prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  [BUG] DeepSpeed 0.7.0 breaks the Accelerate CI due to pip installation
  **Describe the bug**
  For Accelerate we have deepspeed as an extra that gets installed during tests. As of 0.7.0 DeepSpeed is unable to be installed if pytorch is not already installed on the system, so doing `pip install -e .[testing]` (which installs torch and deepspeed at once) fails due to a compilation error on DeepSpeed's side. 
  
  **To Reproduce**
  Steps to reproduce the behavior:
  1. In a new environment:
  ```bash
  git clone https://github.com/huggingface/accelerate
  cd accelerate
  pip install -e .[testing]
  ```
  It won't get past the pip install
  
  **Expected behavior**
  Should install just fine
  
  **System info (please complete the following information):**
   - OS: Ubuntu 20.04
   - GPU count and types: None
   - Interconnects (if applicable) [e.g., two machines connected with 100 Gbps IB]
   - Python version: 3.8.13
   - Any other relevant info about your setup
  
  **Launcher context**
  Are you launching your experiment with the `deepspeed` launcher, MPI, or something else?
  No
  
  **Docker context**
  Are you using a specific docker image that you can share?
  No
  
  **Additional context**
  Add any other context about the problem here.
  
  Full installation trace:
  ```bash
  (deepspeed) zach@workstation:~/accelerate/accelerate$ pip install -e .[testing]
  Obtaining file:///home/zach/accelerate/accelerate
    Installing build dependencies ... done
    Checking if build backend supports build_editable ... done
    Getting requirements to build wheel ... done
    Preparing metadata (pyproject.toml) ... done
  Requirement already satisfied: numpy>=1.17 in /home/zach/.local/lib/python3.8/site-packages (from accelerate==0.12.0.dev0) (1.23.0)
  Requirement already satisfied: packaging>=20.0 in /home/zach/.local/lib/python3.8/site-packages (from accelerate==0.12.0.dev0) (21.3)
  Requirement already satisfied: psutil in /home/zach/.local/lib/python3.8/site-packages (from accelerate==0.12.0.dev0) (5.9.1)
  Collecting pyyaml
    Using cached PyYAML-6.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (701 kB)
  Collecting torch>=1.4.0
    Downloading torch-1.12.0-cp38-cp38-manylinux1_x86_64.whl (776.3 MB)
       ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 776.3/776.3 MB 4.6 MB/s eta 0:00:00
  Collecting deepspeed
    Downloading deepspeed-0.7.0.tar.gz (629 kB)
       ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 630.0/630.0 kB 9.2 MB/s eta 0:00:00
    Preparing metadata (setup.py) ... error
    error: subprocess-exited-with-error
    
    × python setup.py egg_info did not run successfully.
    │ exit code: 1
    ╰─> [12 lines of output]
        Traceback (most recent call last):
          File "<string>", line 2, in <module>
          File "<pip-setuptools-caller>", line 34, in <module>
          File "/tmp/pip-install-022a34y9/deepspeed_68937ff3b2bb4dbdbd7449fa5f5103b6/setup.py", line 33, in <module>
            from op_builder import ALL_OPS, get_default_compute_capabilities, OpBuilder
          File "/tmp/pip-install-022a34y9/deepspeed_68937ff3b2bb4dbdbd7449fa5f5103b6/op_builder/__init__.py", line 13, in <module>
            from .transformer_inference import InferenceBuilder
          File "/tmp/pip-install-022a34y9/deepspeed_68937ff3b2bb4dbdbd7449fa5f5103b6/op_builder/transformer_inference.py", line 1, in <module>
            import torch
        ModuleNotFoundError: No module named 'torch'
        [WARNING] Unable to import torch, pre-compiling ops will be disabled. Please visit https://pytorch.org/ to see how to properly install torch on your system.
         [WARNING]  unable to import torch, please install it if you want to pre-compile any deepspeed ops.
        [end of output]
    
    note: This error originates from a subprocess, and is likely not a problem with pip.
  error: metadata-generation-failed
  
  × Encountered error while generating package metadata.
  ╰─> See above for output.
  
  note: This is an issue with the package mentioned above, not pip.
  hint: See above for details.
  ```
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `op_builder/transformer_inference.py`
  Content:
  ```
  1 import torch
  2 from .builder import CUDAOpBuilder, installed_cuda_version
  3 
  4 
  5 class InferenceBuilder(CUDAOpBuilder):
  6     BUILD_VAR = "DS_BUILD_TRANSFORMER_INFERENCE"
  7     NAME = "transformer_inference"
  8 
  9     def __init__(self, name=None):
  10         name = self.NAME if name is None else name
  11         super().__init__(name=name)
  12 
  13     def absolute_name(self):
  14         return f'deepspeed.ops.transformer.inference.{self.NAME}_op'
  15 
  16     def is_compatible(self, verbose=True):
  17         cuda_okay = True
  18         if not self.is_rocm_pytorch() and torch.cuda.is_available():
  19             sys_cuda_major, _ = installed_cuda_version()
  20             torch_cuda_major = int(torch.version.cuda.split('.')[0])
  21             cuda_capability = torch.cuda.get_device_properties(0).major
  22             if cuda_capability >= 8:
  23                 if torch_cuda_major < 11 or sys_cuda_major < 11:
  24                     self.warning(
  25                         "On Ampere and higher architectures please use CUDA 11+")
  26                     cuda_okay = False
  27         return super().is_compatible(verbose) and cuda_okay
  28 
  29     def sources(self):
  30         return [
  31             'csrc/transformer/inference/csrc/pt_binding.cpp',
  32             'csrc/transformer/inference/csrc/gelu.cu',
  33             'csrc/transformer/inference/csrc/normalize.cu',
  34             'csrc/transformer/inference/csrc/softmax.cu',
  35             'csrc/transformer/inference/csrc/dequantize.cu',
  36             'csrc/transformer/inference/csrc/apply_rotary_pos_emb.cu',
  37             'csrc/transformer/inference/csrc/transform.cu',
  38         ]
  39 
  40     def extra_ldflags(self):
  41         if not self.is_rocm_pytorch():
  42             return ['-lcurand']
  43         else:
  44             return []
  45 
  46     def include_paths(self):
  47         return ['csrc/transformer/inference/includes']
  48
  ```
  --- 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/op_builder/transformer_inference.py b/op_builder/transformer_inference.py
  --- a/op_builder/transformer_inference.py
  +++ b/op_builder/transformer_inference.py
  @@ -1,4 +1,3 @@
  -import torch
   from .builder import CUDAOpBuilder, installed_cuda_version
   
   
  @@ -14,6 +13,13 @@
           return f'deepspeed.ops.transformer.inference.{self.NAME}_op'
   
       def is_compatible(self, verbose=True):
  +        try:
  +            import torch
  +        except ImportError:
  +            self.warning(
  +                "Please install torch if trying to pre-compile inference kernels")
  +            return False
  +
           cuda_okay = True
           if not self.is_rocm_pytorch() and torch.cuda.is_available():
               sys_cuda_major, _ = installed_cuda_version()
  
verification_info: {"golden_diff": "diff --git a/op_builder/transformer_inference.py b/op_builder/transformer_inference.py\n--- a/op_builder/transformer_inference.py\n+++ b/op_builder/transformer_inference.py\n@@ -1,4 +1,3 @@\n-import torch\n from .builder import CUDAOpBuilder, installed_cuda_version\n \n \n@@ -14,6 +13,13 @@\n         return f'deepspeed.ops.transformer.inference.{self.NAME}_op'\n \n     def is_compatible(self, verbose=True):\n+        try:\n+            import torch\n+        except ImportError:\n+            self.warning(\n+                \"Please install torch if trying to pre-compile inference kernels\")\n+            return False\n+\n         cuda_okay = True\n         if not self.is_rocm_pytorch() and torch.cuda.is_available():\n             sys_cuda_major, _ = installed_cuda_version()\n", "issue": "[BUG] DeepSpeed 0.7.0 breaks the Accelerate CI due to pip installation\n**Describe the bug**\r\nFor Accelerate we have deepspeed as an extra that gets installed during tests. As of 0.7.0 DeepSpeed is unable to be installed if pytorch is not already installed on the system, so doing `pip install -e .[testing]` (which installs torch and deepspeed at once) fails due to a compilation error on DeepSpeed's side. \r\n\r\n**To Reproduce**\r\nSteps to reproduce the behavior:\r\n1. In a new environment:\r\n```bash\r\ngit clone https://github.com/huggingface/accelerate\r\ncd accelerate\r\npip install -e .[testing]\r\n```\r\nIt won't get past the pip install\r\n\r\n**Expected behavior**\r\nShould install just fine\r\n\r\n**System info (please complete the following information):**\r\n - OS: Ubuntu 20.04\r\n - GPU count and types: None\r\n - Interconnects (if applicable) [e.g., two machines connected with 100 Gbps IB]\r\n - Python version: 3.8.13\r\n - Any other relevant info about your setup\r\n\r\n**Launcher context**\r\nAre you launching your experiment with the `deepspeed` launcher, MPI, or something else?\r\nNo\r\n\r\n**Docker context**\r\nAre you using a specific docker image that you can share?\r\nNo\r\n\r\n**Additional context**\r\nAdd any other context about the problem here.\r\n\r\nFull installation trace:\r\n```bash\r\n(deepspeed) zach@workstation:~/accelerate/accelerate$ pip install -e .[testing]\r\nObtaining file:///home/zach/accelerate/accelerate\r\n  Installing build dependencies ... done\r\n  Checking if build backend supports build_editable ... done\r\n  Getting requirements to build wheel ... done\r\n  Preparing metadata (pyproject.toml) ... done\r\nRequirement already satisfied: numpy>=1.17 in /home/zach/.local/lib/python3.8/site-packages (from accelerate==0.12.0.dev0) (1.23.0)\r\nRequirement already satisfied: packaging>=20.0 in /home/zach/.local/lib/python3.8/site-packages (from accelerate==0.12.0.dev0) (21.3)\r\nRequirement already satisfied: psutil in /home/zach/.local/lib/python3.8/site-packages (from accelerate==0.12.0.dev0) (5.9.1)\r\nCollecting pyyaml\r\n  Using cached PyYAML-6.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (701 kB)\r\nCollecting torch>=1.4.0\r\n  Downloading torch-1.12.0-cp38-cp38-manylinux1_x86_64.whl (776.3 MB)\r\n     \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 776.3/776.3 MB 4.6 MB/s eta 0:00:00\r\nCollecting deepspeed\r\n  Downloading deepspeed-0.7.0.tar.gz (629 kB)\r\n     \u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501 630.0/630.0 kB 9.2 MB/s eta 0:00:00\r\n  Preparing metadata (setup.py) ... error\r\n  error: subprocess-exited-with-error\r\n  \r\n  \u00d7 python setup.py egg_info did not run successfully.\r\n  \u2502 exit code: 1\r\n  \u2570\u2500> [12 lines of output]\r\n      Traceback (most recent call last):\r\n        File \"<string>\", line 2, in <module>\r\n        File \"<pip-setuptools-caller>\", line 34, in <module>\r\n        File \"/tmp/pip-install-022a34y9/deepspeed_68937ff3b2bb4dbdbd7449fa5f5103b6/setup.py\", line 33, in <module>\r\n          from op_builder import ALL_OPS, get_default_compute_capabilities, OpBuilder\r\n        File \"/tmp/pip-install-022a34y9/deepspeed_68937ff3b2bb4dbdbd7449fa5f5103b6/op_builder/__init__.py\", line 13, in <module>\r\n          from .transformer_inference import InferenceBuilder\r\n        File \"/tmp/pip-install-022a34y9/deepspeed_68937ff3b2bb4dbdbd7449fa5f5103b6/op_builder/transformer_inference.py\", line 1, in <module>\r\n          import torch\r\n      ModuleNotFoundError: No module named 'torch'\r\n      [WARNING] Unable to import torch, pre-compiling ops will be disabled. Please visit https://pytorch.org/ to see how to properly install torch on your system.\r\n       [WARNING]  unable to import torch, please install it if you want to pre-compile any deepspeed ops.\r\n      [end of output]\r\n  \r\n  note: This error originates from a subprocess, and is likely not a problem with pip.\r\nerror: metadata-generation-failed\r\n\r\n\u00d7 Encountered error while generating package metadata.\r\n\u2570\u2500> See above for output.\r\n\r\nnote: This is an issue with the package mentioned above, not pip.\r\nhint: See above for details.\r\n```\n", "before_files": [{"content": "import torch\nfrom .builder import CUDAOpBuilder, installed_cuda_version\n\n\nclass InferenceBuilder(CUDAOpBuilder):\n    BUILD_VAR = \"DS_BUILD_TRANSFORMER_INFERENCE\"\n    NAME = \"transformer_inference\"\n\n    def __init__(self, name=None):\n        name = self.NAME if name is None else name\n        super().__init__(name=name)\n\n    def absolute_name(self):\n        return f'deepspeed.ops.transformer.inference.{self.NAME}_op'\n\n    def is_compatible(self, verbose=True):\n        cuda_okay = True\n        if not self.is_rocm_pytorch() and torch.cuda.is_available():\n            sys_cuda_major, _ = installed_cuda_version()\n            torch_cuda_major = int(torch.version.cuda.split('.')[0])\n            cuda_capability = torch.cuda.get_device_properties(0).major\n            if cuda_capability >= 8:\n                if torch_cuda_major < 11 or sys_cuda_major < 11:\n                    self.warning(\n                        \"On Ampere and higher architectures please use CUDA 11+\")\n                    cuda_okay = False\n        return super().is_compatible(verbose) and cuda_okay\n\n    def sources(self):\n        return [\n            'csrc/transformer/inference/csrc/pt_binding.cpp',\n            'csrc/transformer/inference/csrc/gelu.cu',\n            'csrc/transformer/inference/csrc/normalize.cu',\n            'csrc/transformer/inference/csrc/softmax.cu',\n            'csrc/transformer/inference/csrc/dequantize.cu',\n            'csrc/transformer/inference/csrc/apply_rotary_pos_emb.cu',\n            'csrc/transformer/inference/csrc/transform.cu',\n        ]\n\n    def extra_ldflags(self):\n        if not self.is_rocm_pytorch():\n            return ['-lcurand']\n        else:\n            return []\n\n    def include_paths(self):\n        return ['csrc/transformer/inference/includes']\n", "path": "op_builder/transformer_inference.py"}], "after_files": [{"content": "from .builder import CUDAOpBuilder, installed_cuda_version\n\n\nclass InferenceBuilder(CUDAOpBuilder):\n    BUILD_VAR = \"DS_BUILD_TRANSFORMER_INFERENCE\"\n    NAME = \"transformer_inference\"\n\n    def __init__(self, name=None):\n        name = self.NAME if name is None else name\n        super().__init__(name=name)\n\n    def absolute_name(self):\n        return f'deepspeed.ops.transformer.inference.{self.NAME}_op'\n\n    def is_compatible(self, verbose=True):\n        try:\n            import torch\n        except ImportError:\n            self.warning(\n                \"Please install torch if trying to pre-compile inference kernels\")\n            return False\n\n        cuda_okay = True\n        if not self.is_rocm_pytorch() and torch.cuda.is_available():\n            sys_cuda_major, _ = installed_cuda_version()\n            torch_cuda_major = int(torch.version.cuda.split('.')[0])\n            cuda_capability = torch.cuda.get_device_properties(0).major\n            if cuda_capability >= 8:\n                if torch_cuda_major < 11 or sys_cuda_major < 11:\n                    self.warning(\n                        \"On Ampere and higher architectures please use CUDA 11+\")\n                    cuda_okay = False\n        return super().is_compatible(verbose) and cuda_okay\n\n    def sources(self):\n        return [\n            'csrc/transformer/inference/csrc/pt_binding.cpp',\n            'csrc/transformer/inference/csrc/gelu.cu',\n            'csrc/transformer/inference/csrc/normalize.cu',\n            'csrc/transformer/inference/csrc/softmax.cu',\n            'csrc/transformer/inference/csrc/dequantize.cu',\n            'csrc/transformer/inference/csrc/apply_rotary_pos_emb.cu',\n            'csrc/transformer/inference/csrc/transform.cu',\n        ]\n\n    def extra_ldflags(self):\n        if not self.is_rocm_pytorch():\n            return ['-lcurand']\n        else:\n            return []\n\n    def include_paths(self):\n        return ['csrc/transformer/inference/includes']\n", "path": "op_builder/transformer_inference.py"}]}