sinhprous commited on
Commit
cb27b8b
1 Parent(s): c0fda58

Initial commit

Browse files
dqn-SpaceInvadersNoFrameskip-v4.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:dd550c50096e4c39e0c409a810307080ff6abee5b9c664b8f4b4e4f405f5f261
3
  size 27222211
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b5e81bdec9c5657a8a5025ece93debc8f0e1985544038aba492cc0fcad7503bb
3
  size 27222211
dqn-SpaceInvadersNoFrameskip-v4/data CHANGED
@@ -4,9 +4,9 @@
4
  ":serialized:": "gASVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCUNublBvbGljeZSTlC4=",
5
  "__module__": "stable_baselines3.dqn.policies",
6
  "__doc__": "\n Policy class for DQN when using images as input.\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 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 ",
7
- "__init__": "<function CnnPolicy.__init__ at 0x7f0dc796b710>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc_data object at 0x7f0dc79dc600>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {},
@@ -83,12 +83,12 @@
83
  ":serialized:": "gASVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
84
  "__module__": "stable_baselines3.common.buffers",
85
  "__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:\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 :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 ",
86
- "__init__": "<function ReplayBuffer.__init__ at 0x7f0dc7e680e0>",
87
- "add": "<function ReplayBuffer.add at 0x7f0dc7e68170>",
88
- "sample": "<function ReplayBuffer.sample at 0x7f0dc79c2170>",
89
- "_get_samples": "<function ReplayBuffer._get_samples at 0x7f0dc79c2200>",
90
  "__abstractmethods__": "frozenset()",
91
- "_abc_impl": "<_abc_data object at 0x7f0dc7ea3d20>"
92
  },
93
  "replay_buffer_kwargs": {},
94
  "train_freq": {
 
4
  ":serialized:": "gASVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCUNublBvbGljeZSTlC4=",
5
  "__module__": "stable_baselines3.dqn.policies",
6
  "__doc__": "\n Policy class for DQN when using images as input.\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 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 ",
7
+ "__init__": "<function CnnPolicy.__init__ at 0x7f1afd635680>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc_data object at 0x7f1afd6a6600>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {},
 
83
  ":serialized:": "gASVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
84
  "__module__": "stable_baselines3.common.buffers",
85
  "__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:\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 :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 ",
86
+ "__init__": "<function ReplayBuffer.__init__ at 0x7f1afdb32050>",
87
+ "add": "<function ReplayBuffer.add at 0x7f1afdb320e0>",
88
+ "sample": "<function ReplayBuffer.sample at 0x7f1afd68c0e0>",
89
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x7f1afd68c170>",
90
  "__abstractmethods__": "frozenset()",
91
+ "_abc_impl": "<_abc_data object at 0x7f1afdb6ed20>"
92
  },
93
  "replay_buffer_kwargs": {},
94
  "train_freq": {
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 925.0, "std_reward": 356.3495474951526, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2022-06-26T19:53:13.885852"}
 
1
+ {"mean_reward": 925.0, "std_reward": 356.3495474951526, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2022-06-27T15:29:48.554586"}