Test commit

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- KimHerEnv
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: HER
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: KimHerEnv
+      type: KimHerEnv
+    metrics:
+    - type: mean_reward
+      value: -5.00 +/- 0.00
+      name: mean_reward
+      verified: false
+---
+
+# **HER** Agent playing **KimHerEnv**
+This is a trained model of a **HER** agent playing **KimHerEnv**
+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 0x7bf9f4722200>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bf9f4729200>"}, "verbose": 0, "policy_kwargs": {"net_arch": [256, 256, 256], "n_critics": 1}, "num_timesteps": 100, "_total_timesteps": 100, "_num_timesteps_at_start": 0, "seed": 188156, "action_noise": {":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>", ":serialized:": "gAWVUwEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBIWUjAFDlHSUUpSMBl9zaWdtYZRoCCiWIAAAAAAAAACamZmZmZm5P5qZmZmZmbk/mpmZmZmZuT+amZmZmZm5P5RoDIwCZjiUiYiHlFKUKEsDaBBOTk5K/////0r/////SwB0lGJLBIWUaBN0lFKUjAZfZHR5cGWUaAqMB2Zsb2F0MzKUk5R1Yi4=", "_mu": "[0 0 0 0]", "_sigma": "[0.1 0.1 0.1 0.1]", "_dtype": "<class 'numpy.float32'>"}, "start_time": 1719748341076426805, "learning_rate": 0.0001, "tensorboard_log": "tensorboard_logs/KimHerEnv", "_last_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVAQ0AAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmkxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAUsgSyCHlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAAAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQAAAAAAAAAAAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEAAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJRoDksBSyBLIIeUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGgOSwFLIEsgh5RoEnSUUpR1Lg==", "achieved_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]", "desired_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]", "observation": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'collections.OrderedDict'>", ":serialized:": "gAWVAQ0AAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmkxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAUsgSyCHlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEAAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJRoDksBSyBLIIeUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGgOSwFLIEsgh5RoEnSUUpR1Lg==", "achieved_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]", "desired_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]", "observation": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]"}, "_episode_num": 20, "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:": "gAWVNgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImJiYmJiYmJiYmJiYmJiYmJiYmJZS4="}, "_n_updates": 0, "observation_space": {":type:": "<class 'gymnasium.spaces.dict.Dict'>", ":serialized:": "gAWVXwEAAAAAAACMFWd5bW5hc2l1bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwdZ3ltbmFzaXVtLnNwYWNlcy5tdWx0aV9iaW5hcnmUjAtNdWx0aUJpbmFyeZSTlCmBlH2UKIwBbpRLIEsghpSMBl9zaGFwZZRoEYwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51YowMZGVzaXJlZF9nb2FslGgNKYGUfZQoaBBLIEsghpRoEmggaBNoGWgcTnVijAtvYnNlcnZhdGlvbpRoDSmBlH2UKGgQSyBLIIaUaBJoJGgTaBloHE51YnVoEk5oE05oHE51Yi4=", "spaces": "OrderedDict([('achieved_goal', MultiBinary((32, 32))), ('desired_goal', MultiBinary((32, 32))), ('observation', MultiBinary((32, 32)))])", "_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": "[0. 0. 0. 0.]", "high": "[1. 1. 1. 1.]", "low_repr": "0.0", "high_repr": "1.0", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "buffer_size": 1000000, "batch_size": 256, "learning_starts": 100, "tau": 0.005, "gamma": 0.95, "gradient_steps": -1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMHWhlbHBlcnMuQ3VzdG9tSGVyUmVwbGF5QnVmZmVylIwVQ3VzdG9tSGVyUmVwbGF5QnVmZmVylJOULg==", "__module__": "helpers.CustomHerReplayBuffer", "add": "<function CustomHerReplayBuffer.add at 0x7bf9f460b0a0>", "__doc__": null, "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bf9f4620e00>"}, "replay_buffer_kwargs": {"n_sampled_goal": 4, "goal_selection_strategy": "future", "copy_info_dict": true}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"}, "use_sde_at_warmup": false, "policy_delay": 1, "target_noise_clip": 0.0, "target_policy_noise": 0.1, "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-6.5.0-27-generic-x86_64-with-glibc2.35 # 28~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 15 10:51:06 UTC 2", "Python": "3.10.12", "Stable-Baselines3": "2.2.1", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.26.3", "Cloudpickle": "3.0.0", "Gymnasium": "0.29.1"}}

results.json

@@ -0,0 +1 @@
+{"mean_reward": -5.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-30T13:52:29.358036"}

timestamp.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ed680af1181cb839a4fb57ce58f6ab432a75a2043f5f068966477a31f998a331
+size 14746501

timestamp/_stable_baselines3_version

@@ -0,0 +1 @@
+2.2.1

timestamp/actor.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:90930b0430cfe94c49c98db6d6ff27c8f475af039478ddb05e8c1e8510c95910
+size 1120

timestamp/critic.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:90930b0430cfe94c49c98db6d6ff27c8f475af039478ddb05e8c1e8510c95910
+size 1120

timestamp/data

@@ -0,0 +1,127 @@
+{
+    "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 0x7bf9f4722200>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bf9f4729200>"
+    },
+    "verbose": 0,
+    "policy_kwargs": {
+        "net_arch": [
+            256,
+            256,
+            256
+        ],
+        "n_critics": 1
+    },
+    "num_timesteps": 100,
+    "_total_timesteps": 100,
+    "_num_timesteps_at_start": 0,
+    "seed": 188156,
+    "action_noise": {
+        ":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>",
+        ":serialized:": "gAWVUwEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBIWUjAFDlHSUUpSMBl9zaWdtYZRoCCiWIAAAAAAAAACamZmZmZm5P5qZmZmZmbk/mpmZmZmZuT+amZmZmZm5P5RoDIwCZjiUiYiHlFKUKEsDaBBOTk5K/////0r/////SwB0lGJLBIWUaBN0lFKUjAZfZHR5cGWUaAqMB2Zsb2F0MzKUk5R1Yi4=",
+        "_mu": "[0 0 0 0]",
+        "_sigma": "[0.1 0.1 0.1 0.1]",
+        "_dtype": "<class 'numpy.float32'>"
+    },
+    "start_time": 1719748341076426805,
+    "learning_rate": 0.0001,
+    "tensorboard_log": "tensorboard_logs/KimHerEnv",
+    "_last_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "gAWVAQ0AAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmkxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAUsgSyCHlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAAAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQAAAAAAAAAAAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEAAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJRoDksBSyBLIIeUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGgOSwFLIEsgh5RoEnSUUpR1Lg==",
+        "achieved_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]",
+        "desired_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]",
+        "observation": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'collections.OrderedDict'>",
+        ":serialized:": "gAWVAQ0AAAAAAACMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwSbnVtcHkuY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEAAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmkxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAUsgSyCHlIwBQ5R0lFKUjAxkZXNpcmVkX2dvYWyUaAcolgAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAEBAAAAAAAAAAAAAAAAAAAAAAAAAAABAQAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAAAAAAAAAAABAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEAAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJRoDksBSyBLIIeUaBJ0lFKUjAtvYnNlcnZhdGlvbpRoByiWAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQAAAAEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEBAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQEBAQEBAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBAQEBAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGgOSwFLIEsgh5RoEnSUUpR1Lg==",
+        "achieved_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]",
+        "desired_goal": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]",
+        "observation": "[[[0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  ...\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]\n  [0 0 0 ... 0 0 0]]]"
+    },
+    "_episode_num": 20,
+    "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:": "gAWVNgAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKImJiYmJiYmJiYmJiYmJiYmJiYmJZS4="
+    },
+    "_n_updates": 0,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.dict.Dict'>",
+        ":serialized:": "gAWVXwEAAAAAAACMFWd5bW5hc2l1bS5zcGFjZXMuZGljdJSMBERpY3SUk5QpgZR9lCiMBnNwYWNlc5SMC2NvbGxlY3Rpb25zlIwLT3JkZXJlZERpY3SUk5QpUpQojA1hY2hpZXZlZF9nb2FslIwdZ3ltbmFzaXVtLnNwYWNlcy5tdWx0aV9iaW5hcnmUjAtNdWx0aUJpbmFyeZSTlCmBlH2UKIwBbpRLIEsghpSMBl9zaGFwZZRoEYwFZHR5cGWUjAVudW1weZSMBWR0eXBllJOUjAJpMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51YowMZGVzaXJlZF9nb2FslGgNKYGUfZQoaBBLIEsghpRoEmggaBNoGWgcTnVijAtvYnNlcnZhdGlvbpRoDSmBlH2UKGgQSyBLIIaUaBJoJGgTaBloHE51YnVoEk5oE05oHE51Yi4=",
+        "spaces": "OrderedDict([('achieved_goal', MultiBinary((32, 32))), ('desired_goal', MultiBinary((32, 32))), ('observation', MultiBinary((32, 32)))])",
+        "_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": "[0. 0. 0. 0.]",
+        "high": "[1. 1. 1. 1.]",
+        "low_repr": "0.0",
+        "high_repr": "1.0",
+        "_np_random": "Generator(PCG64)"
+    },
+    "n_envs": 1,
+    "buffer_size": 1000000,
+    "batch_size": 256,
+    "learning_starts": 100,
+    "tau": 0.005,
+    "gamma": 0.95,
+    "gradient_steps": -1,
+    "optimize_memory_usage": false,
+    "replay_buffer_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVOwAAAAAAAACMHWhlbHBlcnMuQ3VzdG9tSGVyUmVwbGF5QnVmZmVylIwVQ3VzdG9tSGVyUmVwbGF5QnVmZmVylJOULg==",
+        "__module__": "helpers.CustomHerReplayBuffer",
+        "add": "<function CustomHerReplayBuffer.add at 0x7bf9f460b0a0>",
+        "__doc__": null,
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bf9f4620e00>"
+    },
+    "replay_buffer_kwargs": {
+        "n_sampled_goal": 4,
+        "goal_selection_strategy": "future",
+        "copy_info_dict": true
+    },
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "policy_delay": 1,
+    "target_noise_clip": 0.0,
+    "target_policy_noise": 0.1,
+    "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": []
+}

timestamp/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d56a10ef7136ee9bd5e3fccd83e156b5b70826d62d5b7725cff83ca0fe2d7a43
+size 14723318

timestamp/pytorch_variables.pth

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

timestamp/system_info.txt

@@ -0,0 +1,8 @@
+- OS: Linux-6.5.0-27-generic-x86_64-with-glibc2.35 # 28~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Mar 15 10:51:06 UTC 2
+- Python: 3.10.12
+- Stable-Baselines3: 2.2.1
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: True
+- Numpy: 1.26.3
+- Cloudpickle: 3.0.0
+- Gymnasium: 0.29.1