arrandi commited on
Commit
8cf57c2
·
1 Parent(s): d4113df

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: -3.17 +/- 0.84
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: PandaReachDense-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -2.33 +/- 0.41
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 sha256:85aff9763d4ed63380632986d7cafc50248487d1b0571c4467ba043112a5b919
3
- size 108028
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4de029bcea875f70aa72865ba6ea52dc61daf46bf8dac9e80bcf2719141020ab
3
+ size 108016
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 0x7fa874418dc0>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc._abc_data object at 0x7fa87441b2c0>"
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": 1678813221653888825,
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": "[[ 0.40487808 -0.00354453 0.5868862 ]\n [ 0.40487808 -0.00354453 0.5868862 ]\n [ 0.40487808 -0.00354453 0.5868862 ]\n [ 0.40487808 -0.00354453 0.5868862 ]]",
60
- "desired_goal": "[[-0.6385342 -0.8121469 -0.3569743 ]\n [-0.9601543 -0.74592215 0.5379474 ]\n [ 1.435658 -1.3165133 -0.96276504]\n [ 0.95910096 -0.6189192 0.27486572]]",
61
- "observation": "[[ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]\n [ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]\n [ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]\n [ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]]"
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": "[[-0.02863303 0.14320652 0.08035825]\n [-0.07134575 -0.14391458 0.14108351]\n [-0.11785957 0.13900812 0.08454493]\n [ 0.06154761 -0.11131537 0.24946252]]",
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 0x7fd27a4b0430>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x7fd27a4af580>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {
 
46
  "_num_timesteps_at_start": 0,
47
  "seed": null,
48
  "action_noise": null,
49
+ "start_time": 1678873721180986923,
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": "[[0.4442716 0.01264362 0.5524804 ]\n [0.4442716 0.01264362 0.5524804 ]\n [0.4442716 0.01264362 0.5524804 ]\n [0.4442716 0.01264362 0.5524804 ]]",
60
+ "desired_goal": "[[-1.0862323 -1.0247656 -1.2077174 ]\n [-0.27669987 0.16841659 0.49349442]\n [ 0.19137198 0.20199403 -0.58439344]\n [ 0.5361653 -0.3888108 -0.2297721 ]]",
61
+ "observation": "[[ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]\n [ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]\n [ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]\n [ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]]"
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": "[[-0.01544902 -0.12609859 0.0208693 ]\n [-0.0564434 0.11718043 0.12588938]\n [ 0.03283464 0.1314947 0.12288331]\n [-0.0561154 -0.1296961 0.05088536]]",
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:facc14b78060c87ca40a3b0864552bbb968e22ac4f7fbfa74bbdfb7884112f59
3
  size 44734
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:95a5aefc821d6030347308ba621dcf4a15f33bd16a4b8320e83b3ac5d8d5fb7d
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:f1348ee9d8427245a609283ae9c12d38d76b9e173cbc80d59eb80e1944fbfd2f
3
  size 46014
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f7ddcd4279892b88ddc563588ff1ae58566da9eeaefd2856675ae3bc277faeef
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 0x7fa874418dc0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fa87441b2c0>"}, "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": 1678813221653888825, "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": "[[ 0.40487808 -0.00354453 0.5868862 ]\n [ 0.40487808 -0.00354453 0.5868862 ]\n [ 0.40487808 -0.00354453 0.5868862 ]\n [ 0.40487808 -0.00354453 0.5868862 ]]", "desired_goal": "[[-0.6385342 -0.8121469 -0.3569743 ]\n [-0.9601543 -0.74592215 0.5379474 ]\n [ 1.435658 -1.3165133 -0.96276504]\n [ 0.95910096 -0.6189192 0.27486572]]", "observation": "[[ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]\n [ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]\n [ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]\n [ 0.40487808 -0.00354453 0.5868862 0.00921254 0.00121192 0.00493393]]"}, "_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": "[[-0.02863303 0.14320652 0.08035825]\n [-0.07134575 -0.14391458 0.14108351]\n [-0.11785957 0.13900812 0.08454493]\n [ 0.06154761 -0.11131537 0.24946252]]", "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 0x7fd27a4b0430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fd27a4af580>"}, "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": 1678873721180986923, "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": "[[0.4442716 0.01264362 0.5524804 ]\n [0.4442716 0.01264362 0.5524804 ]\n [0.4442716 0.01264362 0.5524804 ]\n [0.4442716 0.01264362 0.5524804 ]]", "desired_goal": "[[-1.0862323 -1.0247656 -1.2077174 ]\n [-0.27669987 0.16841659 0.49349442]\n [ 0.19137198 0.20199403 -0.58439344]\n [ 0.5361653 -0.3888108 -0.2297721 ]]", "observation": "[[ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]\n [ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]\n [ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]\n [ 0.4442716 0.01264362 0.5524804 0.01372473 -0.00152895 0.00811957]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAA3h19vP0fAb4W9qo8MjFnvUv87z0l6QA+nn0GPYymBj4/qvs9RNllvQ7PBL4qbVA9lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAADqch09GWwarEMjSj4AAAAAAAAAgAAAAACUaA5LBEsGhpRoEnSUUpR1Lg==", "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": "[[-0.01544902 -0.12609859 0.0208693 ]\n [-0.0564434 0.11718043 0.12588938]\n [ 0.03283464 0.1314947 0.12288331]\n [-0.0561154 -0.1296961 0.05088536]]", "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"}}
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": -3.168594187684357, "std_reward": 0.8432267983890191, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-14T17:43:00.866688"}
 
1
+ {"mean_reward": -2.332672009896487, "std_reward": 0.40878454530018365, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-03-15T11:28:33.412284"}
vec_normalize.pkl CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:9733311c31dded0a7fe376970020c907e7a937bfcfc326a15dbe3cdd4260f563
3
  size 3056
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c82c9d43b3eb17566a7e8f1ffcfe4c3e2a0fe5624c7667b9d906ff73a09acf2c
3
  size 3056