Initial commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- PandaStackDense-v3
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: TD3
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: PandaStackDense-v3
+      type: PandaStackDense-v3
+    metrics:
+    - type: mean_reward
+      value: -31.88 +/- 18.99
+      name: mean_reward
+      verified: false
+---
+
+# **TD3** Agent playing **PandaStackDense-v3**
+This is a trained model of a **TD3** agent playing **PandaStackDense-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 0x7f386567a680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3865688080>"}, "verbose": 0, "policy_kwargs": {}, "num_timesteps": 30015, "_total_timesteps": 30000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718723926891482231, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.99677396 -0.9233664   0.04288133  1.578063   -1.145768    1.8064792 ]]", "desired_goal": "[[-1.0887921e+00  1.0083158e+00  5.7705182e-07 -1.0887921e+00\n   1.0083158e+00  1.7304648e-06]]", "observation": "[[ 8.1198215e-01  6.5270908e-02 -3.3659044e-01  3.4365708e-01\n   9.4728882e-04 -9.8565295e-02 -9.0121442e-01  9.9677396e-01\n  -9.2336643e-01  4.2881329e-02  5.1140696e-02  5.2887674e-02\n  -1.7055364e-02  2.1152453e-02  2.6600799e-02 -3.2401308e-03\n   9.2728380e-03  1.0612251e-02  1.0306666e-02  1.5780630e+00\n  -1.1457680e+00  1.8064792e+00  2.5367310e-02 -1.2132302e-01\n  -5.4428391e-02 -2.7706167e-02  3.6662184e-03  1.3266079e-01\n   6.3753542e-03 -2.3302514e-02 -4.9418886e-03]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "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", "achieved_goal": "[[ 0.09114936 -0.08814947  0.02        0.14600025 -0.09197044  0.06      ]]", "desired_goal": "[[-0.09244539  0.07628673  0.02       -0.09244539  0.07628673  0.06      ]]", "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00  0.0000000e+00  9.1149360e-02\n  -8.8149473e-02  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  1.4600025e-01\n  -9.1970444e-02  5.9999999e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00]]"}, "_episode_num": 315, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0004999999999999449, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImJiYmJiYmJiYmJiImJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYiJiYmIiYmJiYmJiYmJiYmJiYmJiYmJiYmIiYmJiYmJiImJiYmJiYmJiYmJiYmJiYllLg=="}, "_n_updates": 29915, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":serialized:": "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", "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (6,), float32)), ('desired_goal', Box(-10.0, 10.0, (6,), float32)), ('observation', Box(-10.0, 10.0, (31,), 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  True]", "bounded_above": "[ True  True  True  True]", "_shape": [4], "low": "[-1. -1. -1. -1.]", "high": "[1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "buffer_size": 1000000, "batch_size": 100, "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", "__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 0x7f3865679510>", "add": "<function DictReplayBuffer.add at 0x7f38656795a0>", "sample": "<function DictReplayBuffer.sample at 0x7f3865679630>", "_get_samples": "<function DictReplayBuffer._get_samples at 0x7f38656796c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f3865676400>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "policy_delay": 2, "target_noise_clip": 0.5, "target_policy_noise": 0.2, "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": [], "system_info": {"OS": "Linux-5.15.133+-x86_64-with-glibc2.31 # 1 SMP Tue Dec 19 13:14:11 UTC 2023", "Python": "3.10.13", "Stable-Baselines3": "2.1.0", "PyTorch": "2.1.2", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.0.0", "Gymnasium": "0.29.0", "OpenAI Gym": "0.26.2"}}

results.json

@@ -0,0 +1 @@
+{"mean_reward": -31.8774607, "std_reward": 18.992955396314226, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-18T15:27:50.104848"}

td3-PandaStackDense-v3.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5987d6690e7deddff506d2996e5047fc87b8e2acd3da04bfe92b366497886eec
+size 6745831

td3-PandaStackDense-v3/_stable_baselines3_version

@@ -0,0 +1 @@
+2.1.0

td3-PandaStackDense-v3/actor.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6c52e4791a6dd21e20fb1178a3e243dfe5ef7b6be359cf4628963b7e55d6a996
+size 1118112

td3-PandaStackDense-v3/critic.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3361cda5009a3822bcca3377ec1d7d2b583d59a4953f8ffd2e61cc72b6f7eeb8
+size 2246442

td3-PandaStackDense-v3/data

@@ -0,0 +1,113 @@
+{
+    "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 0x7f386567a680>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f3865688080>"
+    },
+    "verbose": 0,
+    "policy_kwargs": {},
+    "num_timesteps": 30015,
+    "_total_timesteps": 30000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1718723926891482231,
+    "learning_rate": 0.001,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.99677396 -0.9233664   0.04288133  1.578063   -1.145768    1.8064792 ]]",
+        "desired_goal": "[[-1.0887921e+00  1.0083158e+00  5.7705182e-07 -1.0887921e+00\n   1.0083158e+00  1.7304648e-06]]",
+        "observation": "[[ 8.1198215e-01  6.5270908e-02 -3.3659044e-01  3.4365708e-01\n   9.4728882e-04 -9.8565295e-02 -9.0121442e-01  9.9677396e-01\n  -9.2336643e-01  4.2881329e-02  5.1140696e-02  5.2887674e-02\n  -1.7055364e-02  2.1152453e-02  2.6600799e-02 -3.2401308e-03\n   9.2728380e-03  1.0612251e-02  1.0306666e-02  1.5780630e+00\n  -1.1457680e+00  1.8064792e+00  2.5367310e-02 -1.2132302e-01\n  -5.4428391e-02 -2.7706167e-02  3.6662184e-03  1.3266079e-01\n   6.3753542e-03 -2.3302514e-02 -4.9418886e-03]]"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "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",
+        "achieved_goal": "[[ 0.09114936 -0.08814947  0.02        0.14600025 -0.09197044  0.06      ]]",
+        "desired_goal": "[[-0.09244539  0.07628673  0.02       -0.09244539  0.07628673  0.06      ]]",
+        "observation": "[[ 3.8439669e-02 -2.1944723e-12  1.9740014e-01  0.0000000e+00\n  -0.0000000e+00  0.0000000e+00  0.0000000e+00  9.1149360e-02\n  -8.8149473e-02  2.0000000e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  1.4600025e-01\n  -9.1970444e-02  5.9999999e-02  0.0000000e+00 -0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00  0.0000000e+00\n   0.0000000e+00  0.0000000e+00  0.0000000e+00]]"
+    },
+    "_episode_num": 315,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.0004999999999999449,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVhgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImJiYmJiYmJiYmJiImJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYmJiYiJiYmIiYmJiYmJiYmJiYmJiYmJiYmJiYmIiYmJiYmJiImJiYmJiYmJiYmJiYmJiYllLg=="
+    },
+    "_n_updates": 29915,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.dict.Dict'>",
+        ":serialized:": "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",
+        "spaces": "OrderedDict([('achieved_goal', Box(-10.0, 10.0, (6,), float32)), ('desired_goal', Box(-10.0, 10.0, (6,), float32)), ('observation', Box(-10.0, 10.0, (31,), 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  True]",
+        "bounded_above": "[ True  True  True  True]",
+        "_shape": [
+            4
+        ],
+        "low": "[-1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1.]",
+        "low_repr": "-1.0",
+        "high_repr": "1.0",
+        "_np_random": "Generator(PCG64)"
+    },
+    "n_envs": 1,
+    "buffer_size": 1000000,
+    "batch_size": 100,
+    "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",
+        "__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 0x7f3865679510>",
+        "add": "<function DictReplayBuffer.add at 0x7f38656795a0>",
+        "sample": "<function DictReplayBuffer.sample at 0x7f3865679630>",
+        "_get_samples": "<function DictReplayBuffer._get_samples at 0x7f38656796c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f3865676400>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "policy_delay": 2,
+    "target_noise_clip": 0.5,
+    "target_policy_noise": 0.2,
+    "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": []
+}

td3-PandaStackDense-v3/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d35af8b6e3b05f0c8ed5b36a8f1f6e2a582308770f8164332f98ee436112d7bd
+size 3363050

td3-PandaStackDense-v3/pytorch_variables.pth

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

td3-PandaStackDense-v3/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-5.15.133+-x86_64-with-glibc2.31 # 1 SMP Tue Dec 19 13:14:11 UTC 2023
+- Python: 3.10.13
+- Stable-Baselines3: 2.1.0
+- PyTorch: 2.1.2
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.0.0
+- Gymnasium: 0.29.0
+- OpenAI Gym: 0.26.2

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2399ed91dd50369992c5a47ce8f89aa30b3977fb28de42b689ee308f466fd501
+size 3647