hossniper commited on
Commit
d955ff6
1 Parent(s): 54b86fb

Initial commit

Browse files
dqn-SpaceInvadersNoFrameskip-v4.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:1de2add24e402b6b4f9b4b893f011b69aa5448a4e1d7e8cd831359f50e3a1448
3
  size 27219125
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:714a549633c277b33004ef1e0cdfb9e9fab53ce9113d0d44325d75088a4b11b9
3
  size 27219125
dqn-SpaceInvadersNoFrameskip-v4/data CHANGED
@@ -4,9 +4,9 @@
4
  ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCUNublBvbGljeZSTlC4=",
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 0x143879e40>",
8
  "__abstractmethods__": "frozenset()",
9
- "_abc_impl": "<_abc._abc_data object at 0x1438737c0>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {},
@@ -81,13 +81,13 @@
81
  "__module__": "stable_baselines3.common.buffers",
82
  "__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'>}",
83
  "__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 ",
84
- "__init__": "<function ReplayBuffer.__init__ at 0x1435bee80>",
85
- "add": "<function ReplayBuffer.add at 0x1435befc0>",
86
- "sample": "<function ReplayBuffer.sample at 0x1435bf060>",
87
- "_get_samples": "<function ReplayBuffer._get_samples at 0x1435bf100>",
88
- "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x1435bf1a0>)>",
89
  "__abstractmethods__": "frozenset()",
90
- "_abc_impl": "<_abc._abc_data object at 0x14354dd00>"
91
  },
92
  "replay_buffer_kwargs": {},
93
  "train_freq": {
 
4
  ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCUNublBvbGljeZSTlC4=",
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 0x164ea1e40>",
8
  "__abstractmethods__": "frozenset()",
9
+ "_abc_impl": "<_abc._abc_data object at 0x164e9bc40>"
10
  },
11
  "verbose": 1,
12
  "policy_kwargs": {},
 
81
  "__module__": "stable_baselines3.common.buffers",
82
  "__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'>}",
83
  "__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 ",
84
+ "__init__": "<function ReplayBuffer.__init__ at 0x164aeae80>",
85
+ "add": "<function ReplayBuffer.add at 0x164aeafc0>",
86
+ "sample": "<function ReplayBuffer.sample at 0x164aeb060>",
87
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x164aeb100>",
88
+ "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x164aeb1a0>)>",
89
  "__abstractmethods__": "frozenset()",
90
+ "_abc_impl": "<_abc._abc_data object at 0x164a75d80>"
91
  },
92
  "replay_buffer_kwargs": {},
93
  "train_freq": {
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:7d483e88ef28e7d67fef568e3fd53cd22f3df3ed2875e6cf7feb0886b2ec5741
3
+ size 286450
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 519.0, "std_reward": 139.97856978837868, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2024-04-25T20:50:29.004543"}
 
1
+ {"mean_reward": 519.0, "std_reward": 139.97856978837868, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2024-04-25T21:22:52.738904"}