Initial commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- PandaReachDense-v3
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DDPG
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaReachDense-v3
+      type: PandaReachDense-v3
+    metrics:
+    - type: mean_reward
+      value: -0.20 +/- 0.07
+      name: mean_reward
+      verified: false
+---
+
+# **DDPG** Agent playing **PandaReachDense-v3**
+This is a trained model of a **DDPG** agent playing **PandaReachDense-v3**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNwAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMEE11bHRpSW5wdXRQb2xpY3mUk5Qu", "__module__": "stable_baselines3.td3.policies", "__doc__": "\n    Policy class (with both actor and critic) for TD3 to be used with Dict observation spaces.\n\n    :param observation_space: Observation space\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 features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\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    :param n_critics: Number of critic networks to create.\n    :param share_features_extractor: Whether to share or not the features extractor\n        between the actor and the critic (this saves computation time)\n    ", "__init__": "<function MultiInputPolicy.__init__ at 0x7bfddade0940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bfddaddcc80>"}, "verbose": 1, "policy_kwargs": {"n_critics": 1}, "num_timesteps": 1000000, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1717756430033347093, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.440281    0.5547311  -0.20201245]\n [-0.7234965   0.5420322   0.35252732]\n [ 0.3304703   0.01011297  0.48541114]\n [-1.2986743  -1.7568817   0.10554398]]", "desired_goal": "[[ 0.89332896  1.3828161  -1.0587928 ]\n [-1.5017471   1.4468223   1.2367333 ]\n [-1.1606451  -1.5127715   0.8157575 ]\n [-0.82494164 -1.2003382   0.23628302]]", "observation": "[[ 0.440281    0.5547311  -0.20201245 -0.12144244  1.8029588  -1.4751432 ]\n [-0.7234965   0.5420322   0.35252732 -0.8168877   1.7984037   0.9248575 ]\n [ 0.3304703   0.01011297  0.48541114  0.57532     0.0077876   0.41351935]\n [-1.2986743  -1.7568817   0.10554398 -1.134174   -1.1281489  -0.81636304]]"}, "_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": "[[ 4.3059584e-02  2.4396311e-02  1.7180830e-01]\n [-5.9024203e-03  2.3827462e-02  1.9245306e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [-3.0101085e-02 -7.9152994e-02  1.8325821e-01]]", "desired_goal": "[[ 0.07472277  0.12530053  0.04477451]\n [-0.14413844  0.13110521  0.25563422]\n [-0.11296866 -0.13729882  0.21696472]\n [-0.08229219 -0.10896441  0.16373605]]", "observation": "[[ 4.3059584e-02  2.4396311e-02  1.7180830e-01 -2.9419860e-01\n   1.2190359e+00 -1.3114345e+00]\n [-5.9024203e-03  2.3827462e-02  1.9245306e-01 -5.8784103e-01\n   1.2159426e+00  3.5505891e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [-3.0101085e-02 -7.9152994e-02  1.8325821e-01 -7.2181094e-01\n  -7.7137339e-01 -8.5399598e-01]]"}, "_episode_num": 377302, "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:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIhlLg=="}, "_n_updates": 249975, "buffer_size": 1000000, "batch_size": 256, "learning_starts": 100, "tau": 0.005, "gamma": 0.99, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwQRGljdFJlcGxheUJ1ZmZlcpSTlC4=", "__module__": "stable_baselines3.common.buffers", "__annotations__": "{'observation_space': <class 'gymnasium.spaces.dict.Dict'>, 'obs_shape': typing.Dict[str, typing.Tuple[int, ...]], 'observations': typing.Dict[str, numpy.ndarray], 'next_observations': typing.Dict[str, numpy.ndarray]}", "__doc__": "\n    Dict Replay buffer used in off-policy algorithms like SAC/TD3.\n    Extends the ReplayBuffer to use dictionary observations\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        Disabled for now (see https://github.com/DLR-RM/stable-baselines3/pull/243#discussion_r531535702)\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ", "__init__": "<function DictReplayBuffer.__init__ at 0x7bfddaf24700>", "add": "<function DictReplayBuffer.add at 0x7bfddaf24790>", "sample": "<function DictReplayBuffer.sample at 0x7bfddaf24820>", "_get_samples": "<function DictReplayBuffer._get_samples at 0x7bfddaf248b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bfddaf17b40>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "policy_delay": 1, "target_noise_clip": 0.0, "target_policy_noise": 0.1, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (6,), float32))])", "_shape": null, "dtype": null, "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True]", "bounded_above": "[ True  True  True]", "_shape": [3], "low": "[-1. -1. -1.]", "high": "[1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": "Generator(PCG64)"}, "n_envs": 4, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVoAMAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLA0sTQwx0AIgAfACDAYMBUwCUToWUjAVmbG9hdJSFlIwScHJvZ3Jlc3NfcmVtYWluaW5nlIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwIPGxhbWJkYT6US2FDAgwAlIwOdmFsdWVfc2NoZWR1bGWUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxJL3Vzci9sb2NhbC9saWIvcHl0aG9uMy4xMC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGghfZR9lChoGGgPjAxfX3F1YWxuYW1lX1+UjCFnZXRfc2NoZWR1bGVfZm4uPGxvY2Fscz4uPGxhbWJkYT6UjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgZjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOUaAIoaAcoSwFLAEsASwFLAUsTQwSIAFMAlGgJKYwBX5SFlGgOjARmdW5jlEuFQwIEAZSMA3ZhbJSFlCl0lFKUaBVOTmgdKVKUhZR0lFKUaCRoPn2UfZQoaBhoNWgnjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlGgpfZRoK05oLE5oLWgZaC5OaC9oMUc/UGJN0vGp/IWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwhZRSlIWUaEZdlGhIfZR1hpSGUjAu"}, "actor_batch_norm_stats": [], "critic_batch_norm_stats": [], "actor_batch_norm_stats_target": [], "critic_batch_norm_stats_target": [], "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.3.2", "PyTorch": "2.3.0+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.29.1", "OpenAI Gym": "0.25.2"}}

ddpg-PandaReachDense-v3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e83279dc9c3e1833e57e37203f35b3df389db1c9ccf6606b5d023b524ddcb484
+size 4092193

ddpg-PandaReachDense-v3/_stable_baselines3_version

@@ -0,0 +1 @@
+2.3.2

ddpg-PandaReachDense-v3/actor.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c0f363680b401621fa107b6ab6d578cb5515f995d03acca01e49c32c9fabacf2
+size 1016352

ddpg-PandaReachDense-v3/critic.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:240e72456397f9c47b5aef9bd63e765bad7c962646870b04d5c4ceda1591fc05
+size 1021088

ddpg-PandaReachDense-v3/data

@@ -0,0 +1,116 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVNwAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMEE11bHRpSW5wdXRQb2xpY3mUk5Qu",
+        "__module__": "stable_baselines3.td3.policies",
+        "__doc__": "\n    Policy class (with both actor and critic) for TD3 to be used with Dict observation spaces.\n\n    :param observation_space: Observation space\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 features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\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    :param n_critics: Number of critic networks to create.\n    :param share_features_extractor: Whether to share or not the features extractor\n        between the actor and the critic (this saves computation time)\n    ",
+        "__init__": "<function MultiInputPolicy.__init__ at 0x7bfddade0940>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bfddaddcc80>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        "n_critics": 1
+    },
+    "num_timesteps": 1000000,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1717756430033347093,
+    "learning_rate": 0.001,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.440281    0.5547311  -0.20201245]\n [-0.7234965   0.5420322   0.35252732]\n [ 0.3304703   0.01011297  0.48541114]\n [-1.2986743  -1.7568817   0.10554398]]",
+        "desired_goal": "[[ 0.89332896  1.3828161  -1.0587928 ]\n [-1.5017471   1.4468223   1.2367333 ]\n [-1.1606451  -1.5127715   0.8157575 ]\n [-0.82494164 -1.2003382   0.23628302]]",
+        "observation": "[[ 0.440281    0.5547311  -0.20201245 -0.12144244  1.8029588  -1.4751432 ]\n [-0.7234965   0.5420322   0.35252732 -0.8168877   1.7984037   0.9248575 ]\n [ 0.3304703   0.01011297  0.48541114  0.57532     0.0077876   0.41351935]\n [-1.2986743  -1.7568817   0.10554398 -1.134174   -1.1281489  -0.81636304]]"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "gAWVuwEAAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QoljAAAAAAAAAAP18wPcbaxzyE7i8+F2nBu88xwzxqEkU+6nIdPRlsGqxDI0o+jZb2vPcaor0KqDs+lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwOGlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcoljAAAAAAAAAAQAiZPchOAD55ZTc9B5kTvnJABj594oI+HVznvRCYDL4ALF4+z4iovbso371sqic+lGgOSwRLA4aUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWYAAAAAAAAAA/XzA9xtrHPITuLz4zoZa+XgmcPxbdp78XacG7zzHDPGoSRT7AfBa/AqSbP0jKtT7qch09GWwarEMjSj4AAAAAAAAAgAAAAACNlva89xqivQqoOz6ayDi/unhFv3ufWr+UaA5LBEsGhpRoEnSUUpR1Lg==",
+        "achieved_goal": "[[ 4.3059584e-02  2.4396311e-02  1.7180830e-01]\n [-5.9024203e-03  2.3827462e-02  1.9245306e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01]\n [-3.0101085e-02 -7.9152994e-02  1.8325821e-01]]",
+        "desired_goal": "[[ 0.07472277  0.12530053  0.04477451]\n [-0.14413844  0.13110521  0.25563422]\n [-0.11296866 -0.13729882  0.21696472]\n [-0.08229219 -0.10896441  0.16373605]]",
+        "observation": "[[ 4.3059584e-02  2.4396311e-02  1.7180830e-01 -2.9419860e-01\n   1.2190359e+00 -1.3114345e+00]\n [-5.9024203e-03  2.3827462e-02  1.9245306e-01 -5.8784103e-01\n   1.2159426e+00  3.5505891e-01]\n [ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00]\n [-3.0101085e-02 -7.9152994e-02  1.8325821e-01 -7.2181094e-01\n  -7.7137339e-01 -8.5399598e-01]]"
+    },
+    "_episode_num": 377302,
+    "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:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIhlLg=="
+    },
+    "_n_updates": 249975,
+    "buffer_size": 1000000,
+    "batch_size": 256,
+    "learning_starts": 100,
+    "tau": 0.005,
+    "gamma": 0.99,
+    "gradient_steps": 1,
+    "optimize_memory_usage": false,
+    "replay_buffer_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVOQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwQRGljdFJlcGxheUJ1ZmZlcpSTlC4=",
+        "__module__": "stable_baselines3.common.buffers",
+        "__annotations__": "{'observation_space': <class 'gymnasium.spaces.dict.Dict'>, 'obs_shape': typing.Dict[str, typing.Tuple[int, ...]], 'observations': typing.Dict[str, numpy.ndarray], 'next_observations': typing.Dict[str, numpy.ndarray]}",
+        "__doc__": "\n    Dict Replay buffer used in off-policy algorithms like SAC/TD3.\n    Extends the ReplayBuffer to use dictionary observations\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        Disabled for now (see https://github.com/DLR-RM/stable-baselines3/pull/243#discussion_r531535702)\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
+        "__init__": "<function DictReplayBuffer.__init__ at 0x7bfddaf24700>",
+        "add": "<function DictReplayBuffer.add at 0x7bfddaf24790>",
+        "sample": "<function DictReplayBuffer.sample at 0x7bfddaf24820>",
+        "_get_samples": "<function DictReplayBuffer._get_samples at 0x7bfddaf248b0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bfddaf17b40>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "policy_delay": 1,
+    "target_noise_clip": 0.0,
+    "target_policy_noise": 0.1,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.dict.Dict'>",
+        ":serialized:": "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",
+        "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (3,), float32)), ('desired_goal', Box(-10.0, 10.0, (3,), float32)), ('observation', Box(-10.0, 10.0, (6,), float32))])",
+        "_shape": null,
+        "dtype": null,
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True]",
+        "bounded_above": "[ True  True  True]",
+        "_shape": [
+            3
+        ],
+        "low": "[-1. -1. -1.]",
+        "high": "[1. 1. 1.]",
+        "low_repr": "-1.0",
+        "high_repr": "1.0",
+        "_np_random": "Generator(PCG64)"
+    },
+    "n_envs": 4,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "actor_batch_norm_stats": [],
+    "critic_batch_norm_stats": [],
+    "actor_batch_norm_stats_target": [],
+    "critic_batch_norm_stats_target": []
+}

ddpg-PandaReachDense-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:22fdcfc04ffdc2ead71c10720b7bbd0a25bd2e0199ad874f13a6f7d5614beb52
+size 2036238

ddpg-PandaReachDense-v3/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ddpg-PandaReachDense-v3/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.3.2
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: False
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.29.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": -0.19687472279183565, "std_reward": 0.0693756430551635, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-07T15:15:53.138043"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:074c42ca5a733e8ed516039b527319c46960509b25964c6019414b95f8c1ca70
+size 2849