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

[BUG]: Testing failed due to triton
### 🐛 Describe the bug

The build on PR workflow failed with the following errors:

<img width="1509" alt="Screenshot 2023-02-07 at 10 30 17" src="https://user-images.githubusercontent.com/31818963/217132926-fd6cffa1-2c4b-46aa-a6cc-1a3d10918411.png">


### Environment

_No response_

--- 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/amp/apex_amp/apex_amp.py`
Content:
```
1 #!/usr/bin/env python
2 # -*- encoding: utf-8 -*-
3 
4 import torch.nn as nn
5 try:
6     import apex.amp as apex_amp
7 except ImportError:
8     pass
9 
10 from torch import Tensor
11 
12 from colossalai.nn.optimizer import ColossalaiOptimizer
13 from colossalai.utils import clip_grad_norm_fp32
14 
15 
16 class ApexAMPOptimizer(ColossalaiOptimizer):
17     """ A wrapper class for APEX optimizer and it implements apex-specific backward and clip_grad_norm
18     methods
19     """
20 
21     def backward(self, loss: Tensor):
22         """Backward pass to get all gradients
23 
24         Args:
25             loss (torch.Tensor): Loss computed by a loss function
26         """
27         with apex_amp.scale_loss(loss, self.optim) as scaled_loss:
28             scaled_loss.backward()
29 
30     def clip_grad_norm(self, model: nn.Module, max_norm: float):
31         """Clip gradients by norm
32 
33         Args:
34             model (torch.nn.Module): Your model object
35             max_norm (float): The max norm value for gradient clipping
36         """
37         if max_norm > 0:
38             clip_grad_norm_fp32(apex_amp.master_params(self.optim), max_norm)
39
```
--- 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/amp/apex_amp/apex_amp.py b/colossalai/amp/apex_amp/apex_amp.py
--- a/colossalai/amp/apex_amp/apex_amp.py
+++ b/colossalai/amp/apex_amp/apex_amp.py
@@ -2,6 +2,7 @@
 # -*- encoding: utf-8 -*-
 
 import torch.nn as nn
+
 try:
     import apex.amp as apex_amp
 except ImportError:

{"golden_diff": "diff --git a/colossalai/amp/apex_amp/apex_amp.py b/colossalai/amp/apex_amp/apex_amp.py\n--- a/colossalai/amp/apex_amp/apex_amp.py\n+++ b/colossalai/amp/apex_amp/apex_amp.py\n@@ -2,6 +2,7 @@\n # -*- encoding: utf-8 -*-\n \n import torch.nn as nn\n+\n try:\n     import apex.amp as apex_amp\n except ImportError:\n", "issue": "[tensor] fix some unittests\n\n[tensor] fix some unittests\n\n[tensor] fix some unittests\n\n[BUG]: Testing failed due to triton\n### \ud83d\udc1b Describe the bug\n\nThe build on PR workflow failed with the following errors:\r\n\r\n<img width=\"1509\" alt=\"Screenshot 2023-02-07 at 10 30 17\" src=\"https://user-images.githubusercontent.com/31818963/217132926-fd6cffa1-2c4b-46aa-a6cc-1a3d10918411.png\">\r\n\n\n### Environment\n\n_No response_\n", "before_files": [{"content": "#!/usr/bin/env python\n# -*- encoding: utf-8 -*-\n\nimport torch.nn as nn\ntry:\n    import apex.amp as apex_amp\nexcept ImportError:\n    pass\n\nfrom torch import Tensor\n\nfrom colossalai.nn.optimizer import ColossalaiOptimizer\nfrom colossalai.utils import clip_grad_norm_fp32\n\n\nclass ApexAMPOptimizer(ColossalaiOptimizer):\n    \"\"\" A wrapper class for APEX optimizer and it implements apex-specific backward and clip_grad_norm\n    methods\n    \"\"\"\n\n    def backward(self, loss: Tensor):\n        \"\"\"Backward pass to get all gradients\n\n        Args:\n            loss (torch.Tensor): Loss computed by a loss function\n        \"\"\"\n        with apex_amp.scale_loss(loss, self.optim) as scaled_loss:\n            scaled_loss.backward()\n\n    def clip_grad_norm(self, model: nn.Module, max_norm: float):\n        \"\"\"Clip gradients by norm\n\n        Args:\n            model (torch.nn.Module): Your model object\n            max_norm (float): The max norm value for gradient clipping\n        \"\"\"\n        if max_norm > 0:\n            clip_grad_norm_fp32(apex_amp.master_params(self.optim), max_norm)\n", "path": "colossalai/amp/apex_amp/apex_amp.py"}], "after_files": [{"content": "#!/usr/bin/env python\n# -*- encoding: utf-8 -*-\n\nimport torch.nn as nn\n\ntry:\n    import apex.amp as apex_amp\nexcept ImportError:\n    pass\n\nfrom torch import Tensor\n\nfrom colossalai.nn.optimizer import ColossalaiOptimizer\nfrom colossalai.utils import clip_grad_norm_fp32\n\n\nclass ApexAMPOptimizer(ColossalaiOptimizer):\n    \"\"\" A wrapper class for APEX optimizer and it implements apex-specific backward and clip_grad_norm\n    methods\n    \"\"\"\n\n    def backward(self, loss: Tensor):\n        \"\"\"Backward pass to get all gradients\n\n        Args:\n            loss (torch.Tensor): Loss computed by a loss function\n        \"\"\"\n        with apex_amp.scale_loss(loss, self.optim) as scaled_loss:\n            scaled_loss.backward()\n\n    def clip_grad_norm(self, model: nn.Module, max_norm: float):\n        \"\"\"Clip gradients by norm\n\n        Args:\n            model (torch.nn.Module): Your model object\n            max_norm (float): The max norm value for gradient clipping\n        \"\"\"\n        if max_norm > 0:\n            clip_grad_norm_fp32(apex_amp.master_params(self.optim), max_norm)\n", "path": "colossalai/amp/apex_amp/apex_amp.py"}]}