prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  [tensor] fix some unittests
  
  [tensor] fix some unittests
  
  [tensor] fix some unittests
  
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `colossalai/booster/mixed_precision/mixed_precision_base.py`
  Content:
  ```
  1 from abc import ABC, abstractmethod
  2 from typing import Callable, Optional, Tuple
  3 
  4 import torch.nn as nn
  5 from torch.optim import Optimizer
  6 
  7 from colossalai.interface import OptimizerWrapper
  8 
  9 
  10 class MixedPrecision(ABC):
  11     """
  12     An abstract class for mixed precision training.
  13     """
  14 
  15     @abstractmethod
  16     def configure(self,
  17                   model: nn.Module,
  18                   optimizer: Optional[Optimizer] = None,
  19                   criterion: Optional[Callable] = None,
  20                   ) -> Tuple[nn.Module, OptimizerWrapper, Callable]:
  21         # TODO: implement this method
  22         pass
  23
  ```
  --- 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/colossalai/booster/mixed_precision/mixed_precision_base.py b/colossalai/booster/mixed_precision/mixed_precision_base.py
  --- a/colossalai/booster/mixed_precision/mixed_precision_base.py
  +++ b/colossalai/booster/mixed_precision/mixed_precision_base.py
  @@ -13,10 +13,11 @@
       """
   
       @abstractmethod
  -    def configure(self,
  -                  model: nn.Module,
  -                  optimizer: Optional[Optimizer] = None,
  -                  criterion: Optional[Callable] = None,
  -                  ) -> Tuple[nn.Module, OptimizerWrapper, Callable]:
  +    def configure(
  +        self,
  +        model: nn.Module,
  +        optimizer: Optional[Optimizer] = None,
  +        criterion: Optional[Callable] = None,
  +    ) -> Tuple[nn.Module, OptimizerWrapper, Callable]:
           # TODO: implement this method
           pass
  
verification_info: {"golden_diff": "diff --git a/colossalai/booster/mixed_precision/mixed_precision_base.py b/colossalai/booster/mixed_precision/mixed_precision_base.py\n--- a/colossalai/booster/mixed_precision/mixed_precision_base.py\n+++ b/colossalai/booster/mixed_precision/mixed_precision_base.py\n@@ -13,10 +13,11 @@\n     \"\"\"\n \n     @abstractmethod\n-    def configure(self,\n-                  model: nn.Module,\n-                  optimizer: Optional[Optimizer] = None,\n-                  criterion: Optional[Callable] = None,\n-                  ) -> Tuple[nn.Module, OptimizerWrapper, Callable]:\n+    def configure(\n+        self,\n+        model: nn.Module,\n+        optimizer: Optional[Optimizer] = None,\n+        criterion: Optional[Callable] = None,\n+    ) -> Tuple[nn.Module, OptimizerWrapper, Callable]:\n         # TODO: implement this method\n         pass\n", "issue": "[tensor] fix some unittests\n\n[tensor] fix some unittests\n\n[tensor] fix some unittests\n\n", "before_files": [{"content": "from abc import ABC, abstractmethod\nfrom typing import Callable, Optional, Tuple\n\nimport torch.nn as nn\nfrom torch.optim import Optimizer\n\nfrom colossalai.interface import OptimizerWrapper\n\n\nclass MixedPrecision(ABC):\n    \"\"\"\n    An abstract class for mixed precision training.\n    \"\"\"\n\n    @abstractmethod\n    def configure(self,\n                  model: nn.Module,\n                  optimizer: Optional[Optimizer] = None,\n                  criterion: Optional[Callable] = None,\n                  ) -> Tuple[nn.Module, OptimizerWrapper, Callable]:\n        # TODO: implement this method\n        pass\n", "path": "colossalai/booster/mixed_precision/mixed_precision_base.py"}], "after_files": [{"content": "from abc import ABC, abstractmethod\nfrom typing import Callable, Optional, Tuple\n\nimport torch.nn as nn\nfrom torch.optim import Optimizer\n\nfrom colossalai.interface import OptimizerWrapper\n\n\nclass MixedPrecision(ABC):\n    \"\"\"\n    An abstract class for mixed precision training.\n    \"\"\"\n\n    @abstractmethod\n    def configure(\n        self,\n        model: nn.Module,\n        optimizer: Optional[Optimizer] = None,\n        criterion: Optional[Callable] = None,\n    ) -> Tuple[nn.Module, OptimizerWrapper, Callable]:\n        # TODO: implement this method\n        pass\n", "path": "colossalai/booster/mixed_precision/mixed_precision_base.py"}]}