          self.output.info(f"Faceswap config written to: {config_file}")
  
      def set_ld_library_path(self):
          """ Update the LD_LIBRARY_PATH environment variable when activating a conda environment
          and revert it when deactivating.
  
          Notes
          -----
          From Tensorflow 2.7, installing Cuda Toolkit from conda-forge and tensorflow from pip
          causes tensorflow to not be able to locate shared libs and hence not use the GPU.
 
</s> remove     def set_ld_library_path(self):
 </s> add     def set_ld_library_path(self) -> None: </s> remove         if not self.is_conda or not self.enable_cuda:
            return

        if self.os_version[0] == "Windows":
 </s> add         if not self.is_conda or not self.enable_cuda or self.os_version[0].lower() != "linux": </s> remove     def update_tf_dep(self):
 </s> add     def update_tf_dep(self) -> None: </s> remove                                       if not pkg.startswith("tensorflow-gpu")]
 </s> add                                       if not pkg[0].startswith("tensorflow-gpu")]
        and revert it when deactivating. Linux/conda only
          self.output.info(f"Faceswap config written to: {config_file}")
  
      def set_ld_library_path(self):
          """ Update the LD_LIBRARY_PATH environment variable when activating a conda environment
        and revert it when deactivating. Linux/conda only
  
          Notes
          -----
          From Tensorflow 2.7, installing Cuda Toolkit from conda-forge and tensorflow from pip
          causes tensorflow to not be able to locate shared libs and hence not use the GPU.
keep keep keep keep replace keep keep keep keep keep
 Add Apple M1 to setup.py

add libblas to requirements 
setup.py