Remove unsupported parameters from decode kernel tests (#4911)

Summary:

X-link: facebookresearch/FBGEMM#1936

D80992628 introduced SWA FWD kernel changes which did not support decode kernels (i.e., supporting sm100_fmha_fwd but not sm100_fmha_gen).
Similarly, softmax_scale introduced in D82788784 did not support decode kernels either.

In blackwell_fmha_test, the these parameters are dropped during decode kernel selection (https://www.internalfb.com/code/fbsource/[cd7066706035]/fbcode/deeplearning/fbgemm/fbgemm_gpu/experimental/gen_ai/test/attention/blackwell_fmha_test.py?lines=182)

To avoid confusion, do not test test_decode with ignored parameters.

Reviewed By: Aya-ZIbra, sryap

Differential Revision: D82991496

Author: Alkaid-Benetnash

fbgemm_gpu/experimental/gen_ai/test/attention/blackwell_fmha_test.py

@@ -439,23 +439,17 @@ def _execute_cutlass_blackwell_attn_varlen(
                 seqlen_k,
                 batch_size,
                 is_mqa,
-                window_size,
-                sm_scale,
             )
             for seqlen_k in [64, 128, 256, 1024]
             for batch_size in [1, 2]
             for is_mqa in [True]
-            for window_size in [(-1, -1), (0, 0), (0, 128), (128, 0), (1024, 0)]
-            for sm_scale in [None, 1.0 / 128]
         ]
     )
     def test_decode(
         self,
         seqlen_k: int,
         batch_size: int,
         is_mqa: bool,
-        window_size: tuple[int, int],
-        sm_scale: Optional[float],
         q_heads: int = 8,
         dtype: torch.dtype = torch.float8_e4m3fn,
     ) -> None:
@@ -473,10 +467,12 @@ def test_decode(
             head_dim=128,
             dtype=dtype,
             causal=causal,
-            window_size=window_size,
+            # Decode kernel does not support sliding window attention yet
+            window_size=(-1, -1),
             fwd_only=True,
             deterministic=False,
-            sm_scale=sm_scale,
+            # Decode kernel does not support sm_scale
+            sm_scale=None,
         )
 
     @skip_cuda_lt_sm100