ChechkovEugene commited on
Commit
5c0aa31
1 Parent(s): 9777c62

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: -3.37 +/- 0.86
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -0.39 +/- 0.11
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 sha256:82ecad3e8e47fe5136f07b08492383b4ffded85df29d0409ac62a1a54732955a
3
  size 108028
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fa4282d3c6d08cc2973fffe24034456581a006e57a4a41373b91f9f34fd88192
3
  size 108028
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 0x7f7ac74aee50>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc._abc_data object at 0x7f7ac74b0280>"
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": 1678810834195114360,
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": "[[ 0.50359076 -0.04878693 0.7170846 ]\n [ 0.50359076 -0.04878693 0.7170846 ]\n [ 0.50359076 -0.04878693 0.7170846 ]\n [ 0.50359076 -0.04878693 0.7170846 ]]",
60
- "desired_goal": "[[ 1.7023548 -0.89549345 -0.06088734]\n [-0.11914909 1.5027947 1.6884228 ]\n [ 1.2066393 -1.6550525 -0.08801737]\n [-1.1279501 0.27687573 -0.05306117]]",
61
- "observation": "[[ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]\n [ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]\n [ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]\n [ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]]"
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:": "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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": "[[ 0.01334742 -0.14928873 0.10353547]\n [ 0.12594645 0.00968797 0.29873434]\n [-0.0871428 0.03158767 0.26363638]\n [ 0.02358704 0.01487906 0.14906189]]",
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 0x7fe02557dd30>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7fe02557cdc0>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
 
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
+ "start_time": 1678891592169632869,
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": "[[ 0.4366091 -0.00603712 0.57536924]\n [ 0.4366091 -0.00603712 0.57536924]\n [ 0.4366091 -0.00603712 0.57536924]\n [ 0.4366091 -0.00603712 0.57536924]]",
60
+ "desired_goal": "[[-0.32589445 -0.80995494 -0.07402899]\n [-1.5784078 -1.34776 1.1053395 ]\n [-0.696395 0.49614567 -1.4433569 ]\n [ 0.15885977 -0.84859467 1.7227648 ]]",
61
+ "observation": "[[ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]\n [ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]\n [ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]\n [ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]]"
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": "[[ 0.02347708 -0.06433485 0.1319467 ]\n [-0.13176103 0.01691826 0.1098742 ]\n [ 0.07601718 0.13031504 0.06293006]\n [-0.12432525 0.12387602 0.00676162]]",
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 sha256:45b4454bfdf0ef2eeef0bbe9a62e502554b36e4360cdf0bbf3ad6345adb36406
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8f0e409456b65ede4014bb93a1ba5056368fe67df1de38365501590472909c48
3
  size 44734
a2c-PandaReachDense-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:8ea2df688523bc811e1d7a78086c82bb8fb404638d789ffd289a8fe726dae993
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1cb9e64d756ed171c419ffe03e788a7f21eb18329cd9f29351a4950925b14191
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 0x7f7ac74aee50>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f7ac74b0280>"}, "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:": "gAWVbQEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLA4WUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWDAAAAAAAAAAAAIC/AACAvwAAgL+UaApLA4WUjAFDlHSUUpSMBGhpZ2iUaBIolgwAAAAAAAAAAACAPwAAgD8AAIA/lGgKSwOFlGgVdJRSlIwNYm91bmRlZF9iZWxvd5RoEiiWAwAAAAAAAAABAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLA4WUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYDAAAAAAAAAAEBAZRoIUsDhZRoFXSUUpSMCl9ucF9yYW5kb22UTnViLg==", "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": 1678810834195114360, "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": "[[ 0.50359076 -0.04878693 0.7170846 ]\n [ 0.50359076 -0.04878693 0.7170846 ]\n [ 0.50359076 -0.04878693 0.7170846 ]\n [ 0.50359076 -0.04878693 0.7170846 ]]", "desired_goal": "[[ 1.7023548 -0.89549345 -0.06088734]\n [-0.11914909 1.5027947 1.6884228 ]\n [ 1.2066393 -1.6550525 -0.08801737]\n [-1.1279501 0.27687573 -0.05306117]]", "observation": "[[ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]\n [ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]\n [ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]\n [ 0.50359076 -0.04878693 0.7170846 0.03384784 -0.00184698 0.05442721]]"}, "_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": "[[ 0.01334742 -0.14928873 0.10353547]\n [ 0.12594645 0.00968797 0.29873434]\n [-0.0871428 0.03158767 0.26363638]\n [ 0.02358704 0.01487906 0.14906189]]", "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:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIlrA2xk5YDsCUhpRSlIwBbJRLMowBdJRHQKnl6384xUN1fZQoaAZoCWgPQwhZ+tAF9X0VwJSGlFKUaBVLMmgWR0Cp5auDJ2dNdX2UKGgGaAloD0MIECIZcmz9BsCUhpRSlGgVSzJoFkdAqeVlUp/gBXV9lChoBmgJaA9DCNE7FXDPEw7AlIaUUpRoFUsyaBZHQKnlKPFvQ4V1fZQoaAZoCWgPQwh2qRH6mfoOwJSGlFKUaBVLMmgWR0Cp5w/3evZAdX2UKGgGaAloD0MIxxAAHHu2+b+UhpRSlGgVSzJoFkdAqebQbhm5D3V9lChoBmgJaA9DCIgwfhr3RgrAlIaUUpRoFUsyaBZHQKnmipd8iOh1fZQoaAZoCWgPQwj27/rMWZ8GwJSGlFKUaBVLMmgWR0Cp5k49xIatdX2UKGgGaAloD0MIcjJxqyCGEMCUhpRSlGgVSzJoFkdAqegsG/vfCXV9lChoBmgJaA9DCAKdSZuqmwnAlIaUUpRoFUsyaBZHQKnn7FhoduJ1fZQoaAZoCWgPQwioHmlwW7sFwJSGlFKUaBVLMmgWR0Cp56ZML4N7dX2UKGgGaAloD0MIvRsLCoMSB8CUhpRSlGgVSzJoFkdAqedp1Ng0CXV9lChoBmgJaA9DCDogCft2UgHAlIaUUpRoFUsyaBZHQKnpSnk1dgR1fZQoaAZoCWgPQwiEm4wqw5gFwJSGlFKUaBVLMmgWR0Cp6Qqnm7rcdX2UKGgGaAloD0MIiLt6FRm9BsCUhpRSlGgVSzJoFkdAqejE4ku6E3V9lChoBmgJaA9DCKN3KuCeJw3AlIaUUpRoFUsyaBZHQKnoiKJEYwZ1fZQoaAZoCWgPQwhq+YGrPNERwJSGlFKUaBVLMmgWR0Cp6mPkzXSSdX2UKGgGaAloD0MIf6Xz4VmCB8CUhpRSlGgVSzJoFkdAqeokBMi8nXV9lChoBmgJaA9DCBTtKqT85AvAlIaUUpRoFUsyaBZHQKnp3g75mAd1fZQoaAZoCWgPQwgLDFnd6vkYwJSGlFKUaBVLMmgWR0Cp6aHAIppfdX2UKGgGaAloD0MIvw8HCVH+A8CUhpRSlGgVSzJoFkdAqeuIjIJZ4nV9lChoBmgJaA9DCIOluoCX2QnAlIaUUpRoFUsyaBZHQKnrSHu7YkF1fZQoaAZoCWgPQwiL+49Mh+4LwJSGlFKUaBVLMmgWR0Cp6wJ1JUYLdX2UKGgGaAloD0MIxvgwe9k2DcCUhpRSlGgVSzJoFkdAqerF7Uoa1nV9lChoBmgJaA9DCKlPcodN9BTAlIaUUpRoFUsyaBZHQKnsoI9kjHJ1fZQoaAZoCWgPQwjNk2sKZLYKwJSGlFKUaBVLMmgWR0Cp7GDoZAIIdX2UKGgGaAloD0MIJAnCFVBICMCUhpRSlGgVSzJoFkdAqewbJhfBvnV9lChoBmgJaA9DCKSoM/eQcAbAlIaUUpRoFUsyaBZHQKnr3y6tknV1fZQoaAZoCWgPQwgYP41781sOwJSGlFKUaBVLMmgWR0Cp7b+rlvIfdX2UKGgGaAloD0MI/3bZrzvdCMCUhpRSlGgVSzJoFkdAqe1/pMYdhnV9lChoBmgJaA9DCJf9utOdBwvAlIaUUpRoFUsyaBZHQKntObnX/YJ1fZQoaAZoCWgPQwgE4nX9gt0OwJSGlFKUaBVLMmgWR0Cp7P3fQ8fWdX2UKGgGaAloD0MIe/ZcpiZBC8CUhpRSlGgVSzJoFkdAqe7fOjZcs3V9lChoBmgJaA9DCM5xbhPuBRPAlIaUUpRoFUsyaBZHQKnunyH2ys11fZQoaAZoCWgPQwgU0a+tn04QwJSGlFKUaBVLMmgWR0Cp7lla8pTddX2UKGgGaAloD0MI7KF9rOB3CMCUhpRSlGgVSzJoFkdAqe4c7U5MlHV9lChoBmgJaA9DCJXXSuguiRXAlIaUUpRoFUsyaBZHQKnv5o3aSLZ1fZQoaAZoCWgPQwh8t3njpMATwJSGlFKUaBVLMmgWR0Cp76am4y44dX2UKGgGaAloD0MIZYnOMovwD8CUhpRSlGgVSzJoFkdAqe9grhBJI3V9lChoBmgJaA9DCK7zb5f92g/AlIaUUpRoFUsyaBZHQKnvI/s3Q2N1fZQoaAZoCWgPQwgNb9bgfXUNwJSGlFKUaBVLMmgWR0Cp8QDt5UtJdX2UKGgGaAloD0MInWfsSza+BsCUhpRSlGgVSzJoFkdAqfDBRuTA33V9lChoBmgJaA9DCPT4vU1/9vu/lIaUUpRoFUsyaBZHQKnwe078vVV1fZQoaAZoCWgPQwhHA3gLJAgPwJSGlFKUaBVLMmgWR0Cp8D7UgB91dX2UKGgGaAloD0MIo8ow7gYxBMCUhpRSlGgVSzJoFkdAqfIq3solU3V9lChoBmgJaA9DCLDiVGthFgbAlIaUUpRoFUsyaBZHQKnx6x46fap1fZQoaAZoCWgPQwgxtaUO8roIwJSGlFKUaBVLMmgWR0Cp8aU1IiC8dX2UKGgGaAloD0MI36RpUDSPDsCUhpRSlGgVSzJoFkdAqfFo0Mw1znV9lChoBmgJaA9DCIMT0a+tPwbAlIaUUpRoFUsyaBZHQKnzQPYFqzt1fZQoaAZoCWgPQwhZi08BMN4EwJSGlFKUaBVLMmgWR0Cp8wEOqebvdX2UKGgGaAloD0MIGy/dJAaBBcCUhpRSlGgVSzJoFkdAqfK7SPU8WHV9lChoBmgJaA9DCGJJufsc3wXAlIaUUpRoFUsyaBZHQKnyfqKxcFB1fZQoaAZoCWgPQwihSs0eaMX+v5SGlFKUaBVLMmgWR0Cp9JJHiFTOdX2UKGgGaAloD0MIGVbxRubxA8CUhpRSlGgVSzJoFkdAqfRTDdgv13V9lChoBmgJaA9DCMtneR7c3Q3AlIaUUpRoFUsyaBZHQKn0Df1Hvtt1fZQoaAZoCWgPQwg/48KBkEwFwJSGlFKUaBVLMmgWR0Cp89JTl1bJdX2UKGgGaAloD0MIiQeUTbliCMCUhpRSlGgVSzJoFkdAqfaccIZ62XV9lChoBmgJaA9DCJT6srRTkwLAlIaUUpRoFUsyaBZHQKn2XVd5Y5l1fZQoaAZoCWgPQwiBWaFI95MCwJSGlFKUaBVLMmgWR0Cp9hh73PAwdX2UKGgGaAloD0MIWDz1SINbCcCUhpRSlGgVSzJoFkdAqfXdBF/hEXV9lChoBmgJaA9DCDo/xXHgFRHAlIaUUpRoFUsyaBZHQKn4j8IAwPB1fZQoaAZoCWgPQwjw+WGE8KgDwJSGlFKUaBVLMmgWR0Cp+FEz41xbdX2UKGgGaAloD0MIVwqBXOIoB8CUhpRSlGgVSzJoFkdAqfgMQ/X5FnV9lChoBmgJaA9DCBefAmA8Qw3AlIaUUpRoFUsyaBZHQKn30OH31z11fZQoaAZoCWgPQwi/SGjLuTQOwJSGlFKUaBVLMmgWR0Cp+nj0163RdX2UKGgGaAloD0MIX5fhP92AA8CUhpRSlGgVSzJoFkdAqfo6IrOJL3V9lChoBmgJaA9DCPROBdzzLBLAlIaUUpRoFUsyaBZHQKn59VvuPWB1fZQoaAZoCWgPQwgo02hyMcYFwJSGlFKUaBVLMmgWR0Cp+bnX2/SIdX2UKGgGaAloD0MIsB9ig4WTAsCUhpRSlGgVSzJoFkdAqfybLB9Cu3V9lChoBmgJaA9DCBReglMfiPy/lIaUUpRoFUsyaBZHQKn8XFo+Ofd1fZQoaAZoCWgPQwjwTdNnB/wCwJSGlFKUaBVLMmgWR0Cp/BeUQkHEdX2UKGgGaAloD0MIB0MdVril/b+UhpRSlGgVSzJoFkdAqfvcImgJ1XV9lChoBmgJaA9DCNb9YyE6ZAzAlIaUUpRoFUsyaBZHQKn+jnYg7o11fZQoaAZoCWgPQwjuemmKAGcOwJSGlFKUaBVLMmgWR0Cp/k+XiR4hdX2UKGgGaAloD0MIsMVun1UGCMCUhpRSlGgVSzJoFkdAqf4KpHZsbnV9lChoBmgJaA9DCNlCkIMSRgfAlIaUUpRoFUsyaBZHQKn9zxSYPXl1fZQoaAZoCWgPQwgJbw9CQL4QwJSGlFKUaBVLMmgWR0Cp//aTnq3WdX2UKGgGaAloD0MIKdAn8iTJA8CUhpRSlGgVSzJoFkdAqf+2vUz9CXV9lChoBmgJaA9DCD6XqUnwxgPAlIaUUpRoFUsyaBZHQKn/cM7U5Ml1fZQoaAZoCWgPQwiR0QFJ2HcGwJSGlFKUaBVLMmgWR0Cp/zRRVIZqdX2UKGgGaAloD0MItDo5Q3HnAsCUhpRSlGgVSzJoFkdAqgEK+ajN6nV9lChoBmgJaA9DCPzh578HrxHAlIaUUpRoFUsyaBZHQKoAywu/UON1fZQoaAZoCWgPQwjir8ka9XALwJSGlFKUaBVLMmgWR0CqAIUWl/H6dX2UKGgGaAloD0MIoFIlyt5yB8CUhpRSlGgVSzJoFkdAqgBIvi97GHV9lChoBmgJaA9DCOYIGcizS/u/lIaUUpRoFUsyaBZHQKoCOqjJuEV1fZQoaAZoCWgPQwhaL4Zyol0IwJSGlFKUaBVLMmgWR0CqAfra24NJdX2UKGgGaAloD0MIoib6fJRRCMCUhpRSlGgVSzJoFkdAqgG06q8143V9lChoBmgJaA9DCINPc/IiMwrAlIaUUpRoFUsyaBZHQKoBeJUo8ZF1fZQoaAZoCWgPQwhi9UcYBpwTwJSGlFKUaBVLMmgWR0CqA1pOvdM1dX2UKGgGaAloD0MI3SObq+Y5CMCUhpRSlGgVSzJoFkdAqgMablRxcXV9lChoBmgJaA9DCO9VKxN+aQfAlIaUUpRoFUsyaBZHQKoC1IH1OCZ1fZQoaAZoCWgPQwhLrfcb7bj8v5SGlFKUaBVLMmgWR0CqApgVfu1GdX2UKGgGaAloD0MICaUvhJw3B8CUhpRSlGgVSzJoFkdAqgSEFt8/lnV9lChoBmgJaA9DCEhrDDohVBDAlIaUUpRoFUsyaBZHQKoEREl3Qld1fZQoaAZoCWgPQwhW73A7NEwLwJSGlFKUaBVLMmgWR0CqA/7J4jbBdX2UKGgGaAloD0MInN8w0SBFBcCUhpRSlGgVSzJoFkdAqgPCfL9uP3V9lChoBmgJaA9DCExw6gPJu/+/lIaUUpRoFUsyaBZHQKoFzE9dNWV1fZQoaAZoCWgPQwi5Us+CUH4DwJSGlFKUaBVLMmgWR0CqBYxrJr+HdX2UKGgGaAloD0MItKz7x0KEEMCUhpRSlGgVSzJoFkdAqgVGcnVoYnV9lChoBmgJaA9DCOYF2EenLgTAlIaUUpRoFUsyaBZHQKoFCfBeok11ZS4="}, "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 0x7fe02557dd30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fe02557cdc0>"}, "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": 1678891592169632869, "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": "[[ 0.4366091 -0.00603712 0.57536924]\n [ 0.4366091 -0.00603712 0.57536924]\n [ 0.4366091 -0.00603712 0.57536924]\n [ 0.4366091 -0.00603712 0.57536924]]", "desired_goal": "[[-0.32589445 -0.80995494 -0.07402899]\n [-1.5784078 -1.34776 1.1053395 ]\n [-0.696395 0.49614567 -1.4433569 ]\n [ 0.15885977 -0.84859467 1.7227648 ]]", "observation": "[[ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]\n [ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]\n [ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]\n [ 0.4366091 -0.00603712 0.57536924 0.0039475 -0.00153436 0.00136425]]"}, "_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": "[[ 0.02347708 -0.06433485 0.1319467 ]\n [-0.13176103 0.01691826 0.1098742 ]\n [ 0.07601718 0.13031504 0.06293006]\n [-0.12432525 0.12387602 0.00676162]]", "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:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIPIcyVMVU3b+UhpRSlIwBbJRLMowBdJRHQKnjWm/nGKh1fZQoaAZoCWgPQwgstklFY+3iv5SGlFKUaBVLMmgWR0Cp4tFId2gWdX2UKGgGaAloD0MI9dbAVgkWzb+UhpRSlGgVSzJoFkdAqeI+LpA2RHV9lChoBmgJaA9DCOxMofMau9q/lIaUUpRoFUsyaBZHQKnhyHPeHi51fZQoaAZoCWgPQwgfEr73N2jdv5SGlFKUaBVLMmgWR0Cp5IVZcLSedX2UKGgGaAloD0MIPbg7a7dd2L+UhpRSlGgVSzJoFkdAqeP8DuBtlHV9lChoBmgJaA9DCL6G4LiMG++/lIaUUpRoFUsyaBZHQKnjaMWoFV11fZQoaAZoCWgPQwijdyrgnifwv5SGlFKUaBVLMmgWR0Cp4vKzRhMKdX2UKGgGaAloD0MI7gbRWtFm4b+UhpRSlGgVSzJoFkdAqeWtxKg7HXV9lChoBmgJaA9DCEzhQbPr3ua/lIaUUpRoFUsyaBZHQKnlJLEDQqt1fZQoaAZoCWgPQwhmTwKbc/Dmv5SGlFKUaBVLMmgWR0Cp5JF5OafBdX2UKGgGaAloD0MIzgAXZMvy4L+UhpRSlGgVSzJoFkdAqeQbfk3juXV9lChoBmgJaA9DCFzK+WLvxeW/lIaUUpRoFUsyaBZHQKnm05EMLF51fZQoaAZoCWgPQwjFO8CTFi7fv5SGlFKUaBVLMmgWR0Cp5kpUYKpldX2UKGgGaAloD0MIXtkFg2tu4b+UhpRSlGgVSzJoFkdAqeW3DNyHVXV9lChoBmgJaA9DCD230JUIVNi/lIaUUpRoFUsyaBZHQKnlQMaS9uh1fZQoaAZoCWgPQwgGE38UdWbkv5SGlFKUaBVLMmgWR0Cp6EaI3zczdX2UKGgGaAloD0MIl6sfm+TH4b+UhpRSlGgVSzJoFkdAqee9/axoqXV9lChoBmgJaA9DCBGo/kEkQ9W/lIaUUpRoFUsyaBZHQKnnK8IRh+h1fZQoaAZoCWgPQwjAsz16w33Yv5SGlFKUaBVLMmgWR0Cp5rZ6D5CXdX2UKGgGaAloD0MItrqcEhAT8r+UhpRSlGgVSzJoFkdAqeoqQ3gk1XV9lChoBmgJaA9DCFKazeMwmNy/lIaUUpRoFUsyaBZHQKnpojRlYlp1fZQoaAZoCWgPQwjZmNcRh2ziv5SGlFKUaBVLMmgWR0Cp6Q++ueSTdX2UKGgGaAloD0MIuW5Kea2E1r+UhpRSlGgVSzJoFkdAqeiapNsWPHV9lChoBmgJaA9DCN+Hg4QoX+W/lIaUUpRoFUsyaBZHQKnr/Imw7kp1fZQoaAZoCWgPQwioABjPoKHYv5SGlFKUaBVLMmgWR0Cp63QzUI9ldX2UKGgGaAloD0MIX5m36jpU4L+UhpRSlGgVSzJoFkdAqerhf6XSjXV9lChoBmgJaA9DCFw7URISac2/lIaUUpRoFUsyaBZHQKnqbCTlkpZ1fZQoaAZoCWgPQwgYk/5eCs/wv5SGlFKUaBVLMmgWR0Cp7eQV9F4LdX2UKGgGaAloD0MIYvay7bQ12L+UhpRSlGgVSzJoFkdAqe1b8UEgXHV9lChoBmgJaA9DCABWR450hue/lIaUUpRoFUsyaBZHQKnsyXrMTvl1fZQoaAZoCWgPQwg9SE+RQ8TPv5SGlFKUaBVLMmgWR0Cp7FRoIv8JdX2UKGgGaAloD0MIuf/IdOj0zL+UhpRSlGgVSzJoFkdAqe/ZPIn0CnV9lChoBmgJaA9DCJdWQ+IeS+K/lIaUUpRoFUsyaBZHQKnvUQ4jrzJ1fZQoaAZoCWgPQwgO3ewPlFvpv5SGlFKUaBVLMmgWR0Cp7r6guh9LdX2UKGgGaAloD0MI4+Ko3EQt3b+UhpRSlGgVSzJoFkdAqe5JlHz6J3V9lChoBmgJaA9DCHNmu0IfLNW/lIaUUpRoFUsyaBZHQKnxw/Glyip1fZQoaAZoCWgPQwiCdRw/VBrfv5SGlFKUaBVLMmgWR0Cp8Tv91loUdX2UKGgGaAloD0MIhIHn3sMl4L+UhpRSlGgVSzJoFkdAqfCpzo2XLXV9lChoBmgJaA9DCFX7dDxmIOa/lIaUUpRoFUsyaBZHQKnwNPC2tuF1fZQoaAZoCWgPQwh40Oy6tyLfv5SGlFKUaBVLMmgWR0Cp86EtdzGQdX2UKGgGaAloD0MIggGEDyVa4r+UhpRSlGgVSzJoFkdAqfMX8yeqaXV9lChoBmgJaA9DCMQmMnOBy+i/lIaUUpRoFUsyaBZHQKnyhJwKjSJ1fZQoaAZoCWgPQwhMcOoDyTvnv5SGlFKUaBVLMmgWR0Cp8g57PY4AdX2UKGgGaAloD0MIwsO0b+6v4r+UhpRSlGgVSzJoFkdAqfTO14Pf9HV9lChoBmgJaA9DCOVFJuDXSN+/lIaUUpRoFUsyaBZHQKn0Racqe9V1fZQoaAZoCWgPQwguHAjJAibyv5SGlFKUaBVLMmgWR0Cp87JBHCoCdX2UKGgGaAloD0MIsyYW+Ipu5r+UhpRSlGgVSzJoFkdAqfM8BwMpgHV9lChoBmgJaA9DCMPzUrExr+y/lIaUUpRoFUsyaBZHQKn1+ews5GV1fZQoaAZoCWgPQwjh7NYyGY7Uv5SGlFKUaBVLMmgWR0Cp9XCfQKKHdX2UKGgGaAloD0MIRzgteNFX2b+UhpRSlGgVSzJoFkdAqfTdMuez2XV9lChoBmgJaA9DCCnQJ/Ik6eS/lIaUUpRoFUsyaBZHQKn0Zx//ech1fZQoaAZoCWgPQwjRBmADIsTiv5SGlFKUaBVLMmgWR0Cp9xtIClrNdX2UKGgGaAloD0MI6BTkZyNX4b+UhpRSlGgVSzJoFkdAqfaR8WsRx3V9lChoBmgJaA9DCJQXmYBfI+W/lIaUUpRoFUsyaBZHQKn1/oYekpJ1fZQoaAZoCWgPQwhF8wAW+fXUv5SGlFKUaBVLMmgWR0Cp9YiRfWtmdX2UKGgGaAloD0MINBMM5xpm3r+UhpRSlGgVSzJoFkdAqfhAdlum8HV9lChoBmgJaA9DCGQhOgSOBNS/lIaUUpRoFUsyaBZHQKn3txz7uUl1fZQoaAZoCWgPQwj1DrdDw2Lhv5SGlFKUaBVLMmgWR0Cp9yOscQyzdX2UKGgGaAloD0MIigYpeAq57L+UhpRSlGgVSzJoFkdAqfatj0+TvHV9lChoBmgJaA9DCLUX0XZMXeC/lIaUUpRoFUsyaBZHQKn5amWMS9N1fZQoaAZoCWgPQwh4YWu28pLjv5SGlFKUaBVLMmgWR0Cp+OEQwsXjdX2UKGgGaAloD0MIYHXkSGfg4L+UhpRSlGgVSzJoFkdAqfhNloUSI3V9lChoBmgJaA9DCKBRuvQvSeu/lIaUUpRoFUsyaBZHQKn3128qWkd1fZQoaAZoCWgPQwj9TpMZbyvpv5SGlFKUaBVLMmgWR0Cp+pSRSxZ/dX2UKGgGaAloD0MIQrRWtDnO2b+UhpRSlGgVSzJoFkdAqfoMPczqKXV9lChoBmgJaA9DCOo8Kv7vCOO/lIaUUpRoFUsyaBZHQKn5eePJaJR1fZQoaAZoCWgPQwhgPlkxXB3iv5SGlFKUaBVLMmgWR0Cp+QRHf/FSdX2UKGgGaAloD0MIuAIK9fSR4b+UhpRSlGgVSzJoFkdAqfu3NzKcNHV9lChoBmgJaA9DCPqYDwh0JuO/lIaUUpRoFUsyaBZHQKn7LeD3/Px1fZQoaAZoCWgPQwgYmBWKdL/pv5SGlFKUaBVLMmgWR0Cp+pqA8SwodX2UKGgGaAloD0MItvepKjQQ47+UhpRSlGgVSzJoFkdAqfokbkwN9nV9lChoBmgJaA9DCE5FKowtBN+/lIaUUpRoFUsyaBZHQKn8+t03fhx1fZQoaAZoCWgPQwjFc7aA0Prhv5SGlFKUaBVLMmgWR0Cp/HHDrJKbdX2UKGgGaAloD0MIBwySPq2i4r+UhpRSlGgVSzJoFkdAqfveirT6SHV9lChoBmgJaA9DCLRzmgXaneu/lIaUUpRoFUsyaBZHQKn7aGrS3LF1fZQoaAZoCWgPQwidg2dCk8Thv5SGlFKUaBVLMmgWR0Cp/huj7ALzdX2UKGgGaAloD0MIPdUhN8MN3r+UhpRSlGgVSzJoFkdAqf2ScI7eVXV9lChoBmgJaA9DCHTudr00Rd+/lIaUUpRoFUsyaBZHQKn8/wVCXyB1fZQoaAZoCWgPQwiE2JlC5zXZv5SGlFKUaBVLMmgWR0Cp/IjXFtKqdX2UKGgGaAloD0MIG2fTEcDN4r+UhpRSlGgVSzJoFkdAqf89ihFmWnV9lChoBmgJaA9DCHAIVWr2wOK/lIaUUpRoFUsyaBZHQKn+tDjR2KV1fZQoaAZoCWgPQwhaaOc0C7Tqv5SGlFKUaBVLMmgWR0Cp/iDVH4GmdX2UKGgGaAloD0MII2WLpN3o4L+UhpRSlGgVSzJoFkdAqf2qq814xHV9lChoBmgJaA9DCA1QGmoUkti/lIaUUpRoFUsyaBZHQKoAaBmwqy51fZQoaAZoCWgPQwhNDwpK0crhv5SGlFKUaBVLMmgWR0Cp/978WKuTdX2UKGgGaAloD0MItTNMbamD57+UhpRSlGgVSzJoFkdAqf9Lx9XtB3V9lChoBmgJaA9DCBCyLJj4o+O/lIaUUpRoFUsyaBZHQKn+1azu4PR1fZQoaAZoCWgPQwgDCB9KtGThv5SGlFKUaBVLMmgWR0CqAYtpVS4wdX2UKGgGaAloD0MIKSDtf4A16L+UhpRSlGgVSzJoFkdAqgECG+K0lnV9lChoBmgJaA9DCABSmzi5396/lIaUUpRoFUsyaBZHQKoAbqyGBWh1fZQoaAZoCWgPQwjDtkWZDTLiv5SGlFKUaBVLMmgWR0Cp//ifg75mdX2UKGgGaAloD0MI3NYWnpeK07+UhpRSlGgVSzJoFkdAqgKwQ4CIUXV9lChoBmgJaA9DCLJiuDoA4ta/lIaUUpRoFUsyaBZHQKoCJvqC6H11fZQoaAZoCWgPQwhm9nmM8szSv5SGlFKUaBVLMmgWR0CqAZOloDgZdX2UKGgGaAloD0MIrFeR0QFJ57+UhpRSlGgVSzJoFkdAqgEdh7Vrh3V9lChoBmgJaA9DCI9v7xr0pdm/lIaUUpRoFUsyaBZHQKoD3g8bJfZ1fZQoaAZoCWgPQwg/kSdJ10zhv5SGlFKUaBVLMmgWR0CqA1TnaFmGdX2UKGgGaAloD0MIe/Xx0He30r+UhpRSlGgVSzJoFkdAqgLBk/bCanV9lChoBmgJaA9DCBt/orJhTdS/lIaUUpRoFUsyaBZHQKoCS3ZPEbZ1ZS4="}, "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"}}
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": -3.37397569892928, "std_reward": 0.8623415361410468, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-14T18:13:26.811410"}
 
1
+ {"mean_reward": -0.3869822229258716, "std_reward": 0.11022678268925998, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-15T15:45:10.199963"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:59cc263bc535beeb36d0cab996fc2e1e6927b24ef5212ff1a7f5a8a494d0ef22
3
  size 3056
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:254e2fd3ccc8e5b545fc5f25d8ab1ef42b0a33db16300df87b73dccf4f48c368
3
  size 3056