Installation errors

[chrischoy]

      [stderr]
      <string>:106: UserWarning: flash_attn was requested, but nvcc was not found.  Are you sure your environment has nvcc available?  If you're installing within a container from
      https://hub.docker.com/r/pytorch/pytorch, only images whose names contain 'devel' will provide nvcc.
      Traceback (most recent call last):
        File "<string>", line 11, in <module>
        File "/workspace/.venv/lib/python3.12/site-packages/setuptools/build_meta.py", line 432, in build_wheel
          return _build(['bdist_wheel'])
                 ^^^^^^^^^^^^^^^^^^^^^^^
        File "/workspace/.venv/lib/python3.12/site-packages/setuptools/build_meta.py", line 423, in _build
          return self._build_with_temp_dir(
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
        File "/workspace/.venv/lib/python3.12/site-packages/setuptools/build_meta.py", line 404, in _build_with_temp_dir
          self.run_setup()
        File "/workspace/.venv/lib/python3.12/site-packages/setuptools/build_meta.py", line 512, in run_setup
          super().run_setup(setup_script=setup_script)
        File "/workspace/.venv/lib/python3.12/site-packages/setuptools/build_meta.py", line 317, in run_setup
          exec(code, locals())
        File "<string>", line 227, in <module>
        File "/workspace/.venv/lib/python3.12/site-packages/torch/utils/cpp_extension.py", line 1347, in CUDAExtension
          library_dirs += library_paths(device_type="cuda")
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        File "/workspace/.venv/lib/python3.12/site-packages/torch/utils/cpp_extension.py", line 1559, in library_paths
          if (not os.path.exists(_join_cuda_home(lib_dir)) and
                                 ^^^^^^^^^^^^^^^^^^^^^^^^
        File "/workspace/.venv/lib/python3.12/site-packages/torch/utils/cpp_extension.py", line 2986, in _join_cuda_home
          raise OSError('CUDA_HOME environment variable is not set. '
      OSError: CUDA_HOME environment variable is not set. Please set it to your CUDA install root.

      hint: This usually indicates a problem with the package or the build environment.

This is due to the library using "cpu" version of pytorch. Check your pytorch version with print(torch.__version__). If you had CUDA version installed, try installing with --no-deps:

pip install -e . --no-deps