gate sparsity tests by presence of cusparselt (#1602)

Summary:

I have a PyTorch build without `cuSparseLt`. Adding logic to properly
skip tests which depend on this library being available.

Test Plan:

Local testing on an H100 without cuSparseLt:

```
pytest test/prototype/test_sparse_api.py -s
```

Reviewers:

Subscribers:

Tasks:

Tags:

Author: vkuzo

test/dtypes/test_affine_quantized.py

@@ -23,6 +23,10 @@
     is_sm_at_least_89,
 )
 
+is_cusparselt_available = (
+    hasattr(torch.backends, "cusparselt") and torch.backends.cusparselt.is_available()
+)
+
 
 def get_quantization_functions(
     do_sparse: bool, do_int4: bool, device: str = "cuda", int4_zp_int: bool = False
@@ -91,7 +95,8 @@ def test_tensor_core_layout_transpose(self):
 
     @unittest.skipIf(not torch.cuda.is_available(), "Need CUDA available")
     @common_utils.parametrize(
-        "apply_quant", get_quantization_functions(True, True, "cuda", True)
+        "apply_quant",
+        get_quantization_functions(is_cusparselt_available, True, "cuda", True),
     )
     def test_weights_only(self, apply_quant):
         linear = torch.nn.Linear(128, 256, dtype=torch.bfloat16, device="cuda")
@@ -168,7 +173,9 @@ def apply_uint6_weight_only_quant(linear):
 
         deregister_aqt_quantized_linear_dispatch(dispatch_condition)
 
-    @common_utils.parametrize("apply_quant", get_quantization_functions(True, True))
+    @common_utils.parametrize(
+        "apply_quant", get_quantization_functions(is_cusparselt_available, True)
+    )
     @unittest.skipIf(not torch.cuda.is_available(), "Need CUDA available")
     def test_print_quantized_module(self, apply_quant):
         linear = torch.nn.Linear(128, 256, dtype=torch.bfloat16, device="cuda")