Initial commit

.gitattributes

@@ -30,3 +30,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- AntBulletEnv-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: A2C
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 1218.38 +/- 203.74
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: AntBulletEnv-v0
+      type: AntBulletEnv-v0
+---
+
+# **A2C** Agent playing **AntBulletEnv-v0**
+This is a trained model of a **A2C** agent playing **AntBulletEnv-v0**
+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
+
+...
+```

a2c-AntBulletEnv-v0.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:52fe91eab1f4833cb9f2d1920a1554fba11445a1ae685f87ce2d900b1913ecfe
+size 129195

a2c-AntBulletEnv-v0/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.1

a2c-AntBulletEnv-v0/data

@@ -0,0 +1,105 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
+        "__module__": "stable_baselines3.common.policies",
+        "__doc__": "\n    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\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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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: 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    ",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7fdaf09cd680>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdaf09cd710>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdaf09cd7a0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdaf09cd830>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fdaf09cd8c0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fdaf09cd950>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdaf09cd9e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fdaf09cda70>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdaf09cdb00>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdaf09cdb90>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdaf09cdc20>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fdaf0a1d870>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {
+        ":type:": "<class 'dict'>",
+        ":serialized:": "gASVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
+        "log_std_init": -2,
+        "ortho_init": false,
+        "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
+        "optimizer_kwargs": {
+            "alpha": 0.99,
+            "eps": 1e-05,
+            "weight_decay": 0
+        }
+    },
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            28
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
+        "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_np_random": null
+    },
+    "n_envs": 4,
+    "num_timesteps": 2000000,
+    "_total_timesteps": 2000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1664838117710510563,
+    "learning_rate": 0.00096,
+    "tensorboard_log": "./tensorboard",
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAAAAACUdJRiLg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_episode_num": 0,
+    "use_sde": true,
+    "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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 62500,
+    "n_steps": 8,
+    "gamma": 0.99,
+    "gae_lambda": 0.9,
+    "ent_coef": 0.0,
+    "vf_coef": 0.4,
+    "max_grad_norm": 0.5,
+    "normalize_advantage": false
+}

a2c-AntBulletEnv-v0/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d32aa849d5a3fc9d401d1a820e1953a3aaafd814dd4be656fa7dee94110f662
+size 56126

a2c-AntBulletEnv-v0/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e959d5067940b124eec299d2425d99fd30dba4d6965d111ecf0bc09603c19027
+size 56766

a2c-AntBulletEnv-v0/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

a2c-AntBulletEnv-v0/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.7.14
+Stable-Baselines3: 1.6.1
+PyTorch: 1.12.1+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

config.json

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    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\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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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: 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    ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7fdaf09cd680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdaf09cd710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdaf09cd7a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdaf09cd830>", "_build": "<function ActorCriticPolicy._build at 0x7fdaf09cd8c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fdaf09cd950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdaf09cd9e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fdaf09cda70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdaf09cdb00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdaf09cdb90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdaf09cdc20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fdaf0a1d870>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gASVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gASViwIAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLHIWUjANsb3eUjBVudW1weS5jb3JlLm11bHRpYXJyYXmUjAxfcmVjb25zdHJ1Y3SUk5RoBowHbmRhcnJheZSTlEsAhZRDAWKUh5RSlChLAUschZRoColDcAAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP+UdJRijARoaWdolGgSaBRLAIWUaBaHlFKUKEsBSxyFlGgKiUNwAACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5R0lGKMDWJvdW5kZWRfYmVsb3eUaBJoFEsAhZRoFoeUUpQoSwFLHIWUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGKJQxwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlHSUYowNYm91bmRlZF9hYm92ZZRoEmgUSwCFlGgWh5RSlChLAUschZRoKolDHAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUdJRijApfbnBfcmFuZG9tlE51Yi4=", "dtype": "float32", "_shape": [28], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gASVwwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBVudW1weS5jb3JlLm11bHRpYXJyYXmUjAxfcmVjb25zdHJ1Y3SUk5RoBowHbmRhcnJheZSTlEsAhZRDAWKUh5RSlChLAUsIhZRoColDIAAAgL8AAIC/AACAvwAAgL8AAIC/AACAvwAAgL8AAIC/lHSUYowEaGlnaJRoEmgUSwCFlGgWh5RSlChLAUsIhZRoColDIAAAgD8AAIA/AACAPwAAgD8AAIA/AACAPwAAgD8AAIA/lHSUYowNYm91bmRlZF9iZWxvd5RoEmgUSwCFlGgWh5RSlChLAUsIhZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDCAEBAQEBAQEBlHSUYowNYm91bmRlZF9hYm92ZZRoEmgUSwCFlGgWh5RSlChLAUsIhZRoKolDCAEBAQEBAQEBlHSUYowKX25wX3JhbmRvbZROdWIu", "dtype": "float32", "_shape": [8], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_np_random": null}, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1664838117710510563, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gASVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP091EE1VHWmFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVTQIAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwRLHIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiULAAQAAv4WdvuRUob2KkyM/ErGjPy/bEL8EUGu/l1dpPzkbL76fKGI/ZWzmvvLv5z7zq1u/8Axjv+C/iz9rLPa+WdY/vIEabD6U3sI+PihUPywoBzzQMlM+G2r+O6ktyr54dQxAP/clP2wmqz5wqAg/ukudv8dkb7/iKC4/wWE7P4A1gD2Rp4K+xIgUP212KT/cTbO9amZYPyr5gL5Ua4G/Im7+vnfxk79jCr8+2T+0ugyCCD8MGpI/rPL7vXw8VD+q/jE9rSQkvpZgLr/6/g2/bDrnPjFwxb9sJqs+cKgIPyRSUD9TWJg/8zVBP1DYOD9OAsw/20cPP2wztj/Soaw/40DDv1Uej79UNUDAF/yMv4TRjTtZlf8+nKr7PjG3FL6whcM/UQWXPyRIxb7B8VM/cQShPGLrcb8475U8/p4HPzbLNT4xcMW/bCarPvjH778kUlA/1E5gvwZxqD8ymgc/pOpxv2FN3T4GY1O9qM7MPurzBr86okA/DtwYQBak8b0eDky/C953P22iBj7TNn4/gBK1PN6kLT9yn2c/vFdVP+Merj4K0jZAbeUUvarhwT65roO8P/clP2wmqz5wqAg/JFJQP5R0lGIu"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAAAAACUdJRiLg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_episode_num": 0, "use_sde": true, "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:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.14", "Stable-Baselines3": "1.6.1", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:703b3a313c7dff91afed11539143e2cc91a9d1072c61d3da3e37f579a6c434b9
+size 1036851

results.json

@@ -0,0 +1 @@
+{"mean_reward": 1218.3753872323025, "std_reward": 203.73862247454903, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-03T23:59:12.036237"}

vec_normalize.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0fc98ff760506e243eacf615e353c017661549d44c4549e907034c4b65f18929
+size 2763