Initial commit

README.md

@@ -16,7 +16,7 @@ model-index:
       type: PandaReachDense-v2
     metrics:
     - type: mean_reward
-      value: -2.84 +/- 0.84
+      value: -6.04 +/- 3.80
       name: mean_reward
       verified: false
 ---

a2c-PandaReachDense-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:09cf3ff405d8d155d5177ebcb560d564863e62f567431b915e90e5913a37fff8
+oid sha256:7e03050f37e35021c60a11e224101674aa2e0bc72ae5f861eae4555a15f2d6ed
 size 108073

a2c-PandaReachDense-v2/data

@@ -24,7 +24,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1687382891367496850,
+    "start_time": 1687384695980320893,
     "learning_rate": 0.0007,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -33,10 +33,10 @@
     },
     "_last_obs": {
         ":type:": "<class 'collections.OrderedDict'>",
-        ":serialized:": "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",
-        "achieved_goal": "[[ 0.3842948  -0.03011806  0.5392589 ]\n [ 0.3842948  -0.03011806  0.5392589 ]\n [ 0.3842948  -0.03011806  0.5392589 ]\n [ 0.3842948  -0.03011806  0.5392589 ]]",
-        "desired_goal": "[[ 0.7736967   1.1518186  -0.28714603]\n [-1.3379412  -0.49171442  1.5211004 ]\n [ 1.613033   -1.4327908  -0.77714384]\n [-1.2221752   1.2617897  -0.4430834 ]]",
-        "observation": "[[ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]\n [ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]\n [ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]\n [ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]]"
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.38287827 -0.01370963  0.6117592 ]\n [ 0.38287827 -0.01370963  0.6117592 ]\n [ 0.38287827 -0.01370963  0.6117592 ]\n [ 0.38287827 -0.01370963  0.6117592 ]]",
+        "desired_goal": "[[ 1.2341293  -0.55205584 -0.21615279]\n [ 0.42665336 -1.7308012  -0.18006688]\n [ 0.9970616   0.5381858   1.6870714 ]\n [-0.53839415 -1.4183811   1.228351  ]]",
+        "observation": "[[ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]\n [ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]\n [ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]\n [ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]]"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -44,9 +44,9 @@
     },
     "_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": "[[ 0.02352525 -0.13760793  0.20690276]\n [ 0.11338398 -0.12570585  0.02361543]\n [ 0.03863534  0.10764696  0.08582053]\n [ 0.12908162 -0.03756215  0.19833021]]",
+        "desired_goal": "[[ 0.02505565  0.02108062  0.12954457]\n [ 0.06732788 -0.06841625  0.19833614]\n [ 0.11150173 -0.06118487  0.10526577]\n [ 0.11922505 -0.08238836  0.02663288]]",
         "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,
@@ -56,7 +56,7 @@
     "_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'>",

a2c-PandaReachDense-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3066b79e7a47715215bdffa7487fc67eaf665a51d4956a1466dfdbf904bd2297
+oid sha256:aad7b7954b1e16c4b111dc90d8135c0353bb784fcd44a8a93f6508eb0da69dda
 size 44734

a2c-PandaReachDense-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3491c312b8611430eed855d6d780d311e95c8c688ed2ee1c8dc6dea4c8dd6c84
+oid sha256:c77c74a572bdccaba3497974460bc5183d33e3cf8ac8fb491b3acc45ba4b850c
 size 46014

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 0x7f468f3cb520>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f468f3bff80>"}, "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": 500000, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687382891367496850, "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": "[[ 0.3842948  -0.03011806  0.5392589 ]\n [ 0.3842948  -0.03011806  0.5392589 ]\n [ 0.3842948  -0.03011806  0.5392589 ]\n [ 0.3842948  -0.03011806  0.5392589 ]]", "desired_goal": "[[ 0.7736967   1.1518186  -0.28714603]\n [-1.3379412  -0.49171442  1.5211004 ]\n [ 1.613033   -1.4327908  -0.77714384]\n [-1.2221752   1.2617897  -0.4430834 ]]", "observation": "[[ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]\n [ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]\n [ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]\n [ 0.3842948  -0.03011806  0.5392589  -0.00495683 -0.00217299 -0.00250989]]"}, "_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": "[[ 0.02352525 -0.13760793  0.20690276]\n [ 0.11338398 -0.12570585  0.02361543]\n [ 0.03863534  0.10764696  0.08582053]\n [ 0.12908162 -0.03756215  0.19833021]]", "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": 25000, "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:": "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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, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+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 0x7f468f3cb520>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f468f3bff80>"}, "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": 500000, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1687384695980320893, "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": "[[ 0.38287827 -0.01370963  0.6117592 ]\n [ 0.38287827 -0.01370963  0.6117592 ]\n [ 0.38287827 -0.01370963  0.6117592 ]\n [ 0.38287827 -0.01370963  0.6117592 ]]", "desired_goal": "[[ 1.2341293  -0.55205584 -0.21615279]\n [ 0.42665336 -1.7308012  -0.18006688]\n [ 0.9970616   0.5381858   1.6870714 ]\n [-0.53839415 -1.4183811   1.228351  ]]", "observation": "[[ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]\n [ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]\n [ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]\n [ 0.38287827 -0.01370963  0.6117592  -0.01089135  0.00090218  0.00163508]]"}, "_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": "[[ 0.02505565  0.02108062  0.12954457]\n [ 0.06732788 -0.06841625  0.19833614]\n [ 0.11150173 -0.06118487  0.10526577]\n [ 0.11922505 -0.08238836  0.02663288]]", "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": 25000, "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:": "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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, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -2.8384433733299375, "std_reward": 0.8358827660223384, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-21T21:54:19.094742"}
+{"mean_reward": -6.035799402184784, "std_reward": 3.801916967503714, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-06-21T22:24:03.247259"}

vec_normalize.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ae6cc0f0787525f3d2b5acc2ba9e4b155e4074b2357cc2929f10baca5411fabd
+oid sha256:755ef407e78745e7650312db0d506982a3270684dbc84e21e88436a07003a470
 size 2387