Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -2.97 +/- 0.68
+      value: -2.07 +/- 0.88
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8c30a17a595336fa8d11668eb433e6b048bffade758bfb77eeb483f34e922966
-size 108111
+oid sha256:f27254fcd75424b3a8a892e205b33fb4433166d419373fdd8afa060018ec0071
+size 108142

a2c-PandaReachDense-v2/_stable_baselines3_version

@@ -1 +1 @@
-1.7.0
+1.8.0

a2c-PandaReachDense-v2/data

@@ -4,9 +4,9 @@
         ":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 0x7faf53bf30d0>",
+        "__init__": "<function MultiInputActorCriticPolicy.__init__ at 0x7fa0e4c91670>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7faf53bf0a40>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fa0e4c8fe00>"
     },
     "verbose": 1,
     "policy_kwargs": {
@@ -19,34 +19,12 @@
             "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": 1680896625716746645,
+    "start_time": 1681337229621119989,
     "learning_rate": 0.0007,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -55,10 +33,10 @@
     },
     "_last_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
-        "achieved_goal": "[[ 0.39871725 -0.01799999  0.5426383 ]\n [ 0.39871725 -0.01799999  0.5426383 ]\n [ 0.39871725 -0.01799999  0.5426383 ]\n [ 0.39871725 -0.01799999  0.5426383 ]]",
-        "desired_goal": "[[-0.2877377  -1.0615396  -0.7202087 ]\n [-1.0493819  -1.3978118  -1.3559717 ]\n [-0.3323625   1.4198117  -0.07663508]\n [ 1.6751617   0.3698127   0.19231305]]",
-        "observation": "[[ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]\n [ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]\n [ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]\n [ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.38699695 -0.0120919   0.52187365]\n [ 0.38699695 -0.0120919   0.52187365]\n [ 0.38699695 -0.0120919   0.52187365]\n [ 0.38699695 -0.0120919   0.52187365]]",
+        "desired_goal": "[[-0.27219224 -0.7607175   0.3967629 ]\n [ 0.5918192   1.5326917   0.42229864]\n [-0.948528   -0.2678311   1.0244865 ]\n [ 1.7120063  -0.91654783 -1.4641476 ]]",
+        "observation": "[[ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]\n [ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]\n [ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]\n [ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -66,18 +44,19 @@
     },
     "_last_original_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
+        ":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": "[[-0.05954547 -0.10441786  0.02837658]\n [ 0.0880677   0.13183056  0.22421335]\n [-0.10080989  0.08223411  0.09444726]\n [-0.141458    0.08670319  0.00786066]]",
+        "desired_goal": "[[ 0.00951254 -0.12481451  0.16665998]\n [-0.01487388 -0.03873746  0.0124986 ]\n [ 0.09468857  0.02660735  0.13113932]\n [-0.03155989  0.14987247  0.23205914]]",
         "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"
     },
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
     "_current_progress_remaining": 0.0,
+    "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -90,5 +69,27 @@
     "ent_coef": 0.0,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
-    "normalize_advantage": false
+    "normalize_advantage": false,
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.dict.Dict'>",
+        ":serialized:": "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",
+        "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])",
+        "_shape": null,
+        "dtype": null,
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            3
+        ],
+        "low": "[-1. -1. -1.]",
+        "high": "[1. 1. 1.]",
+        "bounded_below": "[ True  True  True]",
+        "bounded_above": "[ True  True  True]",
+        "_np_random": null
+    },
+    "n_envs": 4
 }

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4585ff99df32ab61ab3e286053f732f138c60e726020d6793b0073878ddd3d3c
+oid sha256:137918a4c5c5e9ec32b7c2b019bb63ca7c9e3b03484e2c1a2e89da36a04383aa
 size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5eba01860552164488ac16c82671fa66805e61bf544edc95857eadf909de802f
+oid sha256:83fa4781062d606c60d8dd401597ffadb34a598ce403bf169adc054465d2eb35
 size 46014

a2c-PandaReachDense-v2/system_info.txt

@@ -1,6 +1,6 @@
 - 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
+- Stable-Baselines3: 1.8.0
 - PyTorch: 2.0.0+cu118
 - GPU Enabled: True
 - Numpy: 1.22.4

config.json

@@ -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 0x7faf53bf30d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7faf53bf0a40>"}, "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": 1680896625716746645, "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": "[[ 0.39871725 -0.01799999  0.5426383 ]\n [ 0.39871725 -0.01799999  0.5426383 ]\n [ 0.39871725 -0.01799999  0.5426383 ]\n [ 0.39871725 -0.01799999  0.5426383 ]]", "desired_goal": "[[-0.2877377  -1.0615396  -0.7202087 ]\n [-1.0493819  -1.3978118  -1.3559717 ]\n [-0.3323625   1.4198117  -0.07663508]\n [ 1.6751617   0.3698127   0.19231305]]", "observation": "[[ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]\n [ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]\n [ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]\n [ 3.9871725e-01 -1.7999988e-02  5.4263830e-01  4.9711764e-04\n  -3.0025898e-03 -4.5851353e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]]", "desired_goal": "[[-0.05954547 -0.10441786  0.02837658]\n [ 0.0880677   0.13183056  0.22421335]\n [-0.10080989  0.08223411  0.09444726]\n [-0.141458    0.08670319  0.00786066]]", "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": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
+{"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 0x7fa0e4c91670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fa0e4c8fe00>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVgQAAAAAAAAB9lCiMD29wdGltaXplcl9jbGFzc5SME3RvcmNoLm9wdGltLnJtc3Byb3CUjAdSTVNwcm9wlJOUjBBvcHRpbWl6ZXJfa3dhcmdzlH2UKIwFYWxwaGGURz/vrhR64UeujANlcHOURz7k+LWI42jxjAx3ZWlnaHRfZGVjYXmUSwB1dS4=", "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681337229621119989, "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": "[[ 0.38699695 -0.0120919   0.52187365]\n [ 0.38699695 -0.0120919   0.52187365]\n [ 0.38699695 -0.0120919   0.52187365]\n [ 0.38699695 -0.0120919   0.52187365]]", "desired_goal": "[[-0.27219224 -0.7607175   0.3967629 ]\n [ 0.5918192   1.5326917   0.42229864]\n [-0.948528   -0.2678311   1.0244865 ]\n [ 1.7120063  -0.91654783 -1.4641476 ]]", "observation": "[[ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]\n [ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]\n [ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]\n [ 3.8699695e-01 -1.2091900e-02  5.2187365e-01  1.7520886e-02\n   7.6313074e-05  2.4280408e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]]", "desired_goal": "[[ 0.00951254 -0.12481451  0.16665998]\n [-0.01487388 -0.03873746  0.0124986 ]\n [ 0.09468857  0.02660735  0.13113932]\n [-0.03155989  0.14987247  0.23205914]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 50000, "n_steps": 5, "gamma": 0.99, "gae_lambda": 1.0, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "normalize_advantage": false, "observation_space": {":type:": "<class 'gym.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('desired_goal', Box([-10. -10. -10.], [10. 10. 10.], (3,), float32)), ('observation', Box([-10. -10. -10. -10. -10. -10.], [10. 10. 10. 10. 10. 10.], (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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, "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": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -2.9744017706252635, "std_reward": 0.6770879749874938, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-07T20:42:53.688344"}
+{"mean_reward": -2.0748877787031232, "std_reward": 0.8782638842459128, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-12T23:03:55.150590"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4f45eaaed5fdd875b26381deca7a11c5ca1d4ac24c2f6bada549c2ae310d62be
-size 3056
+oid sha256:0b0a80caa403eb291ff3922e54214b1695586ad7ce631f41b1cb7d2f0da1c1e6
+size 2381