fix: Replace libcudart with pytorch api

Author: rapsealk

bitsandbytes/cuda_setup/main.py

@@ -326,31 +326,10 @@ def get_cuda_lib_handle():
 
 
 def get_compute_capabilities(cuda):
-    """
-    1. find libcuda.so library (GPU driver) (/usr/lib)
-       init_device -> init variables -> call function by reference
-    2. call extern C function to determine CC
-       (https://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__DEVICE__DEPRECATED.html)
-    3. Check for CUDA errors
-       https://stackoverflow.com/questions/14038589/what-is-the-canonical-way-to-check-for-errors-using-the-cuda-runtime-api
-    # bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549
-    """
-
-    nGpus = ct.c_int()
-    cc_major = ct.c_int()
-    cc_minor = ct.c_int()
-
-    device = ct.c_int()
-
-    check_cuda_result(cuda, cuda.cuDeviceGetCount(ct.byref(nGpus)))
     ccs = []
-    for i in range(nGpus.value):
-        check_cuda_result(cuda, cuda.cuDeviceGet(ct.byref(device), i))
-        ref_major = ct.byref(cc_major)
-        ref_minor = ct.byref(cc_minor)
-        # 2. call extern C function to determine CC
-        check_cuda_result(cuda, cuda.cuDeviceComputeCapability(ref_major, ref_minor, device))
-        ccs.append(f"{cc_major.value}.{cc_minor.value}")
+    # for i in range(torch.cuda.device_count()):
+    #     device = torch.cuda.device(i)
+    ccs.append(torch.version.cuda)
 
     return ccs