adding arch detect torocm6.2_internal_testing

bitsandbytes/cextension.py

@@ -1,6 +1,8 @@
 import ctypes as ct
 import os
 import torch
+import subprocess
+import re
 
 from pathlib import Path
 from warnings import warn
@@ -30,11 +32,18 @@
     lib.get_context.restype = ct.c_void_p
 
     HIP_ENVIRONMENT = False
+    ROCM_GPU_ARCH = "unknown"
     if torch.version.cuda:
         lib.get_cusparse.restype = ct.c_void_p
     elif torch.version.hip:
         HIP_ENVIRONMENT = True
         lib.get_hipsparse.restype = ct.c_void_p
+        result = subprocess.run(['rocminfo'], capture_output=True, text=True)
+        match = re.search(r'Name:\s+gfx(\d+)', result.stdout)
+        if match:
+            ROCM_GPU_ARCH = "gfx" + match.group(1)
+        else:
+            ROCM_GPU_ARCH = "unknown"
 
     lib.cget_managed_ptr.restype = ct.c_void_p
     COMPILED_WITH_CUDA = True

tests/test_functional.py

@@ -10,7 +10,7 @@
 
 import bitsandbytes as bnb
 from bitsandbytes import functional as F
-from bitsandbytes.cextension import HIP_ENVIRONMENT
+from bitsandbytes.cextension import HIP_ENVIRONMENT, ROCM_GPU_ARCH
 from scipy.stats import norm
 
 torch.set_printoptions(
@@ -2543,6 +2543,7 @@ def test_managed():
 @pytest.mark.parametrize("storage_type", ['nf4', 'fp4'], ids=['nf4', 'fp4'])
 @pytest.mark.parametrize("dtype", [torch.float16, torch.bfloat16, torch.float32], ids=['fp16', 'bf16', 'fp32'])
 @pytest.mark.parametrize("double_quant", [False], ids=['DQ_True'])
+@pytest.mark.skipif(HIP_ENVIRONMENT and ROCM_GPU_ARCH == "gfx90a", reason="this test is not supported on ROCm with gfx90a architecture yet")
 def test_gemv_eye_4bit(storage_type, dtype, double_quant):
     dims = 10
     torch.random.manual_seed(np.random.randint(0, 412424242))