEL19HuM+NHTVPoHIEL19HuM+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAs/WjP2UaOr+b0KQ/NwGvP9X1Vb/Qkru/c1N1vqss1D/hl9m/L2s3PhTwMb/7koe/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAAA0dNU+gcgQvX0e4z5r1SQ8pKgQuZwUETw0dNU+gcgQvX0e4z5r1SQ8pKgQuZwUETw0dNU+gcgQvX0e4z5r1SQ8pKgQuZwUETw0dNU+gcgQvX0e4z5r1SQ8pKgQuZwUETyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[ 0.41690218 -0.03534747 0.44359198]\n [ 0.41690218 -0.03534747 0.44359198]\n [ 0.41690218 -0.03534747 0.44359198]\n [ 0.41690218 -0.03534747 0.44359198]]", "desired_goal": "[[ 1.2809356 -0.72696525 1.2876161 ]\n [ 1.3672246 -0.83578235 -1.4654179 ]\n [-0.23957615 1.6576132 -1.6999475 ]\n [ 0.17911981 -0.69506955 -1.059173 ]]", "observation": "[[ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]\n [ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]\n [ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]\n [ 4.1690218e-01 -3.5347465e-02 4.4359198e-01 1.0060648e-02\n -1.3795734e-04 8.8550113e-03]]"}, "_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": "[[-0.0933798 0.11345476 0.1172279 ]\n [ 0.11070094 0.01264753 0.04787728]\n [ 0.02198941 -0.12328199 0.28748766]\n [ 0.07578752 -0.10977025 0.2052681 ]]", "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": 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"}}
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": -3.0820865646004676, "std_reward": 1.534763244803206, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-01T08:25:57.908798"}
 
1
+ {"mean_reward": -5.59398043891415, "std_reward": 3.6196562175821367, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-02T05:33:58.758246"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d8d0ba4130320ad3d8790000c7eef23ffc2b9820dd3e32ad4252f112cc88ca82
3
  size 2387
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2634d95041e086d603b08ab70b262dd6c6b1560556e2c3405b290b25f1decf33
3
  size 2387