Renamed pull_config to get_config. Updated get_config script, working as I'd like

agents/configtest.json

@@ -1,105 +0,0 @@
-{
-  "policy_class": {
-    ":type:": "<class 'abc.ABCMeta'>",
-    "__module__": "stable_baselines3.dqn.policies",
-    "__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    ",
-    "__init__": "<function CnnPolicy.__init__ at 0x7a562f785c60>",
-    "__abstractmethods__": "frozenset()",
-    "_abc_impl": "<_abc._abc_data object at 0x7a562f798540>"
-  },
-  "verbose": 1,
-  "policy_kwargs": {},
-  "num_timesteps": 6500000,
-  "_total_timesteps": 6500000,
-  "_num_timesteps_at_start": 5500000,
-  "seed": null,
-  "action_noise": null,
-  "start_time": 1715714815567229137,
-  "learning_rate": 5e-05,
-  "tensorboard_log": "./",
-  "_last_obs": {
-    ":type:": "<class 'numpy.ndarray'>"
-  },
-  "_last_episode_starts": {
-    ":type:": "<class 'numpy.ndarray'>"
-  },
-  "_last_original_obs": {
-    ":type:": "<class 'numpy.ndarray'>"
-  },
-  "_episode_num": 6118,
-  "use_sde": false,
-  "sde_sample_freq": -1,
-  "_current_progress_remaining": 0.0,
-  "_stats_window_size": 100,
-  "ep_info_buffer": {
-    ":type:": "<class 'collections.deque'>"
-  },
-  "ep_success_buffer": {
-    ":type:": "<class 'collections.deque'>"
-  },
-  "_n_updates": 1612500,
-  "observation_space": {
-    ":type:": "<class 'gymnasium.spaces.box.Box'>",
-    "dtype": "uint8",
-    "bounded_below": "[[[ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  ...\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]]\n\n [[ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  ...\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]]\n\n [[ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  ...\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]]]",
-    "bounded_above": "[[[ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  ...\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]]\n\n [[ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  ...\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]]\n\n [[ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  ...\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]\n  [ True  True  True ...  True  True  True]]]",
-    "_shape": [
-      3,
-      250,
-      160
-    ],
-    "low": "[[[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]]\n\n [[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]]\n\n [[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]]]",
-    "high": "[[[255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  ...\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]]\n\n [[255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  ...\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]]\n\n [[255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  ...\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]\n  [255 255 255 ... 255 255 255]]]",
-    "low_repr": "0",
-    "high_repr": "255",
-    "_np_random": "Generator(PCG64)"
-  },
-  "action_space": {
-    ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
-    "n": "5",
-    "start": "0",
-    "_shape": [],
-    "dtype": "int64",
-    "_np_random": "Generator(PCG64)"
-  },
-  "n_envs": 1,
-  "buffer_size": 70000,
-  "batch_size": 64,
-  "learning_starts": 50000,
-  "tau": 1.0,
-  "gamma": 0.999,
-  "gradient_steps": 1,
-  "optimize_memory_usage": false,
-  "replay_buffer_class": {
-    ":type:": "<class 'abc.ABCMeta'>",
-    "__module__": "stable_baselines3.common.buffers",
-    "__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 0x7a562f95dc60>",
-    "add": "<function ReplayBuffer.add at 0x7a562f95dcf0>",
-    "sample": "<function ReplayBuffer.sample at 0x7a562f95dd80>",
-    "_get_samples": "<function ReplayBuffer._get_samples at 0x7a562f95de10>",
-    "_maybe_cast_dtype": "<staticmethod(<function ReplayBuffer._maybe_cast_dtype at 0x7a562f95dea0>)>",
-    "__abstractmethods__": "frozenset()",
-    "_abc_impl": "<_abc._abc_data object at 0x7a562f962200>"
-  },
-  "replay_buffer_kwargs": {},
-  "train_freq": {
-    ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>"
-  },
-  "use_sde_at_warmup": false,
-  "exploration_initial_eps": 1.0,
-  "exploration_final_eps": 0.05,
-  "exploration_fraction": 0.3,
-  "target_update_interval": 5000,
-  "_n_calls": 6500000,
-  "max_grad_norm": 10,
-  "exploration_rate": 0.05,
-  "lr_schedule": {
-    ":type:": "<class 'function'>"
-  },
-  "batch_norm_stats": [],
-  "batch_norm_stats_target": [],
-  "exploration_schedule": {
-    ":type:": "<class 'function'>"
-  }
-}

agents/pull_config.py → get_config.py

@@ -1,11 +1,17 @@
 import zipfile
 import json
-# Need to add option flags to specify the file path to the agent
+import argparse
+parser = argparse.ArgumentParser()
+parser.add_argument("-f", "--filepath", help="Specify a filepath to an agent's zip file, .zip extension required.", type=str, required=True)
+parser.add_argument("-s", "--savefile", help="Specify a name and location for the saved configuration file. Will be saved in .json format.", default="config")
+args = parser.parse_args()
 
-archive = zipfile.ZipFile("dqn_v2-5/ALE-Pacman-v5.zip", "r")
+filepath = args.filepath
+savefile = args.savefile
+
+archive = zipfile.ZipFile(filepath, "r")
 file = archive.open("data")
-byte_file = file.read()
-json_file = json.loads(byte_file.decode("utf-8"))
+json_file = json.loads(file.read().decode("utf-8"))
 
 # Only want to remove serialized objects from dictionary
 val_to_remove = ":serialized:"
@@ -16,8 +22,8 @@ for key in json_file.keys():
         if val_to_remove in json_file[key].keys():
             json_file[key].pop(val_to_remove)
 
-outfile = open("configtest.json", "w")
-json.dump(json_file, outfile, indent=2,)
+outfile = open(f"{savefile}.json", "w")
+outfile.write(json.dumps(json_file, indent=2))
 
 file.close()
 outfile.close()