Fix Atari environment issues (#289)

[jacobarrio]

Fixes the three issues reported in #289:

Import path was broken - removed the second arg from try_import since AtariEnv gets imported directly later anyway (line 31).

ale_py pinned to 0.9.0 but that doesn't have Python 3.13 wheels. Bumped to >=0.10.1.

num_workers hardcoded to 16 in atari.ini causes errors on machines with fewer cores. Changed to 0 for auto-detection.

Tested the import and verified no worker errors locally.

Closes #289

[Zentrik]

╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /puffertank/venv/bin/puffer:10 in <module>                                                       │
│                                                                                                  │
│    7 │   │   sys.argv[0] = sys.argv[0][:-11]                                                     │
│    8 │   elif sys.argv[0].endswith(".exe"):                                                      │
│    9 │   │   sys.argv[0] = sys.argv[0][:-4]                                                      │
│ ❱ 10 │   sys.exit(main())                                                                        │
│   11                                                                                             │
│                                                                                                  │
│ /puffertank/pufferlib/pufferlib/pufferl.py:1332 in main                                          │
│                                                                                                  │
│   1329 │   mode = sys.argv.pop(1)                                                                │
│   1330 │   env_name = sys.argv.pop(1)                                                            │
│   1331 │   if mode == 'train':                                                                   │
│ ❱ 1332 │   │   train(env_name=env_name)                                                          │
│   1333 │   elif mode == 'eval':                                                                  │
│   1334 │   │   eval(env_name=env_name)                                                           │
│   1335 │   elif mode == 'sweep':                                                                 │
│                                                                                                  │
│ /puffertank/pufferlib/pufferlib/pufferl.py:924 in train                                          │
│                                                                                                  │
│    921 │   │   torch.cuda.set_device(local_rank)                                                 │
│    922 │   │   os.environ["CUDA_VISIBLE_DEVICES"] = str(local_rank)                              │
│    923 │                                                                                         │
│ ❱  924 │   vecenv = vecenv or load_env(env_name, args)                                           │
│    925 │   policy = policy or load_policy(args, vecenv, env_name)                                │
│    926 │                                                                                         │
│    927 │   if 'LOCAL_RANK' in os.environ:                                                        │
│                                                                                                  │
│ /puffertank/pufferlib/pufferlib/pufferl.py:1177 in load_env                                      │
│                                                                                                  │
│   1174 │   module_name = 'pufferlib.ocean' if package == 'ocean' else f'pufferlib.environments.  │
│   1175 │   env_module = importlib.import_module(module_name)                                     │
│   1176 │   make_env = env_module.env_creator(env_name)                                           │
│ ❱ 1177 │   return pufferlib.vector.make(make_env, env_kwargs=args['env'], **args['vec'])         │
│   1178                                                                                           │
│   1179 def load_policy(args, vecenv, env_name=''):                                               │
│   1180 │   package = args['package']                                                             │
│                                                                                                  │
│ /puffertank/pufferlib/pufferlib/vector.py:646 in make                                            │
│                                                                                                  │
│   643 │   │   │   kwargs['num_workers'] = num_envs                                               │
│   644 │   │                                                                                      │
│   645 │   │   # TODO: None?                                                                      │
│ ❱ 646 │   │   envs_per_worker = num_envs / kwargs['num_workers']                                 │
│   647 │   │   if envs_per_worker != int(envs_per_worker):                                        │
│   648 │   │   │   raise pufferlib.APIUsageError('num_envs must be divisible by num_workers')     │
│   649                                                                                            │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ZeroDivisionError: division by zero

[Zentrik]

I changed it to auto but then it defaults to 128 (num_envs) I think which is even worse

[jacobarrio]

Fixed. Changed it to use auto detection based on CPU cores instead of hardcoding.

Now auto sets num_workers to min(cpu_cores, num_envs) which is safe and performant. Also updated vector.py to handle 'auto' properly instead of defaulting to num_envs.