Initial commit

args.yml

@@ -56,7 +56,7 @@
   - - save_replay_buffer
     - false
   - - seed
-    - 1029813955
+    - 3106717846
   - - storage
     - null
   - - study_name

dqn-FrozenLake-v1.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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 size 115453

dqn-FrozenLake-v1/data

@@ -5,15 +5,15 @@
         "__module__": "stable_baselines3.dqn.policies",
         "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}",
         "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\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    ",
-        "__init__": "<function DQNPolicy.__init__ at 0x7fd7b6023910>",
-        "_build": "<function DQNPolicy._build at 0x7fd7b60239a0>",
-        "make_q_net": "<function DQNPolicy.make_q_net at 0x7fd7b6023a30>",
-        "forward": "<function DQNPolicy.forward at 0x7fd7b6023ac0>",
-        "_predict": "<function DQNPolicy._predict at 0x7fd7b6023b50>",
-        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7fd7b6023be0>",
-        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7fd7b6023c70>",
+        "__init__": "<function DQNPolicy.__init__ at 0x7f482b60f910>",
+        "_build": "<function DQNPolicy._build at 0x7f482b60f9a0>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7f482b60fa30>",
+        "forward": "<function DQNPolicy.forward at 0x7f482b60fac0>",
+        "_predict": "<function DQNPolicy._predict at 0x7f482b60fb50>",
+        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7f482b60fbe0>",
+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7f482b60fc70>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fd7b603c3c0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f482b624c80>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -22,7 +22,7 @@
     "_num_timesteps_at_start": 0,
     "seed": 0,
     "action_noise": null,
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     "ep_success_buffer": {
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@@ -83,13 +83,13 @@
         "__module__": "stable_baselines3.common.buffers",
         "__annotations__": "{'observations': <class 'numpy.ndarray'>, 'next_observations': <class 'numpy.ndarray'>, 'actions': <class 'numpy.ndarray'>, 'rewards': <class 'numpy.ndarray'>, 'dones': <class 'numpy.ndarray'>, 'timeouts': <class 'numpy.ndarray'>}",
         "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\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        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\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 ReplayBuffer.__init__ at 0x7fd7b6169120>",
-        "add": "<function ReplayBuffer.add at 0x7fd7b61691b0>",
-        "sample": "<function ReplayBuffer.sample at 0x7fd7b6169240>",
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-        "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7fd7b6169360>)>",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7f482b759120>",
+        "add": "<function ReplayBuffer.add at 0x7f482b7591b0>",
+        "sample": "<function ReplayBuffer.sample at 0x7f482b759240>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7f482b7592d0>",
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         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fd7b62ecd80>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f482b8d8280>"
     },
     "replay_buffer_kwargs": {},
     "train_freq": {

dqn-FrozenLake-v1/policy.optimizer.pth

@@ -1,3 +1,3 @@
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