change version to tuple format

bitsandbytes/autograd/_functions.py

@@ -224,7 +224,7 @@ def supports_igemmlt(device: torch.device) -> bool:
     if device == torch.device("cpu"):
         return True
     if torch.version.hip:
-        return False if get_compute_capabilities() < 601 else True
+        return False if get_compute_capabilities() < (6, 1) else True
     if get_compute_capabilities() < (7, 5):
         return False
     device_name = torch.cuda.get_device_name(device=device)

bitsandbytes/gpu_specs.py

@@ -10,14 +10,14 @@
 @dataclasses.dataclass(frozen=True)
 class GPUSpecs:
     gpu_backend: str
-    highest_compute_capability: Union[int, Tuple[int, int]]
+    highest_compute_capability: Tuple[int, int]
     backend_version_string: str
     backend_version_tuple: Tuple[int, int]
 
     @property
     def enable_blaslt(self) -> bool:
         if torch.version.hip:
-            return self.highest_compute_capability >= 601
+            return self.highest_compute_capability >= (6, 1)
         else:
             return self.highest_compute_capability >= (7, 5)
 
@@ -32,7 +32,7 @@ def get_gpu_backend() -> str:
 def get_compute_capabilities() -> Union[int, Tuple[int, int]]:
     if torch.version.hip:
         hip_major, hip_minor = get_backend_version_tuple()
-        return hip_major * 100 + hip_minor
+        return (hip_major, hip_minor)
     else:
         return sorted(
             torch.cuda.get_device_capability(torch.cuda.device(i)) for i in range(torch.cuda.device_count())

tests/test_autograd.py

@@ -199,7 +199,7 @@ def test_matmul(dim1, dim2, dim3, dim4, funcs, dtype, req_grad: Tuple[bool, bool
                 assert (idx == 0).sum().item() < n * 0.02
 
 
-@pytest.mark.skipif(0 < get_compute_capabilities() < 601, reason="this test is supported on ROCm from 6.1")
+@pytest.mark.skipif((0, 0) < get_compute_capabilities() < (6, 1), reason="this test is supported on ROCm from 6.1")
 @pytest.mark.parametrize("dim1", get_test_dims(16, 64, n=1), ids=id_formatter("dim1"))
 @pytest.mark.parametrize("dim2", [*get_test_dims(32, 96, n=1), 0], ids=id_formatter("dim2"))
 @pytest.mark.parametrize("dim3", get_test_dims(32, 96, n=1), ids=id_formatter("dim3"))

tests/test_cuda_setup_evaluator.py

@@ -7,18 +7,18 @@
 @pytest.fixture
 def cuda120_spec() -> GPUSpecs:
     return GPUSpecs(
-        cuda_version_string="120",
+        backend_version_string="120",
         highest_compute_capability=(8, 6),
-        cuda_version_tuple=(12, 0),
+        backend_version_tuple=(12, 0),
     )
 
 
 @pytest.fixture
 def cuda111_noblas_spec() -> GPUSpecs:
     return GPUSpecs(
-        cuda_version_string="111",
+        backend_version_string="111",
         highest_compute_capability=(7, 2),
-        cuda_version_tuple=(11, 1),
+        backend_version_tuple=(11, 1),
     )
 
 

tests/test_functional.py

@@ -513,7 +513,7 @@ def test_vector_quant(dim1, dim2, dim3):
         assert_all_approx_close(A1, A, atol=0.01, rtol=0.1, count=int(n * 0.002))
 
 
-@pytest.mark.skipif(0 < get_compute_capabilities() < 601, reason="this test is supported on ROCm from 6.1")
+@pytest.mark.skipif((0, 0) < get_compute_capabilities() < (6, 1), reason="this test is supported on ROCm from 6.1")
 @pytest.mark.parametrize("dim1", get_test_dims(2, 256, n=2), ids=id_formatter("dim1"))
 @pytest.mark.parametrize("dim2", get_test_dims(2, 256, n=2), ids=id_formatter("dim2"))
 @pytest.mark.parametrize("dim3", get_test_dims(2, 256, n=2), ids=id_formatter("dim3"))
@@ -1818,7 +1818,7 @@ def quant_zp(x):
     print(err1, err2, err3, err4, err5, err6)
 
 
-@pytest.mark.skipif(0 < get_compute_capabilities() < 601, reason="this test is supported on ROCm from 6.1")
+@pytest.mark.skipif((0, 0) < get_compute_capabilities() < (6, 1), reason="this test is supported on ROCm from 6.1")
 @pytest.mark.parametrize("device", ["cuda", "cpu"])
 def test_extract_outliers(device):
     for i in range(k):