text: Title: [fabric.example.rl] Not support torch.float64 for MPS device
  Body: ### Bug description
  
  I found an error when run the example `pytorch-lightning/examples/fabric/reinforcement_learning` on M2 Mac (device type=mps)
  
  ### Reproduce Error
  
  
  ```
  reinforcement_learning git:(master) ✗ fabric run train_fabric.py
  W0617 12:53:22.541000 8107367488 torch/distributed/elastic/multiprocessing/redirects.py:27] NOTE: Redirects are currently not supported in Windows or MacOs.
  [rank: 0] Seed set to 42
  Missing logger folder: logs/fabric_logs/2024-06-17_12-53-24/CartPole-v1_default_42_1718596404
  set default torch dtype as torch.float32
  Traceback (most recent call last):
    File "/Users/user/workspace/pytorch-lightning/examples/fabric/reinforcement_learning/train_fabric.py", line 215, in <module>
      main(args)
    File "/Users/user/workspace/pytorch-lightning/examples/fabric/reinforcement_learning/train_fabric.py", line 154, in main
      rewards[step] = torch.tensor(reward, device=device).view(-1)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  TypeError: Cannot convert a MPS Tensor to float64 dtype as the MPS framework doesn't support float64. Please use float32 instead.
  ```
  
  This bug is fixed by checking device.type and type casting to torch.float32 `reward`.
  ```bash
  @@ -146,7 +146,7 @@ def main(args: argparse.Namespace):
               # Single environment step
               next_obs, reward, done, truncated, info = envs.step(action.cpu().numpy())
               done = torch.logical_or(torch.tensor(done), torch.tensor(truncated))
  -            rewards[step] = torch.tensor(reward, device=device).view(-1)
  +            rewards[step] = torch.tensor(reward, device=device, dtype=torch.float32 if device.type == 'mps' else None).view(-1)
  ```
  
  ### What version are you seeing the problem on?
  
  master
  
  ### Environment
  
  <details><summary>Current environment</summary>
  
    ```
    #- Lightning Component (e.g. Trainer, LightningModule, LightningApp, LightningWork, LightningFlow):
    #- PyTorch Lightning Version (e.g., 1.5.0):  2.3.0
    #- Lightning App Version (e.g., 0.5.2): 2.3.0
    #- PyTorch Version (e.g., 2.0): 2.3.1
    #- Python version (e.g., 3.9): 3.12.3
    #- OS (e.g., Linux): Mac
    #- CUDA/cuDNN version: MPS
    #- GPU models and configuration: M2
    #- How you installed Lightning(`conda`, `pip`, source):
    #- Running environment of LightningApp (e.g. local, cloud):
    ```
  
  </details>
  