SpookyWooky5 commited on
Commit
2411b20
·
1 Parent(s): 923e5ae

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: -3.54 +/- 1.08
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -1.49 +/- 0.44
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 sha256:4cd37a7fbb73208ff0d4758fa43b4a4b96fc835a34d28ce533c13a2b4a651495
3
- size 108026
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:faae4dbaf60c18bbdfc9ea9231e61e5e091976c7cbaa491e9856ea48664dba0d
3
+ size 108110
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 0x7f72c4ab6160>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc._abc_data object at 0x7f72c4ab3840>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
@@ -46,7 +46,7 @@
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
- "start_time": 1679993720083302818,
50
  "learning_rate": 0.0007,
51
  "tensorboard_log": null,
52
  "lr_schedule": {
@@ -55,10 +55,10 @@
55
  },
56
  "_last_obs": {
57
  ":type:": "<class 'collections.OrderedDict'>",
58
- ":serialized:": "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",
59
- "achieved_goal": "[[ 0.4716585 -0.00893922 0.53640515]\n [ 0.4716585 -0.00893922 0.53640515]\n [ 0.4716585 -0.00893922 0.53640515]\n [ 0.4716585 -0.00893922 0.53640515]]",
60
- "desired_goal": "[[-0.483372 0.04823176 0.7083429 ]\n [ 0.7405963 0.46374357 1.3698955 ]\n [ 0.10456499 1.071651 -1.6575966 ]\n [-0.5402652 0.9719329 -1.6221786 ]]",
61
- "observation": "[[ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]\n [ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]\n [ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]\n [ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]]"
62
  },
63
  "_last_episode_starts": {
64
  ":type:": "<class 'numpy.ndarray'>",
@@ -66,9 +66,9 @@
66
  },
67
  "_last_original_obs": {
68
  ":type:": "<class 'collections.OrderedDict'>",
69
- ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAVdPpPX5f4D1R5ZI+MX1hvU39Az76t3Y9K+DPvRNCBjy/7M099BTSPFU3Tj2Tnzc+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==",
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": "[[ 0.11417262 0.10955714 0.2869058 ]\n [-0.05505103 0.12889595 0.06023405]\n [-0.10150179 0.00819446 0.10054921]\n [ 0.02564476 0.05034574 0.17931966]]",
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,
@@ -77,7 +77,7 @@
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'>",
 
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 0x7f2e3afce940>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7f2e3afd3080>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
 
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
+ "start_time": 1680009636807092521,
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": "[[ 0.42868927 -0.00483595 0.56760126]\n [ 0.42868927 -0.00483595 0.56760126]\n [ 0.42868927 -0.00483595 0.56760126]\n [ 0.42868927 -0.00483595 0.56760126]]",
60
+ "desired_goal": "[[ 1.39721 1.5320137 1.2623234 ]\n [-0.98453444 0.9106488 -1.2306865 ]\n [-0.24285033 0.12340384 -1.1506573 ]\n [-1.5356904 1.5938026 1.6647646 ]]",
61
+ "observation": "[[ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]\n [ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]\n [ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]\n [ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]]"
62
  },
63
  "_last_episode_starts": {
64
  ":type:": "<class 'numpy.ndarray'>",
 
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": "[[-0.0700159 0.06637321 0.21340546]\n [ 0.08653834 -0.06890088 0.10943418]\n [ 0.02203823 0.01047772 0.11270224]\n [ 0.04625989 0.11495714 0.06059041]]",
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,
 
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'>",
a2c-PandaReachDense-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:bfc329205ef431d6b10c5af8c816a07cd528f84ea4c84d774fdb1f6f7740a6be
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:dc67dfd0bd68de11fc24d444a420f5599d650d03a19c9e76472f5928a5ffa71f
3
  size 44734
a2c-PandaReachDense-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8cff185212d1cdbb3f1485bfaaba42fe1c3b105cf1af7af78e0382eeef4e8c99
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ffde4e533a3c0eae6b89c7c6ee670c5c633e7ce7e02b8dd4d3d283bdf6574237
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 0x7f72c4ab6160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f72c4ab3840>"}, "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": 800000, "_total_timesteps": 800000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1679993720083302818, "learning_rate": 0.0007, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAOX3xPs11ErzZUQk/OX3xPs11ErzZUQk/OX3xPs11ErzZUQk/OX3xPs11ErzZUQk/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAiXz3vquORT32VTU/uJc9P8xv7T68WK8/KybWPdwriT8gLNS/0k4Kv5jQeD+Mo8+/lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAAA5ffE+zXUSvNlRCT9LFR887gudu3DSCTw5ffE+zXUSvNlRCT9LFR887gudu3DSCTw5ffE+zXUSvNlRCT9LFR887gudu3DSCTw5ffE+zXUSvNlRCT9LFR887gudu3DSCTyUaA5LBEsGhpRoEnSUUpR1Lg==", "achieved_goal": "[[ 0.4716585 -0.00893922 0.53640515]\n [ 0.4716585 -0.00893922 0.53640515]\n [ 0.4716585 -0.00893922 0.53640515]\n [ 0.4716585 -0.00893922 0.53640515]]", "desired_goal": "[[-0.483372 0.04823176 0.7083429 ]\n [ 0.7405963 0.46374357 1.3698955 ]\n [ 0.10456499 1.071651 -1.6575966 ]\n [-0.5402652 0.9719329 -1.6221786 ]]", "observation": "[[ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]\n [ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]\n [ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]\n [ 0.4716585 -0.00893922 0.53640515 0.00970967 -0.00479268 0.00841199]]"}, "_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": "[[ 0.11417262 0.10955714 0.2869058 ]\n [-0.05505103 0.12889595 0.06023405]\n [-0.10150179 0.00819446 0.10054921]\n [ 0.02564476 0.05034574 0.17931966]]", "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": 40000, "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 0x7f2e3afce940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f2e3afd3080>"}, "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": 800000, "_total_timesteps": 800000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1680009636807092521, "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": "[[ 0.42868927 -0.00483595 0.56760126]\n [ 0.42868927 -0.00483595 0.56760126]\n [ 0.42868927 -0.00483595 0.56760126]\n [ 0.42868927 -0.00483595 0.56760126]]", "desired_goal": "[[ 1.39721 1.5320137 1.2623234 ]\n [-0.98453444 0.9106488 -1.2306865 ]\n [-0.24285033 0.12340384 -1.1506573 ]\n [-1.5356904 1.5938026 1.6647646 ]]", "observation": "[[ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]\n [ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]\n [ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]\n [ 4.2868927e-01 -4.8359521e-03 5.6760126e-01 -9.4261933e-03\n -3.0791841e-03 1.6665708e-04]]"}, "_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": "[[-0.0700159 0.06637321 0.21340546]\n [ 0.08653834 -0.06890088 0.10943418]\n [ 0.02203823 0.01047772 0.11270224]\n [ 0.04625989 0.11495714 0.06059041]]", "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": 40000, "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": -3.5425984855275603, "std_reward": 1.0787799309778738, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-28T09:34:56.993128"}
 
1
+ {"mean_reward": -1.4892631595022976, "std_reward": 0.43758887174161365, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-28T14:11:43.722098"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:cc2d2bf2f1232f4ca7c6d29df9c599cb6fb93fc71d3bc6d713bd72b5d7de0d29
3
  size 3056
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b1de255a052fc294d0ef110ff62cf315a7d5f4a98012fe3513618df65a1a209f
3
  size 3056