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()

```

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

{"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"}]}