prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Model.load_from_checkpoint tries to open file path as URL and fail
  ## 🐛 Bug
   load_from_checkpoint tries to classify if the input is a file path or an URL and detects the hard drive letter as a scheme and then classify wrongly the input because of this.
  urllib.error.URLError: \<urlopen error unknown url type: d\>
  
  My input:
  D:\Prog\Projects\AceriNet\research_seed\checkpoints\acerinet\bnacerinet0_target=OVA_OK_penalized=None_loss_fn=ce_normalized=True_balanced=FalseFalse_seed=42_val_loss=0.374_val_auroc=0.9041_v0.ckpt
  
  ### To Reproduce
  
  Steps to reproduce the behavior:
  Use any path with a hard drive letter at the start (windows formatting) for pl.LightningModule().load_from_checkpoint(path)
  
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `pytorch_lightning/utilities/cloud_io.py`
  Content:
  ```
  1 import torch
  2 
  3 from urllib.parse import urlparse
  4 
  5 
  6 def load(path_or_url: str, map_location=None):
  7     parsed = urlparse(path_or_url)
  8     if parsed.scheme == '':
  9         # local file
  10         return torch.load(path_or_url, map_location=map_location)
  11     return torch.hub.load_state_dict_from_url(path_or_url, map_location=map_location)
  12
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/pytorch_lightning/utilities/cloud_io.py b/pytorch_lightning/utilities/cloud_io.py
  --- a/pytorch_lightning/utilities/cloud_io.py
  +++ b/pytorch_lightning/utilities/cloud_io.py
  @@ -1,11 +1,12 @@
   import torch
   
  +from pathlib import Path
   from urllib.parse import urlparse
   
   
   def load(path_or_url: str, map_location=None):
       parsed = urlparse(path_or_url)
  -    if parsed.scheme == '':
  -        # local file
  +    if parsed.scheme == '' or Path(path_or_url).is_file():
  +        # no scheme or local file
           return torch.load(path_or_url, map_location=map_location)
       return torch.hub.load_state_dict_from_url(path_or_url, map_location=map_location)
  
verification_info: {"golden_diff": "diff --git a/pytorch_lightning/utilities/cloud_io.py b/pytorch_lightning/utilities/cloud_io.py\n--- a/pytorch_lightning/utilities/cloud_io.py\n+++ b/pytorch_lightning/utilities/cloud_io.py\n@@ -1,11 +1,12 @@\n import torch\n \n+from pathlib import Path\n from urllib.parse import urlparse\n \n \n def load(path_or_url: str, map_location=None):\n     parsed = urlparse(path_or_url)\n-    if parsed.scheme == '':\n-        # local file\n+    if parsed.scheme == '' or Path(path_or_url).is_file():\n+        # no scheme or local file\n         return torch.load(path_or_url, map_location=map_location)\n     return torch.hub.load_state_dict_from_url(path_or_url, map_location=map_location)\n", "issue": "Model.load_from_checkpoint tries to open file path as URL and fail\n## \ud83d\udc1b Bug\r\n load_from_checkpoint tries to classify if the input is a file path or an URL and detects the hard drive letter as a scheme and then classify wrongly the input because of this.\r\nurllib.error.URLError: \\<urlopen error unknown url type: d\\>\r\n\r\nMy input:\r\nD:\\Prog\\Projects\\AceriNet\\research_seed\\checkpoints\\acerinet\\bnacerinet0_target=OVA_OK_penalized=None_loss_fn=ce_normalized=True_balanced=FalseFalse_seed=42_val_loss=0.374_val_auroc=0.9041_v0.ckpt\r\n\r\n### To Reproduce\r\n\r\nSteps to reproduce the behavior:\r\nUse any path with a hard drive letter at the start (windows formatting) for pl.LightningModule().load_from_checkpoint(path)\r\n\n", "before_files": [{"content": "import torch\n\nfrom urllib.parse import urlparse\n\n\ndef load(path_or_url: str, map_location=None):\n    parsed = urlparse(path_or_url)\n    if parsed.scheme == '':\n        # local file\n        return torch.load(path_or_url, map_location=map_location)\n    return torch.hub.load_state_dict_from_url(path_or_url, map_location=map_location)\n", "path": "pytorch_lightning/utilities/cloud_io.py"}], "after_files": [{"content": "import torch\n\nfrom pathlib import Path\nfrom urllib.parse import urlparse\n\n\ndef load(path_or_url: str, map_location=None):\n    parsed = urlparse(path_or_url)\n    if parsed.scheme == '' or Path(path_or_url).is_file():\n        # no scheme or local file\n        return torch.load(path_or_url, map_location=map_location)\n    return torch.hub.load_state_dict_from_url(path_or_url, map_location=map_location)\n", "path": "pytorch_lightning/utilities/cloud_io.py"}]}