Commit
·
6ab1947
1
Parent(s):
5f1c43f
Initial commit
Browse files- README.md +1 -1
- a2c-PandaReachDense-v2.zip +2 -2
- a2c-PandaReachDense-v2/data +18 -16
- a2c-PandaReachDense-v2/policy.optimizer.pth +2 -2
- a2c-PandaReachDense-v2/policy.pth +2 -2
- config.json +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
- vec_normalize.pkl +1 -1
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: PandaReachDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value: -
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: PandaReachDense-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: -0.75 +/- 0.30
|
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:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:73c8856d61c5b5f237c283e1696d6864f0863083c1661bcfd573914140729616
|
3 |
+
size 109484
|
a2c-PandaReachDense-v2/data
CHANGED
@@ -11,7 +11,9 @@
|
|
11 |
"verbose": 1,
|
12 |
"policy_kwargs": {
|
13 |
":type:": "<class 'dict'>",
|
14 |
-
":serialized:": "
|
|
|
|
|
15 |
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
16 |
"optimizer_kwargs": {
|
17 |
"alpha": 0.99,
|
@@ -46,19 +48,19 @@
|
|
46 |
"_num_timesteps_at_start": 0,
|
47 |
"seed": null,
|
48 |
"action_noise": null,
|
49 |
-
"start_time":
|
50 |
-
"learning_rate": 0.
|
51 |
"tensorboard_log": null,
|
52 |
"lr_schedule": {
|
53 |
":type:": "<class 'function'>",
|
54 |
-
":serialized:": "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
|
55 |
},
|
56 |
"_last_obs": {
|
57 |
":type:": "<class 'collections.OrderedDict'>",
|
58 |
-
":serialized:": "
|
59 |
-
"achieved_goal": "[[0.
|
60 |
-
"desired_goal": "[[
|
61 |
-
"observation": "[[0.
|
62 |
},
|
63 |
"_last_episode_starts": {
|
64 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -66,29 +68,29 @@
|
|
66 |
},
|
67 |
"_last_original_obs": {
|
68 |
":type:": "<class 'collections.OrderedDict'>",
|
69 |
-
":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAA6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+6nIdPRlsGqxDI0o+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////
|
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": "[[
|
72 |
"observation": "[[ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12 1.9740014e-01 0.0000000e+00\n -0.0000000e+00 0.0000000e+00]]"
|
73 |
},
|
74 |
"_episode_num": 0,
|
75 |
-
"use_sde":
|
76 |
"sde_sample_freq": -1,
|
77 |
"_current_progress_remaining": 0.0,
|
78 |
"ep_info_buffer": {
|
79 |
":type:": "<class 'collections.deque'>",
|
80 |
-
":serialized:": "gAWVHRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////
|
81 |
},
|
82 |
"ep_success_buffer": {
|
83 |
":type:": "<class 'collections.deque'>",
|
84 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
85 |
},
|
86 |
-
"_n_updates":
|
87 |
-
"n_steps":
|
88 |
"gamma": 0.99,
|
89 |
-
"gae_lambda":
|
90 |
"ent_coef": 0.0,
|
91 |
-
"vf_coef": 0.
|
92 |
"max_grad_norm": 0.5,
|
93 |
"normalize_advantage": false
|
94 |
}
|
|
|
11 |
"verbose": 1,
|
12 |
"policy_kwargs": {
|
13 |
":type:": "<class 'dict'>",
|
14 |
+
":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
|
15 |
+
"log_std_init": -2,
|
16 |
+
"ortho_init": false,
|
17 |
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
18 |
"optimizer_kwargs": {
|
19 |
"alpha": 0.99,
|
|
|
48 |
"_num_timesteps_at_start": 0,
|
49 |
"seed": null,
|
50 |
"action_noise": null,
|
51 |
+
"start_time": 1674216357382478341,
|
52 |
+
"learning_rate": 0.00096,
|
53 |
"tensorboard_log": null,
|
54 |
"lr_schedule": {
|
55 |
":type:": "<class 'function'>",
|
56 |
+
":serialized:": "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"
|
57 |
},
|
58 |
"_last_obs": {
|
59 |
":type:": "<class 'collections.OrderedDict'>",
|
60 |
+
":serialized:": "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",
|
61 |
+
"achieved_goal": "[[0.4367352 0.01521655 0.53750116]\n [0.4367352 0.01521655 0.53750116]\n [0.4367352 0.01521655 0.53750116]\n [0.4367352 0.01521655 0.53750116]]",
|
62 |
+
"desired_goal": "[[-0.33606994 -0.43924043 -1.1947103 ]\n [ 0.84907514 -1.6012307 -0.5799214 ]\n [ 1.1327606 -1.104077 -1.277455 ]\n [-1.6007233 -1.5846356 -1.1472789 ]]",
|
63 |
+
"observation": "[[0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]\n [0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]\n [0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]\n [0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]]"
|
64 |
},
|
65 |
"_last_episode_starts": {
|
66 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
68 |
},
|
69 |
"_last_original_obs": {
|
70 |
":type:": "<class 'collections.OrderedDict'>",
|
71 |
+
":serialized:": "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",
|
72 |
"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]]",
|
73 |
+
"desired_goal": "[[0.0501318 0.04169516 0.24311464]\n [0.10302217 0.11492892 0.01832872]\n [0.02914217 0.02960148 0.12601484]\n [0.12383675 0.06253212 0.18788569]]",
|
74 |
"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]]"
|
75 |
},
|
76 |
"_episode_num": 0,
|
77 |
+
"use_sde": true,
|
78 |
"sde_sample_freq": -1,
|
79 |
"_current_progress_remaining": 0.0,
|
80 |
"ep_info_buffer": {
|
81 |
":type:": "<class 'collections.deque'>",
|
82 |
+
":serialized:": "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"
|
83 |
},
|
84 |
"ep_success_buffer": {
|
85 |
":type:": "<class 'collections.deque'>",
|
86 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
87 |
},
|
88 |
+
"_n_updates": 31250,
|
89 |
+
"n_steps": 8,
|
90 |
"gamma": 0.99,
|
91 |
+
"gae_lambda": 0.9,
|
92 |
"ent_coef": 0.0,
|
93 |
+
"vf_coef": 0.4,
|
94 |
"max_grad_norm": 0.5,
|
95 |
"normalize_advantage": false
|
96 |
}
|
a2c-PandaReachDense-v2/policy.optimizer.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1f624c29a8e8439172cb9aeb1c32cdfd154e2a952a623c0be3e852d40a9004b4
|
3 |
+
size 45438
|
a2c-PandaReachDense-v2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:771cd0cf6fd8e44f496e267b54e957c8fac3df6aa6440bcd1e7b4e24b82bf7c7
|
3 |
+
size 46718
|
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 0x7f8e4f3da160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8e4f43dcc0>"}, "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": 1674213017659076189, "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": "[[0.38597137 0.01262159 0.65504676]\n [0.38597137 0.01262159 0.65504676]\n [0.38597137 0.01262159 0.65504676]\n [0.38597137 0.01262159 0.65504676]]", "desired_goal": "[[ 0.6421309 0.7136528 -0.2673499 ]\n [-0.76631206 0.39301875 -0.8608637 ]\n [ 1.3995352 0.7192844 -0.701537 ]\n [ 1.4645684 -0.318875 1.4761754 ]]", "observation": "[[0.38597137 0.01262159 0.65504676 0.00702846 0.00159805 0.00639273]\n [0.38597137 0.01262159 0.65504676 0.00702846 0.00159805 0.00639273]\n [0.38597137 0.01262159 0.65504676 0.00702846 0.00159805 0.00639273]\n [0.38597137 0.01262159 0.65504676 0.00702846 0.00159805 0.00639273]]"}, "_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": "[[-0.09158579 0.12924533 0.11255939]\n [-0.14697006 0.12241299 0.18409714]\n [-0.08267685 0.14370932 0.28181514]\n [-0.07210309 0.05140615 0.23853904]]", "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-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "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 0x7f8e4f3da160>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8e4f43dcc0>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "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": 1674216357382478341, "learning_rate": 0.00096, "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": "[[0.4367352 0.01521655 0.53750116]\n [0.4367352 0.01521655 0.53750116]\n [0.4367352 0.01521655 0.53750116]\n [0.4367352 0.01521655 0.53750116]]", "desired_goal": "[[-0.33606994 -0.43924043 -1.1947103 ]\n [ 0.84907514 -1.6012307 -0.5799214 ]\n [ 1.1327606 -1.104077 -1.277455 ]\n [-1.6007233 -1.5846356 -1.1472789 ]]", "observation": "[[0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]\n [0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]\n [0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]\n [0.4367352 0.01521655 0.53750116 0.05440094 0.00200883 0.05209596]]"}, "_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": "[[0.0501318 0.04169516 0.24311464]\n [0.10302217 0.11492892 0.01832872]\n [0.02914217 0.02960148 0.12601484]\n [0.12383675 0.06253212 0.18788569]]", "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": true, "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": 31250, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.29 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.8.10", "Stable-Baselines3": "1.7.0", "PyTorch": "1.13.1+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "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": -
|
|
|
1 |
+
{"mean_reward": -0.7461167449597269, "std_reward": 0.29601811177719284, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-20T12:50:38.684801"}
|
vec_normalize.pkl
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 3056
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:00a8baeb36e0db56b15da2dcf1960981db36ea5e11d925cd2496def125b075f1
|
3 |
size 3056
|