Revert "fallback to triton mm_persistent kernel when deepGemm fail" (#13178)

python/sglang/srt/batch_invariant_ops/batch_invariant_ops.py

@@ -253,12 +253,6 @@ def _matmul_persistent_deepgemm(
 def matmul_persistent(
     a: torch.Tensor, b: torch.Tensor, bias: torch.Tensor | None = None
 ):
-    M, K = a.shape
-    K2, N = b.shape
-
-    # DeepGEMM requires minimum dimensions, skip DeepGEMM for small dimensions to avoid CUDA_ERROR_INVALID_VALUE
-    MIN_DIM_FOR_DEEPGEMM = 64
-
     if (
         _ENABLE_MM_DEEPGEMM
         and ENABLE_JIT_DEEPGEMM
@@ -266,8 +260,6 @@ def matmul_persistent(
         and (b.dtype == torch.bfloat16)
         and a.is_contiguous()
         and b.transpose(0, 1).is_contiguous()
-        and M >= MIN_DIM_FOR_DEEPGEMM
-        and N >= MIN_DIM_FOR_DEEPGEMM
     ):
         if _ENABLE_MM_COMPARISON_TEST:
             out_triton = _matmul_persistent_triton(a=a, b=b, bias=bias)
@@ -284,12 +276,7 @@ def matmul_persistent(
             # print(f"{a=} {b=} {bias=} {out_triton=} {out_deepgemm=}")
             return out_deepgemm
 
-        try:
-            return _matmul_persistent_deepgemm(a=a, b=b, bias=bias)
-        except RuntimeError:
-            # DeepGEMM failed, fallback to Triton kernel silently
-            # (dimension checks above should prevent most errors)
-            pass
+        return _matmul_persistent_deepgemm(a=a, b=b, bias=bias)
 
     return _matmul_persistent_triton(a=a, b=b, bias=bias)